Adverse Outcome Pathway (AOP) Network Development for ...

EPA Pesticide Factsheets

Adverse outcome pathways (AOPs) are descriptive biological sequences that start from a molecular initiating event (MIE) and end with an adverse health outcome. AOPs provide biological context for high throughput chemical testing and further prioritize environmental health risk research. According to the Organization for Economic Co-operation and Development guidelines, AOPs are pathways with one MIE anchored to an adverse outcome (AO) by key events (KEs) and key event relationships (KERs). However, this approach does not always capture the cumulative impacts of multiple MIEs on the AO. For example, hepatic lipid flux due to chemical-induced toxicity initiates from multiple ligand-activated receptors and signaling pathways that cascade across biology to converge upon a common fatty liver (FL, also known as steatosis) outcome. To capture this complexity, a top-down strategy was used to develop a FL AOP network (AOPnet). Literature was queried based on the terms steatosis, fatty liver, cirrhosis, and hepatocellular carcinoma. Search results were analyzed for physiological and pathophysiological organ level, cellular and molecular processes, as well as pathway intermediates, to identify potential KEs and MIEs that are key for hepatic lipid metabolism, maintenance, and dysregulation. The analysis identified four apical KE nodes (hepatic fatty acid uptake, de novo fatty acid and lipid synthesis, fatty acid oxidation, and lipid efflux) juxtaposed to the FL AO. The apic

Minimal metabolic pathway structure is consistent with associated biomolecular interactions

PubMed Central

Bordbar, Aarash; Nagarajan, Harish; Lewis, Nathan E; Latif, Haythem; Ebrahim, Ali; Federowicz, Stephen; Schellenberger, Jan; Palsson, Bernhard O

2014-01-01

Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated. PMID:24987116

The NCBI BioSystems database.

PubMed

Geer, Lewis Y; Marchler-Bauer, Aron; Geer, Renata C; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H

2010-01-01

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI's Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

Biological pathways, candidate genes and molecular markers associated with quality-of-life domains: an update

PubMed Central

Sprangers, Mirjam A.G.; Thong, Melissa S.Y.; Bartels, Meike; Barsevick, Andrea; Ordoñana, Juan; Shi, Qiuling; Wang, Xin Shelley; Klepstad, Pål; Wierenga, Eddy A.; Singh, Jasvinder A.; Sloan, Jeff A.

2014-01-01

Background There is compelling evidence of a genetic foundation of patient-reported QOL. Given the rapid development of substantial scientific advances in this area of research, the current paper updates and extends reviews published in 2010. Objectives The objective is to provide an updated overview of the biological pathways, candidate genes and molecular markers involved in fatigue, pain, negative (depressed mood) and positive (well-being/happiness) emotional functioning, social functioning, and overall QOL. Methods We followed a purposeful search algorithm of existing literature to capture empirical papers investigating the relationship between biological pathways and molecular markers and the identified QOL domains. Results Multiple major pathways are involved in each QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes involved in pain perception and the COMT gene is associated with multiple sorts of pain. The neurotransmitter and neuroplasticity theories have the strongest evidence for their relationship with depression. Oxytocin-related genes and genes involved in the serotonergic and dopaminergic pathways play a role in social functioning. Inflammatory pathways, via cytokines, also play an important role in overall QOL. Conclusions Whereas the current findings need future experiments and replication efforts, they will provide researchers supportive background information when embarking on studies relating candidate genes and/or molecular markers to QOL domains. The ultimate goal of this area of research is to enhance patients’ QOL. PMID:24604075

Biological pathways, candidate genes, and molecular markers associated with quality-of-life domains: an update.

PubMed

Sprangers, Mirjam A G; Thong, Melissa S Y; Bartels, Meike; Barsevick, Andrea; Ordoñana, Juan; Shi, Qiuling; Wang, Xin Shelley; Klepstad, Pål; Wierenga, Eddy A; Singh, Jasvinder A; Sloan, Jeff A

2014-09-01

There is compelling evidence of a genetic foundation of patient-reported quality of life (QOL). Given the rapid development of substantial scientific advances in this area of research, the current paper updates and extends reviews published in 2010. The objective was to provide an updated overview of the biological pathways, candidate genes, and molecular markers involved in fatigue, pain, negative (depressed mood) and positive (well-being/happiness) emotional functioning, social functioning, and overall QOL. We followed a purposeful search algorithm of existing literature to capture empirical papers investigating the relationship between biological pathways and molecular markers and the identified QOL domains. Multiple major pathways are involved in each QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes involved in pain perception, and the catechol-O-methyltransferase (COMT) gene is associated with multiple sorts of pain. The neurotransmitter and neuroplasticity theories have the strongest evidence for their relationship with depression. Oxytocin-related genes and genes involved in the serotonergic and dopaminergic pathways play a role in social functioning. Inflammatory pathways, via cytokines, also play an important role in overall QOL. Whereas the current findings need future experiments and replication efforts, they will provide researchers supportive background information when embarking on studies relating candidate genes and/or molecular markers to QOL domains. The ultimate goal of this area of research is to enhance patients' QOL.

Safety and feasibility of targeted agent combinations in solid tumours.

PubMed

Park, Sook Ryun; Davis, Myrtle; Doroshow, James H; Kummar, Shivaani

2013-03-01

The plethora of novel molecular-targeted agents (MTAs) has provided an opportunity to selectively target pathways involved in carcinogenesis and tumour progression. Combination strategies of MTAs are being used to inhibit multiple aberrant pathways in the hope of optimizing antitumour efficacy and to prevent development of resistance. While the selection of specific agents in a given combination has been based on biological considerations (including the role of the putative targets in cancer) and the interactions of the agents used in combination, there has been little exploration of the possible enhanced toxicity of combinations resulting from alterations in multiple signalling pathways in normal cell biology. Owing to the complex networks and crosstalk that govern normal and tumour cell proliferation, inhibiting multiple pathways with MTA combinations can result in unpredictable disturbances in normal physiology. This Review focuses on the main toxicities and the lack of tolerability of some common MTA combinations, particularly where evidence of enhanced toxicity compared to either agent alone is documented or there is development of unexpected toxicity. Toxicities caused by MTA combinations highlight the need to introduce new preclinical testing paradigms early in the drug development process for the assessment of chronic toxicities resulting from such combinations.

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

The NCBI BioSystems database

PubMed Central

Geer, Lewis Y.; Marchler-Bauer, Aron; Geer, Renata C.; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H.

2010-01-01

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI’s Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets. PMID:19854944

Entourage: Visualizing Relationships between Biological Pathways using Contextual Subsets

PubMed Central

Lex, Alexander; Partl, Christian; Kalkofen, Denis; Streit, Marc; Gratzl, Samuel; Wassermann, Anne Mai; Schmalstieg, Dieter; Pfister, Hanspeter

2014-01-01

Biological pathway maps are highly relevant tools for many tasks in molecular biology. They reduce the complexity of the overall biological network by partitioning it into smaller manageable parts. While this reduction of complexity is their biggest strength, it is, at the same time, their biggest weakness. By removing what is deemed not important for the primary function of the pathway, biologists lose the ability to follow and understand cross-talks between pathways. Considering these cross-talks is, however, critical in many analysis scenarios, such as judging effects of drugs. In this paper we introduce Entourage, a novel visualization technique that provides contextual information lost due to the artificial partitioning of the biological network, but at the same time limits the presented information to what is relevant to the analyst’s task. We use one pathway map as the focus of an analysis and allow a larger set of contextual pathways. For these context pathways we only show the contextual subsets, i.e., the parts of the graph that are relevant to a selection. Entourage suggests related pathways based on similarities and highlights parts of a pathway that are interesting in terms of mapped experimental data. We visualize interdependencies between pathways using stubs of visual links, which we found effective yet not obtrusive. By combining this approach with visualization of experimental data, we can provide domain experts with a highly valuable tool. We demonstrate the utility of Entourage with case studies conducted with a biochemist who researches the effects of drugs on pathways. We show that the technique is well suited to investigate interdependencies between pathways and to analyze, understand, and predict the effect that drugs have on different cell types. Fig. 1Entourage showing the Glioma pathway in detail and contextual information of multiple related pathways. PMID:24051820

LASSO-ing Potential Nuclear Receptor Agonists and Antagonists: A New Computational Method for Database Screening

EPA Science Inventory

Nuclear receptors (NRs) are important biological macromolecular transcription factors that are implicated in multiple biological pathways and may interact with other xenobiotics that are endocrine disruptors present in the environment. Examples of important NRs include the androg...

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Alternative Splicing in the Hippo Pathway—Implications for Disease and Potential Therapeutic Targets

PubMed Central

Porazinski, Sean; Ladomery, Michael

2018-01-01

Alternative splicing is a well-studied gene regulatory mechanism that produces biological diversity by allowing the production of multiple protein isoforms from a single gene. An involvement of alternative splicing in the key biological signalling Hippo pathway is emerging and offers new therapeutic avenues. This review discusses examples of alternative splicing in the Hippo pathway, how deregulation of these processes may contribute to disease and whether these processes offer new potential therapeutic targets. PMID:29534050

Mass Spectrometry: A Technique of Many Faces

PubMed Central

Olshina, Maya A.; Sharon, Michal

2016-01-01

Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928

The application of multiple biophysical cues to engineer functional neocartilage for treatment of osteoarthritis. Part II: signal transduction.

PubMed

Brady, Mariea A; Waldman, Stephen D; Ethier, C Ross

2015-02-01

The unique mechanoelectrochemical environment of cartilage has motivated researchers to investigate the effect of multiple biophysical cues, including mechanical, magnetic, and electrical stimulation, on chondrocyte biology. It is well established that biophysical stimuli promote chondrocyte proliferation, differentiation, and maturation within "biological windows" of defined dose parameters, including mode, frequency, magnitude, and duration of stimuli (see companion review Part I: Cellular Response). However, the underlying molecular mechanisms and signal transduction pathways activated in response to multiple biophysical stimuli remain to be elucidated. Understanding the mechanisms of biophysical signal transduction will deepen knowledge of tissue organogenesis, remodeling, and regeneration and aiding in the treatment of pathologies such as osteoarthritis. Further, this knowledge will provide the tissue engineer with a potent toolset to manipulate and control cell fate and subsequently develop functional replacement cartilage. The aim of this article is to review chondrocyte signal transduction pathways in response to mechanical, magnetic, and electrical cues. Signal transduction does not occur along a single pathway; rather a number of parallel pathways appear to be activated, with calcium signaling apparently common to all three types of stimuli, though there are different modes of activation. Current tissue engineering strategies, such as the development of "smart" functionalized biomaterials that enable the delivery of growth factors or integration of conjugated nanoparticles, may further benefit from targeting known signal transduction pathways in combination with external biophysical cues.

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

BMDExpress Data Viewer: A Visualization Tool to Analyze ...

EPA Pesticide Factsheets

Regulatory agencies increasingly apply benchmark dose (BMD) modeling to determine points of departure in human risk assessments. BMDExpress applies BMD modeling to transcriptomics datasets and groups genes to biological processes and pathways for rapid assessment of doses at which biological perturbations occur. However, graphing and analytical capabilities within BMDExpress are limited, and the analysis of output files is challenging. We developed a web-based application, BMDExpress Data Viewer, for visualization and graphical analyses of BMDExpress output files. The software application consists of two main components: ‘Summary Visualization Tools’ and ‘Dataset Exploratory Tools’. We demonstrate through two case studies that the ‘Summary Visualization Tools’ can be used to examine and assess the distributions of probe and pathway BMD outputs, as well as derive a potential regulatory BMD through the modes or means of the distributions. The ‘Functional Enrichment Analysis’ tool presents biological processes in a two-dimensional bubble chart view. By applying filters of pathway enrichment p-value and minimum number of significant genes, we showed that the Functional Enrichment Analysis tool can be applied to select pathways that are potentially sensitive to chemical perturbations. The ‘Multiple Dataset Comparison’ tool enables comparison of BMDs across multiple experiments (e.g., across time points, tissues, or organisms, etc.). The ‘BMDL-BM

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

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.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

PubMed Central

Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-01-01

Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X. Contact: duccio.cavalieri@unifi.it; sorin@wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21653523

Systems Biology and Birth Defects Prevention: Blockade of the Glucocorticoid Receptor Prevents Arsenic-Induced Birth Defects

PubMed Central

Ahir, Bhavesh K.; Sanders, Alison P.; Rager, Julia E.

2013-01-01

Background: The biological mechanisms by which environmental metals are associated with birth defects are largely unknown. Systems biology–based approaches may help to identify key pathways that mediate metal-induced birth defects as well as potential targets for prevention. Objectives: First, we applied a novel computational approach to identify a prioritized biological pathway that associates metals with birth defects. Second, in a laboratory setting, we sought to determine whether inhibition of the identified pathway prevents developmental defects. Methods: Seven environmental metals were selected for inclusion in the computational analysis: arsenic, cadmium, chromium, lead, mercury, nickel, and selenium. We used an in silico strategy to predict genes and pathways associated with both metal exposure and developmental defects. The most significant pathway was identified and tested using an in ovo whole chick embryo culture assay. We further evaluated the role of the pathway as a mediator of metal-induced toxicity using the in vitro midbrain micromass culture assay. Results: The glucocorticoid receptor pathway was computationally predicted to be a key mediator of multiple metal-induced birth defects. In the chick embryo model, structural malformations induced by inorganic arsenic (iAs) were prevented when signaling of the glucocorticoid receptor pathway was inhibited. Further, glucocorticoid receptor inhibition demonstrated partial to complete protection from both iAs- and cadmium-induced neurodevelopmental toxicity in vitro. Conclusions: Our findings highlight a novel approach to computationally identify a targeted biological pathway for examining birth defects prevention. PMID:23458687

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

A multi-pathway model for photosynthetic reaction center

NASA Astrophysics Data System (ADS)

Qin, M.; Shen, H. Z.; Yi, X. X.

2016-03-01

Charge separation occurs in a pair of tightly coupled chlorophylls at the heart of photosynthetic reaction centers of both plants and bacteria. Recently it has been shown that quantum coherence can, in principle, enhance the efficiency of a solar cell, working like a quantum heat engine. Here, we propose a biological quantum heat engine (BQHE) motivated by Photosystem II reaction center (PSII RC) to describe the charge separation. Our model mainly considers two charge-separation pathways which is more than that typically considered in the published literature. We explore how these cross-couplings increase the current and power of the charge separation and discuss the effects of multiple pathways in terms of current and power. The robustness of the BQHE against the charge recombination in natural PSII RC and dephasing induced by environments is also explored, and extension from two pathways to multiple pathways is made. These results suggest that noise-induced quantum coherence helps to suppress the influence of acceptor-to-donor charge recombination, and besides, nature-mimicking architectures with engineered multiple pathways for charge separations might be better for artificial solar energy devices considering the influence of environments.

Modular electron transfer circuits for synthetic biology

PubMed Central

Agapakis, Christina M

2010-01-01

Electron transfer is central to a wide range of essential metabolic pathways, from photosynthesis to fermentation. The evolutionary diversity and conservation of proteins that transfer electrons makes these pathways a valuable platform for engineered metabolic circuits in synthetic biology. Rational engineering of electron transfer pathways containing hydrogenases has the potential to lead to industrial scale production of hydrogen as an alternative source of clean fuel and experimental assays for understanding the complex interactions of multiple electron transfer proteins in vivo. We designed and implemented a synthetic hydrogen metabolism circuit in Escherichia coli that creates an electron transfer pathway both orthogonal to and integrated within existing metabolism. The design of such modular electron transfer circuits allows for facile characterization of in vivo system parameters with applications toward further engineering for alternative energy production. PMID:21468209

Proof of Concept: A review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations

PubMed Central

Azmi, Asfar S.; Wang, Zhiwei; Philip, Philip A.; Mohammad, Ramzi M.; Sarkar, Fazlul H.

2010-01-01

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. This requires innovative approaches such as understanding the global physiological environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases where efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology has emerged as a powerful tool benefiting our understanding of drug mechanism of action in real time. This mini-review highlights the significance of the network and systems biology-based strategy and presents a “proof-of-concept” recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. PMID:21041384

Redundancy control in pathway databases (ReCiPa): an application for improving gene-set enrichment analysis in Omics studies and "Big data" biology.

PubMed

Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy

2013-08-01

Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

PubMed Central

Jones, Lesley; Lambert, Jean-Charles; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Vedernikov, Alexey; Escott-Price, Valentina; Stone, Timothy; Richards, Alexander; Bellenguez, Céline; Ibrahim-Verbaas, Carla A; Naj, Adam C; Sims, Rebecca; Gerrish, Amy; Jun, Gyungah; DeStefano, Anita L; Bis, Joshua C; Beecham, Gary W; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A; Jones, Nicola; Smith, Albert V; Chouraki, Vincent; Thomas, Charlene; Ikram, M Arfan; Zelenika, Diana; Vardarajan, Badri N; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L; Buxbaum, Joseph D; Campion, Dominique; Crane, Paul K; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L; De Jager, Philip L; Deramecourt, Vincent; Johnston, Janet A; Evans, Denis; Lovestone, Simon; Letteneur, Luc; Kornhuber, Johanes; Tárraga, Lluís; Rubinsztein, David C; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M; Fiévet, Nathalie; Huentelman, Matthew J; Gill, Michael; Emilsson, Valur; Brown, Kristelle; Kamboh, M Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B; Myers, Amanda J; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Kehoe, Pat; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleὀ, Alberti; Bayer, Anthony; Tsuang, Debby W; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick; Hardy, John; Naranjo, Maria Candida Deniz; Razquin, Cristina; Bosco, Paola; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Mancuso, Michelangelo; Moebus, Susanne; Mecocci, Patrizia; del Zompo, Maria; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Bullido, Maria; Panza, Francesco; Caffarra, Paolo; Nacmias, Benedetta; Gilbert, John R; Mayhaus, Manuel; Jessen, Frank; Dichgans, Martin; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M; Ingelsson, Martin; Beekly, Duane; Alavarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G; Coto, Eliecer; Hamilton-Nelson, Kara L; Mateo, Ignacio; Owen, Michael J; Faber, Kelley M; Jonsson, Palmi V; Combarros, Onofre; O'Donovan, Michael C; Cantwell, Laura B; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H; Bennett, David A; Harris, Tamara B; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee FAG; Passmore, Peter; Montine, Thomas J; Bettens, Karolien; Rotter, Jerome I; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M; Kukull, Walter A; Hannequin, Didier; Powell, John F; Nalls, Michael A; Ritchie, Karen; Lunetta, Kathryn L; Kauwe, John SK; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R; Pastor, Pau; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M; Graff, Caroline; Psaty, Bruce M; Haines, Jonathan L; Lathrop, Mark; Pericak-Vance, Margaret A; Launer, Lenore J; Farrer, Lindsay A; van Duijn, Cornelia M; Van Broekhoven, Christine; Ramirez, Alfredo; Schellenberg, Gerard D; Seshadri, Sudha; Amouyel, Philippe; Holmans, Peter A

2015-01-01

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics. PMID:25533204

Convergent genetic and expression data implicate immunity in Alzheimer's disease.

PubMed

2015-06-01

Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10(-11)), cholesterol transport (P = 2.96 × 10(-9)), and proteasome-ubiquitin activity (P = 1.34 × 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. Copyright © 2015. Published by Elsevier Inc.

The functional cancer map: a systems-level synopsis of genetic deregulation in cancer.

PubMed

Krupp, Markus; Maass, Thorsten; Marquardt, Jens U; Staib, Frank; Bauer, Tobias; König, Rainer; Biesterfeld, Stefan; Galle, Peter R; Tresch, Achim; Teufel, Andreas

2011-06-30

Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies. Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors. We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'. The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.

Systems biology: An emerging strategy for discovering novel pathogenetic mechanisms that promote cardiovascular disease.

PubMed

Maron, Bradley A; Leopold, Jane A

2016-09-30

Reductionist theory proposes that analyzing complex systems according to their most fundamental components is required for problem resolution, and has served as the cornerstone of scientific methodology for more than four centuries. However, technological gains in the current scientific era now allow for the generation of large datasets that profile the proteomic, genomic, and metabolomic signatures of biological systems across a range of conditions. The accessibility of data on such a vast scale has, in turn, highlighted the limitations of reductionism, which is not conducive to analyses that consider multiple and contemporaneous interactions between intermediates within a pathway or across constructs. Systems biology has emerged as an alternative approach to analyze complex biological systems. This methodology is based on the generation of scale-free networks and, thus, provides a quantitative assessment of relationships between multiple intermediates, such as protein-protein interactions, within and between pathways of interest. In this way, systems biology is well positioned to identify novel targets implicated in the pathogenesis or treatment of diseases. In this review, the historical root and fundamental basis of systems biology, as well as the potential applications of this methodology are discussed with particular emphasis on integration of these concepts to further understanding of cardiovascular disorders such as coronary artery disease and pulmonary hypertension.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

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.

Epigenomics and the concept of degeneracy in biological systems

PubMed Central

Mason, Paul H.; Barron, Andrew B.

2014-01-01

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757

Designed multiple ligands in metabolic disease research: from concept to platform.

PubMed

Gattrell, W; Johnstone, C; Patel, S; Smith, C Sambrook; Scheel, A; Schindler, M

2013-08-01

Type 2 diabetes mellitus (T2DM) is a multifactorial disease, and drug monotherapy typically results in unsatisfactory treatment outcomes for patients. Even when used in combination, existing therapies lack efficacy in the long term. Designed multiple ligands (DMLs) are compounds developed to modulate multiple targets relevant to a disease. DMLs offer the potential to yield greater efficacy over monotherapies, either by modulating different biological pathways, or by boosting a single one. However, examples of DMLs progressing into clinical trials, or onto the market are rare; DML drug discovery is challenging, and perceived by some to be almost impossible. Nevertheless, with the judicious selection of biological targets, both from a biological and chemical perspective, it is possible to develop drug-like DMLs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

PubMed

Bohler, Anwesha; Eijssen, Lars M T; van Iersel, Martijn P; Leemans, Christ; Willighagen, Egon L; Kutmon, Martina; Jaillard, Magali; Evelo, Chris T

2015-08-23

Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

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

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction

PubMed Central

Gunasekara, Chathura; Zhang, Kui; Deng, Wenping; Brown, Laura

2018-01-01

Abstract Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene block. The TGMI calculated the MIM for each triple gene block and then examined its statistical significance using bootstrap. Finally, the frequencies of all TFs present in all significantly interacted triple gene blocks were calculated and ranked. We showed that the TFs with higher frequencies were usually genuine pathway regulators upon evaluating multiple pathways in plants, animals and yeast. Comparison of TGMI with several other algorithms demonstrated its higher accuracy. Therefore, TGMI will be a valuable tool that can help biologists to identify regulators of metabolic pathways and biological processes from the exploded high-throughput gene expression data in public repositories. PMID:29579312

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

PubMed Central

Paley, Suzanne M.; Krummenacker, Markus; Latendresse, Mario; Dale, Joseph M.; Lee, Thomas J.; Kaipa, Pallavi; Gilham, Fred; Spaulding, Aaron; Popescu, Liviu; Altman, Tomer; Paulsen, Ian; Keseler, Ingrid M.; Caspi, Ron

2010-01-01

Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry. PMID:19955237

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

PubMed

Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2017-02-15

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Mass fractionation processes of transition metal isotopes

NASA Astrophysics Data System (ADS)

Zhu, X. K.; Guo, Y.; Williams, R. J. P.; O'Nions, R. K.; Matthews, A.; Belshaw, N. S.; Canters, G. W.; de Waal, E. C.; Weser, U.; Burgess, B. K.; Salvato, B.

2002-06-01

Recent advances in mass spectrometry make it possible to utilise isotope variations of transition metals to address some important issues in solar system and biological sciences. Realisation of the potential offered by these new isotope systems however requires an adequate understanding of the factors controlling their isotope fractionation. Here we show the results of a broadly based study on copper and iron isotope fractionation during various inorganic and biological processes. These results demonstrate that: (1) naturally occurring inorganic processes can fractionate Fe isotope to a detectable level even at temperature ˜1000°C, which challenges the previous view that Fe isotope variations in natural system are unique biosignatures; (2) multiple-step equilibrium processes at low temperatures may cause large mass fractionation of transition metal isotopes even when the fractionation per single step is small; (3) oxidation-reduction is an importation controlling factor of isotope fractionation of transition metal elements with multiple valences, which opens a wide range of applications of these new isotope systems, ranging from metal-silicate fractionation in the solar system to uptake pathways of these elements in biological systems; (4) organisms incorporate lighter isotopes of transition metals preferentially, and transition metal isotope fractionation occurs stepwise along their pathways within biological systems during their uptake.

Aligning Metabolic Pathways Exploiting Binary Relation of Reactions.

PubMed

Huang, Yiran; Zhong, Cheng; Lin, Hai Xiang; Huang, Jing

2016-01-01

Metabolic pathway alignment has been widely used to find one-to-one and/or one-to-many reaction mappings to identify the alternative pathways that have similar functions through different sets of reactions, which has important applications in reconstructing phylogeny and understanding metabolic functions. The existing alignment methods exhaustively search reaction sets, which may become infeasible for large pathways. To address this problem, we present an effective alignment method for accurately extracting reaction mappings between two metabolic pathways. We show that connected relation between reactions can be formalized as binary relation of reactions in metabolic pathways, and the multiplications of zero-one matrices for binary relations of reactions can be accomplished in finite steps. By utilizing the multiplications of zero-one matrices for binary relation of reactions, we efficiently obtain reaction sets in a small number of steps without exhaustive search, and accurately uncover biologically relevant reaction mappings. Furthermore, we introduce a measure of topological similarity of nodes (reactions) by comparing the structural similarity of the k-neighborhood subgraphs of the nodes in aligning metabolic pathways. We employ this similarity metric to improve the accuracy of the alignments. The experimental results on the KEGG database show that when compared with other state-of-the-art methods, in most cases, our method obtains better performance in the node correctness and edge correctness, and the number of the edges of the largest common connected subgraph for one-to-one reaction mappings, and the number of correct one-to-many reaction mappings. Our method is scalable in finding more reaction mappings with better biological relevance in large metabolic pathways.

O-GlcNAcylation in Cancer Biology: Linking Metabolism and Signaling.

PubMed

Ferrer, Christina M; Sodi, Valerie L; Reginato, Mauricio J

2016-08-14

The hexosamine biosynthetic pathway (HBP) is highly dependent on multiple metabolic nutrients including glucose, glutamine, and acetyl-CoA. Increased flux through HBP leads to elevated post-translational addition of β-D-N-acetylglucosamine sugars to nuclear and cytoplasmic proteins. Increased total O-GlcNAcylation is emerging as a general characteristic of cancer cells, and recent studies suggest that O-GlcNAcylation is a central communicator of nutritional status to control key signaling and metabolic pathways that regulate multiple cancer cell phenotypes. This review summarizes our current understanding of changes of O-GlcNAc cycling enzymes in cancer, the role of O-GlcNAcylation in tumorigenesis, and the current challenges in targeting this pathway therapeutically. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systems biology approach to developing S(2)RM-based "systems therapeutics" and naturally induced pluripotent stem cells.

PubMed

Maguire, Greg; Friedman, Peter

2015-05-26

The degree to, and the mechanisms through, which stem cells are able to build, maintain, and heal the body have only recently begun to be understood. Much of the stem cell's power resides in the release of a multitude of molecules, called stem cell released molecules (SRM). A fundamentally new type of therapeutic, namely "systems therapeutic", can be realized by reverse engineering the mechanisms of the SRM processes. Recent data demonstrates that the composition of the SRM is different for each type of stem cell, as well as for different states of each cell type. Although systems biology has been successfully used to analyze multiple pathways, the approach is often used to develop a small molecule interacting at only one pathway in the system. A new model is emerging in biology where systems biology is used to develop a new technology acting at multiple pathways called "systems therapeutics". A natural set of healing pathways in the human that uses SRM is instructive and of practical use in developing systems therapeutics. Endogenous SRM processes in the human body use a combination of SRM from two or more stem cell types, designated as S(2)RM, doing so under various state dependent conditions for each cell type. Here we describe our approach in using state-dependent SRM from two or more stem cell types, S(2)RM technology, to develop a new class of therapeutics called "systems therapeutics." Given the ubiquitous and powerful nature of innate S(2)RM-based healing in the human body, this "systems therapeutic" approach using S(2)RM technology will be important for the development of anti-cancer therapeutics, antimicrobials, wound care products and procedures, and a number of other therapeutics for many indications.

An advanced web query interface for biological databases

PubMed Central

Latendresse, Mario; Karp, Peter D.

2010-01-01

Although most web-based biological databases (DBs) offer some type of web-based form to allow users to author DB queries, these query forms are quite restricted in the complexity of DB queries that they can formulate. They can typically query only one DB, and can query only a single type of object at a time (e.g. genes) with no possible interaction between the objects—that is, in SQL parlance, no joins are allowed between DB objects. Writing precise queries against biological DBs is usually left to a programmer skillful enough in complex DB query languages like SQL. We present a web interface for building precise queries for biological DBs that can construct much more precise queries than most web-based query forms, yet that is user friendly enough to be used by biologists. It supports queries containing multiple conditions, and connecting multiple object types without using the join concept, which is unintuitive to biologists. This interactive web interface is called the Structured Advanced Query Page (SAQP). Users interactively build up a wide range of query constructs. Interactive documentation within the SAQP describes the schema of the queried DBs. The SAQP is based on BioVelo, a query language based on list comprehension. The SAQP is part of the Pathway Tools software and is available as part of several bioinformatics web sites powered by Pathway Tools, including the BioCyc.org site that contains more than 500 Pathway/Genome DBs. PMID:20624715

User-centered evaluation of Arizona BioPathway: an information extraction, integration, and visualization system.

PubMed

Quiñones, Karin D; Su, Hua; Marshall, Byron; Eggers, Shauna; Chen, Hsinchun

2007-09-01

Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This paper presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature-viewing method. Relation aggregation significantly contributes to knowledge-acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multiview, relation-based interface that supports user-controlled exploration of pathway information across multiple granularities.

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

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

Young, M; Craft, D

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less

Decomposition of complex microbial behaviors into resource-based stress responses

PubMed Central

Carlson, Ross P.

2009-01-01

Motivation: Highly redundant metabolic networks and experimental data from cultures likely adapting simultaneously to multiple stresses can complicate the analysis of cellular behaviors. It is proposed that the explicit consideration of these factors is critical to understanding the competitive basis of microbial strategies. Results: Wide ranging, seemingly unrelated Escherichia coli physiological fluxes can be simply and accurately described as linear combinations of a few ecologically relevant stress adaptations. These strategies were identified by decomposing the central metabolism of E.coli into elementary modes (mathematically defined biochemical pathways) and assessing the resource investment cost–benefit properties for each pathway. The approach capitalizes on the inherent tradeoffs related to investing finite resources like nitrogen into different pathway enzymes when the pathways have varying metabolic efficiencies. The subset of ecologically competitive pathways represented 0.02% of the total permissible pathways. The biological relevance of the assembled strategies was tested against 10 000 randomly constructed pathway subsets. None of the randomly assembled collections were able to describe all of the considered experimental data as accurately as the cost-based subset. The results suggest these metabolic strategies are biologically significant. The current descriptions were compared with linear programming (LP)-based flux descriptions using the Euclidean distance metric. The current study's pathway subset described the experimental fluxes with better accuracy than the LP results without having to test multiple objective functions or constraints and while providing additional ecological insight into microbial behavior. The assembled pathways seem to represent a generalized set of strategies that can describe a wide range of microbial responses and hint at evolutionary processes where a handful of successful metabolic strategies are utilized simultaneously in different combinations to adapt to diverse conditions. Contact: rossc@biofilms.montana.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19008248

MicroRNA-1271 inhibits proliferation and promotes apoptosis of multiple myeloma cells through inhibiting smoothened-mediated Hedgehog signaling pathway.

PubMed

Xu, Zhengwei; Huang, Chen; Hao, Dingjun

2017-02-01

MicroRNAs (miRNAs) have emerged as important regulators in multiple myeloma (MM). miR-1271 is a tumor suppressor in many cancer types. However, the biological role of miR-1271 in MM remains unclear. In the present study, we elucidated the biological role of miR-1271 in MM. Results showed that miR-1271 was significantly decreased in primary MM cells from MM patients and MM cell lines. Overexpression of miR-1271 inhibited proliferation and promoted apoptosis of MM cells. Conversely, suppression of miR-1271 showed the opposite effect. Bioinformatics algorithm analysis predicted that smoothened (SMO), the activator of Hedgehog (HH) signaling pathway, was a direct target of miR-1271 that was experimentally verified by a dual-luciferase reporter assay. Furthermore, overexpression of miR-1271 inhibited SMO expression and HH signaling pathway. Conversely, the restoration of SMO expression markedly abolished the effect of miR-1271 overexpression on cell proliferation, apoptosis and HH signaling pathway in MM cells. Taken together, the present study suggests that miR-1271 functions as a tumor suppressor that inhibits proliferation and promotes apoptosis of MM cells through inhibiting SMO-mediated HH signaling pathway. This finding implies that miR-1271 is a potential therapeutic target for the treatment of MM.

Network motifs – recurring circuitry components in biological systems

EPA Science Inventory

Environmental perturbations, elicited by chemicals, dietary supplements, and drugs, can alter the dynamics of the molecular circuits and networks operating in cells, leading to multiple disease endpoints. Multi-component signal transduction pathways and gene regulatory circuits u...

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake

PubMed Central

Do, Duy N.; Strathe, Anders B.; Ostersen, Tage; Pant, Sameer D.; Kadarmideen, Haja N.

2014-01-01

Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher’s exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs. PMID:25250046

Diseases Associated with Defective Responses to DNA Damage

PubMed Central

O’Driscoll, Mark

2012-01-01

Within the last decade, multiple novel congenital human disorders have been described with genetic defects in known and/or novel components of several well-known DNA repair and damage response pathways. Examples include disorders of impaired nucleotide excision repair, DNA double-strand and single-strand break repair, as well as compromised DNA damage-induced signal transduction including phosphorylation and ubiquitination. These conditions further reinforce the importance of multiple genome stability pathways for health and development in humans. Furthermore, these conditions inform our knowledge of the biology of the mechanics of genome stability and in some cases provide potential routes to help exploit these pathways therapeutically. Here, I will review a selection of these exciting findings from the perspective of the disorders themselves, describing how they were identified, how genotype informs phenotype, and how these defects contribute to our growing understanding of genome stability pathways. PMID:23209155

Chemical-agnostic hazard prediction: statistical inference of in ...

EPA Pesticide Factsheets

Toxicity pathways have been defined as normal cellular pathways that, when sufficiently perturbed as a consequence of chemical exposure, lead to an adverse outcome. If an exposure alters one or more normal biological pathways to an extent that leads to an adverse toxicity outcome, a significant correlation must exist between the exposure, the extent of pathway alteration, and the degree of adverse outcome. Biological pathways are regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation, each of which can affect the levels and extents of modification of proteins involved in the pathways. Significant alterations of toxicity pathways resulting from changes in regulation at any of these levels therefore are likely to be detectable as alterations in the proteome. We hypothesize that significant correlations between exposures, adverse outcomes, and changes in the proteome have the potential to identify putative toxicity pathways, facilitating selection of candidate targets for high throughput screening, even in the absence of a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations. We explored this hypothesis in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+, alone and in defined mixtures. Levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

Biological pathways involved in the development of inflammatory bowel disease.

PubMed

Zemljic, Mateja; Pejkovic, Bozena; Krajnc, Ivan; Lipovsek, Saska

2014-10-01

Apoptosis, autophagy and necrosis are three distinct functional types of the mammalian cell death network. All of them are characterized by a number of cell's morphological changes. The inappropriate induction of cell death is involved in the pathogenesis of a number of diseases.Pathogenesis of inflammatory bowel diseases (ulcerative colitis, Crohn's disease) includes an abnormal immunological response to disturbed intestinal microflora. One of the most important reason in pathogenesis of chronic inflammatory disease and subsequent multiple organ pathology is a barrier function of the gut, regulating cellular viability. Recent findings have begun to explain the mechanisms by which intestinal epithelial cells are able to survive in such an environment and how loss of normal regulatory processes may lead to inflammatory bowel disease (IBD).This review focuses on the regulation of biological pathways in development and homeostasis in IBD. Better understanding of the physiological functions of biological pathways and their influence on inflammation, immunity, and barrier function will simplify our expertice of homeostasis in the gastrointestinal tract and in upgrading diagnosis and treatment.

Epigenetic potential of resveratrol and analogs in preclinical models of prostate cancer

USDA-ARS?s Scientific Manuscript database

Prostate cancer is affected by lifestyle, particularly diet. Dietary polyphenols such as resveratrol possess anticancer properties and, therefore, chemopreventive and therapeutic potentials. Resveratrol has pleiotropic effect exerting its biological activity through multiple pathways and targets ass...

Toxicogenomic Effects Common to Triazole Antifungals and Conserved Between Rats and Humans

EPA Science Inventory

The triazole antifungals myclobutanil, propiconazole and triadimefon cause varying degrees of hepatic toxicity and disrupt steroid hormone homeostasis in rodent in vivo models. To identify biological pathways consistently modulated across multiple time-points and various study d...

The micronutrient genomics project: a community-driven knowledge base for micronutrient research

USDA-ARS?s Scientific Manuscript database

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it...

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

PubMed

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

Detecting uber-operons in prokaryotic genomes.

PubMed

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.

Detecting uber-operons in prokaryotic genomes

PubMed Central

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: , the first of its kind. PMID:16682449

Pathways Involved in Sasang Constitution from Genome-Wide Analysis in a Korean Population

PubMed Central

Yu, Sung-Gon; Kim, Jong-Yeol; Song, Kwang Hoon

2012-01-01

Abstract Objective Sasang constitution (SC) medicine, a branch of Korean traditional medicine, classifies the individual into one of four constitutional types (Taeum, TE; Soeum, SE; Soyang, SY; and Taeyang, TY) based on physiologic characteristics. The authors of the current article recently reported individual genetic elements associated with SC types via genome-wide association (GWA) analysis. However, to understand the biologic mechanisms underlying constitution, a comprehensive approach that combines individual genetic effects was applied. Design Genotypes of 1222 subjects of defined constitution types were measured for 341,998 genetic loci across the entire genome. The biologic pathways associated with SC types were identified via GWA analysis using three different algorithms—namely, the Z-static method, a restandardized gene set assay, and a gene set enrichment assay. Results Distinct pathways were associated (p<0.05) with each constitution type. The TE type was significantly associated with cytoskeleton-related pathways. The SE type was significantly associated with cardio- and amino-acid metabolism–related pathways. The SY type was associated with enriched melanoma-related pathways. TY subjects were excluded because of the small size of that sample. Among these functionally related pathways, core-node genes regulating multiple pathways were identified. TJP1, PTK2, and SRC were selected as core-nodes for TE; RHOA, and MAOA/MAOB for SE; and GNAO1 for SY (p<0.05), respectively. Conclusions The current authors systematically identified the biologic pathways and core-node genes associated with SC types from the GWA study; this information should provide insights regarding the molecular mechanisms inherent in constitutional pathophysiology. PMID:22889377

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Systems Genetics Analysis of GWAS reveals Novel Associations between Key Biological Processes and Coronary Artery Disease

PubMed Central

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre FR; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2016-01-01

Objective Genome-wide association (GWA) studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Approaches and Results Employing pathways (gene sets) from Reactome, we carried out a two-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CADGWAS data sets (9,889 cases/11,089 controls), nominally significant gene-sets were tested for replication in a meta-analysis of 9 additional studies (15,502 cases/55,730 controls) from the CARDIoGRAM Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication p<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix integrity, innate immunity, axon guidance, and signaling by PDRF, NOTCH, and the TGF-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (e.g. semaphorin regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared to random networks (p<0.001). Network centrality analysis (‘degree’ and ‘betweenness’) further identified genes (e.g. NCAM1, FYN, FURIN etc.) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. Conclusions These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. PMID:25977570

Joint Identification of Genetic Variants for Physical Activity in Korean Population

PubMed Central

Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung

2014-01-01

There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172

Identification of radiation responsive genes and transcriptome profiling via complete RNA sequencing in a stable radioresistant U87 glioblastoma model.

PubMed

Doan, Ninh B; Nguyen, Ha S; Alhajala, Hisham S; Jaber, Basem; Al-Gizawiy, Mona M; Ahn, Eun-Young Erin; Mueller, Wade M; Chitambar, Christopher R; Mirza, Shama P; Schmainda, Kathleen M

2018-05-04

The absence of major progress in the treatment of glioblastoma (GBM) is partly attributable to our poor understanding of both GBM tumor biology and the acquirement of treatment resistance in recurrent GBMs. Recurrent GBMs are characterized by their resistance to radiation. In this study, we used an established stable U87 radioresistant GBM model and total RNA sequencing to shed light on global mRNA expression changes following irradiation. We identified many genes, the expressions of which were altered in our radioresistant GBM model, that have never before been reported to be associated with the development of radioresistant GBM and should be concertedly further investigated to understand their roles in radioresistance. These genes were enriched in various biological processes such as inflammatory response, cell migration, positive regulation of epithelial to mesenchymal transition, angiogenesis, apoptosis, positive regulation of T-cell migration, positive regulation of macrophage chemotaxis, T-cell antigen processing and presentation, and microglial cell activation involved in immune response genes. These findings furnish crucial information for elucidating the molecular mechanisms associated with radioresistance in GBM. Therapeutically, with the global alterations of multiple biological pathways observed in irradiated GBM cells, an effective GBM therapy may require a cocktail carrying multiple agents targeting multiple implicated pathways in order to have a chance at making a substantial impact on improving the overall GBM survival.

Clinical features and pathophysiology of Complex Regional Pain Syndrome – current state of the art

PubMed Central

Marinus, Johan; Moseley, G. Lorimer; Birklein, Frank; Baron, Ralf; Maihöfner, Christian; Kingery, Wade S.; van Hilten, Jacobus J.

2017-01-01

That a minor injury can trigger a complex regional pain syndrome (CRPS) - multiple system dysfunction, severe and often chronic pain and disability - has fascinated scientists and perplexed clinicians for decades. However, substantial advances across several medical disciplines have recently increased our understanding of CRPS. Compelling evidence implicates biological pathways that underlie aberrant inflammation, vasomotor dysfunction, and maladaptive neuroplasticity in the clinical features of CRPS. Collectively, the evidence points to CRPS being a multifactorial disorder that is associated with an aberrant host response to tissue injury. Varying susceptibility to perturbed regulation of any of the underlying biological pathways probably accounts for the clinical heterogeneity of CRPS. PMID:21683929

Diet and Colorectal Cancer: Analysis of a Candidate Pathway Using SNPS, Haplotypes, and Multi-Gene Assessment

PubMed Central

Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Caan, Bette J.; Potter, John D.; Wolff, Roger K.

2012-01-01

There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined. PMID:21999454

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Defining a Computational Framework for the Assessment of Taxonomic Applicability

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework describes the effects of environmental stressors across multiple scales of biological organization and function. This includes an evaluation of the potential for each key event to occur across a broad range of species in order to determ...

Vasoregression: A Shared Vascular Pathology Underlying Macrovascular And Microvascular Pathologies?

PubMed Central

Gupta, Akanksha

2015-01-01

Abstract Vasoregression is a common phenomenon underlying physiological vessel development as well as pathological microvascular diseases leading to peripheral neuropathy, nephropathy, and vascular oculopathies. In this review, we describe the hallmarks and pathways of vasoregression. We argue here that there is a parallel between characteristic features of vasoregression in the ocular microvessels and atherosclerosis in the larger vessels. Shared molecular pathways and molecular effectors in the two conditions are outlined, thus highlighting the possible systemic causes of local vascular diseases. Our review gives us a system-wide insight into factors leading to multiple synchronous vascular diseases. Because shared molecular pathways might usefully address the diagnostic and therapeutic needs of multiple common complex diseases, the literature analysis presented here is of broad interest to readership in integrative biology, rational drug development and systems medicine. PMID:26669709

A reproducible approach to high-throughput biological data acquisition and integration

PubMed Central

Rahnavard, Gholamali; Waldron, Levi; McIver, Lauren; Shafquat, Afrah; Franzosa, Eric A.; Miropolsky, Larissa; Sweeney, Christopher

2015-01-01

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. PMID:26157642

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

A RHIM with a View: FLYing with Functional Amyloids.

PubMed

Shin, Sunny; Cherry, Sara

2017-10-17

Recognition of bacterial peptidoglycan by the Drosophila IMD pathway triggers NF-κB activation and an associated immune response. In this issue of Immunity, Kleino et al. (2017) show that proteins in the IMD pathway form functional amyloids via a cryptic motif resembling the RHIM motif found in mammalian RIPK proteins. Amyloid formation can be negatively regulated, suggesting that it presents a regulatory point in multiple biological processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Inference of Evolutionary Forces Acting on Human Biological Pathways

PubMed Central

Daub, Josephine T.; Dupanloup, Isabelle; Robinson-Rechavi, Marc; Excoffier, Laurent

2015-01-01

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald–Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures. PMID:25971280

Preclinical anti-cancer activity and multiple mechanisms of action of a cationic silver complex bearing N-heterocyclic carbene ligands.

PubMed

Allison, Simon J; Sadiq, Maria; Baronou, Efstathia; Cooper, Patricia A; Dunnill, Chris; Georgopoulos, Nikolaos T; Latif, Ayşe; Shepherd, Samantha; Shnyder, Steve D; Stratford, Ian J; Wheelhouse, Richard T; Willans, Charlotte E; Phillips, Roger M

2017-09-10

Organometallic complexes offer the prospect of targeting multiple pathways that are important in cancer biology. Here, the preclinical activity and mechanism(s) of action of a silver-bis(N-heterocyclic carbine) complex (Ag8) were evaluated. Ag8 induced DNA damage via several mechanisms including topoisomerase I/II and thioredoxin reductase inhibition and induction of reactive oxygen species. DNA damage induction was consistent with cytotoxicity observed against proliferating cells and Ag8 induced cell death by apoptosis. Ag8 also inhibited DNA repair enzyme PARP1, showed preferential activity against cisplatin resistant A2780 cells and potentiated the activity of temozolomide. Ag8 was substantially less active against non-proliferating non-cancer cells and selectively inhibited glycolysis in cancer cells. Ag8 also induced significant anti-tumour effects against cells implanted intraperitoneally in hollow fibres but lacked activity against hollow fibres implanted subcutaneously. Thus, Ag8 targets multiple pathways of importance in cancer biology, is less active against non-cancer cells and shows activity in vivo in a loco-regional setting. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Concordance in Genomic Changes Between Mouse Lungs and Human Airway Epithelial Cells Exposed to Diesel Exhaust Particles

EPA Science Inventory

Human and animal toxicity studies have shown that exposure to diesel exhaust particles (DEP) or their constituents affect multiple biological processes including immune and inflammatory pathways, mutagenesis and in some cases carcinogenesis. This study compared genomic changes by...

Discovery of cancer common and specific driver gene sets

PubMed Central

2017-01-01

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

The putative roles of the ubiquitin/proteasome pathway in resistance to anticancer therapy.

PubMed

Smith, Laura; Lind, Michael J; Drew, Philip J; Cawkwell, Lynn

2007-11-01

The ubiquitin/proteasome (UP) pathway plays a significant role in many important biological functions and alterations in this pathway have been shown to contribute to the pathology of many human diseases, including cancer. Proteasome inhibition has been well established as a rational strategy for the treatment of multiple myeloma and is currently under investigation for the treatment of other haematological malignancies and solid tumours. Recent evidence suggests that proteasome inhibition may also sensitise tumour cells to the actions of both conventional chemotherapy and radiotherapy, suggesting that this pathway may modify clinical response to anticancer therapy. However, conflicting evidence exists as to the roles of the UP pathway in resistance to treatment. This review endeavours to discuss such roles.

Towards a 21st century roadmap for biomedical research and ...

EPA Pesticide Factsheets

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies and the corporate and NGO sectors, this consensus report analyses, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this. To discover and develop new therapies, we need 21-century roadmaps for biomedical research based on multiscale human disease pathways, and supported by policy and funding strategies that prioritise human relevance.

In vitro DNA SCRaMbLE.

PubMed

Wu, Yi; Zhu, Rui-Ying; Mitchell, Leslie A; Ma, Lu; Liu, Rui; Zhao, Meng; Jia, Bin; Xu, Hui; Li, Yun-Xiang; Yang, Zu-Ming; Ma, Yuan; Li, Xia; Liu, Hong; Liu, Duo; Xiao, Wen-Hai; Zhou, Xiao; Li, Bing-Zhi; Yuan, Ying-Jin; Boeke, Jef D

2018-05-22

The power of synthetic biology has enabled the expression of heterologous pathways in cells, as well as genome-scale synthesis projects. The complexity of biological networks makes rational de novo design a grand challenge. Introducing features that confer genetic flexibility is a powerful strategy for downstream engineering. Here we develop an in vitro method of DNA library construction based on structural variation to accomplish this goal. The "in vitro SCRaMbLE system" uses Cre recombinase mixed in a test tube with purified DNA encoding multiple loxPsym sites. Using a β-carotene pathway designed for expression in yeast as an example, we demonstrate top-down and bottom-up in vitro SCRaMbLE, enabling optimization of biosynthetic pathway flux via the rearrangement of relevant transcription units. We show that our system provides a straightforward way to correlate phenotype and genotype and is potentially amenable to biochemical optimization in ways that the in vivo system cannot achieve.

iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data

PubMed Central

Saha, Ashis; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo

2015-01-01

Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference. PMID:26147457

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD.

PubMed

Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P; Gill, Michael; Miranda, Ana; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V; Buitelaar, Jan K; Arias-Vásquez, Alejandro

2013-11-01

Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic studies. This study investigated whether pathway-based analysis could bring scientists closer to unraveling the biology of ADHD. The pathway was described as a predefined gene selection based on a well-established database or literature data. Common genetic variants in pathways involved in dopamine/norepinephrine and serotonin neurotransmission and genes involved in neuritic outgrowth were investigated in cases from the International Multicentre ADHD Genetics (IMAGE) study. Multivariable analysis was performed to combine the effects of single genetic variants within the pathway genes. Phenotypes were DSM-IV symptom counts for inattention and hyperactivity/impulsivity (n = 871) and symptom severity measured with the Conners Parent (n = 930) and Teacher (n = 916) Rating Scales. Summing genetic effects of common genetic variants within the pathways showed a significant association with hyperactive/impulsive symptoms ((p)empirical = .007) but not with inattentive symptoms ((p)empirical = .73). Analysis of parent-rated Conners hyperactive/impulsive symptom scores validated this result ((p)empirical = .0018). Teacher-rated Conners scores were not associated. Post hoc analyses showed a significant contribution of all pathways to the hyperactive/impulsive symptom domain (dopamine/norepinephrine, (p)empirical = .0004; serotonin, (p)empirical = .0149; neuritic outgrowth, (p)empirical = .0452). The present analysis shows an association between common variants in 3 genetic pathways and the hyperactive/impulsive component of ADHD. This study demonstrates that pathway-based association analyses, using quantitative measurements of ADHD symptom domains, can increase the power of genetic analyses to identify biological risk factors involved in this disorder. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Microarray profiling analysis uncovers common molecular mechanisms of rubella virus, human cytomegalovirus, and herpes simplex virus type 2 infections in ECV304 cells.

PubMed

Mo, X; Xu, L; Yang, Q; Feng, H; Peng, J; Zhang, Y; Yuan, W; Wang, Y; Li, Y; Deng, Y; Wan, Y; Chen, Z; Li, F; Wu, X

2011-08-01

To study the common molecular mechanisms of various viruses infections that might result in congential cardiovascular diseases in perinatal period, changes in mRNA expression levels of ECV304 cells infected by rubella virus (RUBV), human cytomegalovirus (HCMV), and herpes simplex virus type 2 (HSV-2) were analyzed using a microarray system representing 18,716 human genes. 99 genes were found to exhibit differential expression (80 up-regulated and 19 down-regulated). Biological process analysis showed that 33 signaling pathways including 22 genes were relevant significantly to RV, HCMV and HSV-II infections. Of these 33 biological processes, 28 belong to one-gene biological processes and 5 belong to multiple-gene biological processes. Gene annotation indicated that the 5 multiple-gene biological processes including regulation of cell growth, collagen fibril organization, mRNA transport, cell adhesion and regulation of cell shape, and seven down- or up-regulated genes [CRIM1 (cysteine rich transmembrane BMP regulator 1), WISP2 (WNT1 inducible signaling pathway protein 2), COL12A1 (collagen, type XII, alpha 1), COL11A2 (collagen, type XI, alpha 2), CNTN5 (contactin 5), DDR1 (discoidin domain receptor tyrosine kinase 1), VEGF (vascular endothelial growth factor precursor)], are significantly correlated to RUBV, HCMV and HSV-2 infections in ECV304 cells. The results obtained in this study suggested the common molecular mechanisms of viruses infections that might result in congential cardiovascular diseases.

Anti-IL-23 and Anti-IL-17 Biologic Agents for the Treatment of Immune-Mediated Inflammatory Conditions.

PubMed

Frieder, Jillian; Kivelevitch, Dario; Haugh, Isabel; Watson, Ian; Menter, Alan

2018-01-01

Advancements in the immunopathogenesis of psoriasis have identified interleukin (IL)-23 and IL-17 as fundamental contributors in the immune pathways of the disease. Leveraging these promising therapeutic targets has led to the emergence of a number of anti-IL-23 and -17 biologic agents with the potential to treat multiple conditions with common underlying pathology. The unprecedented clinical efficacy of these agents in the treatment of psoriasis has paved way for their evaluation in diseases such as psoriatic arthritis, Crohn's disease, rheumatoid arthritis, in addition to other immune-mediated conditions. Here we review the IL-23/IL-17 immune pathways and discuss the key clinical and safety data of the anti-IL-23 and anti-IL-17 biologic agents in psoriasis and other immune-mediated diseases. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Genetic and Epigenetic Events Generate Multiple Pathways in Colorectal Cancer Progression

PubMed Central

Pancione, Massimo; Remo, Andrea; Colantuoni, Vittorio

2012-01-01

Colorectal cancer (CRC) is one of the most common causes of death, despite decades of research. Initially considered as a disease due to genetic mutations, it is now viewed as a complex malignancy because of the involvement of epigenetic abnormalities. A functional equivalence between genetic and epigenetic mechanisms has been suggested in CRC initiation and progression. A hallmark of CRC is its pathogenetic heterogeneity attained through at least three distinct pathways: a traditional (adenoma-carcinoma sequence), an alternative, and more recently the so-called serrated pathway. While the alternative pathway is more heterogeneous and less characterized, the traditional and serrated pathways appear to be more homogeneous and clearly distinct. One unsolved question in colon cancer biology concerns the cells of origin and from which crypt compartment the different pathways originate. Based on molecular and pathological evidences, we propose that the traditional and serrated pathways originate from different crypt compartments explaining their genetic/epigenetic and clinicopathological differences. In this paper, we will discuss the current knowledge of CRC pathogenesis and, specifically, summarize the role of genetic/epigenetic changes in the origin and progression of the multiple CRC pathways. Elucidation of the link between the molecular and clinico-pathological aspects of CRC would improve our understanding of its etiology and impact both prevention and treatment. PMID:22888469

Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival

PubMed Central

Piegorsch, Walter W.; Lussier, Yves A.

2015-01-01

Motivation: The conventional approach to personalized medicine relies on molecular data analytics across multiple patients. The path to precision medicine lies with molecular data analytics that can discover interpretable single-subject signals (N-of-1). We developed a global framework, N-of-1-pathways, for a mechanistic-anchored approach to single-subject gene expression data analysis. We previously employed a metric that could prioritize the statistical significance of a deregulated pathway in single subjects, however, it lacked in quantitative interpretability (e.g. the equivalent to a gene expression fold-change). Results: In this study, we extend our previous approach with the application of statistical Mahalanobis distance (MD) to quantify personal pathway-level deregulation. We demonstrate that this approach, N-of-1-pathways Paired Samples MD (N-OF-1-PATHWAYS-MD), detects deregulated pathways (empirical simulations), while not inflating false-positive rate using a study with biological replicates. Finally, we establish that N-OF-1-PATHWAYS-MD scores are, biologically significant, clinically relevant and are predictive of breast cancer survival (P < 0.05, n = 80 invasive carcinoma; TCGA RNA-sequences). Conclusion: N-of-1-pathways MD provides a practical approach towards precision medicine. The method generates the magnitude and the biological significance of personal deregulated pathways results derived solely from the patient’s transcriptome. These pathways offer the opportunities for deriving clinically actionable decisions that have the potential to complement the clinical interpretability of personal polymorphisms obtained from DNA acquired or inherited polymorphisms and mutations. In addition, it offers an opportunity for applicability to diseases in which DNA changes may not be relevant, and thus expand the ‘interpretable ‘omics’ of single subjects (e.g. personalome). Availability and implementation: http://www.lussierlab.net/publications/N-of-1-pathways. Contact: yves@email.arizona.edu or piegorsch@math.arizona.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072495

Metabolic engineering with plants for a sustainable biobased economy.

PubMed

Yoon, Jong Moon; Zhao, Le; Shanks, Jacqueline V

2013-01-01

Plants are bona fide sustainable organisms because they accumulate carbon and synthesize beneficial metabolites from photosynthesis. To meet the challenges to food security and health threatened by increasing population growth and depletion of nonrenewable natural resources, recent metabolic engineering efforts have shifted from single pathways to holistic approaches with multiple genes owing to integration of omics technologies. Successful engineering of plants results in the high yield of biomass components for primary food sources and biofuel feedstocks, pharmaceuticals, and platform chemicals through synthetic biology and systems biology strategies. Further discovery of undefined biosynthesis pathways in plants, integrative analysis of discrete omics data, and diversified process developments for production of platform chemicals are essential to overcome the hurdles for sustainable production of value-added biomolecules from plants.

Pathologic and Therapeutic Implications for the Cell Biology of Parkin

PubMed Central

Charan, Rakshita A.; LaVoie, Matthew J.

2015-01-01

Mutations in the E3 ligase parkin are the most common cause of autosomal recessive Parkinson's disease (PD), but it is believed that parkin dysfunction may also contribute to idiopathic PD. Since its discovery, parkin has been implicated in supporting multiple neuroprotective pathways, many revolving around the maintenance of mitochondrial health quality control and governance of cell survival. Recent advances across the structure, biochemistry, and cell biology of parkin have provided great insights into the etiology of parkin-linked and idiopathic PD and may ultimately generate novel therapeutic strategies to slow or halt disease progression. This review describes the various pathways in which parkin acts and the mechanisms by which parkin may be targeted for therapeutic intervention. PMID:25697646

Genetic insights into the mechanisms of Fgf signaling

PubMed Central

Brewer, J. Richard; Mazot, Pierre; Soriano, Philippe

2016-01-01

The fibroblast growth factor (Fgf) family of ligands and receptor tyrosine kinases is required throughout embryonic and postnatal development and also regulates multiple homeostatic functions in the adult. Aberrant Fgf signaling causes many congenital disorders and underlies multiple forms of cancer. Understanding the mechanisms that govern Fgf signaling is therefore important to appreciate many aspects of Fgf biology and disease. Here we review the mechanisms of Fgf signaling by focusing on genetic strategies that enable in vivo analysis. These studies support an important role for Erk1/2 as a mediator of Fgf signaling in many biological processes but have also provided strong evidence for additional signaling pathways in transmitting Fgf signaling in vivo. PMID:27036966

An "EAR" on environmental surveillance and monitoring: A ...

EPA Pesticide Factsheets

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on chemical concentration alone, it can be difficult to identify which compounds may be of toxicological concern for prioritization for further monitoring or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high throughput screening data like the ToxCast™ database, which contains data for over 9,000 compounds screened through up to 1,100 assays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast™ effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast™ database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Biological pathways were then linked to adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts. Anthropogenic contaminants are frequently reported in environm

Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease.

PubMed

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre F R; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2015-07-01

Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. © 2015 American Heart Association, Inc.

Multivariate inference of pathway activity in host immunity and response to therapeutics

PubMed Central

Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.

2014-01-01

Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207

An editor for pathway drawing and data visualization in the Biopathways Workbench.

PubMed

Byrnes, Robert W; Cotter, Dawn; Maer, Andreia; Li, Joshua; Nadeau, David; Subramaniam, Shankar

2009-10-02

Pathway models serve as the basis for much of systems biology. They are often built using programs designed for the purpose. Constructing new models generally requires simultaneous access to experimental data of diverse types, to databases of well-characterized biological compounds and molecular intermediates, and to reference model pathways. However, few if any software applications provide all such capabilities within a single user interface. The Pathway Editor is a program written in the Java programming language that allows de-novo pathway creation and downloading of LIPID MAPS (Lipid Metabolites and Pathways Strategy) and KEGG lipid metabolic pathways, and of measured time-dependent changes to lipid components of metabolism. Accessed through Java Web Start, the program downloads pathways from the LIPID MAPS Pathway database (Pathway) as well as from the LIPID MAPS web server http://www.lipidmaps.org. Data arises from metabolomic (lipidomic), microarray, and protein array experiments performed by the LIPID MAPS consortium of laboratories and is arranged by experiment. Facility is provided to create, connect, and annotate nodes and processes on a drawing panel with reference to database objects and time course data. Node and interaction layout as well as data display may be configured in pathway diagrams as desired. Users may extend diagrams, and may also read and write data and non-lipidomic KEGG pathways to and from files. Pathway diagrams in XML format, containing database identifiers referencing specific compounds and experiments, can be saved to a local file for subsequent use. The program is built upon a library of classes, referred to as the Biopathways Workbench, that convert between different file formats and database objects. An example of this feature is provided in the form of read/construct/write access to models in SBML (Systems Biology Markup Language) contained in the local file system. Inclusion of access to multiple experimental data types and of pathway diagrams within a single interface, automatic updating through connectivity to an online database, and a focus on annotation, including reference to standardized lipid nomenclature as well as common lipid names, supports the view that the Pathway Editor represents a significant, practicable contribution to current pathway modeling tools.

Overcoming Resistance to Inhibitors of the Akt Protein Kinase by Modulation of the Pim Kinase Pathway

DTIC Science & Technology

2014-10-01

during hypoxia were biologically meaningful, we investigated the activity of a reporter with multiple HIF binding sites ( HRE ) in front of a luciferase...inhibitors in a dose dependent fashion blocked the activity of the HRE to activate luciferase mRNA and protein production. This result demonstrates that

Enhancing high throughput toxicology - development of putative adverse outcome pathways linking US EPA ToxCast screening targets to relevant apical hazards.

EPA Science Inventory

High throughput toxicology programs, such as ToxCast and Tox21, have provided biological effects data for thousands of chemicals at multiple concentrations. Compared to traditional, whole-organism approaches, high throughput assays are rapid and cost-effective, yet they generall...

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets

PubMed Central

2014-01-01

Background Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. Results We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways. PMID:25221624

The role of low-grade inflammation and metabolic flexibility in aging and nutritional modulation thereof: a systems biology approach.

PubMed

Calçada, Dulce; Vianello, Dario; Giampieri, Enrico; Sala, Claudia; Castellani, Gastone; de Graaf, Albert; Kremer, Bas; van Ommen, Ben; Feskens, Edith; Santoro, Aurelia; Franceschi, Claudio; Bouwman, Jildau

2014-01-01

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

An overview of bioinformatics methods for modeling biological pathways in yeast

PubMed Central

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao

2016-01-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein–protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae. In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways in S. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. PMID:26476430

Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.

2011-01-01

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212

The m6A pathway facilitates sex determination in Drosophila

PubMed Central

Kan, Lijuan; Grozhik, Anya V.; Vedanayagam, Jeffrey; Patil, Deepak P.; Pang, Nan; Lim, Kok-Seong; Huang, Yi-Chun; Joseph, Brian; Lin, Ching-Jung; Despic, Vladimir; Guo, Jian; Yan, Dong; Kondo, Shu; Deng, Wu-Min; Dedon, Peter C.; Jaffrey, Samie R.; Lai, Eric C.

2017-01-01

The conserved modification N6-methyladenosine (m6A) modulates mRNA processing and activity. Here, we establish the Drosophila system to study the m6A pathway. We first apply miCLIP to map m6A across embryogenesis, characterize its m6A ‘writer’ complex, validate its YTH ‘readers’ CG6422 and YT521-B, and generate mutants in five m6A factors. While m6A factors with additional roles in splicing are lethal, m6A-specific mutants are viable but present certain developmental and behavioural defects. Notably, m6A facilitates the master female determinant Sxl, since multiple m6A components enhance female lethality in Sxl sensitized backgrounds. The m6A pathway regulates Sxl processing directly, since miCLIP data reveal Sxl as a major intronic m6A target, and female-specific Sxl splicing is compromised in multiple m6A pathway mutants. YT521-B is a dominant m6A effector for Sxl regulation, and YT521-B overexpression can induce female-specific Sxl splicing. Overall, our transcriptomic and genetic toolkit reveals in vivo biologic function for the Drosophila m6A pathway. PMID:28675155

Protein C receptor stimulates multiple signaling pathways in breast cancer cells.

PubMed

Wang, Daisong; Liu, Chunye; Wang, Jingqiang; Jia, Yingying; Hu, Xin; Jiang, Hai; Shao, Zhi-Ming; Zeng, Yi Arial

2018-01-26

The protein C receptor (PROCR) has emerged as a stem cell marker in several normal tissues and has also been implicated in tumor progression. However, the functional role of PROCR and the signaling mechanisms downstream of PROCR remain poorly understood. Here, we dissected the PROCR signaling pathways in breast cancer cells. Combining protein array, knockdown, and overexpression methods, we found that PROCR concomitantly activates multiple pathways. We also noted that PROCR-dependent ERK and PI3k-Akt-mTOR signaling pathways proceed through Src kinase and transactivation of insulin-like growth factor 1 receptor (IGF-1R). These pathway activities led to the accumulation of c-Myc and cyclin D1. On the other hand, PROCR-dependent RhoA-ROCK-p38 signaling relied on coagulation factor II thrombin receptor (F2R). We confirmed these findings in primary cells isolated from triple-negative breast cancer-derived xenografts (PDX) that have high expression of PROCR. To the best our knowledge, this is the first comprehensive study of PROCR signaling in breast cancer cells, and its findings also shed light on the molecular mechanisms of PROCR in stem cells in normal tissue. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Molecular biology of bladder cancer.

PubMed

Martin-Doyle, William; Kwiatkowski, David J

2015-04-01

Classic as well as more recent large-scale genomic analyses have uncovered multiple genes and pathways important for bladder cancer development. Genes involved in cell-cycle control, chromatin regulation, and receptor tyrosine and PI3 kinase-mammalian target of rapamycin signaling pathways are commonly mutated in muscle-invasive bladder cancer. Expression-based analyses have identified distinct types of bladder cancer that are similar to subsets of breast cancer, and have prognostic and therapeutic significance. These observations are leading to novel therapeutic approaches in bladder cancer, providing optimism for therapeutic progress. Copyright © 2015 Elsevier Inc. All rights reserved.

DISC1 genetics, biology and psychiatric illness

PubMed Central

THOMSON, Pippa A.; MALAVASI, Elise L.V.; GRÜNEWALD, Ellen; SOARES, Dinesh C.; BORKOWSKA, Malgorzata; MILLAR, J. Kirsty

2012-01-01

Psychiatric disorders are highly heritable, and in many individuals likely arise from the combined effects of genes and the environment. A substantial body of evidence points towards DISC1 being one of the genes that influence risk of schizophrenia, bipolar disorder and depression, and functional studies of DISC1 consequently have the potential to reveal much about the pathways that lead to major mental illness. Here, we review the evidence that DISC1 influences disease risk through effects upon multiple critical pathways in the developing and adult brain. PMID:23550053

Engineering the biological conversion of methanol to specialty chemicals in Escherichia coli

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

Whitaker, W. Brian; Jones, J. Andrew; Bennett, R. Kyle

Methanol is an attractive substrate for biological production of chemicals and fuels. Engineering methylotrophic Escherichia coli as a platform organism for converting methanol to metabolites is desirable. Prior efforts to engineer methylotrophic E. coli were limited by methanol dehydrogenases (Mdhs) with unfavorable enzyme kinetics. We engineered E. coli to utilize methanol using a superior NAD-dependent Mdh from Bacillus stearothermophilus and ribulose monophosphate (RuMP) pathway enzymes from B. methanolicus. Using 13C-labeling, we demonstrate this E. coli strain converts methanol into biomass components. For example, the key TCA cycle intermediates, succinate and malate, exhibit labeling up to 39%, while the lower glycolyticmore » intermediate, 3-phosphoglycerate, up to 53%. Multiple carbons are labeled for each compound, demonstrating a cycling RuMP pathway for methanol assimilation to support growth. In conclusion, by incorporating the pathway to synthesize the flavanone naringenin, we demonstrate the first example of in vivo conversion of methanol into a specialty chemical in E. coli.« less

Genomancy: predicting tumour response to cancer therapy based on the oracle of genetics.

PubMed

Williams, P D; Lee, J K; Theodorescu, D

2009-01-01

Cells are complex systems that regulate a multitude of biologic pathways involving a diverse array of molecules. Cancer can develop when these pathways become deregulated as a result of mutations in the genes coding for these proteins or of epigenetic changes that affect gene expression, or both1,2. The diversity and interconnectedness of these pathways and their molecular components implies that a variety of mutations may lead to tumorigenic cellular deregulation3-6. This variety, combined with the requirement to overcome multiple anticancer defence mechanisms7, contributes to the heterogeneous nature of cancer. Consequently, tumours with similar histology may vary in their underlying molecular circuitry8-10, with resultant differences in biologic behaviour, manifested in proliferation rate, invasiveness, metastatic potential, and unfortunately, response to cytotoxic therapy. Thus, cancer can be thought of as a family of related tumour subtypes, highlighting the need for individualized prediction both of disease progression and of treatment response, based on the molecular characteristics of the tumour.

Engineering the biological conversion of methanol to specialty chemicals in Escherichia coli

DOE PAGES

Whitaker, W. Brian; Jones, J. Andrew; Bennett, R. Kyle; ...

2016-11-01

Methanol is an attractive substrate for biological production of chemicals and fuels. Engineering methylotrophic Escherichia coli as a platform organism for converting methanol to metabolites is desirable. Prior efforts to engineer methylotrophic E. coli were limited by methanol dehydrogenases (Mdhs) with unfavorable enzyme kinetics. We engineered E. coli to utilize methanol using a superior NAD-dependent Mdh from Bacillus stearothermophilus and ribulose monophosphate (RuMP) pathway enzymes from B. methanolicus. Using 13C-labeling, we demonstrate this E. coli strain converts methanol into biomass components. For example, the key TCA cycle intermediates, succinate and malate, exhibit labeling up to 39%, while the lower glycolyticmore » intermediate, 3-phosphoglycerate, up to 53%. Multiple carbons are labeled for each compound, demonstrating a cycling RuMP pathway for methanol assimilation to support growth. In conclusion, by incorporating the pathway to synthesize the flavanone naringenin, we demonstrate the first example of in vivo conversion of methanol into a specialty chemical in E. coli.« less

Hepatic Proteomic Analysis Revealed Altered Metabolic Pathways in Insulin Resistant Akt1+/-/Akt2-/-Mice

PubMed Central

Pedersen, Brian A; Wang, Weiwen; Taylor, Jared F; Khattab, Omar S; Chen, Yu-Han; Edwards, Robert A; Yazdi, Puya G; Wang, Ping H

2015-01-01

Objective The aim of this study was to identify liver proteome changes in a mouse model of severe insulin resistance and markedly decreased leptin levels. Methods Two-dimensional differential gel electrophoresis was utilized to identify liver proteome changes in AKT1+/-/AKT2-/- mice. Proteins with altered levels were identified with tandem mass spectrometry. Ingenuity Pathway analysis was performed for the interpretation of the biological significance of the observed proteomic changes. Results 11 proteins were identified from 2 biological replicates to be differentially expressed by a ratio of at least 1.3 between age-matched insulin resistant (Akt1+/-/Akt2-/-) and wild type mice. Albumin and mitochondrial ornithine aminotransferase were detected from multiple spots, which suggest post-translational modifications. Enzymes of the urea cycle were common members of top regulated pathways. Conclusion Our results help to unveil the regulation of the liver proteome underlying altered metabolism in an animal model of severe insulin resistance. PMID:26455965

Engineering the biological conversion of methanol to specialty chemicals in Escherichia coli.

PubMed

Whitaker, W Brian; Jones, J Andrew; Bennett, R Kyle; Gonzalez, Jacqueline E; Vernacchio, Victoria R; Collins, Shannon M; Palmer, Michael A; Schmidt, Samuel; Antoniewicz, Maciek R; Koffas, Mattheos A; Papoutsakis, Eleftherios T

2017-01-01

Methanol is an attractive substrate for biological production of chemicals and fuels. Engineering methylotrophic Escherichia coli as a platform organism for converting methanol to metabolites is desirable. Prior efforts to engineer methylotrophic E. coli were limited by methanol dehydrogenases (Mdhs) with unfavorable enzyme kinetics. We engineered E. coli to utilize methanol using a superior NAD-dependent Mdh from Bacillus stearothermophilus and ribulose monophosphate (RuMP) pathway enzymes from B. methanolicus. Using 13 C-labeling, we demonstrate this E. coli strain converts methanol into biomass components. For example, the key TCA cycle intermediates, succinate and malate, exhibit labeling up to 39%, while the lower glycolytic intermediate, 3-phosphoglycerate, up to 53%. Multiple carbons are labeled for each compound, demonstrating a cycling RuMP pathway for methanol assimilation to support growth. By incorporating the pathway to synthesize the flavanone naringenin, we demonstrate the first example of in vivo conversion of methanol into a specialty chemical in E. coli. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

PubMed

Dean, Jeffry L; Zhao, Q Jay; Lambert, Jason C; Hawkins, Belinda S; Thomas, Russell S; Wesselkamper, Scott C

2017-05-01

The rate of new chemical development in commerce combined with a paucity of toxicity data for legacy chemicals presents a unique challenge for human health risk assessment. There is a clear need to develop new technologies and incorporate novel data streams to more efficiently inform derivation of toxicity values. One avenue of exploitation lies in the field of transcriptomics and the application of gene expression analysis to characterize biological responses to chemical exposures. In this context, gene set enrichment analysis (GSEA) was employed to evaluate tissue-specific, dose-response gene expression data generated following exposure to multiple chemicals for various durations. Patterns of transcriptional enrichment were evident across time and with increasing dose, and coordinated enrichment plausibly linked to the etiology of the biological responses was observed. GSEA was able to capture both transient and sustained transcriptional enrichment events facilitating differentiation between adaptive versus longer term molecular responses. When combined with benchmark dose (BMD) modeling of gene expression data from key drivers of biological enrichment, GSEA facilitated characterization of dose ranges required for enrichment of biologically relevant molecular signaling pathways, and promoted comparison of the activation dose ranges required for individual pathways. Median transcriptional BMD values were calculated for the most sensitive enriched pathway as well as the overall median BMD value for key gene members of significantly enriched pathways, and both were observed to be good estimates of the most sensitive apical endpoint BMD value. Together, these efforts support the application of GSEA to qualitative and quantitative human health risk assessment. Published by Oxford University Press on behalf of the Society of Toxicology 2017. This work is written by US Government employees and is in the public domain in the US.

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Is the canonical RAF-MEK-ERK signaling pathway a therapeutic target in SCLC?

PubMed Central

Cristea, Sandra; Sage, Julien

2017-01-01

The activity of the RAF-MEK-ERK signaling pathway is critical for the proliferation of normal and cancerous cells. Oncogenic mutations driving the development of lung adenocarcinoma often activate this signaling pathway. In contrast, pathway activity levels and their biological roles are not well established in small cell lung cancer (SCLC), a fast-growing neuroendocrine lung cancer subtype. Here we discuss the function of the RAF-MEK-ERK kinase pathway and the mechanisms leading to its activation in SCLC cells. In particular, we argue that activation of this pathway may be beneficial to the survival, proliferation and spread of SCLC cells in response to multiple stimuli. We also consider evidence that high levels of RAF-MEK-ERK pathway activity may be detrimental to SCLC tumors, including in part by interfering with their neuroendocrine fate. Based on these observations, we examine when small molecules targeting kinases in the RAF-MEK-ERK pathway may be useful therapeutically in SCLC patients, including in combination with other therapeutic agents. PMID:27133774

An overview of bioinformatics methods for modeling biological pathways in yeast.

PubMed

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A pathway-based network analysis of hypertension-related genes

NASA Astrophysics Data System (ADS)

Wang, Huan; Hu, Jing-Bo; Xu, Chuan-Yun; Zhang, De-Hai; Yan, Qian; Xu, Ming; Cao, Ke-Fei; Zhang, Xu-Sheng

2016-02-01

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes.

Metabolic engineering of Bacillus subtilis fueled by systems biology: Recent advances and future directions.

PubMed

Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long

By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization. Copyright © 2016 Elsevier Inc. All rights reserved.

Genes and pathways co-associated with the exposure to multiple drugs of abuse, including alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine, and/or nicotine: a review of proteomics analyses.

PubMed

Wang, Ju; Yuan, Wenji; Li, Ming D

2011-12-01

Drug addiction is a chronic neuronal disease. In recent years, proteomics technology has been widely used to assess the protein expression in the brain tissues of both animals and humans exposed to addictive drugs. Through this approach, a large number of proteins potentially involved in the etiology of drug addictions have been identified, which provide a valuable resource to study protein function, biochemical pathways, and networks related to the molecular mechanisms underlying drug dependence. In this article, we summarize the recent application of proteomics to profiling protein expression patterns in animal or human brain tissues after the administration of alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine/heroin/butorphanol, or nicotine. From available reports, we compiled a list of 497 proteins associated with exposure to one or more addictive drugs, with 160 being related to exposure to at least two abused drugs. A number of biochemical pathways and biological processes appear to be enriched among these proteins, including synaptic transmission and signaling pathways related to neuronal functions. The data included in this work provide a summary and extension of the proteomics studies on drug addiction. Furthermore, the proteins and biological processes highlighted here may provide valuable insight into the cellular activities and biological processes in neurons in the development of drug addiction.

MASM, a Matrine Derivative, Offers Radioprotection by Modulating Lethal Total-Body Irradiation-Induced Multiple Signaling Pathways in Wistar Rats.

PubMed

Li, Jianzhong; Xu, Jing; Lu, Yiming; Qiu, Lei; Xu, Weiheng; Lu, Bin; Hu, Zhenlin; Chu, Zhiyong; Chai, Yifeng; Zhang, Junping

2016-05-17

Matrine is an alkaloid extracted from Sophora flavescens Ait and has many biological activities, such as anti-inflammatory, antitumor, anti-fibrosis, and immunosuppressive properties. In our previous studies, the matrine derivative MASM was synthesized and exhibited potent inhibitory activity against liver fibrosis. In this study, we mainly investigated its protection against lethal total-body irradiation (TBI) in rats. Administration of MASM reduced the radiation sickness characteristics and increased the 30-day survival of rats before or after lethal TBI. Ultrastructural observation illustrated that pretreatment of rats with MASM significantly attenuated the TBI-induced morphological changes in the different organs of irradiated rats. Gene expression profiles revealed that pretreatment with MASM had a dramatic effect on gene expression changes caused by TBI. Pretreatment with MASM prevented differential expression of 53% (765 genes) of 1445 differentially expressed genes induced by TBI. Pathway enrichment analysis indicated that these genes were mainly involved in a total of 21 pathways, such as metabolic pathways, pathways in cancer, and mitogen-activated protein kinase (MAPK) pathways. Our data indicated that pretreatment of rats with MASM modulated these pathways induced by TBI, suggesting that the pretreatment with MASM might provide the protective effects on lethal TBI mainly or partially through the modulation of these pathways, such as multiple MAPK pathways. Therefore, MASM has the potential to be used as an effective therapeutic or radioprotective agent to minimize irradiation damages and in combination with radiotherapy to improve the efficacy of cancer therapy.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species.

PubMed

Perumal, Deepak; Lim, Chu Sing; Chow, Vincent T K; Sakharkar, Kishore R; Sakharkar, Meena K

2008-09-10

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

NOVEL ROLES FOR INSULIN RECEPTOR (IR) IN ADIPOCYTES AND SKELETAL MUSCLE CELLS VIA NEW AND UNEXPECTED SUBSTRATES

PubMed Central

Ramalingam, Latha; Oh, Eunjin; Thurmond, Debbie C.

2012-01-01

The insulin signaling pathway regulates whole-body glucose homeostasis by transducing extracellular signals from the insulin receptor (IR) to downstream intracellular targets, thus coordinating a multitude of biological functions. Dysregulation of IR or its signal transduction is associated with insulin resistance, which may culminate in type 2 diabetes (T2D). Following initial stimulation of IR, insulin signaling diverges into different pathways, activating multiple substrates which have roles in various metabolic and cellular processes. The integration of multiple pathways arising from IR activation continues to expand as new IR substrates are identified and characterized. Accordingly, our review will focus on roles for IR substrates as they pertain to three primary areas: Metabolism/glucose uptake, Mitogenesis/growth, and Aging/Longevity. While IR functions in a seemingly pleotropic manner in many cell types, through these three main roles in fat and skeletal muscle cells, IR multi-tasks to regulate whole-body glucose homeostasis to impact healthspan and lifespan. PMID:23052216

A novel curcumin derivative for the treatment of diabetic neuropathy.

PubMed

Daugherty, Daniel J; Marquez, Alexandra; Calcutt, Nigel A; Schubert, David

2018-02-01

Neuropathy is a common complication of long-term diabetes. Proposed mechanisms of neuronal damage caused by diabetes that are downstream of hyperglycemia and/or loss of insulin signaling include ischemic hypoxia, inflammation and loss of neurotrophic support. The curcumin derivative J147 is a potent neurogenic and neuroprotective drug candidate initially developed for the treatment of neurodegenerative conditions associated with aging that impacts many pathways implicated in the pathogenesis of diabetic neuropathy. Here, we demonstrate efficacy of J147 in ameliorating multiple indices of neuropathy in the streptozotocin-induced mouse model of type 1 diabetes. Diabetes was determined by blood glucose, HbA1c, and insulin levels and efficacy of J147 by behavioral, physiologic, biochemical, proteomic, and transcriptomic assays. Biological efficacy of systemic J147 treatment was confirmed by its capacity to decrease TNFα pathway activation and several other markers of neuroinflammation in the CNS. Chronic oral treatment with J147 protected the sciatic nerve from progressive diabetes-induced slowing of large myelinated fiber conduction velocity while single doses of J147 rapidly and transiently reversed established touch-evoked allodynia. Conduction slowing and allodynia are clinically relevant markers of early diabetic neuropathy and neuropathic pain, respectively. RNA expression profiling suggests that one of the pathways by which J147 imparts its protection against diabetic induced neuropathy may be through activation of the AMP kinase pathway. The diverse biological and therapeutic effects of J147 suggest it as an alternative to the polypharmaceutical approaches required to treat the multiple pathogenic mechanisms that contribute to diabetic neuropathy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

PubMed Central

Kawakami, Eiryo; Singh, Vivek K; Matsubara, Kazuko; Ishii, Takashi; Matsuoka, Yukiko; Hase, Takeshi; Kulkarni, Priya; Siddiqui, Kenaz; Kodilkar, Janhavi; Danve, Nitisha; Subramanian, Indhupriya; Katoh, Manami; Shimizu-Yoshida, Yuki; Ghosh, Samik; Jere, Abhay; Kitano, Hiroaki

2016-01-01

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker’s or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow–tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow–tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems. PMID:28725465

One-Carbon Metabolism in Health and Disease

PubMed Central

Ducker, Gregory S.; Rabinowitz, Joshua D.

2017-01-01

One-carbon (1C) metabolism, mediated by the folate cofactor, supports multiple physiological processes. These include biosynthesis (purines and thymidine), amino acid homeostasis (glycine, serine, and methionine), epigenetic maintenance, and redox defense. Both within eukaryotic cells and across organs, 1C metabolic reactions are compartmentalized. Here we review the fundamentals of mammalian 1C metabolism, including the pathways active in different compartments, cell types, and biological states. Emphasis is given to recent discoveries enabled by modern genetics, analytical chemistry, and isotope tracing. An emerging theme is the biological importance of mitochondrial 1C reactions, both for producing 1C units that are exported to the cytosol and for making additional products, including glycine and NADPH. Increased clarity regarding differential folate pathway usage in cancer, stem cells, development, and adult physiology is reviewed and highlights new opportunities for selective therapeutic intervention. PMID:27641100

Fisetin Acts on Multiple Pathways to Reduce the Impact of Age and Disease on CNS Function

PubMed Central

Maher, Pamela

2017-01-01

It is becoming increasingly clear that neurological diseases are multi-factorial involving disruptions in multiple cellular systems. Thus, while each disease has its own initiating mechanisms and pathologies, certain common pathways appear to be involved in most, if not all, neurological diseases described to date. Thus, it is unlikely that modulating only a single factor will be effective at either preventing disease development or slowing disease progression. A better approach is to identify small (< 900 daltons) molecules that have multiple biological activities relevant to the maintenance of brain function. Over the last few years, we have identified an orally active, novel neuroprotective and cognition-enhancing molecule, the flavonoid fisetin. Fisetin not only has direct antioxidant activity but it can also increase the intracellular levels of glutathione, the major intracellular antioxidant. Fisetin can also activate key neurotrophic factor signaling pathways. In addition, it has anti-inflammatory activity against microglial cells and inhibits the activity of lipoxygenases, thereby reducing the production of pro-inflammatory eicosanoids and their by-products. This wide range of actions suggests that fisetin has the ability to reduce the impact of age-related neurological diseases on brain function. PMID:25961687

Modern Radiobiology: Contention Of Concepts: Advanced Technology And Development Of Effective Prophylaxis, Prevention And Treatment Of Biological Consequences After Irradiation.

NASA Astrophysics Data System (ADS)

Popov, Dmitri; Maliev, Vecheslav; Jones, Jeffrey

"Alle Ding' sind Gift, und nichts ohn' Gift; allein die Dosis macht, daß ein Ding kein Gift ist." Paracelsus Philippus Aureolus Theophrastus Bombastus von Hohenheim. Key worlds: Apoptosis, Necrosis, Domains associated with Cell Death, Caspase (catalytic) Domains, Death Domains (DDs), Death Effector Domains (DEDs), Caspase-Associated Recruitment Domains (CARDs, BIR Domains (IAPs), Bcl-2 Homology (BH) Domains, death ligands - TRAIL (TNF-Related Apoptosis-Inducing Ligand), FasL (Fas Ligand), TNFalpha (Tumor Necrosis Factor alpha), Toll-like receptors (TLR), Systemic inflammatory response syndrome (SIRS), Toxic Multiple Organ Injury (TMOI), Toxic Multiple Organ Dysfunction Syndromes (TMODS), Toxic Multiple Organ Failure (TMOF), Anaphylatoxins, or complement peptides; membrane attack complex (MAC), ROS - Reactive Oxygen Species; ASMase, acid sphingomyelinase; Neurotoxins, Cytotoxins, Haemotoxins. Introduction: Radiation affects many cell structures, organelles and metabolic pathways. Different doses and types of radiation ( gamma-radiation, neutron, heavy ion radiation) progress to reversible and irreversible forms of cell injury. Consideration: Apoptosis and Necrosis, major forms of post-radiation cell death, can be initiated and modulated by programmed control and proceed by similar or different pathways.[Akadi et al.,1993, Dunlacht J., et al. 1999] Radiation induced cell death by triggering apoptosis pathways was described in many articles and supported by many scientists. [Rio et al. 2002, Rakesh et al. 1997.] However some authors present results that two distinct pathways can initiate or apoptotic or necrotic responses: the death receptors and mitochondrial pathways.

Therapeutic Efficacy of Suppressing the JAK/STAT Pathway in Multiple Models of EAE1

PubMed Central

Liu, Yudong; Holdbrooks, Andrew T.; De Sarno, Patrizia; Rowse, Amber L.; Yanagisawa, Lora L.; McFarland, Braden C.; Harrington, Laurie E.; Raman, Chander; Sabbaj, Steffanie; Benveniste, Etty N.; Qin, Hongwei

2014-01-01

Pathogenic T helper cells and myeloid cells are involved in the pathogenesis of Multiple Sclerosis (MS) and Experimental Autoimmune Encephalomyelitis (EAE), an animal model of MS. The JAK/STAT pathway is utilized by numerous cytokines for signaling, and is critical for development, regulation and termination of immune responses. Dysregulation of the JAK/STAT pathway has pathological implications in autoimmune and neuroinflammatory diseases. Many of the cytokines involved in MS/EAE, including IL-6, IL-12, IL-23, IFN-γ and GM-CSF, use the JAK/STAT pathway to induce biological responses. Thus, targeting JAKs has implications for treating autoimmune inflammation of the brain. We have utilized AZD1480, a JAK1/2 inhibitor, to investigate the therapeutic potential of inhibiting the JAK/STAT pathway in models of EAE. AZD1480 treatment inhibits disease severity in MOG-induced classical and atypical EAE models by preventing entry of immune cells into the brain, suppressing differentiation of Th1 and Th17 cells, deactivating myeloid cells, inhibiting STAT activation in the brain, and reducing expression of pro-inflammatory cytokines and chemokines. Treatment of SJL/J mice with AZD1480 delays disease onset of PLP-induced relapsing-remitting disease, reduces relapses and diminishes clinical severity. AZD1480 treatment was also effective in reducing ongoing paralysis induced by adoptive transfer of either pathogenic Th1 or Th17 cells. In vivo AZD1480 treatment impairs both the priming and expansion of T-cells, and attenuates antigen-presentation functions of myeloid cells. Inhibition of the JAK/STAT pathway has clinical efficacy in multiple pre-clinical models of MS, suggesting the feasibility of the JAK/STAT pathway as a target for neuroinflammatory diseases. PMID:24323580

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

PubMed

Miannay, Bertrand; Minvielle, Stéphane; Magrangeas, Florence; Guziolowski, Carito

2018-03-21

The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level. We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP. We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer. We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.

OXIDATIVE STRESS: BIOMARKERS AND NOVEL THERAPEUTIC PATHWAYS

PubMed Central

Maiese, Kenneth; Chong, Zhao Zhong; Hou, Jinling; Shang, Yan Chen

2010-01-01

Oxidative stress significantly impacts multiple cellular pathways that can lead to the initiation and progression of varied disorders throughout the body. It therefore becomes imperative to elucidate the components and function of novel therapeutic strategies against oxidative stress to further clinical diagnosis and care. In particular, both the growth factor and cytokine erythropoietin (EPO) and members of the mammalian forkhead transcription factors of the O class (FoxOs) may offer the greatest promise for new treatment regimens since these agents and the cellular pathways they oversee cover a range of critical functions that directly influence progenitor cell development, cell survival and degeneration, metabolism, immune function, and cancer cell invasion. Furthermore, both EPO and FoxOs function not only as therapeutic targets, but also as biomarkers of disease onset and progression, since their cellular pathways are closely linked and overlap with several unique signal transduction pathways. However, biological outcome with EPO and FoxOs may sometimes be both unexpected and undesirable that can raise caution for these agents and warrant further investigations. Here we present the exciting as well as complicated role EPO and FoxOs possess to uncover the benefits as well as the risks of these agents for cell biology and clinical care in processes that range from stem cell development to uncontrolled cellular proliferation. PMID:20064603

Molecular mechanism of TGF-β signaling pathway in colon carcinogenesis and status of curcumin as chemopreventive strategy.

PubMed

Ramamoorthi, Ganesan; Sivalingam, Nageswaran

2014-08-01

Colon cancer is one of the third most common cancer in man, the second most common cancer in women worldwide, and the second leading cause of mortality in the USA. There are a number of molecular pathways that have been implicated in colon carcinogenesis, including TGF-β/Smad signaling pathway. TGF-β (transforming growth factor-beta) signaling pathway has the potential to regulate various biological processes including cell growth, differentiation, apoptosis, extracellular matrix modeling, and immune response. TGF-β signaling pathway acts as a tumor suppressor, but alterations in TGF-β signaling pathway promotes colon cancer cell growth, migration, invasion, angiogenesis, and metastasis. Here we review the role of TGF-β signaling cascade in colon carcinogenesis and multiple molecular targets of curcumin in colon carcinogenesis. Elucidation of the molecular mechanism of curcumin on TGF-β signaling pathway-induced colon carcinogenesis may ultimately lead to novel and more effective treatments for colon cancer.

Prioritizing biological pathways by recognizing context in time-series gene expression data.

PubMed

Lee, Jusang; Jo, Kyuri; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

2016-12-23

The primary goal of pathway analysis using transcriptome data is to find significantly perturbed pathways. However, pathway analysis is not always successful in identifying pathways that are truly relevant to the context under study. A major reason for this difficulty is that a single gene is involved in multiple pathways. In the KEGG pathway database, there are 146 genes, each of which is involved in more than 20 pathways. Thus activation of even a single gene will result in activation of many pathways. This complex relationship often makes the pathway analysis very difficult. While we need much more powerful pathway analysis methods, a readily available alternative way is to incorporate the literature information. In this study, we propose a novel approach for prioritizing pathways by combining results from both pathway analysis tools and literature information. The basic idea is as follows. Whenever there are enough articles that provide evidence on which pathways are relevant to the context, we can be assured that the pathways are indeed related to the context, which is termed as relevance in this paper. However, if there are few or no articles reported, then we should rely on the results from the pathway analysis tools, which is termed as significance in this paper. We realized this concept as an algorithm by introducing Context Score and Impact Score and then combining the two into a single score. Our method ranked truly relevant pathways significantly higher than existing pathway analysis tools in experiments with two data sets. Our novel framework was implemented as ContextTRAP by utilizing two existing tools, TRAP and BEST. ContextTRAP will be a useful tool for the pathway based analysis of gene expression data since the user can specify the context of the biological experiment in a set of keywords. The web version of ContextTRAP is available at http://biohealth.snu.ac.kr/software/contextTRAP .

Identification of mutated driver pathways in cancer using a multi-objective optimization model.

PubMed

Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

2016-05-01

New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neuroproteomics approach and neurosystems biology analysis: ROCK inhibitors as promising therapeutic targets in neurodegeneration and neurotrauma.

PubMed

Raad, Mohamad; El Tal, Tala; Gul, Rukhsana; Mondello, Stefania; Zhang, Zhiqun; Boustany, Rose-Mary; Guingab, Joy; Wang, Kevin K; Kobeissy, Firas

2012-12-01

Several common degenerative mechanisms and mediators underlying the neuronal injury pathways characterize several neurodegenerative diseases including Alzheimer's, Parkinson's, and Huntington's disease, as well as brain neurotrauma. Such common ground invites the emergence of new approaches and tools to study the altered pathways involved in neural injury alongside with neuritogenesis, an intricate process that commences with neuronal differentiation. Achieving a greater understanding of the impaired pathways of neuritogenesis would significantly help in uncovering detailed mechanisms of axonal regeneration. Among the several agents involved in neuritogenesis are the Rho and Rho kinases (ROCKs), which constitute key integral points in the Rho/ROCK pathway that is known to be disrupted in multiple neuropathologies such as spinal cord injury, traumatic brain injury, and Alzheimer's disease. This in turn renders ROCK inhibition as a promising candidate for therapeutic targets for treatment of neurodegenerative diseases. Among the novel tools to investigate the mechanisms involved in a specific disorder is the use of neuroproteomics/systems biology approach, a growing subfield of bioinformatics aiming to study and establishing a global assessment of the entire neuronal proteome, addressing the dynamic protein changes and interactions. This review aims to examine recent updates regarding how neuroproteomics aids in the understanding of molecular mechanisms of activation and inhibition in the area of neurogenesis and how Rho/ROCK pathway/ROCK inhibitors, primarily Y-27632 and Fasudil compounds, are applied in biological settings, promoting neuronal survival and neuroprotection that has direct future implications in neurotrauma. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A basic helix-loop-helix transcription factor, PhFBH4, regulates flower senescence by modulating ethylene biosynthesis pathway in petunia

USDA-ARS?s Scientific Manuscript database

The basic helix-loop-helix (bHLH) transcription factors (TFs) play important roles in regulating multiple biological processes in plants. However, there are few reports about the function of bHLHs in flower senescence. In this study, a bHLH TF, PhFBH4, was found to be dramatically upregulated during...

Chromatographic analysis of tryptophan metabolites

PubMed Central

Sadok, Ilona; Gamian, Andrzej

2017-01-01

The kynurenine pathway generates multiple tryptophan metabolites called collectively kynurenines and leads to formation of the enzyme cofactor nicotinamide adenine dinucleotide. The first step in this pathway is tryptophan degradation, initiated by the rate‐limiting enzymes indoleamine 2,3‐dioxygenase, or tryptophan 2,3‐dioxygenase, depending on the tissue. The balanced kynurenine metabolism, which has been a subject of multiple studies in last decades, plays an important role in several physiological and pathological conditions such as infections, autoimmunity, neurological disorders, cancer, cataracts, as well as pregnancy. Understanding the regulation of tryptophan depletion provide novel diagnostic and treatment opportunities, however it requires reliable methods for quantification of kynurenines in biological samples with complex composition (body fluids, tissues, or cells). Trace concentrations, interference of sample components, and instability of some tryptophan metabolites need to be addressed using analytical methods. The novel separation approaches and optimized extraction protocols help to overcome difficulties in analyzing kynurenines within the complex tissue material. Recent developments in chromatography coupled with mass spectrometry provide new opportunity for quantification of tryptophan and its degradation products in various biological samples. In this review, we present current accomplishments in the chromatographic methodologies proposed for detection of tryptophan metabolites and provide a guide for choosing the optimal approach. PMID:28590049

Immediate Early Genes Anchor a Biological Pathway of Proteins Required for Memory Formation, Long-Term Depression and Risk for Schizophrenia

PubMed Central

Marballi, Ketan K.; Gallitano, Amelia L.

2018-01-01

While the causes of myriad medical and infectious illnesses have been identified, the etiologies of neuropsychiatric illnesses remain elusive. This is due to two major obstacles. First, the risk for neuropsychiatric disorders, such as schizophrenia, is determined by both genetic and environmental factors. Second, numerous genes influence susceptibility for these illnesses. Genome-wide association studies have identified at least 108 genomic loci for schizophrenia, and more are expected to be published shortly. In addition, numerous biological processes contribute to the neuropathology underlying schizophrenia. These include immune dysfunction, synaptic and myelination deficits, vascular abnormalities, growth factor disruption, and N-methyl-D-aspartate receptor (NMDAR) hypofunction. However, the field of psychiatric genetics lacks a unifying model to explain how environment may interact with numerous genes to influence these various biological processes and cause schizophrenia. Here we describe a biological cascade of proteins that are activated in response to environmental stimuli such as stress, a schizophrenia risk factor. The central proteins in this pathway are critical mediators of memory formation and a particular form of hippocampal synaptic plasticity, long-term depression (LTD). Each of these proteins is also implicated in schizophrenia risk. In fact, the pathway includes four genes that map to the 108 loci associated with schizophrenia: GRIN2A, nuclear factor of activated T-cells (NFATc3), early growth response 1 (EGR1) and NGFI-A Binding Protein 2 (NAB2); each of which contains the “Index single nucleotide polymorphism (SNP)” (most SNP) at its respective locus. Environmental stimuli activate this biological pathway in neurons, resulting in induction of EGR immediate early genes: EGR1, EGR3 and NAB2. We hypothesize that dysfunction in any of the genes in this pathway disrupts the normal activation of Egrs in response to stress. This may result in insufficient electrophysiologic, immunologic, and neuroprotective, processes that these genes normally mediate. Continued adverse environmental experiences, over time, may thereby result in neuropathology that gives rise to the symptoms of schizophrenia. By combining multiple genes associated with schizophrenia susceptibility, in a functional cascade triggered by neuronal activity, the proposed biological pathway provides an explanation for both the polygenic and environmental influences that determine the complex etiology of this mental illness. PMID:29520222

New challenges for text mining: mapping between text and manually curated pathways

PubMed Central

Oda, Kanae; Kim, Jin-Dong; Ohta, Tomoko; Okanohara, Daisuke; Matsuzaki, Takuya; Tateisi, Yuka; Tsujii, Jun'ichi

2008-01-01

Background Associating literature with pathways poses new challenges to the Text Mining (TM) community. There are three main challenges to this task: (1) the identification of the mapping position of a specific entity or reaction in a given pathway, (2) the recognition of the causal relationships among multiple reactions, and (3) the formulation and implementation of required inferences based on biological domain knowledge. Results To address these challenges, we constructed new resources to link the text with a model pathway; they are: the GENIA pathway corpus with event annotation and NF-kB pathway. Through their detailed analysis, we address the untapped resource, ‘bio-inference,’ as well as the differences between text and pathway representation. Here, we show the precise comparisons of their representations and the nine classes of ‘bio-inference’ schemes observed in the pathway corpus. Conclusions We believe that the creation of such rich resources and their detailed analysis is the significant first step for accelerating the research of the automatic construction of pathway from text. PMID:18426550

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

PubMed Central

Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron

2016-01-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094

The R-spondin family of proteins: emerging regulators of WNT signaling

PubMed Central

Jin, Yong-Ri; Yoon, Jeong Kyo

2012-01-01

Recently, the R-spondin (RSPO) family of proteins has emerged as important regulators of WNT signaling. Considering the wide spectrum of WNT signaling functions in normal biological processes and disease conditions, there has been a significantly growing interest in understanding the functional roles of RSPOs in multiple biological processes and determining the molecular mechanisms by which RSPOs regulate the WNT signaling pathway. Recent advances in the RSPO research field revealed some of the in vivo functions of RSPOs and provided new information regarding the mechanistic roles of RSPO activity in regulation of WNT signaling. Herein, we review recent progress in RSPO research with an emphasis on signaling mechanisms and biological functions. PMID:22982762

Defining a Computational Framework for the Assessment of ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework describes the effects of environmental stressors across multiple scales of biological organization and function. This includes an evaluation of the potential for each key event to occur across a broad range of species in order to determine the taxonomic applicability of each AOP. Computational tools are needed to facilitate this process. Recently, we developed a tool that uses sequence homology to evaluate the applicability of molecular initiating events across species (Lalone et al., Toxicol. Sci., 2016). To extend our ability to make computational predictions at higher levels of biological organization, we have created the AOPdb. This database links molecular targets identified associated with key events in the AOPwiki to publically available data (e.g. gene-protein, pathway, species orthology, ontology, chemical, disease) including ToxCast assay information. The AOPdb combines different data types in order to characterize the impacts of chemicals to human health and the environment and serves as a decision support tool for case study development in the area of taxonomic applicability. As a proof of concept, the AOPdb allows identification of relevant molecular targets, biological pathways, and chemical and disease associations across species for four AOPs from the AOP-Wiki (https://aopwiki.org): Estrogen receptor antagonism leading to reproductive dysfunction (Aop:30); Aromatase inhibition leading to reproductive d

Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry*

PubMed Central

Hewel, Johannes A.; Liu, Jian; Onishi, Kento; Fong, Vincent; Chandran, Shamanta; Olsen, Jonathan B.; Pogoutse, Oxana; Schutkowski, Mike; Wenschuh, Holger; Winkler, Dirk F. H.; Eckler, Larry; Zandstra, Peter W.; Emili, Andrew

2010-01-01

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including “label-free” quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations. PMID:20467045

Droplet microfluidics for synthetic biology

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

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Droplet microfluidics for synthetic biology

DOE PAGES

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee; ...

2017-08-10

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Signal persistence and amplification in cancer development and possible, related opportunities for novel therapies.

PubMed

Ford, Shea A; Blanck, George

2015-01-01

Research in cancer biology has been largely driven by experimental approaches whereby discreet inputs are used to assess discreet outputs, for example, gene-knockouts to assess cancer occurrence. However, cancer hallmarks are only rarely, if ever, exclusively dependent on discreet regulatory processes. Rather, cancer-related regulatory factors affect multiple cancer hallmarks. Thus, novel approaches and paradigms are needed for further advances. Signal pathway persistence and amplification, rather than signal pathway activation resulting from an on/off switch, represent emerging paradigms for cancer research, closely related to developmental regulatory paradigms. In this review, we address both mechanisms and effects of signal pathway persistence and amplification in cancer settings; and address the possibility that hyper-activation of pro-proliferative signal pathways in certain cancer settings could be exploited for therapy. Copyright © 2014. Published by Elsevier B.V.

Chemical genetics and regeneration.

PubMed

Sengupta, Sumitra; Zhang, Liyun; Mumm, Jeff S

2015-01-01

Regeneration involves interactions between multiple signaling pathways acting in a spatially and temporally complex manner. As signaling pathways are highly conserved, understanding how regeneration is controlled in animal models exhibiting robust regenerative capacities should aid efforts to stimulate repair in humans. One way to discover molecular regulators of regeneration is to alter gene/protein function and quantify effect(s) on the regenerative process: dedifferentiation/reprograming, stem/progenitor proliferation, migration/remodeling, progenitor cell differentiation and resolution. A powerful approach for applying this strategy to regenerative biology is chemical genetics, the use of small-molecule modulators of specific targets or signaling pathways. Here, we review advances that have been made using chemical genetics for hypothesis-focused and discovery-driven studies aimed at furthering understanding of how regeneration is controlled.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

Radiogenomics: a systems biology approach to understanding genetic risk factors for radiotherapy toxicity ?

PubMed Central

Herskind, Carsten; Talbot, Christopher J.; Kerns, Sarah L.; Veldwijk, Marlon R.; Rosenstein, Barry S.; West, Catharine M. L.

2016-01-01

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review ‘omics’ approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different ‘omics’ approaches may be more efficient in identifying critical pathways than pathway analysis based on single ‘omics’ data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterized by different mechanisms. Thus ‘omics’ and functional approaches may synergize if they are integrated into radiogenomics ‘systems biology’ to facilitate the goal of individualised radiotherapy. PMID:26944314

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

PubMed Central

2012-01-01

Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440

Modeling Drug- and Chemical-Induced Hepatotoxicity with Systems Biology Approaches

PubMed Central

Bhattacharya, Sudin; Shoda, Lisl K.M.; Zhang, Qiang; Woods, Courtney G.; Howell, Brett A.; Siler, Scott Q.; Woodhead, Jeffrey L.; Yang, Yuching; McMullen, Patrick; Watkins, Paul B.; Andersen, Melvin E.

2012-01-01

We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales. PMID:23248599

Cellular and Molecular Actions of Methylene Blue in the Nervous System

PubMed Central

Oz, Murat; Lorke, Dietrich E.; Hasan, Mohammed; Petroianu, George A.

2010-01-01

Methylene Blue (MB), following its introduction to biology in the 19th century by Ehrlich, has found uses in various areas of medicine and biology. At present, MB is the first line of treatment in methemoglobinemias, is used frequently in the treatment of ifosfamide-induced encephalopathy, and is routinely employed as a diagnostic tool in surgical procedures. Furthermore, recent studies suggest that MB has beneficial effects in Alzheimer's disease and memory improvement. Although the modulation of the cGMP pathway is considered the most significant effect of MB, mediating its pharmacological actions, recent studies indicate that it has multiple cellular and molecular targets. In the majority of cases, biological effects and clinical applications of MB are dictated by its unique physicochemical properties including its planar structure, redox chemistry, ionic charges, and light spectrum characteristics. In this review article, these physicochemical features and the actions of MB on multiple cellular and molecular targets are discussed with regard to their relevance to the nervous system. PMID:19760660

Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

PubMed

Drier, Yotam; Domany, Eytan

2011-03-14

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

Pathview Web: user friendly pathway visualization and data integration

PubMed Central

Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

2017-01-01

Abstract Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. PMID:28482075

Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

PubMed Central

Shih, Wei-Liang; Kao, Chung-Feng; Chuang, Li-Chung; Kuo, Po-Hsiu

2012-01-01

MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed. PMID:23264780

SPIKE – a database, visualization and analysis tool of cellular signaling pathways

PubMed Central

Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

2008-01-01

Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

Consensus and conflict cards for metabolic pathway databases

PubMed Central

2013-01-01

Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. Conclusions C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. PMID:23803311

Consensus and conflict cards for metabolic pathway databases.

PubMed

Stobbe, Miranda D; Swertz, Morris A; Thiele, Ines; Rengaw, Trebor; van Kampen, Antoine H C; Moerland, Perry D

2013-06-26

The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. We introduce the concept of Consensus and Conflict Cards (C₂Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C₂Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. C₂Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C₂Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.

Convergence between biological, behavioural and genetic determinants of obesity.

PubMed

Ghosh, Sujoy; Bouchard, Claude

2017-12-01

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.

Extensive cargo identification reveals distinct biological roles of the 12 importin pathways.

PubMed

Kimura, Makoto; Morinaka, Yuriko; Imai, Kenichiro; Kose, Shingo; Horton, Paul; Imamoto, Naoko

2017-01-24

Vast numbers of proteins are transported into and out of the nuclei by approximately 20 species of importin-β family nucleocytoplasmic transport receptors. However, the significance of the multiple parallel transport pathways that the receptors constitute is poorly understood because only limited numbers of cargo proteins have been reported. Here, we identified cargo proteins specific to the 12 species of human import receptors with a high-throughput method that employs stable isotope labeling with amino acids in cell culture, an in vitro reconstituted transport system, and quantitative mass spectrometry. The identified cargoes illuminated the manner of cargo allocation to the receptors. The redundancies of the receptors vary widely depending on the cargo protein. Cargoes of the same receptor are functionally related to one another, and the predominant protein groups in the cargo cohorts differ among the receptors. Thus, the receptors are linked to distinct biological processes by the nature of their cargoes.

Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations.

PubMed

Langley, Gillian R; Adcock, Ian M; Busquet, François; Crofton, Kevin M; Csernok, Elena; Giese, Christoph; Heinonen, Tuula; Herrmann, Kathrin; Hofmann-Apitius, Martin; Landesmann, Brigitte; Marshall, Lindsay J; McIvor, Emily; Muotri, Alysson R; Noor, Fozia; Schutte, Katrin; Seidle, Troy; van de Stolpe, Anja; Van Esch, Hilde; Willett, Catherine; Woszczek, Grzegorz

2017-02-01

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and non-governmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this. Copyright © 2016 Elsevier Ltd. All rights reserved.

Natural history of hepatic metastases from colorectal cancer--pathobiological pathways with clinical significance.

PubMed

Paschos, Konstantinos A; Majeed, Ali W; Bird, Nigel C

2014-04-14

Colorectal cancer hepatic metastases represent the final stage of a multi-step biological process. This process starts with a series of mutations in colonic epithelial cells, continues with their detachment from the large intestine, dissemination through the blood and/or lymphatic circulation, attachment to the hepatic sinusoids and interactions with the sinusoidal cells, such as sinusoidal endothelial cells, Kupffer cells, stellate cells and pit cells. The metastatic sequence terminates with colorectal cancer cell invasion, adaptation and colonisation of the hepatic parenchyma. All these events, termed the colorectal cancer invasion-metastasis cascade, include multiple molecular pathways, intercellular interactions and expression of a plethora of chemokines and growth factors, and adhesion molecules, such as the selectins, the integrins or the cadherins, as well as enzymes including matrix metalloproteinases. This review aims to present recent advances that provide insights into these cell-biological events and emphasizes those that may be amenable to therapeutic targeting.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Pathogenesis-related proteins and peptides as promising tools for engineering plants with multiple stress tolerance.

PubMed

Ali, Sajad; Ganai, Bashir Ahmad; Kamili, Azra N; Bhat, Ajaz Ali; Mir, Zahoor Ahmad; Bhat, Javaid Akhter; Tyagi, Anshika; Islam, Sheikh Tajamul; Mushtaq, Muntazir; Yadav, Prashant; Rawat, Sandhya; Grover, Anita

Pathogenesis-related (PR) proteins and antimicrobial peptides (AMPs) are a group of diverse molecules that are induced by phytopathogens as well as defense related signaling molecules. They are the key components of plant innate immune system especially systemic acquired resistance (SAR), and are widely used as diagnostic molecular markers of defense signaling pathways. Although, PR proteins and peptides have been isolated much before but their biological function remains largely enigmatic despite the availability of new scientific tools. The earlier studies have demonstrated that PR genes provide enhanced resistance against both biotic and abiotic stresses, which make them one of the most promising candidates for developing multiple stress tolerant crop varieties. In this regard, plant genetic engineering technology is widely accepted as one of the most fascinating approach to develop the disease resistant transgenic crops using different antimicrobial genes like PR genes. Overexpression of PR genes (chitinase, glucanase, thaumatin, defensin and thionin) individually or in combination have greatly uplifted the level of defense response in plants against a wide range of pathogens. However, the detailed knowledge of signaling pathways that regulates the expression of these versatile proteins is critical for improving crop plants to multiple stresses, which is the future theme of plant stress biology. Hence, this review provides an overall overview on the PR proteins like their classification, role in multiple stresses (biotic and abiotic) as well as in various plant defense signaling cascades. We also highlight the success and snags of transgenic plants expressing PR proteins and peptides. Copyright © 2018 Elsevier GmbH. All rights reserved.

Moving beyond a descriptive aquatic toxicology: the value of biological process and trait information.

PubMed

Segner, Helmut

2011-10-01

In order to improve the ability to link chemical exposure to toxicological and ecological effects, aquatic toxicology will have to move from observing what chemical concentrations induce adverse effects to more explanatory approaches, that are concepts which build on knowledge of biological processes and pathways leading from exposure to adverse effects, as well as on knowledge on stressor vulnerability as given by the genetic, physiological and ecological (e.g., life history) traits of biota. Developing aquatic toxicology in this direction faces a number of challenges, including (i) taking into account species differences in toxicant responses on the basis of the evolutionarily developed diversity of phenotypic vulnerability to environmental stressors, (ii) utilizing diversified biological response profiles to serve as biological read across for prioritizing chemicals, categorizing them according to modes of action, and for guiding targeted toxicity evaluation; (iii) prediction of ecological consequences of toxic exposure from knowledge of how biological processes and phenotypic traits lead to effect propagation across the levels of biological hierarchy; and (iv) the search for concepts to assess the cumulative impact of multiple stressors. An underlying theme in these challenges is that, in addition to the question of what the chemical does to the biological receptor, we should give increasing emphasis to the question how the biological receptor handles the chemicals, i.e., through which pathways the initial chemical-biological interaction extends to the adverse effects, how this extension is modulated by adaptive or compensatory processes as well as by phenotypic traits of the biological receptor. 2011 Elsevier B.V. All rights reserved.

BIOZON: a system for unification, management and analysis of heterogeneous biological data.

PubMed

Birkland, Aaron; Yona, Golan

2006-02-15

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.

Effects of acute dieldrin exposure on neurotransmitters and global gene transcription in largemouth bass (Micropterus salmoides) hypothalamus

PubMed Central

Martyniuk, Christopher J.; Feswick, April; Spade, Daniel J.; Kroll, Kevin J.; Barber, David S.; Denslow, Nancy D.

2010-01-01

Exposure to dieldrin induces neurotoxic effects in the vertebrate CNS and disrupts reproductive processes in teleost fish. Reproductive impairment observed in fish by dieldrin is likely the result of multiple effects along the hypothalamic-pituitary-gonadal axis but the molecular signaling cascades are not well characterized. To better elucidate the mode of action of dieldrin in the hypothalamus, this study measured neurotransmitter levels and examined the transcriptomic response in female largemouth bass (LMB) to an acute treatment of dieldrin. Male and female LMB were injected with either vehicle or 10 mg dieldrin/kg and sacrificed after seven days. There were no significant changes in dopamine or DOPAC concentrations in the neuroendocrine brain of males and females after treatment but GABA levels in females were moderately increased 20–30% in the hypothalamus and cerebellum. In the female hypothalamus, there were 227 transcripts (p<0.001) identified as being differentially regulated by dieldrin. Functional enrichment analysis revealed transcription, DNA repair, ubiquitin-proteasome pathway, and cell communication, as biological processes over-represented in the microarray analysis. Pathway analysis identified DNA damage, inflammation, regeneration, and Alzheimer’s disease as major cell processes and diseases affected by dieldrin. Using multiple bioinformatics approaches, this study demonstrates that the teleostean hypothalamus is a target for dieldrin-induced neurotoxicity and provides mechanistic evidence that dieldrin activates similar cell pathways and biological processes that are also associated with the etiology of human neurological disorders. PMID:20438755

Downregulation of PI3-K/Akt/PTEN pathway and activation of mitochondrial intrinsic apoptosis by Diclofenac and Curcumin in colon cancer.

PubMed

Rana, Chandan; Piplani, Honit; Vaish, Vivek; Nehru, Bimla; Sanyal, S N

2015-04-01

Phosphatidylinositol 3-kinase (PI3-K)/PTEN/Akt signaling is over activated in various tumors including colon cancer. Activation of this pathway regulates multiple biological processes such as apoptosis, metabolism, cell proliferation, and cell growth that underlie the biology of a cancer cell. In the present study, the chemopreventive effects have been observed of Diclofenac, a preferential COX-2 inhibitory non-steroidal anti-inflammatory drugs, and Curcumin, a natural anti-inflammatory agent, in the early stage of colorectal carcinogenesis induced by 1,2-dimethylhydrazine dihydrochloride in rats. The tumor-promoting role of PI3-K/Akt/PTEN signal transduction pathway and its association with anti-apoptotic family of proteins are also observed. Both Diclofenac and Curcumin downregulated the PI3-K and Akt expression while promoting the apoptotic mechanism. Diclofenac and Curcumin administration significantly increased the expression of pro-apoptotic Bcl-2 family members (Bad and Bax) while decreasing the anti-apoptotic Bcl-2 protein. An up-regulation of cysteine protease family apoptosis executioner, such as caspase-3 and -9, is seen. Diclofenac and Curcumin inhibited the Bcl-2 protein by directly interacting at the active site by multiple hydrogen bonding, as also evident by negative glide score of Bcl-2. These drugs stimulated apoptosis by increasing reactive oxygen species (ROS) generation and simultaneously decreasing the mitochondrial membrane potential (ΔΨ M). Diclofenac and Curcumin showed anti-neoplastic effects by downregulating PI3-K/Akt/PTEN pathway, inducing apoptosis, increasing ROS generation, and decreasing ΔΨ M. The anti-neoplastic and apoptotic effects were found enhanced when both Diclofenac and Curcumin were administered together, rather than individually.

An integrated global chemomics and system biology approach to analyze the mechanisms of the traditional Chinese medicinal preparation Eriobotrya japonica - Fritillaria usuriensis dropping pills for pulmonary diseases.

PubMed

Tao, Jin; Hou, Yuanyuan; Ma, Xiaoyao; Liu, Dan; Tong, Yongling; Zhou, Hong; Gao, Jie; Bai, Gang

2016-01-08

Traditional Chinese medicine (TCM) herbal formulae provide valuable therapeutic strategies. However, the active ingredients and mechanisms of action remain unclear for most of these formulae. Therefore, the identification of complex mechanisms is a major challenge in TCM research. This study used a network pharmacology approach to clarify the anti-inflammatory and cough suppressing mechanisms of the Chinese medicinal preparation Eriobotrya japonica - Fritillaria usuriensis dropping pills (ChuanbeiPipa dropping pills, CBPP). The chemical constituents of CBPP were identified by high-quality ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS), and anti-inflammatory ingredients were selected and analyzed using the PharmMapper and Kyoto Encyclopedia of Genes and Genomes (KEGG) bioinformatics websites to predict the target proteins and related pathways, respectively. Then, an RNA-sequencing (RNA-Seq) analysis was carried out to investigate the different expression of genes in the lung tissue of rats with chronic bronchitis. Six main constituents affected 19 predicted pathways, including ursolic acid and oleanolic acid from Eriobotrya japonica (Thunb.) Lindl. (Eri), peiminine from Fritillaria usuriensis Maxim. (Fri), platycodigenin and polygalacic acid from Platycodon grandiflorum (Jacq.) A. DC. (Pla) and guanosine from Pinellia ternata (Thunb.) Makino. (Pin). Expression of 34 genes was significantly decreased after CBPP treatment, affecting four therapeutic functions: immunoregulation, anti-inflammation, collagen formation and muscle contraction. The active components acted on the mitogen activated protein kinase (MAPK) pathway, transforming growth factor (TGF)-beta pathway, focal adhesion, tight junctions and the action cytoskeleton to exert anti-inflammatory effects, resolve phlegm, and relieve cough. This novel approach of global chemomics-integrated systems biology represents an effective and accurate strategy for the study of TCM with multiple components and multiple target mechanisms.

An integrative systems biology approach to understanding pulmonary diseases.

PubMed

Auffray, Charles; Adcock, Ian M; Chung, Kian Fan; Djukanovic, Ratko; Pison, Christophe; Sterk, Peter J

2010-06-01

Chronic inflammatory pulmonary diseases such as COPD and asthma are highly prevalent and associated with a major health burden worldwide. Despite a wealth of biologic and clinical information on normal and pathologic airway structure and function, the primary causes and mechanisms of disease remain to a large extent unknown, preventing the development of more efficient diagnosis and treatment. We propose to overcome these limitations through an integrative systems biology research strategy designed to identify the functional and regulatory pathways that play central roles in respiratory pathophysiology, starting with severe asthma. This approach relies on global genome, transcriptome, proteome, and metabolome data sets collected in cross-sectional patient cohorts with high-throughput measurement platforms and integrated with biologic and clinical data to inform predictive multiscale models ranging from the molecular to the organ levels. Working hypotheses formulated on the mechanisms and pathways involved in various disease states are tested through perturbation experiments using model simulation combined with targeted and global technologies in cellular and animal models. The responses observed are compared with those predicted by the initial models, which are refined to account better for the results. Novel perturbation experiments are designed and tested both computationally and experimentally to arbitrate between competing hypotheses. The process is iterated until the derived knowledge allows a better classification and subphenotyping of severe asthma using complex biomarkers, which will facilitate the development of novel diagnostic and therapeutic interventions targeting multiple components of the molecular and cellular pathways involved. This can be tested and validated in prospective clinical trials.

Characterization of p38 MAPK isoforms for drug resistance study using systems biology approach.

PubMed

Peng, Huiming; Peng, Tao; Wen, Jianguo; Engler, David A; Matsunami, Risë K; Su, Jing; Zhang, Le; Chang, Chung-Che Jeff; Zhou, Xiaobo

2014-07-01

p38 mitogen-activated protein kinase activation plays an important role in resistance to chemotherapeutic cytotoxic drugs in treating multiple myeloma (MM). However, how the p38 mitogen-activated protein kinase signaling pathway is involved in drug resistance, in particular the roles that the various p38 isoforms play, remains largely unknown. To explore the underlying mechanisms, we developed a novel systems biology approach by integrating liquid chromatography-mass spectrometry and reverse phase protein array data from human MM cell lines with computational pathway models in which the unknown parameters were inferred using a proposed novel algorithm called modularized factor graph. New mechanisms predicted by our models suggest that combined activation of various p38 isoforms may result in drug resistance in MM via regulating the related pathways including extracellular signal-regulated kinase (ERK) pathway and NFкB pathway. ERK pathway regulating cell growth is synergistically regulated by p38δ isoform, whereas nuclear factor kappa B (NFкB) pathway regulating cell apoptosis is synergistically regulated by p38α isoform. This finding that p38δ isoform promotes the phosphorylation of ERK1/2 in MM cells treated with bortezomib was validated by western blotting. Based on the predicted mechanisms, we further screened drug combinations in silico and found that a promising drug combination targeting ERK1/2 and NFκB might reduce the effects of drug resistance in MM cells. This study provides a framework of a systems biology approach to studying drug resistance and drug combination selection. RPPA experimental Data and Matlab source codes of modularized factor graph for parameter estimation are freely available online at http://ctsb.is.wfubmc.edu/publications/modularized-factor-graph.php. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Developmental Pathways Are Blueprints for Designing Successful Crops

PubMed Central

Trevaskis, Ben

2018-01-01

Genes controlling plant development have been studied in multiple plant systems. This has provided deep insights into conserved genetic pathways controlling core developmental processes including meristem identity, phase transitions, determinacy, stem elongation, and branching. These pathways control plant growth patterns and are fundamentally important to crop biology and agriculture. This review describes the conserved pathways that control plant development, using Arabidopsis as a model. Historical examples of how plant development has been altered through selection to improve crop performance are then presented. These examples, drawn from diverse crops, show how the genetic pathways controlling development have been modified to increase yield or tailor growth patterns to suit local growing environments or specialized crop management practices. Strategies to apply current progress in genomics and developmental biology to future crop improvement are then discussed within the broader context of emerging trends in plant breeding. The ways that knowledge of developmental processes and understanding of gene function can contribute to crop improvement, beyond what can be achieved by selection alone, are emphasized. These include using genome re-sequencing, mutagenesis, and gene editing to identify or generate novel variation in developmental genes. The expanding scope for comparative genomics, the possibility to engineer new developmental traits and new approaches to resolve gene–gene or gene–environment interactions are also discussed. Finally, opportunities to integrate fundamental research and crop breeding are highlighted. PMID:29922318

Developmental Pathways Are Blueprints for Designing Successful Crops.

PubMed

Trevaskis, Ben

2018-01-01

Genes controlling plant development have been studied in multiple plant systems. This has provided deep insights into conserved genetic pathways controlling core developmental processes including meristem identity, phase transitions, determinacy, stem elongation, and branching. These pathways control plant growth patterns and are fundamentally important to crop biology and agriculture. This review describes the conserved pathways that control plant development, using Arabidopsis as a model. Historical examples of how plant development has been altered through selection to improve crop performance are then presented. These examples, drawn from diverse crops, show how the genetic pathways controlling development have been modified to increase yield or tailor growth patterns to suit local growing environments or specialized crop management practices. Strategies to apply current progress in genomics and developmental biology to future crop improvement are then discussed within the broader context of emerging trends in plant breeding. The ways that knowledge of developmental processes and understanding of gene function can contribute to crop improvement, beyond what can be achieved by selection alone, are emphasized. These include using genome re-sequencing, mutagenesis, and gene editing to identify or generate novel variation in developmental genes. The expanding scope for comparative genomics, the possibility to engineer new developmental traits and new approaches to resolve gene-gene or gene-environment interactions are also discussed. Finally, opportunities to integrate fundamental research and crop breeding are highlighted.

Curcumin inhibits cancer progression through regulating expression of microRNAs.

PubMed

Zhou, Siying; Zhang, Sijie; Shen, Hongyu; Chen, Wei; Xu, Hanzi; Chen, Xiu; Sun, Dawei; Zhong, Shanliang; Zhao, Jianhua; Tang, Jinhai

2017-02-01

Curcumin, a major yellow pigment and spice in turmeric and curry, is a powerful anti-cancer agent. The anti-tumor activities of curcumin include inhibition of tumor proliferation, angiogenesis, invasion and metastasis, induction of tumor apoptosis, increase of chemotherapy sensitivity, and regulation of cell cycle and cancer stem cell, indicating that curcumin maybe a strong therapeutic potential through modulating various cancer progression. It has been reported that microRNAs as small noncoding RNA molecules are related to cancer progression, which can be regulated by curcumin. Dysregulated microRNAs play vital roles in tumor biology via regulating expressions of target genes and then influencing multiple cancer-related signaling pathways. In this review, we focused on the inhibition effect of curcumin on various cancer progression by regulating expression of multiple microRNAs. Curcumin-induced dysregulation of microRNAs may activate or inactivate a set of signaling pathways, such as Akt, Bcl-2, PTEN, p53, Notch, and Erbb signaling pathways. A better understanding of the relation between curcumin and microRNAs may provide a potential therapeutic target for various cancers.

Endocrine Pancreas Development and Regeneration: Noncanonical Ideas From Neural Stem Cell Biology.

PubMed

Masjkur, Jimmy; Poser, Steven W; Nikolakopoulou, Polyxeni; Chrousos, George; McKay, Ronald D; Bornstein, Stefan R; Jones, Peter M; Androutsellis-Theotokis, Andreas

2016-02-01

Loss of insulin-producing pancreatic islet β-cells is a hallmark of type 1 diabetes. Several experimental paradigms demonstrate that these cells can, in principle, be regenerated from multiple endogenous sources using signaling pathways that are also used during pancreas development. A thorough understanding of these pathways will provide improved opportunities for therapeutic intervention. It is now appreciated that signaling pathways should not be seen as "on" or "off" but that the degree of activity may result in wildly different cellular outcomes. In addition to the degree of operation of a signaling pathway, noncanonical branches also play important roles. Thus, a pathway, once considered as "off" or "low" may actually be highly operational but may be using noncanonical branches. Such branches are only now revealing themselves as new tools to assay them are being generated. A formidable source of noncanonical signal transduction concepts is neural stem cells because these cells appear to have acquired unusual signaling interpretations to allow them to maintain their unique dual properties (self-renewal and multipotency). We discuss how such findings from the neural field can provide a blueprint for the identification of new molecular mechanisms regulating pancreatic biology, with a focus on Notch, Hes/Hey, and hedgehog pathways. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Pathway-Based Analysis of Genome-Wide siRNA Screens Reveals the Regulatory Landscape of App Processing

PubMed Central

Camargo, Luiz Miguel; Zhang, Xiaohua Douglas; Loerch, Patrick; Caceres, Ramon Miguel; Marine, Shane D.; Uva, Paolo; Ferrer, Marc; de Rinaldis, Emanuele; Stone, David J.; Majercak, John; Ray, William J.; Yi-An, Chen; Shearman, Mark S.; Mizuguchi, Kenji

2015-01-01

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the “regulatory landscape” of APP. PMID:25723573

Explore the Features of Brain-Derived Neurotrophic Factor in Mood Disorders

PubMed Central

Yeh, Fan-Chi; Kao, Chung-Feng; Kuo, Po-Hsiu

2015-01-01

Objectives Brain-derived neurotrophic factor (BDNF) plays important roles in neuronal survival and differentiation; however, the effects of BDNF on mood disorders remain unclear. We investigated BDNF from the perspective of various aspects of systems biology, including its molecular evolution, genomic studies, protein functions, and pathway analysis. Methods We conducted analyses examining sequences, multiple alignments, phylogenetic trees and positive selection across 12 species and several human populations. We summarized the results of previous genomic and functional studies of pro-BDNF and mature-BDNF (m-BDNF) found in a literature review. We identified proteins that interact with BDNF and performed pathway-based analysis using large genome-wide association (GWA) datasets obtained for mood disorders. Results BDNF is encoded by a highly conserved gene. The chordate BDNF genes exhibit an average of 75% identity with the human gene, while vertebrate orthologues are 85.9%-100% identical to human BDNF. No signs of recent positive selection were found. Associations between BDNF and mood disorders were not significant in most of the genomic studies (e.g., linkage, association, gene expression, GWA), while relationships between serum/plasma BDNF level and mood disorders were consistently reported. Pro-BDNF is important in the response to stress; the literature review suggests the necessity of studying both pro- and m-BDNF with regard to mood disorders. In addition to conventional pathway analysis, we further considered proteins that interact with BDNF (I-Genes) and identified several biological pathways involved with BDNF or I-Genes to be significantly associated with mood disorders. Conclusions Systematically examining the features and biological pathways of BDNF may provide opportunities to deepen our understanding of the mechanisms underlying mood disorders. PMID:26091093

The Need for Integrated Approaches in Metabolic Engineering

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

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

This review highlights state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. We emphasize that a combination of different approaches over multiple time and size scales must b e considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the "system" that is being manipulated: transcriptome, translatome, proteome, or reactome. By bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

The Need for Integrated Approaches in Metabolic Engineering

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

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

Highlights include state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. A combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the “system” that is being manipulated: transcriptome, translatome, proteome, or reactome. Here, by bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

The Need for Integrated Approaches in Metabolic Engineering

DOE PAGES

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

2016-08-15

Highlights include state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. A combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the “system” that is being manipulated: transcriptome, translatome, proteome, or reactome. Here, by bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

PubMed

McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

2012-04-01

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. Copyright © 2011 Elsevier Inc. All rights reserved.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

PubMed Central

McGuire, Mary F.; Iyengar, M. Sriram; Mercer, David W.

2012-01-01

Motivation Although trauma is the leading cause of death for those below 45 years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. Results In the node/molecular analysis of the first 24 hours from trauma, PSA uncovered 7 molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which 3 molecules had not been previously associated with any shock / trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships – activation, expression, inhibition, and transcription – and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. PMID:22200681

Molecular Signaling in Tumorigenesis of Gastric Cancer

PubMed

Molaei, Fatemeh; Forghanifard, Mohammad Mahdi; Fahim, Yasaman; Abbaszadegan, Mohammad Reza

2018-07-01

Gastric cancer (GC) is regarded as the fifth most common cancer and the third cause of cancer-related deaths worldwide. Mechanism of GC pathogenesis is still unclear and relies on multiple factors, including environmental and genetic characteristics. One of the most important environmental factors of GC occurrence is infection with Helicobacter pylori that is classified as class one carcinogens. Dysregulation of several genes and pathways play an essential role during gastric carcinogenesis. Dysregulation of developmental pathways such as Wnt/β-catenin signaling, Hedgehog signaling, Hippo pathway, Notch signaling, nuclear factor-kB, and epidermal growth factor receptor have been found in GC. Epithelial-mesenchymal transition, as an important process during embryogenesis and tumorigenesis, is supposed to play a role in initiation, invasion, metastasis, and progression of GC. Although surgery is the main therapeutic modality of the disease, the understanding of biological processes of cell signaling pathways may help to develop new therapeutic targets for GC.

miR2Pathway: A novel analytical method to discover MicroRNA-mediated dysregulated pathways involved in hepatocellular carcinoma.

PubMed

Li, Chaoxing; Dinu, Valentin

2018-05-01

MicroRNAs (miRNAs) are small, non-coding RNAs involved in the regulation of gene expression at a post-transcriptional level. Recent studies have shown miRNAs as key regulators of a variety of biological processes, such as proliferation, differentiation, apoptosis, metabolism, etc. Aberrantly expressed miRNAs influence individual gene expression level, but rewired miRNA-mRNA connections can influence the activity of biological pathways. Here, we define rewired miRNA-mRNA connections as the differential (rewiring) effects on the activity of biological pathways between hepatocellular carcinoma (HCC) and normal phenotypes. Our work presented here uses a PageRank-based approach to measure the degree of miRNA-mediated dysregulation of biological pathways between HCC and normal samples based on rewired miRNA-mRNA connections. In our study, we regard the degree of miRNA-mediated dysregulation of biological pathways as disease risk of biological pathways. Therefore, we propose a new method, miR2Pathway, to measure and rank the degree of miRNA-mediated dysregulation of biological pathways by measuring the total differential influence of miRNAs on the activity of pathways between HCC and normal states. miR2Pathway proposed here systematically shows the first evidence for a mechanism of biological pathways being dysregulated by rewired miRNA-mRNA connections, and provides new insight into exploring mechanisms behind HCC. Thus, miR2Pathway is a novel method to identify and rank miRNA-dysregulated pathways in HCC. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiple-Localization and Hub Proteins

PubMed Central

Ota, Motonori; Gonja, Hideki; Koike, Ryotaro; Fukuchi, Satoshi

2016-01-01

Protein-protein interactions are fundamental for all biological phenomena, and protein-protein interaction networks provide a global view of the interactions. The hub proteins, with many interaction partners, play vital roles in the networks. We investigated the subcellular localizations of proteins in the human network, and found that the ones localized in multiple subcellular compartments, especially the nucleus/cytoplasm proteins (NCP), the cytoplasm/cell membrane proteins (CMP), and the nucleus/cytoplasm/cell membrane proteins (NCMP), tend to be hubs. Examinations of keywords suggested that among NCP, those related to post-translational modifications and transcription functions are the major contributors to the large number of interactions. These types of proteins are characterized by a multi-domain architecture and intrinsic disorder. A survey of the typical hub proteins with prominent numbers of interaction partners in the type revealed that most are either transcription factors or co-regulators involved in signaling pathways. They translocate from the cytoplasm to the nucleus, triggered by the phosphorylation and/or ubiquitination of intrinsically disordered regions. Among CMP and NCMP, the contributors to the numerous interactions are related to either kinase or ubiquitin ligase activity. Many of them reside on the cytoplasmic side of the cell membrane, and act as the upstream regulators of signaling pathways. Overall, these hub proteins function to transfer external signals to the nucleus, through the cell membrane and the cytoplasm. Our analysis suggests that multiple-localization is a crucial concept to characterize groups of hub proteins and their biological functions in cellular information processing. PMID:27285823

miR-150 exerts antileukemia activity in vitro and in vivo through regulating genes in multiple pathways

PubMed Central

Fang, Zhi Hong; Wang, Si Li; Zhao, Jin Tao; Lin, Zhi Juan; Chen, Lin Yan; Su, Rui; Xie, Si Ting; Carter, Bing Z; Xu, Bing

2016-01-01

MicroRNAs, a class of small noncoding RNAs, have been implicated to regulate gene expression in virtually all important biological processes. Although accumulating evidence demonstrates that miR-150, an important regulator in hematopoiesis, is deregulated in various types of hematopoietic malignancies, the precise mechanisms of miR-150 action are largely unknown. In this study, we found that miR-150 is downregulated in samples from patients with acute lymphoblastic leukemia, acute myeloid leukemia, and chronic myeloid leukemia, and normalized after patients achieved complete remission. Restoration of miR-150 markedly inhibited growth and induced apoptosis of leukemia cells, and reduced tumorigenicity in a xenograft leukemia murine model. Microarray analysis identified multiple novel targets of miR-150, which were validated by quantitative real-time PCR and luciferase reporter assay. Gene ontology and pathway analysis illustrated potential roles of these targets in small-molecule metabolism, transcriptional regulation, RNA metabolism, proteoglycan synthesis in cancer, mTOR signaling pathway, or Wnt signaling pathway. Interestingly, knockdown one of four miR-150 targets (EIF4B, FOXO4B, PRKCA, and TET3) showed an antileukemia activity similar to that of miR-150 restoration. Collectively, our study demonstrates that miR-150 functions as a tumor suppressor through multiple mechanisms in human leukemia and provides a rationale for utilizing miR-150 as a novel therapeutic agent for leukemia treatment. PMID:27899822

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine.

PubMed

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-16

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM's diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients' target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ's cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the "multi-component, multi-target and multi-pathway" combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM's molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways

NASA Astrophysics Data System (ADS)

Kohlhoff, Kai J.; Shukla, Diwakar; Lawrenz, Morgan; Bowman, Gregory R.; Konerding, David E.; Belov, Dan; Altman, Russ B.; Pande, Vijay S.

2014-01-01

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.

PubMed

Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron

2016-09-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis.

PubMed

Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John

2016-02-24

In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.

Formate Assimilation: The Metabolic Architecture of Natural and Synthetic Pathways.

PubMed

Bar-Even, Arren

2016-07-19

Formate may become an ideal mediator between the physicochemical and biological realms, as it can be produced efficiently from multiple available sources, such as electricity and biomass, and serve as one of the simplest organic compounds for providing both carbon and energy to living cells. However, limiting the realization of formate as a microbial feedstock is the low diversity of formate-fixing enzymes and thereby the small number of naturally occurring formate-assimilation pathways. Here, the natural enzymes and pathways supporting formate assimilation are presented and discussed together with proposed synthetic routes that could permit growth on formate via existing as well as novel formate-fixing reactions. By considering such synthetic routes, the diversity of metabolic solutions for formate assimilation can be expanded dramatically, such that different host organisms, cultivation conditions, and desired products could be matched with the most suitable pathway. Astute application of old and new formate-assimilation pathways may thus become a cornerstone in the development of sustainable strategies for microbial production of value-added chemicals.

PRISMATIC: Unified Hierarchical Probabilistic Verification Tool

DTIC Science & Technology

2011-09-01

security protocols such as for anonymity and quantum cryptography ; and biological reaction pathways. PRISM is currently the leading probabilistic...a whole will only deadlock and fail with a probability ≤ p/2. The assumption allows us to partition the overall system verification problem into two ...run on any port using the standard HTTP protocol. In this way multiple instances of the PRISMATIC web service can respond to different requests when

Regulation of the Hippo signaling pathway by ubiquitin modification.

PubMed

Kim, Youngeun; Jho, Eek-Hoon

2018-03-01

The Hippo signaling pathway plays an essential role in adult tissue homeostasis and organ size control. Abnormal regulation of Hippo signaling can be a cause for multiple types of human cancers. Since the awareness of the importance of the Hippo signaling in a wide range of biological fields has been continually grown, it is also understood that a thorough and well-rounded comprehension of the precise dynamics could provide fundamental insights for therapeutic applications. Several components in the Hippo signaling pathway are known to be targeted for proteasomal degradation via ubiquitination by E3 ligases. β-TrCP is a well-known E3 ligase of YAP/TAZ, which leads to the reduction of YAP/TAZ levels. The Hippo signaling pathway can also be inhibited by the E3 ligases (such as ITCH) which target LATS1/2 for degradation. Regulation via ubiquitination involves not only complex network of E3 ligases but also deubiquitinating enzymes (DUBs), which remove ubiquitin from its targets. Interestingly, non-degradative ubiquitin modifications are also known to play important roles in the regulation of Hippo signaling. Although there has been much advanced progress in the investigation of ubiquitin modifications acting as regulators of the Hippo signaling pathway, research done to date still remains inadequate due to the sheer complexity and diversity of the subject. Herein, we review and discuss recent developments that implicate ubiquitin-mediated regulatory mechanisms at multiple steps of the Hippo signaling pathway. [BMB Reports 2018; 51(3): 143-150].

Galvanic zinc-copper microparticles inhibit melanogenesis via multiple pigmentary pathways.

PubMed

Won, Yen-Kim; Lin, Connie B; Seiberg, Miri; Chen, Nannan; Hu, Yaping; Rossetti, Dianne; Saliou, Claude; Loy, Chong-Jin

2014-01-01

The endogenous electrical field of human skin plays an important role in many skin functions. However, the biological effects and mechanism of action of externally applied electrical stimulation on skin remain unclear. Recent study showed that galvanic zinc-copper microparticles produce electrical stimulation and reduce inflammatory and immune responses in intact skin, suggesting the important role of electrical stimulation in non-wounded skin. The objective of this study is to investigate the biological effect of galvanic zinc-copper microparticles on skin pigmentation. Our findings showed that galvanic zinc-copper microparticles inhibited melanogenesis in a human melanoma cell line (MNT-1), human keratinocytes and melanoma cells co-cultures, and in pigmented epidermal equivalents. Treatment of galvanic zinc-copper microparticles inhibited melanogenesis by reducing the promoter transactivation of tyrosinase and tyrosinase-related protein-1 in human melanoma cells. In a co-culture Transwell system of keratinocytes and melanoma cells, galvanic zinc-copper microparticles reduced melanin production via downregulation of endothelin-1 secretion from keratinocytes and reduced tyrosinase gene expression in melanoma cells. In addition, exposure of pigmented epidermal equivalents to galvanic zinc-copper microparticles resulted in reduced melanin deposition. In conclusion, our data demonstrated for the first time that galvanic zinc-copper microparticles reduced melanogenesis in melanoma cells and melanin deposition in pigmented epidermal equivalents by affecting multiple pigmentary pathways.

Application of High-Throughput In Vitro Assays for Risk-Based ...

EPA Pesticide Factsheets

Multiple drivers shape the types of human-health assessments performed on chemicals by U.S. EPA resulting in chemical assessments are “fit-for-purpose” ranging from prioritization for further testing to full risk assessments. Layered on top of the diverse assessment needs are the resource intensive nature of traditional toxicological studies used to test chemicals and the lack of toxicity information on many chemicals. To address these challenges, the Agency initiated the ToxCast program to screen thousands of chemicals across hundreds of high-throughput screening assays in concentrations-response format. One of the findings of the project has been that the majority of chemicals interact with multiple biological targets within a narrow concentration range and the extent of interactions increases rapidly near the concentration causing cytotoxicity. This means that application of high-throughput in vitro assays to chemical assessments will need to identify both the relative selectivity at chemicals interact with biological targets and the concentration at which these interactions perturb signaling pathways. The integrated analyses will be used to both define a point-of-departure for comparison with human exposure estimates and identify which chemicals may benefit from further studies in a mode-of-action or adverse outcome pathway framework. The application of new technologies in a risk-based, tiered manner provides flexibility in matching throughput and cos

Irreparable complex DNA double-strand breaks induce chromosome breakage in organotypic three-dimensional human lung epithelial cell culture

PubMed Central

Asaithamby, Aroumougame; Hu, Burong; Delgado, Oliver; Ding, Liang-Hao; Story, Michael D.; Minna, John D.; Shay, Jerry W.; Chen, David J.

2011-01-01

DNA damage and consequent mutations initiate the multistep carcinogenic process. Differentiated cells have a reduced capacity to repair DNA lesions, but the biological impact of unrepaired DNA lesions in differentiated lung epithelial cells is unclear. Here, we used a novel organotypic human lung three-dimensional (3D) model to investigate the biological significance of unrepaired DNA lesions in differentiated lung epithelial cells. We showed, consistent with existing notions that the kinetics of loss of simple double-strand breaks (DSBs) were significantly reduced in organotypic 3D culture compared to kinetics of repair in two-dimensional (2D) culture. Strikingly, we found that, unlike simple DSBs, a majority of complex DNA lesions were irreparable in organotypic 3D culture. Levels of expression of multiple DNA damage repair pathway genes were significantly reduced in the organotypic 3D culture compared with those in 2D culture providing molecular evidence for the defective DNA damage repair in organotypic culture. Further, when differentiated cells with unrepaired DNA lesions re-entered the cell cycle, they manifested a spectrum of gross-chromosomal aberrations in mitosis. Our data suggest that downregulation of multiple DNA repair pathway genes in differentiated cells renders them vulnerable to DSBs, promoting genome instability that may lead to carcinogenesis. PMID:21421565

20150325 - Application of High-Throughput In Vitro Assays for ...

EPA Pesticide Factsheets

Multiple drivers shape the types of human-health assessments performed on chemicals by U.S. EPA resulting in chemical assessments are “fit-for-purpose” ranging from prioritization for further testing to full risk assessments. Layered on top of the diverse assessment needs are the resource intensive nature of traditional toxicological studies used to test chemicals and the lack of toxicity information on many chemicals. To address these challenges, the Agency initiated the ToxCast program to screen thousands of chemicals across hundreds of high-throughput screening assays in concentrations-response format. One of the findings of the project has been that the majority of chemicals interact with multiple biological targets within a narrow concentration range and the extent of interactions increases rapidly near the concentration causing cytotoxicity. This means that application of high-throughput in vitro assays to chemical assessments will need to identify both the relative selectivity at chemicals interact with biological targets and the concentration at which these interactions perturb signaling pathways. The integrated analyses will be used to both define a point-of-departure for comparison with human exposure estimates and identify which chemicals may benefit from further studies in a mode-of-action or adverse outcome pathway framework. The application of new technologies in a risk-based, tiered manner provides flexibility in matching throughput and cos

Dissecting DNA repair in adult high grade gliomas for patient stratification in the post-genomic era

PubMed Central

Perry, Christina; Agarwal, Devika; Abdel-Fatah, Tarek M.A.; Lourdusamy, Anbarasu; Grundy, Richard; Auer, Dorothee T.; Walker, David; Lakhani, Ravi; Scott, Ian S.; Chan, Stephen; Ball, Graham; Madhusudan, Srinivasan

2014-01-01

Deregulation of multiple DNA repair pathways may contribute to aggressive biology and therapy resistance in gliomas. We evaluated transcript levels of 157 genes involved in DNA repair in an adult glioblastoma Test set (n=191) and validated in ‘The Cancer Genome Atlas’ (TCGA) cohort (n=508). A DNA repair prognostic index model was generated. Artificial neural network analysis (ANN) was conducted to investigate global gene interactions. Protein expression by immunohistochemistry was conducted in 61 tumours. A fourteen DNA repair gene expression panel was associated with poor survival in Test and TCGA cohorts. A Cox multivariate model revealed APE1, NBN, PMS2, MGMT and PTEN as independently associated with poor prognosis. A DNA repair prognostic index incorporating APE1, NBN, PMS2, MGMT and PTEN stratified patients in to three prognostic sub-groups with worsening survival. APE1, NBN, PMS2, MGMT and PTEN also have predictive significance in patients who received chemotherapy and/or radiotherapy. ANN analysis of APE1, NBN, PMS2, MGMT and PTEN revealed interactions with genes involved in transcription, hypoxia and metabolic regulation. At the protein level, low APE1 and low PTEN remain associated with poor prognosis. In conclusion, multiple DNA repair pathways operate to influence biology and clinical outcomes in adult high grade gliomas. PMID:25026297

Multifarious Roles of Intrinsic Disorder in Proteins Illustrate Its Broad Impact on Plant Biology

PubMed Central

Sun, Xiaolin; Rikkerink, Erik H.A.; Jones, William T.; Uversky, Vladimir N.

2013-01-01

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein–protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein–protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways. PMID:23362206

Nanoparticles that Communicate In Vivo to Amplify Tumour Targeting

PubMed Central

von Maltzahn, Geoffrey; Park, Ji-Ho; Lin, Kevin Y.; Singh, Neetu; Schwöppe, Christian; Mesters, Rolf; Berdel, Wolfgang E.; Ruoslahti, Erkki; Sailor, Michael J.; Bhatia, Sangeeta N.

2012-01-01

Nanomedicines have enormous potential to improve the precision of cancer therapy, yet our ability to efficiently home these materials to regions of disease in vivo remains very limited. Inspired by the ability for communication to improve targeting in biological systems, such inflammatory cell recruitment to sites of disease, we construct systems where synthetic biological and nanotechnological components communicate to amplify disease targeting in vivo. These systems are composed of ‘Signalling’ modules (nanoparticles or engineered proteins) that target tumours and then locally active the coagulation cascade to broadcast tumour location to clot-targeted ‘Receiving’ nanoparticles in circulation that carry a diagnostic or therapeutic cargo, thereby amplifying their delivery. We show that communicating nanoparticle systems can be composed from multiple types of Signalling and Receiving modules, can transmit information via multiple molecular pathways in coagulation, can operate autonomously, and can target over 40-fold higher doses of chemotherapeutics to tumours than non-communicating controls. PMID:21685903

Target proteins of ganoderic acid DM provides clues to various pharmacological mechanisms

PubMed Central

Liu, Jie; Shimizu, Kuniyoshi; Tanaka, Akinobu; Shinobu, Wakako; Ohnuki, Koichiro; Nakamura, Takanori; Kondo, Ryuichiro

2012-01-01

Ganoderma fungus (Ganodermataceae) is a multifunctional medicinal mushroom and has been traditionally used for the treatment of various types of disease. Ganoderic acid DM (1) is a representative triterpenoid isolated from G. lingzhi and exhibits various biological activities. However, a universal starting point that triggers multiple signaling pathways and results in multifunctionality of 1 is unknown. Here we demonstrate the important clues regarding the mechanisms underlying multi-medicinal action of 1. We examined structure–activity relationships between 1 and its analogs and found that the carbonyl group at C-3 was essential for cytotoxicity. Subsequently, we used 1-conjugated magnetic beads as a probe and identified tubulin as a specific 1-binding protein. Furthermore, 1 showed a similar Kd to that of vinblastine and also affected assembly of tubulin polymers. This study revealed multiple biological activities of 1 and may contribute to the design and development of new tubulin-inhibiting agents. PMID:23205267

Nanoparticles that communicate in vivo to amplify tumour targeting

NASA Astrophysics Data System (ADS)

von Maltzahn, Geoffrey; Park, Ji-Ho; Lin, Kevin Y.; Singh, Neetu; Schwöppe, Christian; Mesters, Rolf; Berdel, Wolfgang E.; Ruoslahti, Erkki; Sailor, Michael J.; Bhatia, Sangeeta N.

2011-07-01

Nanomedicines have enormous potential to improve the precision of cancer therapy, yet our ability to efficiently home these materials to regions of disease in vivo remains very limited. Inspired by the ability of communication to improve targeting in biological systems, such as inflammatory-cell recruitment to sites of disease, we construct systems where synthetic biological and nanotechnological components communicate to amplify disease targeting in vivo. These systems are composed of ‘signalling’ modules (nanoparticles or engineered proteins) that target tumours and then locally activate the coagulation cascade to broadcast tumour location to clot-targeted ‘receiving’ nanoparticles in circulation that carry a diagnostic or therapeutic cargo, thereby amplifying their delivery. We show that communicating nanoparticle systems can be composed of multiple types of signalling and receiving modules, can transmit information through multiple molecular pathways in coagulation, can operate autonomously and can target over 40 times higher doses of chemotherapeutics to tumours than non-communicating controls.

Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway.

PubMed

Shin, Sung-Young; Nguyen, Lan K

2017-01-01

The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.

Long Noncoding RNAs: a New Regulatory Code in Metabolic Control

PubMed Central

Zhao, Xu-Yun; Lin, Jiandie D.

2015-01-01

Long noncoding RNAs (lncRNAs) are emerging as an integral part of the regulatory information encoded in the genome. LncRNAs possess the unique capability to interact with nucleic acids and proteins and exert discrete effects on numerous biological processes. Recent studies have delineated multiple lncRNA pathways that control metabolic tissue development and function. The expansion of the regulatory code that links nutrient and hormonal signals to tissue metabolism gives new insights into the genetic and pathogenic mechanisms underlying metabolic disease. This review discusses lncRNA biology with a focus on its role in the development, signaling, and function of key metabolic tissues. PMID:26410599

Droplet microfluidics for synthetic biology

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

Gach, PC; Iwai, K; Kim, PW

2017-01-01

© 2017 The Royal Society of Chemistry. Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselvesmore » expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Identification and Analyses of AUX-IAA target genes controlling multiple pathways in developing fiber cells of Gossypium hirsutum L

PubMed Central

Nigam, Deepti; Sawant, Samir V

2013-01-01

Technological development led to an increased interest in systems biological approaches in plants to characterize developmental mechanism and candidate genes relevant to specific tissue or cell morphology. AUX-IAA proteins are important plant-specific putative transcription factors. There are several reports on physiological response of this family in Arabidopsis but in cotton fiber the transcriptional network through which AUX-IAA regulated its target genes is still unknown. in-silico modelling of cotton fiber development specific gene expression data (108 microarrays and 22,737 genes) using Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) reveals 3690 putative AUX-IAA target genes of which 139 genes were known to be AUX-IAA co-regulated within Arabidopsis. Further AUX-IAA targeted gene regulatory network (GRN) had substantial impact on the transcriptional dynamics of cotton fiber, as showed by, altered TF networks, and Gene Ontology (GO) biological processes and metabolic pathway associated with its target genes. Analysis of the AUX-IAA-correlated gene network reveals multiple functions for AUX-IAA target genes such as unidimensional cell growth, cellular nitrogen compound metabolic process, nucleosome organization, DNA-protein complex and process related to cell wall. These candidate networks/pathways have a variety of profound impacts on such cellular functions as stress response, cell proliferation, and cell differentiation. While these functions are fairly broad, their underlying TF networks may provide a global view of AUX-IAA regulated gene expression and a GRN that guides future studies in understanding role of AUX-IAA box protein and its targets regulating fiber development. PMID:24497725

Targeting disease through novel pathways of apoptosis and autophagy.

PubMed

Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Wang, Shaohui

2012-12-01

Apoptosis and autophagy impact cell death in multiple systems of the body. Development of new therapeutic strategies that target these processes must address their complex role during developmental cell growth as well as during the modulation of toxic cellular environments. Novel signaling pathways involving Wnt1-inducible signaling pathway protein 1 (WISP1), phosphoinositide 3-kinase (PI3K), protein kinase B (Akt), β-catenin and mammalian target of rapamycin (mTOR) govern apoptotic and autophagic pathways during oxidant stress that affect the course of a broad spectrum of disease entities including Alzheimer's disease, Parkinson's disease, myocardial injury, skeletal system trauma, immune system dysfunction and cancer progression. Implications of potential biological and clinical outcome for these signaling pathways are presented. The CCN family member WISP1 and its intimate relationship with canonical and non-canonical wingless signaling pathways of PI3K, Akt1, β-catenin and mTOR offer an exciting approach for governing the pathways of apoptosis and autophagy especially in clinical disorders that are currently without effective treatments. Future studies that can elucidate the intricate role of these cytoprotective pathways during apoptosis and autophagy can further the successful translation and development of these cellular targets into robust and safe clinical therapeutic strategies.

A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability

PubMed Central

2014-01-01

Background Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Methods We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. Results Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. Conclusions We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability. PMID:24965703

Pathview Web: user friendly pathway visualization and data integration.

PubMed

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K; Blanchard, Steven G; Brouwer, Cory

2017-07-03

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Passing Messages between Biological Networks to Refine Predicted Interactions

PubMed Central

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402

In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line.

PubMed

Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R; Shen, Han-Ming; Lin, Qingsong

2016-02-26

To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQ(TM) quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway Analysis(TM) (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death.

In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line

PubMed Central

Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R.; Shen, Han-Ming; Lin, Qingsong

2016-01-01

To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQTM quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway AnalysisTM (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death. PMID:26915414

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.

Engineering of protein folding and secretion-strategies to overcome bottlenecks for efficient production of recombinant proteins.

PubMed

Delic, Marizela; Göngrich, Rebecca; Mattanovich, Diethard; Gasser, Brigitte

2014-07-20

Recombinant protein production has developed into a huge market with enormous positive implications for human health and for the future direction of a biobased economy. Limitations in the economic and technical feasibility of production processes are often related to bottlenecks of in vivo protein folding. Based on cell biological knowledge, some major bottlenecks have been overcome by the overexpression of molecular chaperones and other folding related proteins, or by the deletion of deleterious pathways that may lead to misfolding, mistargeting, or degradation. While important success could be achieved by this strategy, the list of reported unsuccessful cases is disappointingly long and obviously dependent on the recombinant protein to be produced. Singular engineering of protein folding steps may not lead to desired results if the pathway suffers from several limitations. In particular, the connection between folding quality control and proteolytic degradation needs further attention. Based on recent understanding that multiple steps in the folding and secretion pathways limit productivity, synergistic combinations of the cell engineering approaches mentioned earlier need to be explored. In addition, systems biology-based whole cell analysis that also takes energy and redox metabolism into consideration will broaden the knowledge base for future rational engineering strategies.

ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs.

PubMed

Nicoletti, Paola; Bansal, Mukesh; Lefebvre, Celine; Guarnieri, Paolo; Shen, Yufeng; Pe'er, Itsik; Califano, Andrea; Floratos, Aris

2015-01-01

Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) represent rare but serious adverse drug reactions (ADRs). Both are characterized by distinctive blistering lesions and significant mortality rates. While there is evidence for strong drug-specific genetic predisposition related to HLA alleles, recent genome wide association studies (GWAS) on European and Asian populations have failed to identify genetic susceptibility alleles that are common across multiple drugs. We hypothesize that this is a consequence of the low to moderate effect size of individual genetic risk factors. To test this hypothesis we developed Pointer, a new algorithm that assesses the aggregate effect of multiple low risk variants on a pathway using a gene set enrichment approach. A key advantage of our method is the capability to associate SNPs with genes by exploiting physical proximity as well as by using expression quantitative trait loci (eQTLs) that capture information about both cis- and trans-acting regulatory effects. We control for known bias-inducing aspects of enrichment based analyses, such as: 1) gene length, 2) gene set size, 3) presence of biologically related genes within the same linkage disequilibrium (LD) region, and, 4) genes shared among multiple gene sets. We applied this approach to publicly available SJS/TEN genome-wide genotype data and identified the ABC transporter and Proteasome pathways as potentially implicated in the genetic susceptibility of non-drug-specific SJS/TEN. We demonstrated that the innovative SNP-to-gene mapping phase of the method was essential in detecting the significant enrichment for those pathways. Analysis of an independent gene expression dataset provides supportive functional evidence for the involvement of Proteasome pathways in SJS/TEN cutaneous lesions. These results suggest that Pointer provides a useful framework for the integrative analysis of pharmacogenetic GWAS data, by increasing the power to detect aggregate effects of multiple low risk variants. The software is available for download at https://sourceforge.net/projects/pointergsa/.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

PubMed

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

CARFMAP: A Curated Pathway Map of Cardiac Fibroblasts.

PubMed

Nim, Hieu T; Furtado, Milena B; Costa, Mauro W; Kitano, Hiroaki; Rosenthal, Nadia A; Boyd, Sarah E

2015-01-01

The adult mammalian heart contains multiple cell types that work in unison under tightly regulated conditions to maintain homeostasis. Cardiac fibroblasts are a significant and unique population of non-muscle cells in the heart that have recently gained substantial interest in the cardiac biology community. To better understand this renaissance cell, it is essential to systematically survey what has been known in the literature about the cellular and molecular processes involved. We have built CARFMAP (http://visionet.erc.monash.edu.au/CARFMAP), an interactive cardiac fibroblast pathway map derived from the biomedical literature using a software-assisted manual data collection approach. CARFMAP is an information-rich interactive tool that enables cardiac biologists to explore the large body of literature in various creative ways. There is surprisingly little overlap between the cardiac fibroblast pathway map, a foreskin fibroblast pathway map, and a whole mouse organism signalling pathway map from the REACTOME database. Among the use cases of CARFMAP is a common task in our cardiac biology laboratory of identifying new genes that are (1) relevant to cardiac literature, and (2) differentially regulated in high-throughput assays. From the expression profiles of mouse cardiac and tail fibroblasts, we employed CARFMAP to characterise cardiac fibroblast pathways. Using CARFMAP in conjunction with transcriptomic data, we generated a stringent list of six genes that would not have been singled out using bioinformatics analyses alone. Experimental validation showed that five genes (Mmp3, Il6, Edn1, Pdgfc and Fgf10) are differentially regulated in the cardiac fibroblast. CARFMAP is a powerful tool for systems analyses of cardiac fibroblasts, facilitating systems-level cardiovascular research.

Modules for in vitro metabolic engineering: Pathway assembly for bio-based production of value-added chemicals.

PubMed

Taniguchi, Hironori; Okano, Kenji; Honda, Kohsuke

2017-06-01

Bio-based chemical production has drawn attention regarding the realization of a sustainable society. In vitro metabolic engineering is one of the methods used for the bio-based production of value-added chemicals. This method involves the reconstitution of natural or artificial metabolic pathways by assembling purified/semi-purified enzymes in vitro . Enzymes from distinct sources can be combined to construct desired reaction cascades with fewer biological constraints in one vessel, enabling easier pathway design with high modularity. Multiple modules have been designed, built, tested, and improved by different groups for different purpose. In this review, we focus on these in vitro metabolic engineering modules, especially focusing on the carbon metabolism, and present an overview of input modules, output modules, and other modules related to cofactor management.

Stress signaling pathways for the pathogenicity of Cryptococcus.

PubMed

Bahn, Yong-Sun; Jung, Kwang-Woo

2013-12-01

Sensing, responding, and adapting to the surrounding environment are crucial for all living organisms to survive, proliferate, and differentiate in their biological niches. This ability is also essential for Cryptococcus neoformans and its sibling species Cryptococcus gattii, as these pathogens have saprobic and parasitic life cycles in natural and animal host environments. The ability of Cryptococcus to cause fatal meningoencephalitis is highly related to its capability to remodel and optimize its metabolic and physiological status according to external cues. These cues act through multiple stress signaling pathways through a panoply of signaling components, including receptors/sensors, small GTPases, secondary messengers, kinases, transcription factors, and other miscellaneous adaptors or regulators. In this minireview, we summarize and highlight the importance of several stress signaling pathways that influence the pathogenicity of Cryptococcus and discuss future challenges in these areas.

Stress Signaling Pathways for the Pathogenicity of Cryptococcus

PubMed Central

Jung, Kwang-Woo

2013-01-01

Sensing, responding, and adapting to the surrounding environment are crucial for all living organisms to survive, proliferate, and differentiate in their biological niches. This ability is also essential for Cryptococcus neoformans and its sibling species Cryptococcus gattii, as these pathogens have saprobic and parasitic life cycles in natural and animal host environments. The ability of Cryptococcus to cause fatal meningoencephalitis is highly related to its capability to remodel and optimize its metabolic and physiological status according to external cues. These cues act through multiple stress signaling pathways through a panoply of signaling components, including receptors/sensors, small GTPases, secondary messengers, kinases, transcription factors, and other miscellaneous adaptors or regulators. In this minireview, we summarize and highlight the importance of several stress signaling pathways that influence the pathogenicity of Cryptococcus and discuss future challenges in these areas. PMID:24078305

Nitrifier-induced denitrification is an important source of soil nitrous oxide and can be inhibited by a nitrification inhibitor 3,4-dimethylpyrazole phosphate.

PubMed

Shi, Xiuzhen; Hu, Hang-Wei; Zhu-Barker, Xia; Hayden, Helen; Wang, Juntao; Suter, Helen; Chen, Deli; He, Ji-Zheng

2017-12-01

Soil ecosystem represents the largest contributor to global nitrous oxide (N 2 O) production, which is regulated by a wide variety of microbial communities in multiple biological pathways. A mechanistic understanding of these N 2 O production biological pathways in complex soil environment is essential for improving model performance and developing innovative mitigation strategies. Here, combined approaches of the 15 N- 18 O labelling technique, transcriptome analysis, and Illumina MiSeq sequencing were used to identify the relative contributions of four N 2 O pathways including nitrification, nitrifier-induced denitrification (nitrifier denitrification and nitrification-coupled denitrification) and heterotrophic denitrification in six soils (alkaline vs. acid soils). In alkaline soils, nitrification and nitrifier-induced denitrification were the dominant pathways of N 2 O production, and application of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) significantly reduced the N 2 O production from these pathways; this is probably due to the observed reduction in the expression of the amoA gene in ammonia-oxidizing bacteria (AOB) in the DMPP-amended treatments. In acid soils, however, heterotrophic denitrification was the main source for N 2 O production, and was not impacted by the application of DMPP. Our results provide robust evidence that the nitrification inhibitor DMPP can inhibit the N 2 O production from nitrifier-induced denitrification, a potential significant source of N 2 O production in agricultural soils. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Genetic changes associated with testicular cancer susceptibility.

PubMed

Pyle, Louise C; Nathanson, Katherine L

2016-10-01

Testicular germ cell tumor (TGCT) is a highly heritable cancer primarily affecting young white men. Genome-wide association studies (GWAS) have been particularly effective in identifying multiple common variants with strong contribution to TGCT risk. These loci identified through association studies have implicated multiple genes as associated with TGCT predisposition, many of which are unique among cancer types, and regulate processes such as pluripotency, sex specification, and microtubule assembly. Together these biologically plausible genes converge on pathways involved in male germ cell development and maturation, and suggest that perturbation of them confers susceptibility to TGCT, as a developmental defect of germ cell differentiation. Copyright © 2016 Elsevier Inc. All rights reserved.

Epigenetics Mechanisms in Alzheimer’s disease

PubMed Central

Mastroeni, Diego; Grover, Andrew; Delvaux, Elaine; Whiteside, Charisse; Coleman, Paul D.; Rogers, Joseph

2011-01-01

Epigenetic modifications help orchestrate sweeping developmental, aging, and disease-causing changes in phenotype by altering transcriptional activity in multiple genes spanning multiple biologic pathways. Although previous epigenetic research has focused primarily on dividing cells, particularly in cancer, recent studies have shown rapid, dynamic, and persistent epigenetic modifications in neurons that have significant neuroendocrine, neurophysiologic, and neurodegenerative consequences. Here, we provide a review of the major mechanisms for epigenetic modification and how they are reportedly altered in aging and Alzheimer’s disease (AD). Because of their reach across the genome, epigenetic mechanisms may provide a unique integrative framework for the pathologic diversity and complexity of AD. PMID:21482442

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

PubMed Central

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

2018-01-01

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

PubMed

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

Lipidomics of oxidized polyunsaturated fatty acids

PubMed Central

Massey, Karen A.; Nicolaou, Anna

2013-01-01

Lipid mediators are produced from the oxidation of polyunsaturated fatty acids through enzymatic and free radical-mediated reactions. When subject to oxygenation via cyclooxygenases, lipoxygenases, and cytochrome P450 monooxygenases, polyunsaturated fatty acids give rise to an array of metabolites including eicosanoids, docosanoids, and octadecanoids. These potent bioactive lipids are involved in many biochemical and signaling pathways, with inflammation being of particular importance. Moreover, because they are produced by more than one pathway and substrate, and are present in a variety of biological milieus, their analysis is not always possible with conventional assays. Liquid chromatography coupled to electrospray mass spectrometry offers a versatile and sensitive approach for the analysis of bioactive lipids, allowing specific and accurate quantitation of multiple species present in the same sample. Here we explain the principles of this approach to mediator lipidomics and present detailed protocols for the assay of enzymatically produced oxygenated metabolites of polyunsaturated fatty acids that can be tailored to answer biological questions or facilitate assessment of nutritional and pharmacological interventions. PMID:22940496

Integrative systems control approach for reactivating Kaposi's sarcoma-associated herpesvirus (KSHV) with combinatory drugs

PubMed Central

Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming

2009-01-01

Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators. PMID:19851479

Integrative systems control approach for reactivating Kaposi's sarcoma-associated herpesvirus (KSHV) with combinatory drugs.

PubMed

Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming

2009-01-01

Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators.

Genetics and language: a neurobiological perspective on the missing link (-ing hypotheses).

PubMed

Poeppel, David

2011-12-01

The paper argues that both evolutionary and genetic approaches to studying the biological foundations of speech and language could benefit from fractionating the problem at a finer grain, aiming not to map genetics to "language"-or even subdomains of language such as "phonology" or "syntax"-but rather to link genetic results to component formal operations that underlie processing the comprehension and production of linguistic representations. Neuroanatomic and neurophysiological research suggests that language processing is broken down in space (distributed functional anatomy along concurrent pathways) and time (concurrent processing on multiple time scales). These parallel neuronal pathways and their local circuits form the infrastructure of speech and language and are the actual targets of evolution/genetics. Therefore, investigating the mapping from gene to brain circuit to linguistic phenotype at the level of generic computational operations (subroutines actually executable in these circuits) stands to provide a new perspective on the biological foundations in the healthy and challenged brain.

An Update on ToxCast™ | Science Inventory | US EPA

EPA Pesticide Factsheets

In its first phase, ToxCast™ is profiling over 300 well-characterized chemicals (primarily pesticides) in over 400 HTS endpoints. These endpoints include biochemical assays of protein function, cell-based transcriptional reporter assays, multi-cell interaction assays, transcriptomics on primary cell cultures, and developmental assays in zebrafish embryos. Almost all of the compounds being examined in Phase 1 of ToxCast™ have been tested in traditional toxicology tests, including developmental toxicity, multi-generation studies, and sub-chronic and chronic rodent bioassays Lessons learned to date for ToxCast: Large amounts of quality HTS data can be economically obtained. Large scale data sets will be required to understand potential for biological activity. Value in having multiple assays with overlapping coverage of biological pathways and a variety of methodologies Concentration-response will be important for ultimate interpretation Data transparency will be important for acceptance. Metabolic capabilities and coverage of developmental toxicity pathways will need additional attention. Need to define the gold standard Partnerships are needed to bring critical mass and expertise.

Fate of Engineered Nanoparticles: Implications in the ...

EPA Pesticide Factsheets

The increased flux of the engineered nanoparticles (ENPs) in consumer and commercial products has become a viable threat, particularly if their release affects the environment. The aim of this paper is to review the recent literature results pertaining to the underlying mechanisms initiating the transformations of ENPs for both, the biotic and abiotic processes. The transformation of ENPs is necessarily interrelated to multiple environmental aspects and many concepts overlap. Physicochemical, macromolecular, and biological pathways contribute to assessing the impact of the altered activities of ENPs on the surrounding environmental matrices. Transformations involving both organic and inorganic ligands are vital in soil and water systems. Energy-efficient biocatalytic pathways can easily facilitate biotransformation involving enzymatic reactions and biomolecules. The relationship between physicochemical and biological parameters triggers transformation, greatly affecting the bioavailability and aging of ENPs to various extents. Therefore, the interaction of ENPs in environmental matrices is significant in understanding the risk of potential exposure and/or uptake by biota. Submitted to Elsevier journal, Coordination Chemistry Reviews

Biomimicry Promotes the Efficiency of a 10-Step Sequential Enzymatic Reaction on Nanoparticles, Converting Glucose to Lactate.

PubMed

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L; Lata, James P; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M; Bergkvist, Magnus; Sherwood, Robert W; Zhang, Sheng; Travis, Alexander J

2017-01-02

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomimicry promotes the efficiency of a 10-step sequential enzymatic reaction on nanoparticles, converting glucose to lactate

PubMed Central

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L.; Lata, James P.; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M.; Bergkvist, Magnus; Sherwood, Robert W.; Zhang, Sheng; Travis, Alexander J.

2016-01-01

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. PMID:27901298

Constructing biological pathway models with hybrid functional Petri nets.

PubMed

Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

2004-01-01

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

Constructing biological pathway models with hybrid functional petri nets.

PubMed

Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

2011-01-01

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

PubMed

Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

2011-08-01

The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Integration of plastids with their hosts: Lessons learned from dinoflagellates

PubMed Central

Dorrell, Richard G.; Howe, Christopher J.

2015-01-01

After their endosymbiotic acquisition, plastids become intimately connected with the biology of their host. For example, genes essential for plastid function may be relocated from the genomes of plastids to the host nucleus, and pathways may evolve within the host to support the plastid. In this review, we consider the different degrees of integration observed in dinoflagellates and their associated plastids, which have been acquired through multiple different endosymbiotic events. Most dinoflagellate species possess plastids that contain the pigment peridinin and show extreme reduction and integration with the host biology. In some species, these plastids have been replaced through serial endosymbiosis with plastids derived from a different phylogenetic derivation, of which some have become intimately connected with the biology of the host whereas others have not. We discuss in particular the evolution of the fucoxanthin-containing dinoflagellates, which have adapted pathways retained from the ancestral peridinin plastid symbiosis for transcript processing in their current, serially acquired plastids. Finally, we consider why such a diversity of different degrees of integration between host and plastid is observed in different dinoflagellates and how dinoflagellates may thus inform our broader understanding of plastid evolution and function. PMID:25995366

Integration of plastids with their hosts: Lessons learned from dinoflagellates.

PubMed

Dorrell, Richard G; Howe, Christopher J

2015-08-18

After their endosymbiotic acquisition, plastids become intimately connected with the biology of their host. For example, genes essential for plastid function may be relocated from the genomes of plastids to the host nucleus, and pathways may evolve within the host to support the plastid. In this review, we consider the different degrees of integration observed in dinoflagellates and their associated plastids, which have been acquired through multiple different endosymbiotic events. Most dinoflagellate species possess plastids that contain the pigment peridinin and show extreme reduction and integration with the host biology. In some species, these plastids have been replaced through serial endosymbiosis with plastids derived from a different phylogenetic derivation, of which some have become intimately connected with the biology of the host whereas others have not. We discuss in particular the evolution of the fucoxanthin-containing dinoflagellates, which have adapted pathways retained from the ancestral peridinin plastid symbiosis for transcript processing in their current, serially acquired plastids. Finally, we consider why such a diversity of different degrees of integration between host and plastid is observed in different dinoflagellates and how dinoflagellates may thus inform our broader understanding of plastid evolution and function.

Diversity in Pathways to Common Childhood Disruptive Behavior Disorders

PubMed Central

Martel, Michelle M.; Nikolas, Molly; Jernigan, Katherine; Friderici, Karen; Nigg, Joel T.

2014-01-01

Oppositional-Defiant Disorder (ODD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are highly comorbid, a phenomenon thought to be due to shared etiological factors and mechanisms. Little work has attempted to chart multiple-level-of-analysis pathways (i.e., simultaneously including biological, environmental, and trait influences) to ODD and ADHD, the goal of the present investigation. 559 children/adolescents (325 boys) between the ages of 6 and 18 participated in a multi-stage, comprehensive diagnostic procedure. 148 were classified as ODD; 309 were classified as ADHD, based on parent, teacher, and clinician ratings. Children provided buccal or salivary samples of DNA, assayed for select markers in DRD4 and 5HTT. Parents completed the Alabama Parenting Questionnaire and the California Q-Sort. Children completed the Child Perception of Interparental Conflict Scale. Correlational associations consistent with multiple-level-of-analysis pathways to ODD and ADHD emerged. For ODD, children with the short allele of the 5HTT promoter polymorphism had higher neuroticism and ODD symptoms regardless of level of self-blame in relation to inter-parental conflict, whereas children without this allele had more ODD symptoms only in the context of more self-blame for inter-parental conflict. For ADHD (and ODD), children homozygous for the long allele of DRD4 120bp insertion polymorphism had lower conscientiousness when exposed to inconsistent parenting, whereas children without this genotype were more resilient to effects of inconsistent discipline on conscientiousness. Thus, ODD and ADHD appear to demonstrate somewhat distinct correlational associations between etiological factors and mechanisms consistent with pathway models using a multiple-level-of-analysis approach. PMID:22584505

MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data.

PubMed

Lee, Sangseon; Park, Youngjune; Kim, Sun

2017-07-15

Pathway based analysis of high throughput transcriptome data is a widely used approach to investigate biological mechanisms. Since a pathway consists of multiple functions, the recent approach is to determine condition specific sub-pathways or subpaths. However, there are several challenges. First, few existing methods utilize explicit gene expression information from RNA-seq. More importantly, subpath activity is usually an average of statistical scores, e.g., correlations, of edges in a candidate subpath, which fails to reflect gene expression quantity information. In addition, none of existing methods can handle multiple phenotypes. To address these technical problems, we designed and implemented an algorithm, MIDAS, that determines condition specific subpaths, each of which has different activities across multiple phenotypes. MIDAS utilizes gene expression quantity information fully and the network centrality information to determine condition specific subpaths. To test performance of our tool, we used TCGA breast cancer RNA-seq gene expression profiles with five molecular subtypes. 36 differentially activate subpaths were determined. The utility of our method, MIDAS, was demonstrated in four ways. All 36 subpaths are well supported by the literature information. Subsequently, we showed that these subpaths had a good discriminant power for five cancer subtype classification and also had a prognostic power in terms of survival analysis. Finally, in a performance comparison of MIDAS to a recent subpath prediction method, PATHOME, our method identified more subpaths and much more genes that are well supported by the literature information. http://biohealth.snu.ac.kr/software/MIDAS/. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

De novo assembly and functional annotation of Myrciaria dubia fruit transcriptome reveals multiple metabolic pathways for L-ascorbic acid biosynthesis.

PubMed

Castro, Juan C; Maddox, J Dylan; Cobos, Marianela; Requena, David; Zimic, Mirko; Bombarely, Aureliano; Imán, Sixto A; Cerdeira, Luis A; Medina, Andersson E

2015-11-24

Myrciaria dubia is an Amazonian fruit shrub that produces numerous bioactive phytochemicals, but is best known by its high L-ascorbic acid (AsA) content in fruits. Pronounced variation in AsA content has been observed both within and among individuals, but the genetic factors responsible for this variation are largely unknown. The goals of this research, therefore, were to assemble, characterize, and annotate the fruit transcriptome of M. dubia in order to reconstruct metabolic pathways and determine if multiple pathways contribute to AsA biosynthesis. In total 24,551,882 high-quality sequence reads were de novo assembled into 70,048 unigenes (mean length = 1150 bp, N50 = 1775 bp). Assembled sequences were annotated using BLASTX against public databases such as TAIR, GR-protein, FB, MGI, RGD, ZFIN, SGN, WB, TIGR_CMR, and JCVI-CMR with 75.2 % of unigenes having annotations. Of the three core GO annotation categories, biological processes comprised 53.6 % of the total assigned annotations, whereas cellular components and molecular functions comprised 23.3 and 23.1 %, respectively. Based on the KEGG pathway assignment of the functionally annotated transcripts, five metabolic pathways for AsA biosynthesis were identified: animal-like pathway, myo-inositol pathway, L-gulose pathway, D-mannose/L-galactose pathway, and uronic acid pathway. All transcripts coding enzymes involved in the ascorbate-glutathione cycle were also identified. Finally, we used the assembly to identified 6314 genic microsatellites and 23,481 high quality SNPs. This study describes the first next-generation sequencing effort and transcriptome annotation of a non-model Amazonian plant that is relevant for AsA production and other bioactive phytochemicals. Genes encoding key enzymes were successfully identified and metabolic pathways involved in biosynthesis of AsA, anthocyanins, and other metabolic pathways have been reconstructed. The identification of these genes and pathways is in agreement with the empirically observed capability of M. dubia to synthesize and accumulate AsA and other important molecules, and adds to our current knowledge of the molecular biology and biochemistry of their production in plants. By providing insights into the mechanisms underpinning these metabolic processes, these results can be used to direct efforts to genetically manipulate this organism in order to enhance the production of these bioactive phytochemicals. The accumulation of AsA precursor and discovery of genes associated with their biosynthesis and metabolism in M. dubia is intriguing and worthy of further investigation. The sequences and pathways produced here present the genetic framework required for further studies. Quantitative transcriptomics in concert with studies of the genome, proteome, and metabolome under conditions that stimulate production and accumulation of AsA and their precursors are needed to provide a more comprehensive view of how these pathways for AsA metabolism are regulated and linked in this species.

CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis.

PubMed

Vrahatis, Aristidis G; Dimitrakopoulou, Konstantina; Balomenos, Panos; Tsakalidis, Athanasios K; Bezerianos, Anastasios

2016-03-15

In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific 'active parts' of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical 'themes'-in the form of enriched biologically relevant microRNA-mediated subpathways-that determine the functionality of signaling networks across time. To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/ tassos.bezerianos@nus.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integrative analysis of RUNX1 downstream pathways and target genes

PubMed Central

Michaud, Joëlle; Simpson, Ken M; Escher, Robert; Buchet-Poyau, Karine; Beissbarth, Tim; Carmichael, Catherine; Ritchie, Matthew E; Schütz, Frédéric; Cannon, Ping; Liu, Marjorie; Shen, Xiaofeng; Ito, Yoshiaki; Raskind, Wendy H; Horwitz, Marshall S; Osato, Motomi; Turner, David R; Speed, Terence P; Kavallaris, Maria; Smyth, Gordon K; Scott, Hamish S

2008-01-01

Background The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. Results Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFβ, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFβ. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. Conclusion This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications. PMID:18671852

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.

Novel applications of trophic factors, Wnt and WISP for neuronal repair and regeneration in metabolic disease

PubMed Central

Maiese, Kenneth

2015-01-01

Diabetes mellitus affects almost 350 million individuals throughout the globe resulting in significant morbidity and mortality. Of further concern is the growing population of individuals that remain undiagnosed but are susceptible to the detrimental outcomes of this disorder. Diabetes mellitus leads to multiple complications in the central and peripheral nervous systems that include cognitive impairment, retinal disease, neuropsychiatric disease, cerebral ischemia, and peripheral nerve degeneration. Although multiple strategies are being considered, novel targeting of trophic factors, Wnt signaling, Wnt1 inducible signaling pathway protein 1, and stem cell tissue regeneration are considered to be exciting prospects to overcome the cellular mechanisms that lead to neuronal injury in diabetes mellitus involving oxidative stress, apoptosis, and autophagy. Pathways that involve insulin-like growth factor-1, fibroblast growth factor, epidermal growth factor, and erythropoietin can govern glucose homeostasis and are intimately tied to Wnt signaling that involves Wnt1 and Wnt1 inducible signaling pathway protein 1 (CCN4) to foster control over stem cell proliferation, wound repair, cognitive decline, β-cell proliferation, vascular regeneration, and programmed cell death. Ultimately, cellular metabolism through Wnt signaling is driven by primary metabolic pathways of the mechanistic target of rapamycin and AMP activated protein kinase. These pathways offer precise biological control of cellular metabolism, but are exquisitely sensitive to the different components of Wnt signaling. As a result, unexpected clinical outcomes can ensue and therefore demand careful translation of the mechanisms that govern neural repair and regeneration in diabetes mellitus. PMID:26170801

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

F-box protein interactions with the hallmark pathways in cancer.

PubMed

Randle, Suzanne J; Laman, Heike

2016-02-01

F-box proteins (FBP) are the substrate specifying subunit of Skp1-Cul1-FBP (SCF)-type E3 ubiquitin ligases and are responsible for directing the ubiquitination of numerous proteins essential for cellular function. Due to their ability to regulate the expression and activity of oncogenes and tumour suppressor genes, FBPs themselves play important roles in cancer development and progression. In this review, we provide a comprehensive overview of FBPs and their targets in relation to their interaction with the hallmarks of cancer cell biology, including the regulation of proliferation, epigenetics, migration and invasion, metabolism, angiogenesis, cell death and DNA damage responses. Each cancer hallmark is revealed to have multiple FBPs which converge on common signalling hubs or response pathways. We also highlight the complex regulatory interplay between SCF-type ligases and other ubiquitin ligases. We suggest six highly interconnected FBPs affecting multiple cancer hallmarks, which may prove sensible candidates for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evolution of synthetic signaling scaffolds by recombination of modular protein domains.

PubMed

Lai, Andicus; Sato, Paloma M; Peisajovich, Sergio G

2015-06-19

Signaling scaffolds are proteins that interact via modular domains with multiple partners, regulating signaling networks in space and time and providing an ideal platform from which to alter signaling functions. However, to better exploit scaffolds for signaling engineering, it is necessary to understand the full extent of their modularity. We used a directed evolution approach to identify, from a large library of randomly shuffled protein interaction domains, variants capable of rescuing the signaling defect of a yeast strain in which Ste5, the scaffold in the mating pathway, had been deleted. After a single round of selection, we identified multiple synthetic scaffold variants with diverse domain architectures, able to mediate mating pathway activation in a pheromone-dependent manner. The facility with which this signaling network accommodates changes in scaffold architecture suggests that the mating signaling complex does not possess a single, precisely defined geometry into which the scaffold has to fit. These relaxed geometric constraints may facilitate the evolution of signaling networks, as well as their engineering for applications in synthetic biology.

Epigenetic modifications in multiple myeloma: recent advances on the role of DNA and histone methylation.

PubMed

Amodio, Nicola; D'Aquila, Patrizia; Passarino, Giuseppe; Tassone, Pierfrancesco; Bellizzi, Dina

2017-01-01

Multiple Myeloma (MM) is a clonal late B-cell disorder accounting for about 13% of hematological cancers and 1% of all neoplastic diseases. Recent studies on the molecular pathogenesis and biology of MM have highlighted a complex epigenomic landscape contributing to MM onset, prognosis and high individual variability. Areas covered: We describe here the current knowledge on epigenetic events characterizing MM initiation and progression, focusing on the role of DNA and histone methylation and on the most promising epi-therapeutic approaches targeting the methylation pathway. Expert opinion: Data published so far indicate that alterations of the epigenetic framework, which include aberrant global or gene/non-coding RNA specific methylation profiles, feature prominently in the pathobiology of MM. Indeed, the aberrant expression of components of the epigenetic machinery as well as the reversibility of the epigenetic marks make this pathway druggable, providing the basis for the design of epigenetic therapies against this still fatal malignancy.

DAG tales: the multiple faces of diacylglycerol--stereochemistry, metabolism, and signaling.

PubMed

Eichmann, Thomas Oliver; Lass, Achim

2015-10-01

The neutral lipids diacylglycerols (DAGs) are involved in a plethora of metabolic pathways. They function as components of cellular membranes, as building blocks for glycero(phospho)lipids, and as lipid second messengers. Considering their central role in multiple metabolic processes and signaling pathways, cellular DAG levels require a tight regulation to ensure a constant and controlled availability. Interestingly, DAG species are versatile in their chemical structure. Besides the different fatty acid species esterified to the glycerol backbone, DAGs can occur in three different stereo/regioisoforms, each with unique biological properties. Recent scientific advances have revealed that DAG metabolizing enzymes generate and distinguish different DAG isoforms, and that only one DAG isoform holds signaling properties. Herein, we review the current knowledge of DAG stereochemistry and their impact on cellular metabolism and signaling. Further, we describe intracellular DAG turnover and its stereochemistry in a 3-pool model to illustrate the spatial and stereochemical separation and hereby the diversity of cellular DAG metabolism.

Two White Spot Syndrome Virus MicroRNAs Target the Dorsal Gene To Promote Virus Infection in Marsupenaeus japonicus Shrimp

PubMed Central

Ren, Qian; Huang, Xin; Cui, Yalei; Sun, Jiejie; Wang, Wen

2017-01-01

ABSTRACT In eukaryotes, microRNAs (miRNAs) serve as regulators of many biological processes, including virus infection. An miRNA can generally target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs has not yet been extensively explored during virus infection. This study found that the Spaztle (Spz)-Toll-Dorsal-antilipopolysaccharide factor (ALF) signaling pathway plays a very important role in antiviral immunity against invasion of white spot syndrome virus (WSSV) in shrimp (Marsupenaeus japonicus). Dorsal, the central gene in the Toll pathway, was targeted by two viral miRNAs (WSSV-miR-N13 and WSSV-miR-N23) during WSSV infection. The regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo, leading to virus infection. Our study contributes novel insights into the viral miRNA-mediated Toll signaling pathway during the virus-host interaction. IMPORTANCE An miRNA can target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs during virus infection has not yet been extensively explored. The results of this study indicated that the shrimp Dorsal gene, the central gene in the Toll pathway, was targeted by two viral miRNAs during infection with white spot syndrome virus. Regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo, leading to virus infection. Our study provides new insight into the viral miRNA-mediated Toll signaling pathway in virus-host interactions. PMID:28179524

Two White Spot Syndrome Virus MicroRNAs Target the Dorsal Gene To Promote Virus Infection in Marsupenaeus japonicus Shrimp.

PubMed

Ren, Qian; Huang, Xin; Cui, Yalei; Sun, Jiejie; Wang, Wen; Zhang, Xiaobo

2017-04-15

In eukaryotes, microRNAs (miRNAs) serve as regulators of many biological processes, including virus infection. An miRNA can generally target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs has not yet been extensively explored during virus infection. This study found that the Spaztle (Spz)-Toll-Dorsal-antilipopolysaccharide factor (ALF) signaling pathway plays a very important role in antiviral immunity against invasion of white spot syndrome virus (WSSV) in shrimp ( Marsupenaeus japonicus ). Dorsal , the central gene in the Toll pathway, was targeted by two viral miRNAs (WSSV-miR-N13 and WSSV-miR-N23) during WSSV infection. The regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo , leading to virus infection. Our study contributes novel insights into the viral miRNA-mediated Toll signaling pathway during the virus-host interaction. IMPORTANCE An miRNA can target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs during virus infection has not yet been extensively explored. The results of this study indicated that the shrimp Dorsal gene, the central gene in the Toll pathway, was targeted by two viral miRNAs during infection with white spot syndrome virus. Regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo , leading to virus infection. Our study provides new insight into the viral miRNA-mediated Toll signaling pathway in virus-host interactions. Copyright © 2017 American Society for Microbiology.

SAR202 Genomes from the Dark Ocean Predict Pathways for the Oxidation of Recalcitrant Dissolved Organic Matter.

PubMed

Landry, Zachary; Swan, Brandon K; Herndl, Gerhard J; Stepanauskas, Ramunas; Giovannoni, Stephen J

2017-04-18

Deep-ocean regions beyond the reach of sunlight contain an estimated 615 Pg of dissolved organic matter (DOM), much of which persists for thousands of years. It is thought that bacteria oxidize DOM until it is too dilute or refractory to support microbial activity. We analyzed five single-amplified genomes (SAGs) from the abundant SAR202 clade of dark-ocean bacterioplankton and found they encode multiple families of paralogous enzymes involved in carbon catabolism, including several families of oxidative enzymes that we hypothesize participate in the degradation of cyclic alkanes. The five partial genomes encoded 152 flavin mononucleotide/F420-dependent monooxygenases (FMNOs), many of which are predicted to be type II Baeyer-Villiger monooxygenases (BVMOs) that catalyze oxygen insertion into semilabile alicyclic alkanes. The large number of oxidative enzymes, as well as other families of enzymes that appear to play complementary roles in catabolic pathways, suggests that SAR202 might catalyze final steps in the biological oxidation of relatively recalcitrant organic compounds to refractory compounds that persist. IMPORTANCE Carbon in the ocean is massively sequestered in a complex mixture of biologically refractory molecules that accumulate as the chemical end member of biological oxidation and diagenetic change. However, few details are known about the biochemical machinery of carbon sequestration in the deep ocean. Reconstruction of the metabolism of a deep-ocean microbial clade, SAR202, led to postulation of new biochemical pathways that may be the penultimate stages of DOM oxidation to refractory forms that persist. These pathways are tied to a proliferation of oxidative enzymes. This research illuminates dark-ocean biochemistry that is broadly consequential for reconstructing the global carbon cycle. Copyright © 2017 Landry et al.

Development and Clinical Assessment of a Comprehensive Product for Pigmentation Control in Multiple Ethnic Populations.

PubMed

Makino, Elizabeth T; Kadoya, Kuniko; Sigler, Monya L; Hino, Peter D; Mehta, Rahul C

2016-12-01

Pigmentary changes in people of different ethnic origins are controlled by slight variations in key biological pathways leading to different outcomes from the same treatment. It is important to develop and test products for desired outcomes in varying ethnic populations. To develop a comprehensive product (LYT2) that affects all major biological pathways controlling pigmentation and test for clinical efficacy and safety in different ethnic populations. A thorough analysis of biological pathways was used to identify ingredient combinations for LYT2 that provided optimal melanin reduction in a 3-D skin model. Expression of four key genes for melanogenesis, TYR, TYRP-1, DCT, and MITF was analyzed by qPCR. Clinical study was conducted to compare the efficacy and tolerability of LYT2 against 4% hydroquinone (HQ). Average melanin suppression by LYT2 in 7 independent experiments was 45%. All four key genes show significant down- regulation of expression. LYT2 provided statistically significant reductions in mean overall hyperpigmentation grades as early as week 2 compared to baseline, with continued significant improvements through week 12 in all ethnic groups tested. We have successfully combined management of 6 categories of pathways related to melanogenesis: melanocyte activation, melanosome development, melanin production, melanin distribution, keratinocyte turnover, and barrier function to create a comprehensive HQ-free product. The outcome clearly shows greater pigmentation control with LYT2 compared to other HQ-free products in skin tissue models and earlier control in clinical studies compared to 4% HQ. Clinical study shows pigmentation control benefits of LYT2 in people of Caucasian, Hispanic, and African ethnic origins. J Drugs Dermatol. 2016;15(12):1562-1570.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

PubMed Central

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

PubMed

Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

2016-06-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory

PubMed Central

Shuai, Yichun; Hirokawa, Areekul; Ai, Yulian; Zhang, Min; Li, Wanhe; Zhong, Yi

2015-01-01

Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β′1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts. PMID:26627257

BMP Signaling in Astrocytes Downregulates EGFR to Modulate Survival and Maturation

PubMed Central

Scholze, Anja R.; Foo, Lynette C.; Mulinyawe, Sara; Barres, Ben A.

2014-01-01

Astrocytes constitute a major cell population in the brain with a myriad of essential functions, yet we know remarkably little about the signaling pathways and mechanisms that direct astrocyte maturation. To explore the signals regulating astrocyte development, we prospectively purified and cultured immature postnatal rodent astrocytes. We identified fibroblast growth factors (FGFs) and bone morphogenetic proteins (BMPs) as robust trophic factors for immature astrocytes. We showed that astrocytes respond directly to BMPs via phosphorylation of the smad1/5/8 pathway. In vitro, BMP signaling promoted immature astrocytes to adopt multiple characteristics of mature astrocytes, including a more process-bearing morphology, aquaporin-4 (AQP4) and S100β immunoreactivity, limited proliferation, and strong downregulation of epidermal growth factor receptor (EGFR). In vivo, activation of the smad1/5/8 pathway in astrocytes was seen during early postnatal development, but inhibition of astrocyte proliferation was not observed. These insights can aid in the further dissection of the mechanisms and pathways controlling astrocyte biology and development. PMID:25330173

Simultaneous utilization of cellobiose, xylose, and acetic acid from lignocellulosic biomass for biofuel production by an engineered yeast platform.

PubMed

Wei, Na; Oh, Eun Joong; Million, Gyver; Cate, Jamie H D; Jin, Yong-Su

2015-06-19

The inability of fermenting microorganisms to use mixed carbon components derived from lignocellulosic biomass is a major technical barrier that hinders the development of economically viable cellulosic biofuel production. In this study, we integrated the fermentation pathways of both hexose and pentose sugars and an acetic acid reduction pathway into one Saccharomyces cerevisiae strain for the first time using synthetic biology and metabolic engineering approaches. The engineered strain coutilized cellobiose, xylose, and acetic acid to produce ethanol with a substantially higher yield and productivity than the control strains, and the results showed the unique synergistic effects of pathway coexpression. The mixed substrate coutilization strategy is important for making complete and efficient use of cellulosic carbon and will contribute to the development of consolidated bioprocessing for cellulosic biofuel. The study also presents an innovative metabolic engineering approach whereby multiple substrate consumption pathways can be integrated in a synergistic way for enhanced bioconversion.

Cognitive dysfunction in depression - pathophysiology and novel targets.

PubMed

Carvalho, Andre F; Miskowiak, Kamilla K; Hyphantis, Thomas N; Kohler, Cristiano A; Alves, Gilberto S; Bortolato, Beatrice; G Sales, Paulo Marcelo; Machado-Vieira, Rodrigo; Berk, Michael; McIntyre, Roger S

2014-01-01

Major depressive disorder (MDD) is associated with cognitive dysfunction encompassing several domains, including memory, executive function, processing speed and attention. Cognitive deficits persist in a significant proportion of patients even in remission, compromising psychosocial functioning and workforce performance. While monoaminergic antidepressants may improve cognitive performance in MDD, most antidepressants have limited clinical efficacy. The overarching aims of this review were: (1) to synthesize extant literature on putative biological pathways related to cognitive dysfunction in MDD and (2) to review novel neurotherapeutic targets for cognitive enhancement in MDD. We found that reciprocal and overlapping biological pathways may contribute to cognitive dysfunction in MDD, including an hyperactive hypothalamic-pituitary-adrenal axis, an increase in oxidative and nitrosative stress, inflammation (e.g., enhanced production of pro-inflammatory cytokines), mitochondrial dysfunction, increased apoptosis as well as a diminished neurotrophic support. Several promising neurotherapeutic targets were identified such as minocycline, statins, anti-inflammatory compounds, N-acetylcysteine, omega-3 poliunsaturated fatty acids, erythropoietin, thiazolidinediones, glucagon-like peptide-1 analogues, S-adenosyl-l-methionine (SAMe), cocoa flavonols, creatine monohydrate and lithium. Erythropoietin and SAMe had pro-cognitive effects in randomized controlled trials (RCT) involving MDD patients. Despite having preclinical and/or preliminary evidences from trials suggesting possible efficacy as novel cognitive enhancing agents for MDD, no RCT to date was performed for most of the other therapeutic targets reviewed herein. In conclusion, multiple biological pathways are involved in cognitive dysfunction in MDD. RCTs testing genuinely novel pro-cognitive compounds for MDD are warranted.

Mutant Allele-Specific Uncoupling of PENETRATION3 Functions Reveals Engagement of the ATP-Binding Cassette Transporter in Distinct Tryptophan Metabolic Pathways1[OPEN

PubMed Central

Lu, Xunli; Dittgen, Jan; Piślewska-Bednarek, Mariola; Molina, Antonio; Schneider, Bernd; Doubský, Jan; Schneeberger, Korbinian; Schulze-Lefert, Paul

2015-01-01

Arabidopsis (Arabidopsis thaliana) PENETRATION (PEN) genes quantitatively contribute to the execution of different forms of plant immunity upon challenge with diverse leaf pathogens. PEN3 encodes a plasma membrane-resident pleiotropic drug resistance-type ATP-binding cassette transporter and is thought to act in a pathogen-inducible and PEN2 myrosinase-dependent metabolic pathway in extracellular defense. This metabolic pathway directs the intracellular biosynthesis and activation of tryptophan-derived indole glucosinolates for subsequent PEN3-mediated efflux across the plasma membrane at pathogen contact sites. However, PEN3 also functions in abiotic stress responses to cadmium and indole-3-butyric acid (IBA)-mediated auxin homeostasis in roots, raising the possibility that PEN3 exports multiple functionally unrelated substrates. Here, we describe the isolation of a pen3 allele, designated pen3-5, that encodes a dysfunctional protein that accumulates in planta like wild-type PEN3. The specific mutation in pen3-5 uncouples PEN3 functions in IBA-stimulated root growth modulation, callose deposition induced with a conserved peptide epitope of bacterial flagellin (flg22), and pathogen-inducible salicylic acid accumulation from PEN3 activity in extracellular defense, indicating the engagement of multiple PEN3 substrates in different PEN3-dependent biological processes. We identified 4-O-β-d-glucosyl-indol-3-yl formamide (4OGlcI3F) as a pathogen-inducible, tryptophan-derived compound that overaccumulates in pen3 leaf tissue and has biosynthesis that is dependent on an intact PEN2 metabolic pathway. We propose that a precursor of 4OGlcI3F is the PEN3 substrate in extracellular pathogen defense. These precursors, the shared indole core present in IBA and 4OGlcI3F, and allele-specific uncoupling of a subset of PEN3 functions suggest that PEN3 transports distinct indole-type metabolites in distinct biological processes. PMID:26023163

Multiple Roles of Photosynthetic and Sunscreen Pigments in Cyanobacteria Focusing on the Oxidative Stress

PubMed Central

Wada, Naoki; Sakamoto, Toshio; Matsugo, Seiichi

2013-01-01

Cyanobacteria have two types of sunscreen pigments, scytonemin and mycosporine-like amino acids (MAAs). These secondary metabolites are thought to play multiple roles against several environmental stresses such as UV radiation and desiccation. Not only the large molar absorption coefficients of these sunscreen pigments, but also their antioxidative properties may be necessary for the protection of biological molecules against the oxidative damages induced by UV radiation. The antioxidant activity and vitrification property of these pigments are thought to be requisite for the desiccation and rehydration processes in anhydrobiotes. In this review, the multiple roles of photosynthetic pigments and sunscreen pigments on stress resistance, especially from the viewpoint of their structures, biosynthetic pathway, and in vitro studies of their antioxidant activity, will be discussed. PMID:24958001

Approximation of super-ions for single-file diffusion of multiple ions through narrow pores.

PubMed

Kharkyanen, Valery N; Yesylevskyy, Semen O; Berezetskaya, Natalia M

2010-11-01

The general theory of the single-file multiparticle diffusion in the narrow pores could be greatly simplified in the case of inverted bell-like shape of the single-particle energy profile, which is often observed in biological ion channels. There is a narrow and deep groove in the energy landscape of multiple interacting ions in such profiles, which corresponds to the pre-defined optimal conduction pathway in the configurational space. If such groove exists, the motion of multiple ions can be reduced to the motion of single quasiparticle, called the superion, which moves in one-dimensional effective potential. The concept of the superions dramatically reduces the computational complexity of the problem and provides very clear physical interpretation of conduction phenomena in the narrow pores.

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

PubMed

Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R

2006-02-01

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.

Multiplexed, quantitative, and targeted metabolite profiling by LC-MS/MRM.

PubMed

Wei, Ru; Li, Guodong; Seymour, Albert B

2014-01-01

Targeted metabolomics, which focuses on a subset of known metabolites representative of biologically relevant metabolic pathways, is a valuable tool to discover biomarkers and link disease phenotypes to underlying mechanisms or therapeutic modes of action. A key advantage of targeted metabolomics, compared to discovery metabolomics, is its immediate readiness for extracting biological information derived from known metabolites and quantitative measurements. However, simultaneously analyzing hundreds of endogenous metabolites presents a challenge due to their diverse chemical structures and properties. Here we report a method which combines different chromatographic separation conditions, optimal ionization polarities, and the most sensitive triple-quadrupole MS-based data acquisition mode, multiple reaction monitoring (MRM), to quantitatively profile 205 endogenous metabolites in 10 min.

miRegulome: a knowledge-base of miRNA regulomics and analysis.

PubMed

Barh, Debmalya; Kamapantula, Bhanu; Jain, Neha; Nalluri, Joseph; Bhattacharya, Antaripa; Juneja, Lucky; Barve, Neha; Tiwari, Sandeep; Miyoshi, Anderson; Azevedo, Vasco; Blum, Kenneth; Kumar, Anil; Silva, Artur; Ghosh, Preetam

2015-08-05

miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics. miRegulome attempts to bridge this gap. The current version of miRegulome v1.0 provides details on the entire regulatory modules of miRNAs altered in response to chemical treatments and transcription factors, based on validated data manually curated from published literature. Modules of miRegulome (upstream regulators, downstream targets, miRNA regulated pathways, functions, diseases, etc) are hyperlinked to an appropriate external resource and are displayed visually to provide a comprehensive understanding. Four analysis tools are incorporated to identify relationships among different modules based on user specified datasets. miRegulome and its tools are helpful in understanding the biology of miRNAs and will also facilitate the discovery of biomarkers and therapeutics. With added features in upcoming releases, miRegulome will be an essential resource to the scientific community. http://bnet.egr.vcu.edu/miRegulome.

Multi-target drugs to address multiple checkpoints in complex inflammatory pathologies: evolutionary cues for novel "first-in-class" anti-inflammatory drug candidates: a reviewer's perspective.

PubMed

Mathew, Geetha; Unnikrishnan, M K

2015-10-01

Inflammation is a complex, metabolically expensive process involving multiple signaling pathways and regulatory mechanisms which have evolved over evolutionary timescale. Addressing multiple targets of inflammation holistically, in moderation, is probably a more evolutionarily viable strategy, as compared to current therapy which addresses drug targets in isolation. Polypharmacology, addressing multiple targets, is commonly used in complex ailments, suggesting the superior safety and efficacy profile of multi-target (MT) drugs. Phenotypic drug discovery, which generated successful MT and first-in-class drugs in the past, is now re-emerging. A multi-pronged approach, which modulates the evolutionarily conserved, robust and pervasive cellular mechanisms of tissue repair, with AMPK at the helm, regulating the complex metabolic/immune/redox pathways underlying inflammation, is perhaps a more viable strategy than addressing single targets in isolation. Molecules that modulate multiple molecular mechanisms of inflammation in moderation (modulating TH cells toward the anti-inflammatory phenotype, activating AMPK, stimulating Nrf2 and inhibiting NFκB) might serve as a model for a novel Darwinian "first-in-class" therapeutic category that holistically addresses immune, redox and metabolic processes associated with inflammatory repair. Such a multimodal biological activity is supported by the fact that several non-calorific pleiotropic natural products with anti-inflammatory action have been incorporated into diet (chiefly guided by the adaptive development of olfacto-gustatory preferences over evolutionary timescales) rendering such molecules, endowed with evolutionarily privileged molecular scaffolds, naturally oriented toward multiple targets.

BioPAX – A community standard for pathway data sharing

PubMed Central

Demir, Emek; Cary, Michael P.; Paley, Suzanne; Fukuda, Ken; Lemer, Christian; Vastrik, Imre; Wu, Guanming; D’Eustachio, Peter; Schaefer, Carl; Luciano, Joanne; Schacherer, Frank; Martinez-Flores, Irma; Hu, Zhenjun; Jimenez-Jacinto, Veronica; Joshi-Tope, Geeta; Kandasamy, Kumaran; Lopez-Fuentes, Alejandra C.; Mi, Huaiyu; Pichler, Elgar; Rodchenkov, Igor; Splendiani, Andrea; Tkachev, Sasha; Zucker, Jeremy; Gopinath, Gopal; Rajasimha, Harsha; Ramakrishnan, Ranjani; Shah, Imran; Syed, Mustafa; Anwar, Nadia; Babur, Ozgun; Blinov, Michael; Brauner, Erik; Corwin, Dan; Donaldson, Sylva; Gibbons, Frank; Goldberg, Robert; Hornbeck, Peter; Luna, Augustin; Murray-Rust, Peter; Neumann, Eric; Reubenacker, Oliver; Samwald, Matthias; van Iersel, Martijn; Wimalaratne, Sarala; Allen, Keith; Braun, Burk; Whirl-Carrillo, Michelle; Dahlquist, Kam; Finney, Andrew; Gillespie, Marc; Glass, Elizabeth; Gong, Li; Haw, Robin; Honig, Michael; Hubaut, Olivier; Kane, David; Krupa, Shiva; Kutmon, Martina; Leonard, Julie; Marks, Debbie; Merberg, David; Petri, Victoria; Pico, Alex; Ravenscroft, Dean; Ren, Liya; Shah, Nigam; Sunshine, Margot; Tang, Rebecca; Whaley, Ryan; Letovksy, Stan; Buetow, Kenneth H.; Rzhetsky, Andrey; Schachter, Vincent; Sobral, Bruno S.; Dogrusoz, Ugur; McWeeney, Shannon; Aladjem, Mirit; Birney, Ewan; Collado-Vides, Julio; Goto, Susumu; Hucka, Michael; Le Novère, Nicolas; Maltsev, Natalia; Pandey, Akhilesh; Thomas, Paul; Wingender, Edgar; Karp, Peter D.; Sander, Chris; Bader, Gary D.

2010-01-01

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery. PMID:20829833

Phosphoproteomics profiling of human skin fibroblast cells reveals pathways and proteins affected by low doses of ionizing radiation.

PubMed

Yang, Feng; Waters, Katrina M; Miller, John H; Gritsenko, Marina A; Zhao, Rui; Du, Xiuxia; Livesay, Eric A; Purvine, Samuel O; Monroe, Matthew E; Wang, Yingchun; Camp, David G; Smith, Richard D; Stenoien, David L

2010-11-30

High doses of ionizing radiation result in biological damage; however, the precise relationships between long-term health effects, including cancer, and low-dose exposures remain poorly understood and are currently extrapolated using high-dose exposure data. Identifying the signaling pathways and individual proteins affected at the post-translational level by radiation should shed valuable insight into the molecular mechanisms that regulate dose-dependent responses to radiation. We have identified 7117 unique phosphopeptides (2566 phosphoproteins) from control and irradiated (2 and 50 cGy) primary human skin fibroblasts 1 h post-exposure. Semi-quantitative label-free analyses were performed to identify phosphopeptides that are apparently altered by radiation exposure. This screen identified phosphorylation sites on proteins with known roles in radiation responses including TP53BP1 as well as previously unidentified radiation-responsive proteins such as the candidate tumor suppressor SASH1. Bioinformatic analyses suggest that low and high doses of radiation affect both overlapping and unique biological processes and suggest a role for MAP kinase and protein kinase A (PKA) signaling in the radiation response as well as differential regulation of p53 networks at low and high doses of radiation. Our results represent the most comprehensive analysis of the phosphoproteomes of human primary fibroblasts exposed to multiple doses of ionizing radiation published to date and provide a basis for the systems-level identification of biological processes, molecular pathways and individual proteins regulated in a dose dependent manner by ionizing radiation. Further study of these modified proteins and affected networks should help to define the molecular mechanisms that regulate biological responses to radiation at different radiation doses and elucidate the impact of low-dose radiation exposure on human health.

Phosphoproteomics Profiling of Human Skin Fibroblast Cells Reveals Pathways and Proteins Affected by Low Doses of Ionizing Radiation

PubMed Central

Yang, Feng; Waters, Katrina M.; Miller, John H.; Gritsenko, Marina A.; Zhao, Rui; Du, Xiuxia; Livesay, Eric A.; Purvine, Samuel O.; Monroe, Matthew E.; Wang, Yingchun; Camp, David G.; Smith, Richard D.; Stenoien, David L.

2010-01-01

Background High doses of ionizing radiation result in biological damage; however, the precise relationships between long-term health effects, including cancer, and low-dose exposures remain poorly understood and are currently extrapolated using high-dose exposure data. Identifying the signaling pathways and individual proteins affected at the post-translational level by radiation should shed valuable insight into the molecular mechanisms that regulate dose-dependent responses to radiation. Principal Findings We have identified 7117 unique phosphopeptides (2566 phosphoproteins) from control and irradiated (2 and 50 cGy) primary human skin fibroblasts 1 h post-exposure. Semi-quantitative label-free analyses were performed to identify phosphopeptides that are apparently altered by radiation exposure. This screen identified phosphorylation sites on proteins with known roles in radiation responses including TP53BP1 as well as previously unidentified radiation-responsive proteins such as the candidate tumor suppressor SASH1. Bioinformatic analyses suggest that low and high doses of radiation affect both overlapping and unique biological processes and suggest a role for MAP kinase and protein kinase A (PKA) signaling in the radiation response as well as differential regulation of p53 networks at low and high doses of radiation. Conclusions Our results represent the most comprehensive analysis of the phosphoproteomes of human primary fibroblasts exposed to multiple doses of ionizing radiation published to date and provide a basis for the systems-level identification of biological processes, molecular pathways and individual proteins regulated in a dose dependent manner by ionizing radiation. Further study of these modified proteins and affected networks should help to define the molecular mechanisms that regulate biological responses to radiation at different radiation doses and elucidate the impact of low-dose radiation exposure on human health. PMID:21152398

High salt diet induces metabolic alterations in multiple biological processes of Dahl salt-sensitive rats.

PubMed

Wang, Yanjun; Liu, Xiangyang; Zhang, Chen; Wang, Zhengjun

2018-06-01

High salt induced renal disease is a condition resulting from the interactions of genetic and dietary factors causing multiple complications. To understand the metabolic alterations associated with renal disease, we comprehensively analyzed the metabonomic changes induced by high salt intake in Dahl salt-sensitive (SS) rats using GC-MS technology and biochemical analyses. Physiological features, serum chemistry, and histopathological data were obtained as complementary information. Our results showed that high salt (HS) intake for 16 weeks caused significant metabolic alterations in both the renal medulla and cortex involving a variety pathways involved in the metabolism of organic acids, amino acids, fatty acids, and purines. In addition, HS enhanced glycolysis (hexokinase, phosphofructokinase and pyruvate kinase) and amino acid metabolism and suppressed the TCA (citrate synthase and aconitase) cycle. Finally, HS intake caused up-regulation of the pentose phosphate pathway (glucose 6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase), the ratio of NADPH/NADP + , NADPH oxidase activity and ROS production, suggesting that increased oxidative stress was associated with an altered PPP pathway. The metabolic pathways identified may serve as potential targets for the treatment of renal damage. Our findings provide comprehensive biochemical details about the metabolic responses to a high salt diet, which may contribute to the understanding of renal disease and salt-induced hypertension in SS rats. Copyright © 2018. Published by Elsevier Inc.

Phosphoproteomics analyses show subnetwork systems in T-cell receptor signaling.

PubMed

Hatano, Atsushi; Matsumoto, Masaki; Nakayama, Keiichi I

2016-10-01

A key issue in the study of signal transduction is how multiple signaling pathways are systematically integrated into the cell. We have now performed multiple phosphoproteomics analyses focused on the dynamics of the T-cell receptor (TCR) signaling network and its subsystem mediated by the Ca 2+ signaling pathway. Integration of these phosphoproteomics data sets and extraction of components of the TCR signaling network dependent on Ca 2+ signaling showed unexpected phosphorylation kinetics for candidate substrates of the Ca 2+ -dependent phosphatase calcineurin (CN) during TCR stimulation. Detailed characterization of the TCR-induced phosphorylation of a novel CN substrate, Itpkb, showed that phosphorylation of this protein is regulated by both CN and the mitogen-activated protein kinase Erk in a competitive manner. Phosphorylation of additional CN substrates was also found to be regulated by Erk and CN in a similar manner. The combination of multiple phosphoproteomics approaches thus showed two major subsystems mediated by Erk and CN in the TCR signaling network, with these subsystems regulating the phosphorylation of a group of proteins in a competitive manner. © 2016 Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.

Epigenomics of Hypertension

PubMed Central

Liang, Mingyu; Cowley, Allen W.; Mattson, David L.; Kotchen, Theodore A.; Liu, Yong

2013-01-01

Multiple genes and pathways are involved in the pathogenesis of hypertension. Epigenomic studies of hypertension are beginning to emerge and hold great promise of providing novel insights into the mechanisms underlying hypertension. Epigenetic marks or mediators including DNA methylation, histone modifications, and non-coding RNA can be studied at a genome or near-genome scale using epigenomic approaches. At the single gene level, several studies have identified changes in epigenetic modifications in genes expressed in the kidney that correlate with the development of hypertension. Systematic analysis and integration of epigenetic marks at the genome scale, demonstration of cellular and physiological roles of specific epigenetic modifications, and investigation of inheritance are among the major challenges and opportunities for future epigenomic and epigenetic studies of hypertension. Essential hypertension is a multifactorial disease involving multiple genetic and environmental factors and mediated by alterations in multiple biological pathways. Because the non-genetic mechanisms may involve epigenetic modifications, epigenomics is one of the latest concepts and approaches brought to bear on hypertension research. In this article, we summarize briefly the concepts and techniques for epigenomics, discuss the rationale for applying epigenomic approaches to study hypertension, and review the current state of this research area. PMID:24011581

Expansion of Protein Farnesyltransferase Specificity Using “Tunable” Active Site Interactions

PubMed Central

Hougland, James L.; Gangopadhyay, Soumyashree A.; Fierke, Carol A.

2012-01-01

Post-translational modifications play essential roles in regulating protein structure and function. Protein farnesyltransferase (FTase) catalyzes the biologically relevant lipidation of up to several hundred cellular proteins. Site-directed mutagenesis of FTase coupled with peptide selectivity measurements demonstrates that molecular recognition is determined by a combination of multiple interactions. Targeted randomization of these interactions yields FTase variants with altered and, in some cases, bio-orthogonal selectivity. We demonstrate that FTase specificity can be “tuned” using a small number of active site contacts that play essential roles in discriminating against non-substrates in the wild-type enzyme. This tunable selectivity extends in vivo, with FTase variants enabling the creation of bioengineered parallel prenylation pathways with altered substrate selectivity within a cell. Engineered FTase variants provide a novel avenue for probing both the selectivity of prenylation pathway enzymes and the effects of prenylation pathway modifications on the cellular function of a protein. PMID:22992747

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

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

Gastrointestinal Toxicities With Combined Antiangiogenic and Stereotactic Body Radiation Therapy

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

Pollom, Erqi L.; Deng, Lei; Pai, Reetesh K.

2015-07-01

Combining the latest targeted biologic agents with the most advanced radiation technologies has been an exciting development in the treatment of cancer patients. Stereotactic body radiation therapy (SBRT) is an ablative radiation approach that has become established for the treatment of a variety of malignancies, and it has been increasingly used in combination with biologic agents, including those targeting angiogenesis-specific pathways. Multiple reports have emerged describing unanticipated toxicities arising from the combination of SBRT and angiogenesis-targeting agents, particularly of late luminal gastrointestinal toxicities. In this review, we summarize the literature describing these toxicities, explore the biological mechanism of action ofmore » toxicity with the combined use of antiangiogenic therapies, and discuss areas of future research, so that this combination of treatment modalities can continue to be used in broader clinical contexts.« less

On determining firing delay time of transitions for Petri net based signaling pathways by introducing stochastic decision rules.

PubMed

Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru

2010-01-01

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

On determining firing delay time of transitions for petri net based signaling pathways by introducing stochastic decision rules.

PubMed

Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru

2011-01-01

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

Service-based analysis of biological pathways

PubMed Central

Zheng, George; Bouguettaya, Athman

2009-01-01

Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403

Prediction of target genes for miR-140-5p in pulmonary arterial hypertension using bioinformatics methods.

PubMed

Li, Fangwei; Shi, Wenhua; Wan, Yixin; Wang, Qingting; Feng, Wei; Yan, Xin; Wang, Jian; Chai, Limin; Zhang, Qianqian; Li, Manxiang

2017-12-01

The expression of microRNA (miR)-140-5p is known to be reduced in both pulmonary arterial hypertension (PAH) patients and monocrotaline-induced PAH models in rat. Identification of target genes for miR-140-5p with bioinformatics analysis may reveal new pathways and connections in PAH. This study aimed to explore downstream target genes and relevant signaling pathways regulated by miR-140-5p to provide theoretical evidences for further researches on role of miR-140-5p in PAH. Multiple downstream target genes and upstream transcription factors (TFs) of miR-140-5p were predicted in the analysis. Gene ontology (GO) enrichment analysis indicated that downstream target genes of miR-140-5p were enriched in many biological processes, such as biological regulation, signal transduction, response to chemical stimulus, stem cell proliferation, cell surface receptor signaling pathways. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis found that downstream target genes were mainly located in Notch, TGF-beta, PI3K/Akt, and Hippo signaling pathway. According to TF-miRNA-mRNA network, the important downstream target genes of miR-140-5p were PPI, TGF-betaR1, smad4, JAG1, ADAM10, FGF9, PDGFRA, VEGFA, LAMC1, TLR4, and CREB. After thoroughly reviewing published literature, we found that 23 target genes and seven signaling pathways were truly inhibited by miR-140-5p in various tissues or cells; most of these verified targets were in accordance with our present prediction. Other predicted targets still need further verification in vivo and in vitro .

Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.

PubMed

Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas

2016-01-01

Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

Evolution of Bow-Tie Architectures in Biology

PubMed Central

Friedlander, Tamar; Mayo, Avraham E.; Tlusty, Tsvi; Alon, Uri

2015-01-01

Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. PMID:25798588

THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK: A FRAMEWORK FOR ORGANIZING BIOLOGICAL KNOWLEDGE LEADING TO HEALTH RISKS.

EPA Science Inventory

An Adverse Outcome Pathway (AOP) represents the organization of current and newly acquired knowledge of biological pathways. These pathways contain a series of nodes (Key Events, KEs) that when sufficiently altered influence the next node on the pathway, beginning from an Molecul...

Gene expression analysis of colorectal cancer by bioinformatics strategy.

PubMed

Cui, Meng; Yuan, Junhua; Li, Jun; Sun, Bing; Li, Tao; Li, Yuantao; Wu, Guoliang

2014-10-01

We used bioinformatics technology to analyze gene expression profiles involved in colorectal cancer tissue samples and healthy controls. In this paper, we downloaded the gene expression profile GSE4107 from Gene Expression Omnibus (GEO) database, in which a total of 22 chips were available, including normal colonic mucosa tissue from normal healthy donors (n=10), colorectal cancer tissue samples from colorectal patients (n=33). To further understand the biological functions of the screened DGEs, the KEGG pathway enrichment analysis were conducted. Then we built a transcriptome network to study differentially co-expressed links. A total of 3151 DEGs of CRC were selected. Besides, total 164 DCGs (Differentially Coexpressed Gene, DCG) and 29279 DCLs (Differentially Co-expressed Link, DCL) were obtained. Furthermore, the significantly enriched KEGG pathways were Endocytosis, Calcium signaling pathway, Vascular smooth muscle contraction, Linoleic acid metabolism, Arginine and proline metabolism, Inositol phosphate metabolism and MAPK signaling pathway. Our results show that the generation of CRC involves multiple genes, TFs and pathways. Several signal and immune pathways are linked to CRC and give us more clues in the process of CRC. Hence, our work would pave ways for novel diagnosis of CRC, and provided theoretical guidance into cancer therapy.

Interactive and coordinated visualization approaches for biological data analysis.

PubMed

Cruz, António; Arrais, Joel P; Machado, Penousal

2018-03-26

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.

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.

Modeling biochemical pathways in the gene ontology

DOE PAGES

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...

2016-09-01

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

The Need for Integrated Approaches in Metabolic Engineering.

PubMed

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D

2016-11-01

This review highlights state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. We emphasize that a combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the "system" that is being manipulated: transcriptome, translatome, proteome, or reactome. By bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.

The β-Arrestins: Multifunctional Regulators of G Protein-coupled Receptors.

PubMed

Smith, Jeffrey S; Rajagopal, Sudarshan

2016-04-22

The β-arrestins (βarrs) are versatile, multifunctional adapter proteins that are best known for their ability to desensitize G protein-coupled receptors (GPCRs), but also regulate a diverse array of cellular functions. To signal in such a complex fashion, βarrs adopt multiple conformations and are regulated at multiple levels to differentially activate downstream pathways. Recent structural studies have demonstrated that βarrs have a conserved structure and activation mechanism, with plasticity of their structural fold, allowing them to adopt a wide array of conformations. Novel roles for βarrs continue to be identified, demonstrating the importance of these dynamic regulators of cellular signaling. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multiple biological pathways link cognitive lifestyle to protection from dementia.

PubMed

Valenzuela, Michael J; Matthews, Fiona E; Brayne, Carol; Ince, Paul; Halliday, Glenda; Kril, Jillian J; Dalton, Marshall A; Richardson, Kathryn; Forster, Gill; Sachdev, Perminder S

2012-05-01

An active cognitive lifestyle is linked to diminished dementia risk, but the underlying mechanisms are poorly understood. Potential mechanisms include disease modification, neuroprotection, and compensation. Prospective, population-based brain series provide the rare opportunity to test the plausibility of these mechanisms in humans. Participants came from the United Kingdom Medical Research Council Cognitive Function and Ageing Study, comprising 13,004 individuals aged over 65 years and followed for 14 years. In study 1, a Cognitive Lifestyle Score (CLS) was computed on all Cognitive Function and Ageing Study subjects to define low, middle, and high groups. By August 2004, 329 individuals with CLS data had come to autopsy and underwent Consortium to Establish a Registry of Alzheimer's Disease assessment. Study 2 involved more detailed quantitative histology in the hippocampus and Brodmann area 9 in 72 clinically matched individuals with high and low CLS. CLS groups did not differ on several Alzheimer disease neuropathologic measures; however, high CLS men had less cerebrovascular disease after accounting for vascular risk factors, and women had greater brain weight. No group differences were evident in hippocampal neuronal density. In Brodmann area 9, cognitively active individuals had significantly greater neuronal density, as well as correlated increases in cortical thickness. An active cognitive lifestyle was associated with protection from cerebrovascular disease in men, but there was no evidence for Alzheimer disease modification or hippocampal neuroprotection. Men and women both exhibited neurotrophic changes in the prefrontal lobe linked to cognitive lifestyle, consistent with a compensatory process. Lifespan complex cognitive activity may therefore protect against dementia through multiple biological pathways. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

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

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.

2016-05-03

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of thismore » protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical). IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.« less

Proteomic analysis of Bombyx mori molting fluid: Insights into the molting process.

PubMed

Liu, Hua-Wei; Wang, Luo-Ling; Tang, Xin; Dong, Zhao-Ming; Guo, Peng-Chao; Zhao, Dong-Chao; Xia, Qing-You; Zhao, Ping

2018-02-20

Molting is an essential biological process occurring multiple times throughout the life cycle of most Ecdysozoa. Molting fluids accumulate and function in the exuvial space during the molting process. In this study, we used liquid chromatography-tandem mass spectrometry to investigate the molting fluids to analyze the molecular mechanisms of molting in the silkworm, Bombyx mori. In total, 375 proteins were identified in molting fluids from the silkworm at 14-16h before pupation and eclosion, including 12 chitin metabolism-related enzymes, 35 serine proteases, 15 peptidases, and 38 protease inhibitors. Gene ontology analysis indicated that "catalytic" constitutes the most enriched function in the molting fluid. Gene expression patterns and bioinformatic analyses suggested that numerous enzymes are involved in the degradation of cuticle proteins and chitin. Protein-protein interaction network and activity analyses showed that protease inhibitors are involved in the regulation of multiple pathways in molting fluid. Additionally, many immune-related proteins may be involved in the immune defense during molting. These results provide a comprehensive proteomic insight into proteolytic enzymes and protease inhibitors in molting fluid, and will likely improve the current understanding of physiological processes in insect molting. Insect molting constitutes a dynamic physiological process. To better understand this process, we used LC-MS/MS to investigate the proteome of silkworm molting fluids and identified key proteins involved in silkworm molting. The biological processes of the old cuticle degradation pathway and immune defense response were analyzed in the proteome of silkworm molting fluid. We report that protease inhibitors serve as key factors in the regulation of the molting process. The proteomic results provide new insight into biological molting processes in insects. Copyright © 2017 Elsevier B.V. All rights reserved.

Synthetic Biology: Putting Synthesis into Biology

PubMed Central

Liang, Jing; Luo, Yunzi; Zhao, Huimin

2010-01-01

The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways, and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself – encompassing many branches of science, and across many scales of application. New DNA synthesis and assembly techniques have made routine the customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery – a self-replicating organism – is being pursued at this moment. It is the purpose of this review to dissect and organize these various components of synthetic biology into a coherent picture. PMID:21064036

An integrated pathway system modeling of Saccharomyces cerevisiae HOG pathway: a Petri net based approach.

PubMed

Tomar, Namrata; Choudhury, Olivia; Chakrabarty, Ankush; De, Rajat K

2013-02-01

Biochemical networks comprise many diverse components and interactions between them. It has intracellular signaling, metabolic and gene regulatory pathways which are highly integrated and whose responses are elicited by extracellular actions. Previous modeling techniques mostly consider each pathway independently without focusing on the interrelation of these which actually functions as a single system. In this paper, we propose an approach of modeling an integrated pathway using an event-driven modeling tool, i.e., Petri nets (PNs). PNs have the ability to simulate the dynamics of the system with high levels of accuracy. The integrated set of signaling, regulatory and metabolic reactions involved in Saccharomyces cerevisiae's HOG pathway has been collected from the literature. The kinetic parameter values have been used for transition firings. The dynamics of the system has been simulated and the concentrations of major biological species over time have been observed. The phenotypic characteristics of the integrated system have been investigated under two conditions, viz., under the absence and presence of osmotic pressure. The results have been validated favorably with the existing experimental results. We have also compared our study with the study of idFBA (Lee et al., PLoS Comput Biol 4:e1000-e1086, 2008) and pointed out the differences between both studies. We have simulated and monitored concentrations of multiple biological entities over time and also incorporated feedback inhibition by Ptp2 which has not been included in the idFBA study. We have concluded that our study is the first to the best of our knowledge to model signaling, metabolic and regulatory events in an integrated form through PN model framework. This study is useful in computational simulation of system dynamics for integrated pathways as there are growing evidences that the malfunctioning of the interplay among these pathways is associated with disease.

Discovery of functional interactions among actin regulators by analysis of image fluctuations in an unperturbed motile cell system.

PubMed

Isogai, Tadamoto; Danuser, Gaudenz

2018-05-26

Cell migration is driven by propulsive forces derived from polymerizing actin that pushes and extends the plasma membrane. The underlying actin network is constantly undergoing adaptation to new mechano-chemical environments and intracellular conditions. As such, mechanisms that regulate actin dynamics inherently contain multiple feedback loops and redundant pathways. Given the highly adaptable nature of such a system, studies that use only perturbation experiments (e.g. knockdowns, overexpression, pharmacological activation/inhibition, etc.) are challenged by the nonlinearity and redundancy of the pathway. In these pathway configurations, perturbation experiments at best describe the function(s) of a molecular component in an adapting (e.g. acutely drug-treated) or fully adapted (e.g. permanent gene silenced) cell system, where the targeted component now resides in a non-native equilibrium. Here, we propose how quantitative live-cell imaging and analysis of constitutive fluctuations of molecular activities can overcome these limitations. We highlight emerging actin filament barbed-end biology as a prime example of a complex, nonlinear molecular process that requires a fluctuation analytic approach, especially in an unperturbed cellular system, to decipher functional interactions of barbed-end regulators, actin polymerization and membrane protrusion.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Comprehensive analysis of miRNAs expression profiles revealed potential key miRNA/mRNAs regulating colorectal cancer stem cell self-renewal.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-05-20

Self-renewal is essential for the malignant biological behaviors of colorectal cancer stem cells. While the self-renewal molecular mechanisms of colorectal cancer stem cells are not yet fully understood. Recently, miRNAs are reported to be relevant to the self-renewal ability of cancer stem cells. In this study, we first isolated colorectal cancer stem cell from colorectal cancer cell line HCT-116 by 1% low serum culture. Then we conducted a comprehensive analysis based on the miRNAs profiles data of both colorectal cancer stem cells and normal cultured colorectal cancer cells. Pathway analysis revealed multiple pathways including Jak-STAT, TGF-beta, PI3K-Akt and MAPK signaling pathway that are correlated to colorectal cancer. Further, we constructed a miRNA-mRNA network, based on which, several miRNA/mRNA pairs were ranked according to their impact index to the self-renewal of colorectal cancer stem cells. Further biological experiment showed that up-regulation of miR-92a-3p led to cell cycle arrest and reduced colony formation. This work provides clues to find the new potential biomarkers for colorectal cancer stem cell diagnosis and select effective miRNAs for targeted therapy. Copyright © 2018 Elsevier B.V. All rights reserved.

Functional Analogy in Human Metabolism: Enzymes with Different Biological Roles or Functional Redundancy?

PubMed Central

Piergiorge, Rafael Mina; de Miranda, Antonio Basílio; Catanho, Marcos

2017-01-01

Abstract Since enzymes catalyze almost all chemical reactions that occur in living organisms, it is crucial that genes encoding such activities are correctly identified and functionally characterized. Several studies suggest that the fraction of enzymatic activities in which multiple events of independent origin have taken place during evolution is substantial. However, this topic is still poorly explored, and a comprehensive investigation of the occurrence, distribution, and implications of these events has not been done so far. Fundamental questions, such as how analogous enzymes originate, why so many events of independent origin have apparently occurred during evolution, and what are the reasons for the coexistence in the same organism of distinct enzymatic forms catalyzing the same reaction, remain unanswered. Also, several isofunctional enzymes are still not recognized as nonhomologous, even with substantial evidence indicating different evolutionary histories. In this work, we begin to investigate the biological significance of the cooccurrence of nonhomologous isofunctional enzymes in human metabolism, characterizing functional analogous enzymes identified in metabolic pathways annotated in the human genome. Our hypothesis is that the coexistence of multiple enzymatic forms might not be interpreted as functional redundancy. Instead, these enzymatic forms may be implicated in distinct (and probably relevant) biological roles. PMID:28854631

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis.

PubMed

Baranzini, Sergio E; Srinivasan, Radhika; Khankhanian, Pouya; Okuda, Darin T; Nelson, Sarah J; Matthews, Paul M; Hauser, Stephen L; Oksenberg, Jorge R; Pelletier, Daniel

2010-09-01

Glutamate is the main excitatory neurotransmitter in the mammalian brain. Appropriate transmission of nerve impulses through glutamatergic synapses is required throughout the brain and forms the basis of many processes including learning and memory. However, abnormally high levels of extracellular brain glutamate can lead to neuroaxonal cell death. We have previously reported elevated glutamate levels in the brains of patients suffering from multiple sclerosis. Here two complementary analyses to assess the extent of genomic control over glutamate levels were used. First, a genome-wide association analysis in 382 patients with multiple sclerosis using brain glutamate concentration as a quantitative trait was conducted. In a second approach, a protein interaction network was used to find associated genes within the same pathway. The top associated marker was rs794185 (P < 6.44 x 10(-7)), a non-coding single nucleotide polymorphism within the gene sulphatase modifying factor 1. Our pathway approach identified a module composed of 70 genes with high relevance to glutamate biology. Individuals carrying a higher number of associated alleles from genes in this module showed the highest levels of glutamate. These individuals also showed greater decreases in N-acetylaspartate and in brain volume over 1 year of follow-up. Patients were then stratified by the amount of annual brain volume loss and the same approach was performed in the 'high' (n = 250) and 'low' (n = 132) neurodegeneration groups. The association with rs794185 was highly significant in the group with high neurodegeneration. Further, results from the network-based pathway analysis remained largely unchanged even after stratification. Results from these analyses indicated that variance in the activity of neurochemical pathways implicated in neurodegeneration is explained, at least in part, by the inheritance of common genetic polymorphisms. Spectroscopy-based imaging provides a novel quantitative endophenotype for genetic association studies directed towards identifying new factors that contribute to the heterogeneity of clinical expression of multiple sclerosis.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy. PMID:26680552

ReNE: A Cytoscape Plugin for Regulatory Network Enhancement

PubMed Central

Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

2014-01-01

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by ReNE is exportable in multiple formats for further analysis via third party applications. ReNE can be freely installed from the Cytoscape App Store (http://apps.cytoscape.org/apps/rene) and the full source code is freely available for download through a SVN repository accessible at http://www.sysbio.polito.it/tools_svn/BioInformatics/Rene/releases/. ReNE enhances a network by only integrating data from public repositories, without any inference or prediction. The reliability of the introduced interactions only depends on the reliability of the source data, which is out of control of ReNe developers. PMID:25541727

Cancer Systems Biology Consortium | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Cancer is a complex disease system involving multiple molecular, genetic, and cellular events. From its early initiation through progression and metastasis, cancer can adapt and evolve as a result of both internal and external signals. These properties make cancer difficult to predict, prevent, and treat. There has been significant progress in characterizing the genetics of cancer, as well as the downstream effects on the molecular and cellular pathways that are critical for the initiation and progression of cancer.

Identification of Chiari Type I Malformation subtypes using whole genome expression profiles and cranial base morphometrics

PubMed Central

2014-01-01

Background Chiari Type I Malformation (CMI) is characterized by herniation of the cerebellar tonsils through the foramen magnum at the base of the skull, resulting in significant neurologic morbidity. As CMI patients display a high degree of clinical variability and multiple mechanisms have been proposed for tonsillar herniation, it is hypothesized that this heterogeneous disorder is due to multiple genetic and environmental factors. The purpose of the present study was to gain a better understanding of what factors contribute to this heterogeneity by using an unsupervised statistical approach to define disease subtypes within a case-only pediatric population. Methods A collection of forty-four pediatric CMI patients were ascertained to identify disease subtypes using whole genome expression profiles generated from patient blood and dura mater tissue samples, and radiological data consisting of posterior fossa (PF) morphometrics. Sparse k-means clustering and an extension to accommodate multiple data sources were used to cluster patients into more homogeneous groups using biological and radiological data both individually and collectively. Results All clustering analyses resulted in the significant identification of patient classes, with the pure biological classes derived from patient blood and dura mater samples demonstrating the strongest evidence. Those patient classes were further characterized by identifying enriched biological pathways, as well as correlated cranial base morphological and clinical traits. Conclusions Our results implicate several strong biological candidates warranting further investigation from the dura expression analysis and also identified a blood gene expression profile corresponding to a global down-regulation in protein synthesis. PMID:24962150

Identification of urinary metabolites of imperatorin with a single run on an LC/Triple TOF system based on multiple mass defect filter data acquisition and multiple data mining techniques.

PubMed

Qiao, Shi; Shi, Xiaowei; Shi, Rui; Liu, Man; Liu, Ting; Zhang, Kerong; Wang, Qiao; Yao, Meicun; Zhang, Lantong

2013-08-01

The detection of drug metabolites, especially for minor metabolites, continues to be a challenge because of the complexity of biological samples. Imperatorin (IMP) is an active natural furocoumarin component originating from many traditional Chinese herbal medicines and is expected to be pursued as a new vasorelaxant agent. In the present study, a generic and efficient approach was developed for the in vivo screening and identification of IMP metabolites using liquid chromatography-Triple TOF mass spectrometry. In this approach, a novel on-line data acquisition method mutiple mass defect filter (MMDF) combined with dynamic background subtraction was developed to trace all probable urinary metabolites of IMP. Comparing with the traditionally intensity-dependent data acquisition method, MMDF method could give the information of low-level metabolites masked by background noise and endogenous components. Thus, the minor metabolites in complex biological matrices could be detected. Then, the sensitive and specific multiple data-mining techniques extracted ion chromatography, mass defect filter, product ion filter, and neutral loss filter were used for the discovery of IMP metabolites. Based on the proposed strategy, 44 phase I and 7 phase II metabolites were identified in rat urine after oral administration of IMP. The results indicated that oxidization was the main metabolic pathway and that different oxidized substituent positions had a significant influence on the fragmentation of the metabolites. Two types of characteristic ions at m/z 203 and 219 can be observed in the MS/MS spectra. This is the first study of IMP metabolism in vivo. The interpretation of the MS/MS spectra of these metabolites and the proposed metabolite pathway provide essential data for further pharmacological studies of other linear-type furocoumarins.

An Oral Load of [13C3]Glycerol and Blood NMR Analysis Detect Fatty Acid Esterification, Pentose Phosphate Pathway, and Glycerol Metabolism through the Tricarboxylic Acid Cycle in Human Liver.

PubMed

Jin, Eunsook S; Sherry, A Dean; Malloy, Craig R

2016-09-02

Drugs and other interventions for high impact hepatic diseases often target biochemical pathways such as gluconeogenesis, lipogenesis, or the metabolic response to oxidative stress. However, traditional liver function tests do not provide quantitative data about these pathways. In this study, we developed a simple method to evaluate these processes by NMR analysis of plasma metabolites. Healthy subjects ingested [U-(13)C3]glycerol, and blood was drawn at multiple times. Each subject completed three visits under differing nutritional states. High resolution (13)C NMR spectra of plasma triacylglycerols and glucose provided new insights into a number of hepatic processes including fatty acid esterification, the pentose phosphate pathway, and gluconeogenesis through the tricarboxylic acid cycle. Fasting stimulated pentose phosphate pathway activity and metabolism of [U-(13)C3]glycerol in the tricarboxylic acid cycle prior to gluconeogenesis or glyceroneogenesis. Fatty acid esterification was transient in the fasted state but continuous under fed conditions. We conclude that a simple NMR analysis of blood metabolites provides an important biomarker of pentose phosphate pathway activity, triacylglycerol synthesis, and flux through anaplerotic pathways in mitochondria of human liver. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

PTEN: Multiple Functions in Human Malignant Tumors.

PubMed

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Cesta Incani, Ursula; Del Curatolo, Anais; Inzerilli, Nicola; Nuzzo, Carmen M A; Vaccaro, Vanja; Vari, Sabrina; Cognetti, Francesco; Ciuffreda, Ludovica

2015-01-01

PTEN is the most important negative regulator of the PI3K signaling pathway. In addition to its canonical, PI3K inhibition-dependent functions, PTEN can also function as a tumor suppressor in a PI3K-independent manner. Indeed, the PTEN network regulates a broad spectrum of biological functions, modulating the flow of information from membrane-bound growth factor receptors to nuclear transcription factors, occurring in concert with other tumor suppressors and oncogenic signaling pathways. PTEN acts through its lipid and protein phosphatase activity and other non-enzymatic mechanisms. Studies conducted over the past 10 years have expanded our understanding of the biological role of PTEN, showing that in addition to its ability to regulate proliferation and cell survival, it also plays an intriguing role in regulating genomic stability, cell migration, stem cell self-renewal, and tumor microenvironment. Changes in PTEN protein levels, location, and enzymatic activity through various molecular mechanisms can generate a continuum of functional PTEN levels in inherited syndromes, sporadic cancers, and other diseases. PTEN activity can indeed, be modulated by mutations, epigenetic silencing, transcriptional repression, aberrant protein localization, and post-translational modifications. This review will discuss our current understanding of the biological role of PTEN, how PTEN expression and activity are regulated, and the consequences of PTEN dysregulation in human malignant tumors.

PTEN: Multiple Functions in Human Malignant Tumors

PubMed Central

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Cesta Incani, Ursula; Del Curatolo, Anais; Inzerilli, Nicola; Nuzzo, Carmen M. A.; Vaccaro, Vanja; Vari, Sabrina; Cognetti, Francesco; Ciuffreda, Ludovica

2015-01-01

PTEN is the most important negative regulator of the PI3K signaling pathway. In addition to its canonical, PI3K inhibition-dependent functions, PTEN can also function as a tumor suppressor in a PI3K-independent manner. Indeed, the PTEN network regulates a broad spectrum of biological functions, modulating the flow of information from membrane-bound growth factor receptors to nuclear transcription factors, occurring in concert with other tumor suppressors and oncogenic signaling pathways. PTEN acts through its lipid and protein phosphatase activity and other non-enzymatic mechanisms. Studies conducted over the past 10 years have expanded our understanding of the biological role of PTEN, showing that in addition to its ability to regulate proliferation and cell survival, it also plays an intriguing role in regulating genomic stability, cell migration, stem cell self-renewal, and tumor microenvironment. Changes in PTEN protein levels, location, and enzymatic activity through various molecular mechanisms can generate a continuum of functional PTEN levels in inherited syndromes, sporadic cancers, and other diseases. PTEN activity can indeed, be modulated by mutations, epigenetic silencing, transcriptional repression, aberrant protein localization, and post-translational modifications. This review will discuss our current understanding of the biological role of PTEN, how PTEN expression and activity are regulated, and the consequences of PTEN dysregulation in human malignant tumors. PMID:25763354

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Refining Pathways: A Model Comparison Approach

PubMed Central

Moffa, Giusi; Erdmann, Gerrit; Voloshanenko, Oksana; Hundsrucker, Christian; Sadeh, Mohammad J.; Boutros, Michael; Spang, Rainer

2016-01-01

Cellular signalling pathways consolidate multiple molecular interactions into working models of signal propagation, amplification, and modulation. They are described and visualized as networks. Adjusting network topologies to experimental data is a key goal of systems biology. While network reconstruction algorithms like nested effects models are well established tools of computational biology, their data requirements can be prohibitive for their practical use. In this paper we suggest focussing on well defined aspects of a pathway and develop the computational tools to do so. We adapt the framework of nested effect models to focus on a specific aspect of activated Wnt signalling in HCT116 colon cancer cells: Does the activation of Wnt target genes depend on the secretion of Wnt ligands or do mutations in the signalling molecule β-catenin make this activation independent from them? We framed this question into two competing classes of models: Models that depend on Wnt ligands secretion versus those that do not. The model classes translate into restrictions of the pathways in the network topology. Wnt dependent models are more flexible than Wnt independent models. Bayes factors are the standard Bayesian tool to compare different models fairly on the data evidence. In our analysis, the Bayes factors depend on the number of potential Wnt signalling target genes included in the models. Stability analysis with respect to this number showed that the data strongly favours Wnt ligands dependent models for all realistic numbers of target genes. PMID:27248690

Roles for miR-375 in Neuroendocrine Differentiation and Tumor Suppression via Notch Pathway Suppression in Merkel Cell Carcinoma.

PubMed

Abraham, Karan J; Zhang, Xiao; Vidal, Ricardo; Paré, Geneviève C; Feilotter, Harriet E; Tron, Victor A

2016-04-01

Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Mutational analysis of PI3K/AKT and RAS/RAF pathway activation in malignant salivary gland tumours with a new mutation of PIK3CA.

PubMed

Shalmon, B; Drendel, M; Wolf, M; Hirshberg, A; Cohen, Y

2016-06-01

The phosphoinositide 3-kinase (PIK3)/v-akt murine thymoma (AKT) oncogene pathway and the RAS/RAF pathway are involved in regulating the signalling of multiple biological processes, including apoptosis, metabolism, cell proliferation, and cell growth. Mutations in the genes within these pathways are frequently found in several tumours. The aim of this study was to investigate the frequency of mutations in the PIK3CA, BRAF, and KRAS genes in cases of malignant salivary gland tumours. Mutational analysis of the PIK3CA, KRAS, and BRAF genes was performed by direct sequencing of material from 21 patients with malignant salivary gland tumours who underwent surgery between 1992 and 2001. No mutations were found in the KRAS exon 2, BRAF exon 15, or PIK3CA exon 9 genes. However, an unpublished mutation of the PIK3CA gene in exon 20 (W1051 stop mutation) was found in one case of adenocarcinoma NOS. The impact of this mutation on the biological behaviour of the tumour has yet to be explored, however the patient with adenocarcinoma NOS harbouring this mutation has survived for over 20 years following surgery despite a high stage at presentation. Further studies with more homogeneous patient cohorts are needed to address whether this mutation reflects a different clinical presentation and may benefit from targeted treatment strategies. Copyright © 2015 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

LncRNA MEG3 repressed malignant melanoma progression via inactivating Wnt signaling pathway.

PubMed

Li, Peng; Gao, Ying; Li, Jun; Zhou, Yu; Yuan, Jing; Guan, Huiwen; Yao, Peng

2018-05-21

Accumulating evidence has indicated that MEG3 can serve as a tumor suppressive lncRNA in various tumors. It is aberrantly expressed in multiple cancers. However, the biological roles of MEG3 in melanoma are poorly understood. Therefore, in our study, we concentrated on the biological mechanism of MEG3 in melanoma progression. First, we observed that MEG3 was obviously decreased in melanoma cells including A375, SK-MEL-1, B16, and A2058 cells compared to human epidermal melanocytes HEMa-LP. MEG3 was restored by transfecting LV-MEG3 in to A375 and A2058 cells. Subsequently, we found that overexpression of MEG3 was able to inhibit cell proliferation and colony formation capacity. Meanwhile, melanoma cell apoptosis was induced by up-regulation of MEG3. Overexpression of MEG3 greatly repressed melanoma cell migration and invasion ability. In addition, Wnt signaling pathway has been identified in the progression of various cancers. Here, in our study, it was indicated that Wnt signaling was highly activated in melanoma cells with β-catenin expression significantly increased and GSK-3β decreased. Interestingly, MEG restoration strongly inactivated Wnt signaling pathway by reducing β-catenin and CyclinD1, elevating GSK-3β levels in vitro. Finally, in vivo experiments were carried out to confirm the inhibitory roles of MEG3 in vivo. Taken these together, we suggested that MEG3 can inhibit melanoma development through blocking Wnt signaling pathway. © 2018 Wiley Periodicals, Inc.

Rofecoxib modulates multiple gene expression pathways in a clinical model of acute inflammatory pain

PubMed Central

Wang, Xiao-Min; Wu, Tian-Xia; Hamza, May; Ramsay, Edward S.; Wahl, Sharon M.; Dionne, Raymond A.

2007-01-01

New insights into the biological properties of cyclooxygenase-2 (COX-2) and its response pathway challenge the hypothesis that COX-2 is simply pro-inflammatory and inhibition of COX-2 solely prevents the development of inflammation and ameliorates inflammatory pain. The present study performed a comprehensive analysis of gene/protein expression induced by a selective inhibitor of COX-2, rofecoxib, compared with a non-selective COX inhibitor, ibuprofen, and placebo in a clinical model of acute inflammatory pain (the surgical extraction of impacted third molars) using microarray analysis followed by quantitative RT-PCR verification and Western blotting. Inhibition of COX-2 modulated gene expression related to inflammation and pain, the arachidonic acid pathway, apoptosis/angiogenesis, cell adhesion and signal transduction. Compared to placebo, rofecoxib treatment increased the gene expression of ANXA3 (annexin 3), SOD2 (superoxide dismutase 2), SOCS3 (suppressor of cytokine signaling 3) and IL1RN (IL1 receptor antagonist) which are associated with inhibition of phospholipase A2 and suppression of cytokine signaling cascades, respectively. Both rofecoxib and ibuprofen treatment increased the gene expression of the pro-inflammatory mediators, IL6 and CCL2 (chemokine C-C motif ligand 2), following tissue injury compared to the placebo treatment. These results indicate a complex role for COX-2 in the inflammatory cascade in addition to the well-characterized COX-dependent pathway, as multiple pathways are also involved in rofecoxib-induced anti-inflammatory and analgesic effects at the gene expression level. These findings may also suggest an alternative hypothesis for the adverse effects attributed to selective inhibition of COX-2. PMID:17070997

Relation extraction for biological pathway construction using node2vec.

PubMed

Kim, Munui; Baek, Seung Han; Song, Min

2018-06-13

Systems biology is an important field for understanding whole biological mechanisms composed of interactions between biological components. One approach for understanding complex and diverse mechanisms is to analyze biological pathways. However, because these pathways consist of important interactions and information on these interactions is disseminated in a large number of biomedical reports, text-mining techniques are essential for extracting these relationships automatically. In this study, we applied node2vec, an algorithmic framework for feature learning in networks, for relationship extraction. To this end, we extracted genes from paper abstracts using pkde4j, a text-mining tool for detecting entities and relationships. Using the extracted genes, a co-occurrence network was constructed and node2vec was used with the network to generate a latent representation. To demonstrate the efficacy of node2vec in extracting relationships between genes, performance was evaluated for gene-gene interactions involved in a type 2 diabetes pathway. Moreover, we compared the results of node2vec to those of baseline methods such as co-occurrence and DeepWalk. Node2vec outperformed existing methods in detecting relationships in the type 2 diabetes pathway, demonstrating that this method is appropriate for capturing the relatedness between pairs of biological entities involved in biological pathways. The results demonstrated that node2vec is useful for automatic pathway construction.

International Union of Basic and Clinical Pharmacology. XCVII. G Protein–Coupled Estrogen Receptor and Its Pharmacologic Modulators

PubMed Central

2015-01-01

Estrogens are critical mediators of multiple and diverse physiologic effects throughout the body in both sexes, including the reproductive, cardiovascular, endocrine, nervous, and immune systems. As such, alterations in estrogen function play important roles in many diseases and pathophysiological conditions (including cancer), exemplified by the lower prevalence of many diseases in premenopausal women. Estrogens mediate their effects through multiple cellular receptors, including the nuclear receptor family (ERα and ERβ) and the G protein–coupled receptor (GPCR) family (GPR30/G protein–coupled estrogen receptor [GPER]). Although both receptor families can initiate rapid cell signaling and transcriptional regulation, the nuclear receptors are traditionally associated with regulating gene expression, whereas GPCRs are recognized as mediating rapid cellular signaling. Estrogen-activated pathways are not only the target of multiple therapeutic agents (e.g., tamoxifen, fulvestrant, raloxifene, and aromatase inhibitors) but are also affected by a plethora of phyto- and xeno-estrogens (e.g., genistein, coumestrol, bisphenol A, dichlorodiphenyltrichloroethane). Because of the existence of multiple estrogen receptors with overlapping ligand specificities, expression patterns, and signaling pathways, the roles of the individual receptors with respect to the diverse array of endogenous and exogenous ligands have been challenging to ascertain. The identification of GPER-selective ligands however has led to a much greater understanding of the roles of this receptor in normal physiology and disease as well as its interactions with the classic estrogen receptors ERα and ERβ and their signaling pathways. In this review, we describe the history and characterization of GPER over the past 15 years focusing on the pharmacology of steroidal and nonsteroidal compounds that have been employed to unravel the biology of this most recently recognized estrogen receptor. PMID:26023144

Exogenous hydrogen sulfide exerts proliferation, anti-apoptosis, migration effects and accelerates cell cycle progression in multiple myeloma cells via activating the Akt pathway.

PubMed

Zheng, Dong; Chen, Ziang; Chen, Jingfu; Zhuang, Xiaomin; Feng, Jianqiang; Li, Juan

2016-10-01

Hydrogen sulfide (H2S), regarded as the third gaseous transmitter, mediates and induces various biological effects. The present study investigated the effects of H2S on multiple myeloma cell progression via amplifying the activation of Akt pathway in multiple myeloma cells. The level of H2S produced in multiple myeloma (MM) patients and healthy subjects was measured using enzyme-linked immunosorbent assay (ELISA). MM cells were treated with 500 µmol/l NaHS (a donor of H2S) for 24 h. The expression levels of phosphorylated-Akt (p-Akt), Bcl-2 and caspase-3 were measured by western blot assay. Cell viability was detected by Cell Counting Kit 8 (CCK-8). The cell cycle was analyzed by flow cytometry. Our results show that the concentration of H2S was higher in MM patients and that it increased in parallel with disease progression. Treating MM cells with 500 µmol/l NaHS for 24 h markedly increased the expression level of Bcl-2 and the activation of p-Akt, however, the expression level of caspase-3 was decreased, cell viability was increased, and cell cycle progression was accelerated in MM cells. NaHS also induced migration in MM cells in transwell migration assay. Furthermore, co-treatment of MM cells with 500 µmol/l NaHS and 50 µmol/l LY294002 for 24 h significantly overset these effects. In conclusion, our findings demonstrate that the Akt pathway contributes to NaHS-induced cell proliferation, migration and acceleration of cell cycle progression in MM cells.

International Union of Basic and Clinical Pharmacology. XCVII. G Protein-Coupled Estrogen Receptor and Its Pharmacologic Modulators.

PubMed

Prossnitz, Eric R; Arterburn, Jeffrey B

2015-07-01

Estrogens are critical mediators of multiple and diverse physiologic effects throughout the body in both sexes, including the reproductive, cardiovascular, endocrine, nervous, and immune systems. As such, alterations in estrogen function play important roles in many diseases and pathophysiological conditions (including cancer), exemplified by the lower prevalence of many diseases in premenopausal women. Estrogens mediate their effects through multiple cellular receptors, including the nuclear receptor family (ERα and ERβ) and the G protein-coupled receptor (GPCR) family (GPR30/G protein-coupled estrogen receptor [GPER]). Although both receptor families can initiate rapid cell signaling and transcriptional regulation, the nuclear receptors are traditionally associated with regulating gene expression, whereas GPCRs are recognized as mediating rapid cellular signaling. Estrogen-activated pathways are not only the target of multiple therapeutic agents (e.g., tamoxifen, fulvestrant, raloxifene, and aromatase inhibitors) but are also affected by a plethora of phyto- and xeno-estrogens (e.g., genistein, coumestrol, bisphenol A, dichlorodiphenyltrichloroethane). Because of the existence of multiple estrogen receptors with overlapping ligand specificities, expression patterns, and signaling pathways, the roles of the individual receptors with respect to the diverse array of endogenous and exogenous ligands have been challenging to ascertain. The identification of GPER-selective ligands however has led to a much greater understanding of the roles of this receptor in normal physiology and disease as well as its interactions with the classic estrogen receptors ERα and ERβ and their signaling pathways. In this review, we describe the history and characterization of GPER over the past 15 years focusing on the pharmacology of steroidal and nonsteroidal compounds that have been employed to unravel the biology of this most recently recognized estrogen receptor. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Metabolic Coevolution in the Bacterial Symbiosis of Whiteflies and Related Plant Sap-Feeding Insects.

PubMed

Luan, Jun-Bo; Chen, Wenbo; Hasegawa, Daniel K; Simmons, Alvin M; Wintermantel, William M; Ling, Kai-Shu; Fei, Zhangjun; Liu, Shu-Sheng; Douglas, Angela E

2015-09-15

Genomic decay is a common feature of intracellular bacteria that have entered into symbiosis with plant sap-feeding insects. This study of the whitefly Bemisia tabaci and two bacteria (Portiera aleyrodidarum and Hamiltonella defensa) cohoused in each host cell investigated whether the decay of Portiera metabolism genes is complemented by host and Hamiltonella genes, and compared the metabolic traits of the whitefly symbiosis with other sap-feeding insects (aphids, psyllids, and mealybugs). Parallel genomic and transcriptomic analysis revealed that the host genome contributes multiple metabolic reactions that complement or duplicate Portiera function, and that Hamiltonella may contribute multiple cofactors and one essential amino acid, lysine. Homologs of the Bemisia metabolism genes of insect origin have also been implicated in essential amino acid synthesis in other sap-feeding insect hosts, indicative of parallel coevolution of shared metabolic pathways across multiple symbioses. Further metabolism genes coded in the Bemisia genome are of bacterial origin, but phylogenetically distinct from Portiera, Hamiltonella and horizontally transferred genes identified in other sap-feeding insects. Overall, 75% of the metabolism genes of bacterial origin are functionally unique to one symbiosis, indicating that the evolutionary history of metabolic integration in these symbioses is strongly contingent on the pattern of horizontally acquired genes. Our analysis, further, shows that bacteria with genomic decay enable host acquisition of complex metabolic pathways by multiple independent horizontal gene transfers from exogenous bacteria. Specifically, each horizontally acquired gene can function with other genes in the pathway coded by the symbiont, while facilitating the decay of the symbiont gene coding the same reaction. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

PathJam: a new service for integrating biological pathway information.

PubMed

Glez-Peña, Daniel; Reboiro-Jato, Miguel; Domínguez, Rubén; Gómez-López, Gonzalo; Pisano, David G; Fdez-Riverola, Florentino

2010-10-28

Biological pathways are crucial to much of the scientific research today including the study of specific biological processes related with human diseases. PathJam is a new comprehensive and freely accessible web-server application integrating scattered human pathway annotation from several public sources. The tool has been designed for both (i) being intuitive for wet-lab users providing statistical enrichment analysis of pathway annotations and (ii) giving support to the development of new integrative pathway applications. PathJam’s unique features and advantages include interactive graphs linking pathways and genes of interest, downloadable results in fully compatible formats, GSEA compatible output files and a standardized RESTful API.

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

Molecular and clinical significance of fibroblast growth factor 2 (FGF2 /bFGF) in malignancies of solid and hematological cancers for personalized therapies

PubMed Central

Akl, Mohamed R.; Nagpal, Poonam; Ayoub, Nehad M.; Tai, Betty; Prabhu, Sathyen A.; Capac, Catherine M.; Gliksman, Matthew; Goy, Andre; Suh, K. Stephen

2016-01-01

Fibroblast growth factor (FGF) signaling is essential for normal and cancer biology. Mammalian FGF family members participate in multiple signaling pathways by binding to heparan sulfate and FGF receptors (FGFR) with varying affinities. FGF2 is the prototype member of the FGF family and interacts with its receptor to mediate receptor dimerization, phosphorylation, and activation of signaling pathways, such as Ras-MAPK and PI3K pathways. Excessive mitogenic signaling through the FGF/FGFR axis may induce carcinogenic effects by promoting cancer progression and increasing the angiogenic potential, which can lead to metastatic tumor phenotypes. Dysregulated FGF/FGFR signaling is associated with aggressive cancer phenotypes, enhanced chemotherapy resistance and poor clinical outcomes. In vitro experimental settings have indicated that extracellular FGF2 affects proliferation, drug sensitivity, and apoptosis of cancer cells. Therapeutically targeting FGF2 and FGFR has been extensively assessed in multiple preclinical studies and numerous drugs and treatment options have been tested in clinical trials. Diagnostic assays are used to quantify FGF2, FGFRs, and downstream signaling molecules to better select a target patient population for higher efficacy of cancer therapies. This review focuses on the prognostic significance of FGF2 in cancer with emphasis on therapeutic intervention strategies for solid and hematological malignancies. PMID:27007053

Oxidative DNA damage background estimated by a system model of base excision repair

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

Sokhansanj, B A; Wilson, III, D M

Human DNA can be damaged by natural metabolism through free radical production. It has been suggested that the equilibrium between innate damage and cellular DNA repair results in an oxidative DNA damage background that potentially contributes to disease and aging. Efforts to quantitatively characterize the human oxidative DNA damage background level based on measuring 8-oxoguanine lesions as a biomarker have led to estimates varying over 3-4 orders of magnitude, depending on the method of measurement. We applied a previously developed and validated quantitative pathway model of human DNA base excision repair, integrating experimentally determined endogenous damage rates and model parametersmore » from multiple sources. Our estimates of at most 100 8-oxoguanine lesions per cell are consistent with the low end of data from biochemical and cell biology experiments, a result robust to model limitations and parameter variation. Our results show the power of quantitative system modeling to interpret composite experimental data and make biologically and physiologically relevant predictions for complex human DNA repair pathway mechanisms and capacity.« less

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

A liver full of JNK: signaling in regulation of cell function and disease pathogenesis, and clinical approaches.

PubMed

Seki, Ekihiro; Brenner, David A; Karin, Michael

2012-08-01

c-Jun-N-terminal kinase (JNK) is a mitogen-activated protein kinase family member that is activated by diverse stimuli, including cytokines (such as tumor necrosis factor and interleukin-1), reactive oxygen species (ROS), pathogens, toxins, drugs, endoplasmic reticulum stress, free fatty acids, and metabolic changes. Upon activation, JNK induces multiple biologic events through the transcription factor activator protein-1 and transcription-independent control of effector molecules. JNK isozymes regulate cell death and survival, differentiation, proliferation, ROS accumulation, metabolism, insulin signaling, and carcinogenesis in the liver. The biologic functions of JNK are isoform, cell type, and context dependent. Recent studies using genetically engineered mice showed that loss or hyperactivation of the JNK pathway contributes to the development of inflammation, fibrosis, cancer growth, and metabolic diseases that include obesity, hepatic steatosis, and insulin resistance. We review the functions and pathways of JNK in liver physiology and pathology and discuss findings from preclinical studies with JNK inhibitors. Copyright © 2012 AGA Institute. Published by Elsevier Inc. All rights reserved.

The new follow-on-biologics law: a section by section analysis of the patent litigation provisions in the Biologics Price Competition and Innovation Act of 2009.

PubMed

Dougherty, Michael P

2010-01-01

An abbreviated pathway for the approval of biosimilar biological products, often called "follow-on biologics," has been enacted into law as part of the health care legislation recently passed by Congress and signed by the President. The subtitle of the health care bill establishing this approval pathway, the Biologics Price Competition and Innovation Act of 2009, includes many provisions governing the identification of patents relevant to a given biosimilar biological product and the assertion of those patents in infringement suits. This article provides a section-by-section analysis of the patent-related provisions of the new approval pathway for biosimilar biological products, and points out several ways in which the new law differs fundamentally from the Hatch-Waxman Act, which provides the approval pathway for generic versions of small molecule drugs.

Angiosperm phylogeny inferred from multiple genes as a tool for comparative biology.

PubMed

Soltis, P S; Soltis, D E; Chase, M W

1999-11-25

Comparative biology requires a firm phylogenetic foundation to uncover and understand patterns of diversification and evaluate hypotheses of the processes responsible for these patterns. In the angiosperms, studies of diversification in floral form, stamen organization, reproductive biology, photosynthetic pathway, nitrogen-fixing symbioses and life histories have relied on either explicit or implied phylogenetic trees. Furthermore, to understand the evolution of specific genes and gene families, evaluate the extent of conservation of plant genomes and make proper sense of the huge volume of molecular genetic data available for model organisms such as Arabidopsis, Antirrhinum, maize, rice and wheat, a phylogenetic perspective is necessary. Here we report the results of parsimony analyses of DNA sequences of the plastid genes rbcL and atpB and the nuclear 18S rDNA for 560 species of angiosperms and seven non-flowering seed plants and show a well-resolved and well-supported phylogenetic tree for the angiosperms for use in comparative biology.

Essential roles of Gab1 tyrosine phosphorylation in growth factor-mediated signaling and angiogenesis.

PubMed

Wang, Weiye; Xu, Suowen; Yin, Meimei; Jin, Zheng Gen

2015-02-15

Growth factors and their downstream receptor tyrosine kinases (RTKs) mediate a number of biological processes controlling cell function. Adaptor (docking) proteins, which consist exclusively of domains and motifs that mediate molecular interactions, link receptor activation to downstream effectors. Recent studies have revealed that Grb2-associated-binders (Gab) family members (including Gab1, Gab2, and Gab3), when phosphorylated on tyrosine residues, provide binding sites for multiple effector proteins, such as Src homology-2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) and phosphatidylinositol 3-kinase (PI3K) regulatory subunit p85, thereby playing important roles in transducing RTKs-mediated signals into pathways with diversified biological functions. Here, we provide an up-to-date overview on the domain structure and biological functions of Gab1, the most intensively studied Gab family protein, in growth factor signaling and biological functions, with a special focus on angiogenesis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Anopheline Reproductive Biology: Impacts on Vectorial Capacity and Potential Avenues for Malaria Control.

PubMed

Mitchell, Sara N; Catteruccia, Flaminia

2017-12-01

Vectorial capacity is a mathematical approximation of the efficiency of vector-borne disease transmission, measured as the number of new infections disseminated per case per day by an insect vector. Multiple elements of mosquito biology govern their vectorial capacity, including survival, population densities, feeding preferences, and vector competence. Intriguingly, biological pathways essential to mosquito reproductive fitness directly or indirectly influence a number of these elements. Here, we explore this complex interaction, focusing on how the interplay between mating and blood feeding in female Anopheles not only shapes their reproductive success but also influences their ability to sustain Plasmodium parasite development. Central to malaria transmission, mosquito reproductive biology has recently become the focus of research strategies aimed at malaria control, and we discuss promising new methods based on the manipulation of key reproductive steps. In light of widespread resistance to all public health-approved insecticides targeting mosquito reproduction may prove crucial to the success of malaria-eradication campaigns. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts.

PubMed

Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D; Bader, Joel S

2016-03-15

Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder joel.bader@jhu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Art and brain: insights from neuropsychology, biology and evolution.

PubMed

Zaidel, Dahlia W

2010-02-01

Art is a uniquely human activity associated fundamentally with symbolic and abstract cognition. Its practice in human societies throughout the world, coupled with seeming non-functionality, has led to three major brain theories of art. (1) The localized brain regions and pathways theory links art to multiple neural regions. (2) The display of art and its aesthetics theory is tied to the biological motivation of courtship signals and mate selection strategies in animals. (3) The evolutionary theory links the symbolic nature of art to critical pivotal brain changes in Homo sapiens supporting increased development of language and hierarchical social grouping. Collectively, these theories point to art as a multi-process cognition dependent on diverse brain regions and on redundancy in art-related functional representation.

Nutrition and skin.

PubMed

Pappas, Apostolos; Liakou, Aikaterini; Zouboulis, Christos C

2016-09-01

Nutrition has long been associated with skin health, including all of its possible aspects from beauty to its integrity and even the aging process. Multiple pathways within skin biology are associated with the onset and clinical course of various common skin diseases, such as acne, atopic dermatitis, aging, or even photoprotection. These conditions have been shown to be critically affected by nutritional patterns and dietary interventions where well-documented studies have demonstrated beneficial effects of essential nutrients on impaired skin structural and functional integrity and have restored skin appearance and health. Although the subject could be vast, the intention of this review is to provide the most relevant and the most well-documented information on the role of nutrition in common skin conditions and its impact on skin biology.

Art and brain: insights from neuropsychology, biology and evolution

PubMed Central

Zaidel, Dahlia W

2010-01-01

Art is a uniquely human activity associated fundamentally with symbolic and abstract cognition. Its practice in human societies throughout the world, coupled with seeming non-functionality, has led to three major brain theories of art. (1) The localized brain regions and pathways theory links art to multiple neural regions. (2) The display of art and its aesthetics theory is tied to the biological motivation of courtship signals and mate selection strategies in animals. (3) The evolutionary theory links the symbolic nature of art to critical pivotal brain changes in Homo sapiens supporting increased development of language and hierarchical social grouping. Collectively, these theories point to art as a multi-process cognition dependent on diverse brain regions and on redundancy in art-related functional representation. PMID:19490399

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens

PubMed Central

Zeng, Y.; Yin, T.; Brügemann, K.

2018-01-01

Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle. PMID:29608619

Transcriptomic characterization of temperature stress responses in larval zebrafish.

PubMed

Long, Yong; Li, Linchun; Li, Qing; He, Xiaozhen; Cui, Zongbin

2012-01-01

Temperature influences nearly all biochemical, physiological and life history activities of fish, but the molecular mechanisms underlying the temperature acclimation remains largely unknown. Previous studies have identified many temperature-regulated genes in adult tissues; however, the transcriptional responses of fish larvae to temperature stress are not well understood. In this study, we characterized the transcriptional responses in larval zebrafish exposed to cold or heat stress using microarray analysis. In comparison with genes expressed in the control at 28 °C, a total of 2680 genes were found to be affected in 96 hpf larvae exposed to cold (16 °C) or heat (34 °C) for 2 and 48h and most of these genes were expressed in a temperature-specific and temporally regulated manner. Bioinformatic analysis identified multiple temperature-regulated biological processes and pathways. Biological processes overrepresented among the earliest genes induced by temperature stress include regulation of transcription, nucleosome assembly, chromatin organization and protein folding. However, processes such as RNA processing, cellular metal ion homeostasis and protein transport and were enriched in genes up-regulated under cold exposure for 48 h. Pathways such as mTOR signalling, p53 signalling and circadian rhythm were enriched among cold-induced genes, while adipocytokine signalling, protein export and arginine and praline metabolism were enriched among heat-induced genes. Although most of these biological processes and pathways were specifically regulated by cold or heat, common responses to both cold and heat stresses were also found. Thus, these findings provide new interesting clues for elucidation of mechanisms underlying the temperature acclimation in fish.

Biological properties of 6-gingerol: a brief review.

PubMed

Wang, Shaopeng; Zhang, Caihua; Yang, Guang; Yang, Yanzong

2014-07-01

Numerous studies have revealed that regular consumption of certain fruits and vegetables can reduce the risk of many diseases. The rhizome of Zingiber officinale (ginger) is consumed worldwide as a spice and herbal medicine. It contains pungent phenolic substances collectively known as gingerols. 6-Gingerol is the major pharmacologically-active component of ginger. It is known to exhibit a variety of biological activities including anticancer, anti-inflammation, and anti-oxidation. 6-Gingerol has been found to possess anticancer activities via its effect on a variety of biological pathways involved in apoptosis, cell cycle regulation, cytotoxic activity, and inhibition of angiogenesis. Thus, due to its efficacy and regulation of multiple targets, as well as its safety for human use, 6-gingerol has received considerable interest as a potential therapeutic agent for the prevention and/or treatment of various diseases. Taken together, this review summarizes the various in vitro and in vivo pharmacological aspects of 6-gingerol and the underlying mechanisms.

Geological and Chemical Factors that Impacted the Biological Utilization of Cobalt in the Archean Eon

NASA Astrophysics Data System (ADS)

Moore, Eli K.; Hao, Jihua; Prabhu, Anirudh; Zhong, Hao; Jelen, Ben I.; Meyer, Mike; Hazen, Robert M.; Falkowski, Paul G.

2018-03-01

The geosphere and biosphere coevolved and influenced Earth's biological and mineralogical diversity. Changing redox conditions influenced the availability of different transition metals, which are essential components in the active sites of oxidoreductases, proteins that catalyze electron transfer reactions across the tree of life. Despite its relatively low abundance in the environment, cobalt (Co) is a unique metal in biology due to its importance to a wide range of organisms as the metal center of vitamin B12 (aka cobalamin, Cbl). Cbl is vital to multiple methyltransferase enzymes involved in energetically favorable metabolic pathways. It is unclear how Co availability is linked to mineral evolution and weathering processes. Here we examine important biological functions of Co, as well as chemical and geological factors that may have influenced the utilization of Co early in the evolution of life. Only 66 natural minerals are known to contain Co as an essential element. However, Co is incorporated as a minor element in abundant rock-forming minerals, potentially representing a reliable source of Co as a trace element in marine systems due to weathering processes. We developed a mineral weathering model that indicates that dissolved Co was potentially more bioavailable in the Archean ocean under low S conditions than it is today. Mineral weathering, redox chemistry, Co complexation with nitrogen-containing organics, and hydrothermal environments were crucial in the incorporation of Co in primitive metabolic pathways. These chemical and geological characteristics of Co can inform the biological utilization of other trace metals in early forms of life.

Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities.

PubMed

DePaoli, Henrique C; Borland, Anne M; Tuskan, Gerald A; Cushman, John C; Yang, Xiaohan

2014-07-01

To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Differentiating pathway-specific from nonspecific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development

EPA Science Inventory

The U.S. Environmental Protection Agency’s ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential ...

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

The evolution of bladder cancer genomics: What have we learned and how can we use it?

PubMed

Audenet, François; Attalla, Kyrollis; Sfakianos, John P

2018-03-21

With advancements in molecular biology techniques, great progress has been made in the understanding of urothelial carcinoma pathogenesis. To examine the historic description of molecular alterations in bladder cancer and their evolution towards our current comprehension of the biology of the disease. Historically, a two-pathway model was described from histological and cytogenetic studies: low-grade papillary non-muscle invasive bladder cancers (NMIBC) were described to arise from epithelial hyperplasia with loss of chromosome 9 as an early event, whereas muscle-invasive bladder cancers (MIBC) were considered to develop from dysplasia, associated with genetic instability. Although there could be connections between the 2 pathways, NMIBC and MIBC were largely believed to develop secondary to different molecular alterations. Next-generation sequencing has allowed important insights into cancer biology and a better understanding of the pathways involved in bladder cancer pathogenesis and heterogeneity. Urothelial carcinoma has been found to have a high frequency of somatic mutations compared to other solid tumors, including several mutations in multiple signaling pathways, such as cell cycle regulators (TP53, RB1), RTK/RAS/RAF pathway, PI3K/AKT/mTOR pathway and TERT gene promoter. Epigenetic changes and mutations in chromatin remodeling genes are especially frequent in bladder cancer. Mutations in FGFR3 and KDM6A are more common in NMIBC than in MIBC, whereas mutations in TP53 and KMT2D are more common in MIBC, suggesting the previously hypothesized 2 different pathways, with a subset of tumors progressing from NMIBC to MIBC. Using comprehensive RNA expression profiling studies, at least 5 subtypes of bladder cancer have been identified, the most fundamental division being Basal/Squamous-like and Luminal. These subtypes have different prognoses, natural histories and responses to systemic treatments: Luminal subtypes are enriched with papillary histology and have a better prognosis, while Basal/Squamous-like subtypes are enriched with squamous features, are associated with advanced stage at presentation, and portend a worse prognosis. This new understanding of bladder cancer will optimistically translate into better understanding of this heterogeneous disease and lead to improvement in patient outcome and quality of life through better tailored treatments. Copyright © 2018 Elsevier Inc. All rights reserved.

PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data.

PubMed

Hernández-de-Diego, Rafael; Tarazona, Sonia; Martínez-Mira, Carlos; Balzano-Nogueira, Leandro; Furió-Tarí, Pedro; Pappas, Georgios J; Conesa, Ana

2018-05-25

The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org.

Illuminating the Reaction Pathways of Viromimetic Assembly.

PubMed

Cingil, Hande E; Boz, Emre B; Biondaro, Giovanni; de Vries, Renko; Cohen Stuart, Martien A; Kraft, Daniela J; van der Schoot, Paul; Sprakel, Joris

2017-04-05

The coassembly of well-defined biological nanostructures relies on a delicate balance between attractive and repulsive interactions between biomolecular building blocks. Viral capsids are a prototypical example, where coat proteins exhibit not only self-interactions but also interact with the cargo they encapsulate. In nature, the balance between antagonistic and synergistic interactions has evolved to avoid kinetic trapping and polymorphism. To date, it has remained a major challenge to experimentally disentangle the complex kinetic reaction pathways that underlie successful coassembly of biomolecular building blocks in a noninvasive approach with high temporal resolution. Here we show how macromolecular force sensors, acting as a genome proxy, allow us to probe the pathways through which a viromimetic protein forms capsids. We uncover the complex multistage process of capsid assembly, which involves recruitment and complexation, followed by allosteric growth of the proteinaceous coat. Under certain conditions, the single-genome particles condense into capsids containing multiple copies of the template. Finally, we derive a theoretical model that quantitatively describes the kinetics of recruitment and growth. These results shed new light on the origins of the pathway complexity in biomolecular coassembly.

Wnt signal transduction pathways: modules, development and evolution.

PubMed

Nayak, Losiana; Bhattacharyya, Nitai P; De, Rajat K

2016-08-01

Wnt signal transduction pathway (Wnt STP) is a crucial intracellular pathway mainly due to its participation in important biological processes, functions, and diseases, i.e., embryonic development, stem-cell management, and human cancers among others. This is why Wnt STP is one of the highest researched signal transduction pathways. Study and analysis of its origin, expansion and gradual development to the present state as found in humans is one aspect of Wnt research. The pattern of development and evolution of the Wnt STP among various species is not clear till date. A phylogenetic tree created from Wnt STPs of multiple species may address this issue. In this respect, we construct a phylogenetic tree from modules of Wnt STPs of diverse species. We term it as the 'Module Tree'. A module is nothing but a self-sufficient minimally-dependent subset of the original Wnt STP. Authenticity of the module tree is tested by comparing it with the two reference trees. The module tree performs better than an alternative phylogenetic tree constructed from pathway topology of Wnt STPs. Moreover, an evolutionary emergence pattern of the Wnt gene family is created and the module tree is tallied with it to showcase the significant resemblances.

Lactoferricin mediates anabolic and anti-catabolic effects in the intervertebral disc.

PubMed

Kim, Jae-Sung; Ellman, Michael B; An, Howard S; Yan, Dongyao; van Wijnen, Andre J; Murphy, Gillian; Hoskin, David W; Im, Hee-Jeong

2012-04-01

Lactoferricin (LfcinB) antagonizes biological effects mediated by angiogenic and catabolic growth factors, in addition to pro-inflammatory cytokines and chemokines in human endothelial cells and tumor cells. However, the effect of LfcinB on intervertebral disc (IVD) cell metabolism has not yet been investigated. Using bovine nucleus pulposus (NP) cells, we analyzed the effect of LfcinB on proteoglycan (PG) accumulation, PG synthesis, and anabolic gene expression. We assessed expression of genes for matrix-degrading enzymes such as matrix metalloproteases (MMPs) and a disintegrin-like and metalloprotease with thrombospondin motifs (ADAMTS family), as well as their endogenous inhibitors, tissue inhibitor of metalloproteases (TIMPs). In order to understand the specific molecular mechanisms by which LfcinB exerts its biological effects, we investigated intracellular signaling pathways in NP cells. LfcinB increased PG accumulation mainly via PG synthesis in a dose-dependent manner. Simultaneously, LfcinB dose-dependently downregulated catabolic enzymes. LfcinB's anti-catabolic effects were further demonstrated by a dose-dependent increase in multiple TIMP family members. Our results demonstrate that ERK and/or p38 mitogen-activated protein kinase pathways are the key signaling cascades that exert the biological effects of LfcinB in NP cells, regulating transcription of aggrecan, SOX-9, TIMP-1, TIMP-2, TIMP-3, and iNOS. Our results suggest that LfcinB has anabolic and potent anti-catabolic biological effects on bovine IVD cells that may have considerable promise in the treatment of disc degeneration in the future. Copyright © 2011 Wiley Periodicals, Inc.

Vitamin D and its effects on cardiovascular diseases: a comprehensive review.

PubMed

Pérez-Hernández, Nonanzit; Aptilon-Duque, Gad; Nostroza-Hernández, María Cristina; Vargas-Alarcón, Gilberto; Rodríguez-Pérez, José Manuel; Blachman-Braun, Ruben

2016-11-01

Vitamin D is a molecule that is actively involved in multiple metabolic pathways. It is mostly known for its implications related to calcium metabolism. It has also been determined that it actively participates in the cardiovascular system, influencing blood pressure, coronary artery disease and other vascular diseases, such as heart failure and atrial fibrillation. Furthermore, it has been established that this vitamin is extensively involved in the regulation of both the renin angiotensin aldosterone system and the immune system. In this review, we present the different vitamin D metabolic pathways associated with the cardiovascular pathophysiology, and we include studies in animal and human models, as well as some of the controversies found in the literature. This review also incorporates an overview of the implications in the molecular biology and public health fields.

Recent insights into the biology of Hodgkin lymphoma: unraveling the mysteries of the Reed-Sternberg cell.

PubMed

Roullet, Michele R; Bagg, Adam

2007-11-01

The microscopic pathology of Hodgkin lymphoma has been recognized for well over a century; however, only in the past 15 years has the enigmatic nature of this peculiar neoplasm been somewhat unraveled. This has been accomplished via a combination of the acquisition, via microdissection, of the prototypically rare malignant cells and their subsequent analysis via a variety of modalities, including genomic studies and expression profiling. This has facilitated the elucidation of the surreptitiously concealed B-cell origin of the cells, their complex but vital relationships with the surrounding micro- and macroenvironment, as well as multiple pathways involved in the pathobiology of this lymphoma. Understanding the intricacies of these intra- and extracellular pathways should allow for the development of less-toxic targeted therapies.

Not just gRASping at flaws: Finding vulnerabilities to develop novel therapies for treating KRAS mutant cancers

PubMed Central

Ebi, Hiromichi; Faber, Anthony C; Engelman, Jeffrey A; Yano, Seiji

2014-01-01

Mutations in Kirsten rat-sarcoma (KRAS) are well appreciated to be major drivers of human cancers through dysregulation of multiple growth and survival pathways. Similar to many other non-kinase oncogenes and tumor suppressors, efforts to directly target KRAS pharmaceutically have not yet materialized. As a result, there is broad interest in an alternative approach to develop therapies that induce synthetic lethality in cancers with mutant KRAS, therefore exposing the particular vulnerabilities of these cancers. Fueling these efforts is our increased understanding into the biology driving KRAS mutant cancers, in particular the important pathways that mutant KRAS governs to promote survival. In this mini-review, we summarize the latest approaches to treat KRAS mutant cancers and the rationale behind them. PMID:24612015

Myeloid neoplasms with germline DDX41 mutation.

PubMed

Cheah, Jesse J C; Hahn, Christopher N; Hiwase, Devendra K; Scott, Hamish S; Brown, Anna L

2017-08-01

Recently, DDX41 mutations have been identified both as germline and acquired somatic mutations in families with multiple cases of late-onset myelodysplastic syndrome (MDS) and/or acute myeloid leukemia. The majority of germline mutations are frameshift mutations suggesting loss of function with DDX41 acting as a tumor suppressor, and there is a common somatic missense mutation found in a majority of germline mutated tumors. Clinically, DDX41 mutations lead to development of high-risk MDS at an age similar to that observed in sporadic cohorts, presenting a unique challenge to hematologists in recognizing the familial context. Functionally, DDX41 has been shown to contribute to multiple pathways and processes including mRNA splicing, innate immunity and rRNA processing. Mutations in DDX41 result in aberrations to each of these in ways that could potentially impact on tumorigenesis-initiation, maintenance or progression. This review discusses the various molecular, clinical and biological aspects of myeloid malignancy predisposition due to DDX41 mutation and highlights how each of these suggest potential therapeutic opportunities through the use of pathway-specific inhibitors.

Pathways to Identity: Aiding Law Enforcement in Identification Tasks With Visual Analytics

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

Bruce, Joseph R.; Scholtz, Jean; Hodges, Duncan

The nature of identity has changed dramatically in recent years, and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but also biographical and cyber elements are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing its importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, includingmore » law enforcement, as well as the modeling and visualization tools design to aid in those use cases.« less

Pathways to Identity. Using Visualization to Aid Law Enforcement in Identification Tasks

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

Bruce, Joseph R.; Scholtz, Jean; Hodges, Duncan

The nature of identity has changed dramatically in recent years and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but biographical and cyber elements also are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing identity’s importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, includingmore » law enforcement, and describe the modeling and visualization tools design to aid in those use cases.« less

Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species

PubMed Central

Thomas, Reuben; Thomas, Russell S.; Auerbach, Scott S.; Portier, Christopher J.

2013-01-01

Background Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. Objectives To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Methods Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Results Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Conclusions Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species. PMID:23737943

Biological networks for predicting chemical hepatocarcinogenicity using gene expression data from treated mice and relevance across human and rat species.

PubMed

Thomas, Reuben; Thomas, Russell S; Auerbach, Scott S; Portier, Christopher J

2013-01-01

Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species.

Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development

EPA Science Inventory

The U.S. Environmental Protection Agency’s ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with pote...

Pin1 inhibition exerts potent activity against acute myeloid leukemia through blocking multiple cancer-driving pathways.

PubMed

Lian, Xiaolan; Lin, Yu-Min; Kozono, Shingo; Herbert, Megan K; Li, Xin; Yuan, Xiaohong; Guo, Jiangrui; Guo, Yafei; Tang, Min; Lin, Jia; Huang, Yiping; Wang, Bixin; Qiu, Chenxi; Tsai, Cheng-Yu; Xie, Jane; Cao, Ziang Jeff; Wu, Yong; Liu, Hekun; Zhou, Xiaozhen; Lu, Kunping; Chen, Yuanzhong

2018-05-30

The increasing genomic complexity of acute myeloid leukemia (AML), the most common form of acute leukemia, poses a major challenge to its therapy. To identify potent therapeutic targets with the ability to block multiple cancer-driving pathways is thus imperative. The unique peptidyl-prolyl cis-trans isomerase Pin1 has been reported to promote tumorigenesis through upregulation of numerous cancer-driving pathways. Although Pin1 is a key drug target for treating acute promyelocytic leukemia (APL) caused by a fusion oncogene, much less is known about the role of Pin1 in other heterogeneous leukemia. The mRNA and protein levels of Pin1 were detected in samples from de novo leukemia patients and healthy controls using real-time quantitative RT-PCR (qRT-PCR) and western blot. The establishment of the lentiviral stable-expressed short hairpin RNA (shRNA) system and the tetracycline-inducible shRNA system for targeting Pin1 were used to analyze the biological function of Pin1 in AML cells. The expression of cancer-related Pin1 downstream oncoproteins in shPin1 (Pin1 knockdown) and Pin1 inhibitor all-trans retinoic acid (ATRA) treated leukemia cells were examined by western blot, followed by evaluating the effects of genetic and chemical inhibition of Pin1 in leukemia cells on transformed phenotype, including cell proliferation and colony formation ability, using trypan blue, cell counting assay, and colony formation assay in vitro, as well as the tumorigenesis ability using in vivo xenograft mouse models. First, we found that the expression of Pin1 mRNA and protein was significantly increased in both de novo leukemia clinical samples and multiple leukemia cell lines, compared with healthy controls. Furthermore, genetic or chemical inhibition of Pin1 in human multiple leukemia cell lines potently inhibited multiple Pin1 substrate oncoproteins and effectively suppressed leukemia cell proliferation and colony formation ability in cell culture models in vitro. Moreover, tetracycline-inducible Pin1 knockdown and slow-releasing ATRA potently inhibited tumorigenicity of U937 and HL-60 leukemia cells in xenograft mouse models. We demonstrate that Pin1 is highly overexpressed in human AML and is a promising therapeutic target to block multiple cancer-driving pathways in AML.

Simultaneous knockdown of six non-family genes using a single synthetic RNAi fragment in Arabidopsis thaliana

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

Czarnecki, Olaf; Bryan, Anthony C.; Jawdy, Sara S.

Genetic engineering of plants that results in successful establishment of new biochemical or regulatory pathways requires stable introduction of one or more genes into the plant genome. It might also be necessary to down-regulate or turn off expression of endogenous genes in order to reduce activity of competing pathways. An established way to knockdown gene expression in plants is expressing a hairpin-RNAi construct, eventually leading to degradation of a specifically targeted mRNA. Knockdown of multiple genes that do not share homologous sequences is still challenging and involves either sophisticated cloning strategies to create vectors with different serial expression constructs ormore » multiple transformation events that is often restricted by a lack of available transformation markers. Synthetic RNAi fragments were assembled in yeast carrying homologous sequences to six or seven non-family genes and introduced into pAGRIKOLA. Transformation of Arabidopsis thaliana and subsequent expression analysis of targeted genes proved efficient knockdown of all target genes. In conclusion, we present a simple and cost-effective method to create constructs to simultaneously knockdown multiple non-family genes or genes that do not share sequence homology. The presented method can be applied in plant and animal synthetic biology as well as traditional plant and animal genetic engineering.« less

Simultaneous knockdown of six non-family genes using a single synthetic RNAi fragment in Arabidopsis thaliana

DOE PAGES

Czarnecki, Olaf; Bryan, Anthony C.; Jawdy, Sara S.; ...

2016-02-17

Genetic engineering of plants that results in successful establishment of new biochemical or regulatory pathways requires stable introduction of one or more genes into the plant genome. It might also be necessary to down-regulate or turn off expression of endogenous genes in order to reduce activity of competing pathways. An established way to knockdown gene expression in plants is expressing a hairpin-RNAi construct, eventually leading to degradation of a specifically targeted mRNA. Knockdown of multiple genes that do not share homologous sequences is still challenging and involves either sophisticated cloning strategies to create vectors with different serial expression constructs ormore » multiple transformation events that is often restricted by a lack of available transformation markers. Synthetic RNAi fragments were assembled in yeast carrying homologous sequences to six or seven non-family genes and introduced into pAGRIKOLA. Transformation of Arabidopsis thaliana and subsequent expression analysis of targeted genes proved efficient knockdown of all target genes. In conclusion, we present a simple and cost-effective method to create constructs to simultaneously knockdown multiple non-family genes or genes that do not share sequence homology. The presented method can be applied in plant and animal synthetic biology as well as traditional plant and animal genetic engineering.« less

Coordinated regulation of intracellular pH by two glucose-sensing pathways in yeast.

PubMed

Isom, Daniel G; Page, Stephani C; Collins, Leonard B; Kapolka, Nicholas J; Taghon, Geoffrey J; Dohlman, Henrik G

2018-02-16

The yeast Saccharomyces cerevisiae employs multiple pathways to coordinate sugar availability and metabolism. Glucose and other sugars are detected by a G protein-coupled receptor, Gpr1, as well as a pair of transporter-like proteins, Rgt2 and Snf3. When glucose is limiting, however, an ATP-driven proton pump (Pma1) is inactivated, leading to a marked decrease in cytoplasmic pH. Here we determine the relative contribution of the two sugar-sensing pathways to pH regulation. Whereas cytoplasmic pH is strongly dependent on glucose abundance and is regulated by both glucose-sensing pathways, ATP is largely unaffected and therefore cannot account for the changes in Pma1 activity. These data suggest that the pH is a second messenger of the glucose-sensing pathways. We show further that different sugars differ in their ability to control cellular acidification, in the manner of inverse agonists. We conclude that the sugar-sensing pathways act via Pma1 to invoke coordinated changes in cellular pH and metabolism. More broadly, our findings support the emerging view that cellular systems have evolved the use of pH signals as a means of adapting to environmental stresses such as those caused by hypoxia, ischemia, and diabetes. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

ToxCast Phase I

EPA Pesticide Factsheets

Background: Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use and the thousands of environmental chemicals lacking toxicity data. EPA's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches. Objectives: This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity. Methods: We tested 309 mostly pesticide active chemicals in 467 assays across 9 technologies, including high-throughput cell-free assays and cell-based assays in multiple human primary cells and cell lines, plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed. Results: Chemicals display a broad spectrum of activity at the molecular and pathway levels. Many expected interactions are seen, including endocrine and xenobiotic metabolism enzyme activity. Chemicals range in promiscuity across pathways, from no activity to affecting dozens of pathways. We find a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also find associations between a small set in vitro ass

Conservation of the photoperiodic neuroendocrine axis among vertebrates: evidence from the teleost fish, Gasterosteus aculeatus

PubMed Central

O’Brien, Conor S.; Bourdo, Ryan; Bradshaw, William E.; Holzapfel, Christina M.; Cresko, William. A.

2012-01-01

Photoperiod, or length of day, has a predictable annual cycle, making it an important cue for the timing of seasonal behavior and development in many organisms. Photoperiod is widely used among temperate and polar animals to regulate the timing of sexual maturation. The proper sensing and interpretation of photoperiod can be tightly tied to an organism’s overall fitness. In photoperiodic mammals and birds the thyroid hormone pathway initiates sexual maturation, but the degree to which this pathway is conserved across other vertebrates is not well known. We use the threespine stickleback Gasterosteus aculeatus, as a representative teleost to quantify the photoperiodic response of key genes in the thyroid hormone pathway under controlled laboratory conditions. We find that the photoperiodic responses of the hormones are largely consistent amongst multiple populations, although differences suggest physiological adaptation to various climates. We conclude that the thyroid hormone pathway initiates sexual maturation in response to photoperiod in G. aculeatus, and our results show that more components of this pathway are conserved among mammals, birds, and teleost fish than was previously known. However, additional endocrinology, cell biology and molecular research will be required to define precisely which aspects of the pathway are conserved across vertebrates. PMID:22504272

Conservation of the photoperiodic neuroendocrine axis among vertebrates: evidence from the teleost fish, Gasterosteus aculeatus.

PubMed

O'Brien, Conor S; Bourdo, Ryan; Bradshaw, William E; Holzapfel, Christina M; Cresko, William A

2012-08-01

Photoperiod, or length of day, has a predictable annual cycle, making it an important cue for the timing of seasonal behavior and development in many organisms. Photoperiod is widely used among temperate and polar animals to regulate the timing of sexual maturation. The proper sensing and interpretation of photoperiod can be tightly tied to an organism's overall fitness. In photoperiodic mammals and birds the thyroid hormone pathway initiates sexual maturation, but the degree to which this pathway is conserved across other vertebrates is not well known. We use the threespine stickleback Gasterosteus aculeatus, as a representative teleost to quantify the photoperiodic response of key genes in the thyroid hormone pathway under controlled laboratory conditions. We find that the photoperiodic responses of the hormones are largely consistent amongst multiple populations, although differences suggest physiological adaptation to various climates. We conclude that the thyroid hormone pathway initiates sexual maturation in response to photoperiod in G. aculeatus, and our results show that more components of this pathway are conserved among mammals, birds, and teleost fish than was previously known. However, additional endocrinology, cell biology and molecular research will be required to define precisely which aspects of the pathway are conserved across vertebrates. Copyright © 2012 Elsevier Inc. All rights reserved.

A taxonomy of visualization tasks for the analysis of biological pathway data.

PubMed

Murray, Paul; McGee, Fintan; Forbes, Angus G

2017-02-15

Understanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity. Here, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy. Our taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.

Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae.

PubMed

Li, Mingji; Borodina, Irina

2015-02-01

Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Assessing biological invasions in European Seas: Biological traits of the most widespread non-indigenous species

NASA Astrophysics Data System (ADS)

Cardeccia, Alice; Marchini, Agnese; Occhipinti-Ambrogi, Anna; Galil, Bella; Gollasch, Stephan; Minchin, Dan; Narščius, Aleksas; Olenin, Sergej; Ojaveer, Henn

2018-02-01

The biological traits of the sixty-eight most widespread multicellular non-indigenous species (MWNIS) in European Seas: Baltic Sea, Western European Margin of the Atlantic Ocean and the Mediterranean Sea were examined. Data for nine biological traits was analyzed, and a total of 41 separate categories were used to describe the biological and ecological functions of these NIS. Our findings show that high dispersal ability, high reproductive rate and ecological generalization are the biological traits commonly associated with MWNIS. The functional groups that describe most of the 68 MWNIS are: photoautotrophic, zoobenthic (both sessile and motile) and nektonic predatory species. However, these 'most widespread' species comprise a wide range of taxa and biological trait profiles; thereby a clear "identikit of a perfect invader" for marine and brackish environments is difficult to define. Some traits, for example: "life form", "feeding method" and "mobility", feature multiple behaviours and strategies. Even species introduced by a single pathway, e.g. vessels, feature diverse biological trait profiles. MWNIS likely to impact community organization, structure and diversity are often associated with brackish environments. For many traits ("life form", "sociability", "reproductive type", "reproductive frequency", "haploid and diploid dispersal" and "mobility"), the categories mostly expressed by the impact-causing MWNIS do not differ substantially from the whole set of MWNIS.

Adverse outcome pathway (AOP) development I: Strategies and principles

EPA Science Inventory

An adverse outcome pathway (AOP) is a conceptual framework that organizes existing knowledge concerning biologically plausible, and empirically-supported, links between molecular-level perturbation of a biological system and an adverse outcome at a level of biological organizatio...

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

NASA Astrophysics Data System (ADS)

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-01

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

PubMed Central

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-01-01

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm. PMID:26879404

An “EAR” on environmental surveillance and monitoring: A case study on the use of Exposure–Activity Ratios (EARs) to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters

USGS Publications Warehouse

Blackwell, Brett R.; Ankley, Gerald T.; Corsi, Steven; DeCicco, Laura; Houck, Kieth A.; Judson, Richard S.; Li, Shibin; Martin, Matthew T.; Murphy, Elizabeth; Schroeder, Anthony L.; Smith, Edwin R.; Swintek, Joe; Villeneuve, Daniel L.

2017-01-01

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure–activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.

Light and Dark of Reactive Oxygen Species for Vascular Function: 2014 ASVB (Asian Society of Vascular Biology).

PubMed

Shimokawa, Hiroaki; Satoh, Kimio

2015-05-01

Vascular-derived hydrogen peroxide (H2O2) serves as an important signaling molecule in the cardiovascular system and contributes to vascular homeostasis. H2O2 is a second messenger, transducing the oxidative signal into biological responses through posttranslational protein modification. The balance between oxidant and antioxidant systems regulates intracellular redox status, and their imbalance causes oxidative or reductive stress, leading to cellular damage in cardiovascular systems. Excessive H2O2 deteriorates vascular functions and promotes vascular disease through multiple pathways. The RhoA/Rho-kinase pathway plays an important role in various fundamental cellular functions, including production of excessive reactive oxygen species, leading to the development of cardiovascular diseases. Rho-kinase (ROCK1 and ROCK2) belongs to the family of serine/threonine kinases and is an important downstream effector of the small GTP-binding protein RhoA. Rho-kinase plays a crucial role in the pathogenesis of vasospasm, arteriosclerosis, ischemia/reperfusion injury, hypertension, pulmonary hypertension, stroke, and heart failure. Thus, Rho-kinase inhibitors may be useful for the treatment of cardiovascular diseases in humans. In this review, we will briefly discuss the roles of vascular-derived H2O2 and review the recent progress in the translational research on the therapeutic importance of the Rho-kinase pathway in cardiovascular medicine.

Joint-specific DNA methylation and transcriptome signatures in rheumatoid arthritis identify distinct pathogenic processes

PubMed Central

Ai, Rizi; Hammaker, Deepa; Boyle, David L.; Morgan, Rachel; Walsh, Alice M.; Fan, Shicai; Firestein, Gary S.; Wang, Wei

2016-01-01

Stratifying patients on the basis of molecular signatures could facilitate development of therapeutics that target pathways specific to a particular disease or tissue location. Previous studies suggest that pathogenesis of rheumatoid arthritis (RA) is similar in all affected joints. Here we show that distinct DNA methylation and transcriptome signatures not only discriminate RA fibroblast-like synoviocytes (FLS) from osteoarthritis FLS, but also distinguish RA FLS isolated from knees and hips. Using genome-wide methods, we show differences between RA knee and hip FLS in the methylation of genes encoding biological pathways, such as IL-6 signalling via JAK-STAT pathway. Furthermore, differentially expressed genes are identified between knee and hip FLS using RNA-sequencing. Double-evidenced genes that are both differentially methylated and expressed include multiple HOX genes. Joint-specific DNA signatures suggest that RA disease mechanisms might vary from joint to joint, thus potentially explaining some of the diversity of drug responses in RA patients. PMID:27282753

Two-dimensional isobutyl acetate production pathways to improve carbon yield

PubMed Central

Tashiro, Yohei; Desai, Shuchi H.; Atsumi, Shota

2015-01-01

For an economically competitive biological process, achieving high carbon yield of a target chemical is crucial. In biochemical production, pyruvate and acetyl-CoA are primary building blocks. When sugar is used as the sole biosynthetic substrate, acetyl-CoA is commonly generated by pyruvate decarboxylation. However, pyruvate decarboxylation during acetyl-CoA formation limits the theoretical maximum carbon yield (TMCY) by releasing carbon, and in some cases also leads to redox imbalance. To avoid these problems, we describe here the construction of a metabolic pathway that simultaneously utilizes glucose and acetate. Acetate is utilized to produce acetyl-CoA without carbon loss or redox imbalance. We demonstrate the utility of this approach for isobutyl acetate (IBA) production, wherein IBA production with glucose and acetate achieves a higher carbon yield than with either sole carbon source. These results highlight the potential for this multiple carbon source approach to improve the TMCY and balance redox in biosynthetic pathways. PMID:26108471

Diverse exocytic pathways for mast cell mediators.

PubMed

Xu, Hao; Bin, Na-Ryum; Sugita, Shuzo

2018-04-17

Mast cells play pivotal roles in innate and adaptive immunities but are also culprits in allergy, autoimmunity, and cardiovascular diseases. Mast cells respond to environmental changes by initiating regulated exocytosis/secretion of various biologically active compounds called mediators (e.g. proteases, amines, and cytokines). Many of these mediators are stored in granules/lysosomes and rely on intricate degranulation processes for release. Mast cell stabilizers (e.g. sodium cromoglicate), which prevent such degranulation processes, have therefore been clinically employed to treat asthma and allergic rhinitis. However, it has become increasingly clear that different mast cell diseases often involve multiple mediators that rely on overlapping but distinct mechanisms for release. This review illustrates existing evidence that highlights the diverse exocytic pathways in mast cells. We also discuss strategies to delineate these pathways so as to identify unique molecular components which could serve as new drug targets for more effective and specific treatments against mast cell-related diseases. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

A mathematical model of the mevalonate cholesterol biosynthesis pathway.

PubMed

Pool, Frances; Currie, Richard; Sweby, Peter K; Salazar, José Domingo; Tindall, Marcus J

2018-04-14

We formulate, parameterise and analyse a mathematical model of the mevalonate pathway, a key pathway in the synthesis of cholesterol. Of high clinical importance, the pathway incorporates rate limiting enzymatic reactions with multiple negative feedbacks. In this work we investigate the pathway dynamics and demonstrate that rate limiting steps and negative feedbacks within it act in concert to tightly regulate intracellular cholesterol levels. Formulated using the theory of nonlinear ordinary differential equations and parameterised in the context of a hepatocyte, the governing equations are analysed numerically and analytically. Sensitivity and mathematical analysis demonstrate the importance of the two rate limiting enzymes 3-hydroxy-3-methylglutaryl-CoA reductase and squalene synthase in controlling the concentration of substrates within the pathway as well as that of cholesterol. The role of individual feedbacks, both global (between that of cholesterol and sterol regulatory element-binding protein 2; SREBP-2) and local internal (between substrates in the pathway) are investigated. We find that whilst the cholesterol SREBP-2 feedback regulates the overall system dynamics, local feedbacks activate within the pathway to tightly regulate the overall cellular cholesterol concentration. The network stability is analysed by constructing a reduced model of the full pathway and is shown to exhibit one real, stable steady-state. We close by addressing the biological question as to how farnesyl-PP levels are affected by CYP51 inhibition, and demonstrate that the regulatory mechanisms within the network work in unison to ensure they remain bounded. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact of constitutional copy number variants on biological pathway evolution.

PubMed

Poptsova, Maria; Banerjee, Samprit; Gokcumen, Omer; Rubin, Mark A; Demichelis, Francesca

2013-01-23

Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data. We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels. The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations.

Impact of constitutional copy number variants on biological pathway evolution

PubMed Central

2013-01-01

Background Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data. Results We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels. Conclusions The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations. PMID:23342974

Proteome response of fish under multiple stress exposure: Effects of pesticide mixtures and temperature increase.

PubMed

Gandar, Allison; Laffaille, Pascal; Marty-Gasset, Nathalie; Viala, Didier; Molette, Caroline; Jean, Séverine

2017-03-01

Aquatic systems can be subjected to multiple stressors, including pollutant cocktails and elevated temperature. Evaluating the combined effects of these stressors on organisms is a great challenge in environmental sciences. To the best of our knowledge, this is the first study to assess the molecular stress response of an aquatic fish species subjected to individual and combined pesticide mixtures and increased temperatures. For that, goldfish (Carassius auratus) were acclimated to two different temperatures (22 and 32°C) for 15 days. They were then exposed for 96h to a cocktail of herbicides and fungicides (S-metolachlor, isoproturon, linuron, atrazine-desethyl, aclonifen, pendimethalin and tebuconazole) at two environmentally relevant concentrations (total concentrations of 8.4μgL -1 and 42μgL -1 ) at these two temperatures (22 and 32°C). The molecular response in liver was assessed by 2D-proteomics. Identified proteins were integrated using pathway enrichment analysis software to determine the biological functions involved in the individual or combined stress responses and to predict the potential deleterious outcomes. The pesticide mixtures elicited pathways involved in cellular stress response, carbohydrate, protein and lipid metabolisms, methionine cycle, cellular functions, cell structure and death control, with concentration- and temperature-dependent profiles of response. We found that combined temperature increase and pesticide exposure affected the cellular stress response: the effects of oxidative stress were more marked and there was a deregulation of the cell cycle via apoptosis inhibition. Moreover a decrease in the formation of glucose by liver and in ketogenic activity was observed in this multi-stress condition. The decrease in both pathways could reflect a shift from a metabolic compensation strategy to a conservation state. Taken together, our results showed (1) that environmental cocktails of herbicides and fungicides induced important changes in pathways involved in metabolism, cell structure and cell cycle, with possible deleterious outcomes at higher biological scales and (2) that increasing temperature could affect the response of fish to pesticide exposure. Copyright © 2017 Elsevier B.V. All rights reserved.

Orphan Nuclear Receptors as Targets for Drug Development

PubMed Central

Mukherjee, Subhajit

2012-01-01

Orphan nuclear receptors regulate diverse biological processes. These important molecules are ligand-activated transcription factors that act as natural sensors for a wide range of steroid hormones and xenobiotic ligands. Because of their importance in regulating various novel signaling pathways, recent research has focused on identifying xenobiotics targeting these receptors for the treatment of multiple human diseases. In this review, we will highlight these receptors in several physiologic and pathophysiologic actions and demonstrate how their functions can be exploited for the successful development of newer drugs. PMID:20372994

Janus Kinase Antagonists and Other Novel Small Molecules for the Treatment of Crohn's Disease.

PubMed

Boland, Brigid S; Vermeire, Séverine

2017-09-01

There is an ongoing, unmet need for effective therapies for Crohn's disease. Treatments for Crohn's disease continue to evolve from the traditional biologics to novel small molecules, with targeted mechanisms directed toward pathways that are dysregulated in Crohn's disease. There are multiple emerging mechanisms of action, including Janus kinase inhibition, Smad7 inhibition, and sphingosine-1-phosphate receptor modulators, that are administered as oral medications, and small molecules represent the next generation of therapies for Crohn's disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins.

PubMed

Boja, Emily S; Rodriguez, Henry

2012-04-01

Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dimethyl Fumarate Inhibits the Nuclear Factor κB Pathway in Breast Cancer Cells by Covalent Modification of p65 Protein.

PubMed

Kastrati, Irida; Siklos, Marton I; Calderon-Gierszal, Esther L; El-Shennawy, Lamiaa; Georgieva, Gergana; Thayer, Emily N; Thatcher, Gregory R J; Frasor, Jonna

2016-02-12

In breast tumors, activation of the nuclear factor κB (NFκB) pathway promotes survival, migration, invasion, angiogenesis, stem cell-like properties, and resistance to therapy--all phenotypes of aggressive disease where therapy options remain limited. Adding an anti-inflammatory/anti-NFκB agent to breast cancer treatment would be beneficial, but no such drug is approved as either a monotherapy or adjuvant therapy. To address this need, we examined whether dimethyl fumarate (DMF), an anti-inflammatory drug already in clinical use for multiple sclerosis, can inhibit the NFκB pathway. We found that DMF effectively blocks NFκB activity in multiple breast cancer cell lines and abrogates NFκB-dependent mammosphere formation, indicating that DMF has anti-cancer stem cell properties. In addition, DMF inhibits cell proliferation and significantly impairs xenograft tumor growth. Mechanistically, DMF prevents p65 nuclear translocation and attenuates its DNA binding activity but has no effect on upstream proteins in the NFκB pathway. Dimethyl succinate, the inactive analog of DMF that lacks the electrophilic double bond of fumarate, is unable to inhibit NFκB activity. Also, the cell-permeable thiol N-acetyl l-cysteine, reverses DMF inhibition of the NFκB pathway, supporting the notion that the electrophile, DMF, acts via covalent modification. To determine whether DMF interacts directly with p65, we synthesized and used a novel chemical probe of DMF by incorporating an alkyne functionality and found that DMF covalently modifies p65, with cysteine 38 being essential for the activity of DMF. These results establish DMF as an NFκB inhibitor with anti-tumor activity that may add therapeutic value in the treatment of aggressive breast cancers. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Digital gene expression analysis in mice lung with coinfection of influenza and streptococcus pneumoniae.

PubMed

Luo, Jun; Zhou, Linlin; Wang, Hongren; Qin, Zhen; Xiang, Li; Zhu, Jie; Huang, Xiaojun; Yang, Yuan; Li, Wanyi; Wang, Baoning; Li, Mingyuan

2017-12-22

Influenza A virus (IAV) and Streptococcus pneumoniae (SP) are two major upper respiratory tract pathogens that can also cause infection in polarized bronchial epithelial cells to exacerbate disease in coinfected individuals which may result in significant morbidity. However, the underlying molecular mechanism is poorly understood. Here, we employed BALB/c ByJ mice inflected with SP, IAV, IAV followed by SP (IAV+SP) and PBS (Control) as models to survey the global gene expression using digital gene expression (DGE) profiling. We attempt to gain insights into the underlying genetic basis of this synergy at the expression level. Gene expression profiles were obtain using the Illimina/Hisseq sequencing technique, and further analyzed by enrichment analysis of Gene Ontology (GO) and Pathway function. The hematoxylin-eosin (HE) staining revealed different tissue changes in groups during which IAV+SP group showed the most severe cell apoptosis. Compared with Control, a total of 2731, 3221 and 3946 differentially expressed genes (DEGs) were detected in SP, IAV and IAV+SP respectively. Besides, sixty-two GO terms were identified by Gene Ontology functional enrichment analysis, such as cell killing, biological regulation, response to stimulus, signaling, biological adhesion, enzyme regulator activity, receptor regulator activity and translation regulator activity. Pathway significant enrichment analysis indicated the dysregulation of multiple pathways, including apoptosis pathway. Among these, five selected genes were further verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). This study shows that infection with SP, IAV or IAV+SP induces apoptosis with different degrees which might provide insights into the molecular mechanisms to facilitate further research.

Next-Generation Connexin and Pannexin Cell Biology.

PubMed

Esseltine, Jessica L; Laird, Dale W

2016-12-01

Connexins and pannexins are two families of large-pore channel forming proteins that are capable of passing small signaling molecules. While connexins serve the seminal task of direct gap junctional intercellular communication, pannexins are far less understood but function primarily as single membrane channels in autocrine and paracrine signaling. Advancements in connexin and pannexin biology in recent years has revealed that in addition to well-described classical functions at the plasma membrane, exciting new evidence suggests that connexins and pannexins participate in alternative pathways involving multiple intracellular compartments. Here we briefly highlight classical functions of connexins and pannexins but focus our attention mostly on the transformative findings that suggest that these channel-forming proteins may serve roles far beyond our current understandings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

Phosphoproteomics profiling of human skin fibroblast cells reveals pathways and proteins affected by low doses of ionizing radiation

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

Yang, Feng; Waters, Katrina M.; Miller, John H.

2010-11-30

Background: High doses of ionizing radiation result in biological damage, however the precise relationships between long term health effects, including cancer, and low dose exposures remain poorly understood and are currently extrapolated using high dose exposure data. Identifying the signaling pathways and individual proteins affected at the post-translational level by radiation should shed valuable insight into the molecular mechanisms that regulate dose dependent responses to radiation. Principle Findings: We have identified 6845 unique phosphopeptides (2566 phosphoproteins) from control and irradiated (2 and 50 cGy) primary human skin fibroblasts one hour post-exposure. Dual statistical analyses based on spectral counts and peakmore » intensities identified 287 phosphopeptides (from 231 proteins) and 244 phosphopeptides (from 182 proteins) that varied significantly following exposure to 2 and 50 cGy respectively. This screen identified phosphorylation sites on proteins with known roles in radiation responses including TP53BP1 as well as previously unidentified radiation responsive proteins such as the candidate tumor suppressor SASH1. Bioinformatics analyses suggest that low and high doses of radiation affect both overlapping and unique biological processes and suggest a role of MAP kinase and protein kinase A (PKA) signaling in the radiation response as well as differential regulation of p53 networks at low and high doses of radiation. Conlcusions: Our results represent the most comprehensive analysis of the phosphoproteomes of human primary fibroblasts exposed to multiple doses of ionizing radiation published to date and provides a basis for the systems level identification of biological processes, molecular pathways and individual proteins regulated in a dose dependent manner by ionizing radiation. Further study of these modified proteins and affected networks should help to define the molecular mechanisms that regulate biological responses to radiation at different radiation doses and elucidate the impact of low dose radiation exposure on human health.« less

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

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

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

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

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

PubMed

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

2011-09-22

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

An Integrative data mining approach to identifying Adverse Outcome Pathway (AOP) Signatures

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or populatio...

Biochemistry and biology: heart-to-heart to investigate cardiac progenitor cells.

PubMed

Chimenti, Isotta; Forte, Elvira; Angelini, Francesco; Messina, Elisa; Giacomello, Alessandro

2013-02-01

Cardiac regenerative medicine is a rapidly evolving field, with promising future developments for effective personalized treatments. Several stem/progenitor cells are candidates for cardiac cell therapy, and emerging evidence suggests how multiple metabolic and biochemical pathways strictly regulate their fate and renewal. In this review, we will explore a selection of areas of common interest for biology and biochemistry concerning stem/progenitor cells, and in particular cardiac progenitor cells. Numerous regulatory mechanisms have been identified that link stem cell signaling and functions to the modulation of metabolic pathways, and vice versa. Pharmacological treatments and culture requirements may be exploited to modulate stem cell pluripotency and self-renewal, possibly boosting their regenerative potential for cell therapy. Mitochondria and their many related metabolites and messengers, such as oxygen, ROS, calcium and glucose, have a crucial role in regulating stem cell fate and the balance of their functions, together with many metabolic enzymes. Furthermore, protein biochemistry and proteomics can provide precious clues on the definition of different progenitor cell populations, their physiology and their autocrine/paracrine regulatory/signaling networks. Interdisciplinary approaches between biology and biochemistry can provide productive insights on stem/progenitor cells, allowing the development of novel strategies and protocols for effective cardiac cell therapy clinical translation. This article is part of a Special Issue entitled Biochemistry of Stem Cells. Copyright © 2012 Elsevier B.V. All rights reserved.

A Database of Reaction Monitoring Mass Spectrometry Assays for Elucidating Therapeutic Response in Cancer

PubMed Central

Remily-Wood, Elizabeth R.; Liu, Richard Z.; Xiang, Yun; Chen, Yi; Thomas, C. Eric; Rajyaguru, Neal; Kaufman, Laura M.; Ochoa, Joana E.; Hazlehurst, Lori; Pinilla-Ibarz, Javier; Lancet, Jeffrey; Zhang, Guolin; Haura, Eric; Shibata, David; Yeatman, Timothy; Smalley, Keiran S.M.; Dalton, William S.; Huang, Emina; Scott, Ed; Bloom, Gregory C.; Eschrich, Steven A.; Koomen, John M.

2012-01-01

Purpose The Quantitative Assay Database (QuAD), http://proteome.moffitt.org/QUAD/, facilitates widespread implementation of quantitative mass spectrometry in cancer biology and clinical research through sharing of methods and reagents for monitoring protein expression and modification. Experimental Design Liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM) assays are developed using SDS-PAGE fractionated lysates from cancer cell lines. Pathway maps created using GeneGO Metacore provide the biological relationships between proteins and illustrate concepts for multiplexed analysis; each protein can be selected to examine assay development at the protein and peptide level. Results The coupling of SDS-PAGE and LC-MRM screening has been used to detect 876 peptides from 218 cancer-related proteins in model systems including colon, lung, melanoma, leukemias, and myeloma, which has led to the development of 95 quantitative assays including stable-isotope labeled peptide standards. Methods are published online and peptide standards are made available to the research community. Protein expression measurements for heat shock proteins, including a comparison with ELISA and monitoring response to the HSP90 inhibitor, 17-DMAG, are used to illustrate the components of the QuAD and its potential utility. Conclusions and Clinical Relevance This resource enables quantitative assessment of protein components of signaling pathways and biological processes and holds promise for systematic investigation of treatment responses in cancer. PMID:21656910

Boosting probabilistic graphical model inference by incorporating prior knowledge from multiple sources.

PubMed

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.

GOSAP: Gene Ontology-Based Semantic Alignment of Biological Pathways.

PubMed

Gamalielsson, Jonas; Olsson, Bjorn

2008-01-01

We present a new method for semantic comparison of biological pathways, aiming to discover evolutionary conservation of pathways between species. Our method uses all three sub-ontologies of Gene Ontology (GO) and a measure of semantic similarity to calculate match scores between gene products. These scores are used for finding local pairwise pathway alignments. This approach has the advantage of being applicable to all types of pathways where nodes are gene products, e.g., regulatory pathways, signalling pathways and metabolic enzyme-to-enzyme pathways. We demonstrate the usefulness of the method using regulatory and metabolic pathways from E. coli and S. cerevisiae as examples.

Two insulin-like peptide family members from the mosquito Aedes aegypti exhibit differential biological and receptor binding activities

PubMed Central

Wen, Zhimou; Gulia, Monika; Clark, Kevin D.; Dhara, Animesh; Crim, Joe W.; Strand, Michael R.; Brown, Mark R.

2010-01-01

Insects encode multiple ILPs but only one homolog of the vertebrate IR that activates the insulin signaling pathway. However, it remains unclear whether all insect ILPs are high affinity ligands for the IR or have similar biological functions. The yellow fever mosquito, Aedes aegypti, encodes eight ILPs with prior studies strongly implicating ILPs from the brain in regulating metabolism and the maturation of eggs following blood feeding. Here we addressed whether two ILP family members expressed in the brain, ILP4 and ILP3, have overlapping functional and receptor binding activities. Our results indicated that ILP3 exhibits strong insulin-like activity by elevating carbohydrate and lipid storage in sugar-fed adult females, whereas ILP4 does not. In contrast, both ILPs exhibited dose-dependent gonadotropic activity in blood-fed females as measured by the stimulation of ovaries to produce ecdysteroids and the uptake of yolk by primary oocytes. Binding studies using ovary membranes indicated that ILP4 and ILP3 do not cross compete; a finding further corroborated by cross-linking and immunoblotting experiments showing that ILP3 binds the MIR while ILP4 binds an unknown 55 kDa membrane protein. In contrast, each ILP activated the insulin signaling pathway in ovaries as measured by enhanced phosphorylation of Akt. RNAi and inhibitor studies further indicated that the gonadotropic activity of ILP4 and ILP3 requires the MIR and a functional insulin signaling pathway. Taken together, our results indicate that two members of the Ae. aegypti ILP family exhibit partially overlapping biological activity and different binding interactions with the MIR. PMID:20643184

Petiveria alliacea extracts uses multiple mechanisms to inhibit growth of human and mouse tumoral cells.

PubMed

Urueña, Claudia; Cifuentes, Claudia; Castañeda, Diana; Arango, Amparo; Kaur, Punit; Asea, Alexzander; Fiorentino, Susana

2008-11-18

There is ethnopharmacological evidence that Petiveria alliacea can have antitumor activity; however, the mechanism of its cytotoxic activity is not well understood. We assessed multiple in vitro biological activities of an ethyl acetate soluble plant fraction over several tumor cell lines. Tumor cell lines were evaluated using the following tests: trypan blue exclusion test, MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide], flow cytometry, cytoskeleton organization analysis, cell cycle, mitochondria membrane depolarization, clonogenicity test, DNA fragmentation test and differential protein expression by HPLC-Chip/MS analysis. F4 fraction characterization was made by HPLC-MS. Petiveria alliacea fraction characterized by de-replication was found to alter actin cytoskeleton organization, induce G2 cell cycle arrest and cause apoptotic cell death in a mitochondria independent way. In addition, we found down regulation of cytoskeleton, chaperone, signal transduction proteins, and proteins involved in metabolic pathways. Finally up regulation of proteins involved in translation and intracellular degradation was also observed. The results of this study indicate that Petiveria alliacea exerts multiple biological activities in vitro consistent with cytotoxicity. Further studies in animal models are needed but Petiveria alliacea appears to be a good candidate to be used as an antitumor agent.

Petiveria alliacea extracts uses multiple mechanisms to inhibit growth of human and mouse tumoral cells

PubMed Central

Urueña, Claudia; Cifuentes, Claudia; Castañeda, Diana; Arango, Amparo; Kaur, Punit; Asea, Alexzander; Fiorentino, Susana

2008-01-01

Background There is ethnopharmacological evidence that Petiveria alliacea can have antitumor activity; however, the mechanism of its cytotoxic activity is not well understood. We assessed multiple in vitro biological activities of an ethyl acetate soluble plant fraction over several tumor cell lines. Methods Tumor cell lines were evaluated using the following tests: trypan blue exclusion test, MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide], flow cytometry, cytoskeleton organization analysis, cell cycle, mitochondria membrane depolarization, clonogenicity test, DNA fragmentation test and differential protein expression by HPLC-Chip/MS analysis. F4 fraction characterization was made by HPLC-MS. Results Petiveria alliacea fraction characterized by de-replication was found to alter actin cytoskeleton organization, induce G2 cell cycle arrest and cause apoptotic cell death in a mitochondria independent way. In addition, we found down regulation of cytoskeleton, chaperone, signal transduction proteins, and proteins involved in metabolic pathways. Finally up regulation of proteins involved in translation and intracellular degradation was also observed. Conclusion The results of this study indicate that Petiveria alliacea exerts multiple biological activities in vitro consistent with cytotoxicity. Further studies in animal models are needed but Petiveria alliacea appears to be a good candidate to be used as an antitumor agent. PMID:19017389

Synthetic biology: applying biological circuits beyond novel therapies.

PubMed

Dobrin, Anton; Saxena, Pratik; Fussenegger, Martin

2016-04-18

Synthetic biology, an engineering, circuit-driven approach to biology, has developed whole new classes of therapeutics. Unfortunately, these advances have thus far been undercapitalized upon by basic researchers. As discussed herein, using synthetic circuits, one can undertake exhaustive investigations of the endogenous circuitry found in nature, develop novel detectors and better temporally and spatially controlled inducers. One could detect changes in DNA, RNA, protein or even transient signaling events, in cell-based systems, in live mice, and in humans. Synthetic biology has also developed inducible systems that can be induced chemically, optically or using radio waves. This induction has been re-wired to lead to changes in gene expression, RNA stability and splicing, protein stability and splicing, and signaling via endogenous pathways. Beyond simple detectors and inducible systems, one can combine these modalities and develop novel signal integration circuits that can react to a very precise pre-programmed set of conditions or even to multiple sets of precise conditions. In this review, we highlight some tools that were developed in which these circuits were combined such that the detection of a particular event automatically triggered a specific output. Furthermore, using novel circuit-design strategies, circuits have been developed that can integrate multiple inputs together in Boolean logic gates composed of up to 6 inputs. We highlight the tools available and what has been developed thus far, and highlight how some clinical tools can be very useful in basic science. Most of the systems that are presented can be integrated together; and the possibilities far exceed the number of currently developed strategies.

Biological Pathways

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Genomic Instability and Radiation Risk in Molecular Pathways to Colon Cancer

PubMed Central

Kaiser, Jan Christian; Meckbach, Reinhard; Jacob, Peter

2014-01-01

Colon cancer is caused by multiple genomic alterations which lead to genomic instability (GI). GI appears in molecular pathways of microsatellite instability (MSI) and chromosomal instability (CIN) with clinically observed case shares of about 15–20% and 80–85%. Radiation enhances the colon cancer risk by inducing GI, but little is known about different outcomes for MSI and CIN. Computer-based modelling can facilitate the understanding of the phenomena named above. Comprehensive biological models, which combine the two main molecular pathways to colon cancer, are fitted to incidence data of Japanese a-bomb survivors. The preferred model is selected according to statistical criteria and biological plausibility. Imprints of cell-based processes in the succession from adenoma to carcinoma are identified by the model from age dependences and secular trends of the incidence data. Model parameters show remarkable compliance with mutation rates and growth rates for adenoma, which has been reported over the last fifteen years. Model results suggest that CIN begins during fission of intestinal crypts. Chromosomal aberrations are generated at a markedly elevated rate which favors the accelerated growth of premalignant adenoma. Possibly driven by a trend of Westernization in the Japanese diet, incidence rates for the CIN pathway increased notably in subsequent birth cohorts, whereas rates pertaining to MSI remained constant. An imbalance between number of CIN and MSI cases began to emerge in the 1980s, whereas in previous decades the number of cases was almost equal. The CIN pathway exhibits a strong radio-sensitivity, probably more intensive in men. Among young birth cohorts of both sexes the excess absolute radiation risk related to CIN is larger by an order of magnitude compared to the MSI-related risk. Observance of pathway-specific risks improves the determination of the probability of causation for radiation-induced colon cancer in individual patients, if their exposure histories are known. PMID:25356998

How cigarette smoking may increase the risk of anxiety symptoms and anxiety disorders: a critical review of biological pathways

PubMed Central

Moylan, Steven; Jacka, Felice N; Pasco, Julie A; Berk, Michael

2013-01-01

Multiple studies have demonstrated an association between cigarette smoking and increased anxiety symptoms or disorders, with early life exposures potentially predisposing to enhanced anxiety responses in later life. Explanatory models support a potential role for neurotransmitter systems, inflammation, oxidative and nitrosative stress, mitochondrial dysfunction, neurotrophins and neurogenesis, and epigenetic effects, in anxiety pathogenesis. All of these pathways are affected by exposure to cigarette smoke components, including nicotine and free radicals. This review critically examines and summarizes the literature exploring the role of these systems in increased anxiety and how exposure to cigarette smoke may contribute to this pathology at a biological level. Further, this review explores the effects of cigarette smoke on normal neurodevelopment and anxiety control, suggesting how exposure in early life (prenatal, infancy, and adolescence) may predispose to higher anxiety in later life. A large heterogenous literature was reviewed that detailed the association between cigarette smoking and anxiety symptoms and disorders with structural brain changes, inflammation, and cell-mediated immune markers, markers of oxidative and nitrosative stress, mitochondrial function, neurotransmitter systems, neurotrophins and neurogenesis. Some preliminary data were found for potential epigenetic effects. The literature provides some support for a potential interaction between cigarette smoking, anxiety symptoms and disorders, and the above pathways; however, limitations exist particularly in delineating causative effects. The literature also provides insight into potential effects of cigarette smoke, in particular nicotine, on neurodevelopment. The potential treatment implications of these findings are discussed in regards to future therapeutic targets for anxiety. The aforementioned pathways may help mediate increased anxiety seen in people who smoke. Further research into the specific actions of nicotine and other cigarette components on these pathways, and how these pathways interact, may provide insights that lead to new treatment for anxiety and a greater understanding of anxiety pathogenesis. PMID:23785661

A synthetic biology approach to engineer a functional reversal of the β-oxidation cycle.

PubMed

Clomburg, James M; Vick, Jacob E; Blankschien, Matthew D; Rodríguez-Moyá, María; Gonzalez, Ramon

2012-11-16

While we have recently constructed a functional reversal of the β-oxidation cycle as a platform for the production of fuels and chemicals by engineering global regulators and eliminating native fermentative pathways, the system-level approach used makes it difficult to determine which of the many deregulated enzymes are responsible for product synthesis. This, in turn, limits efforts to fine-tune the synthesis of specific products and prevents the transfer of the engineered pathway to other organisms. In the work reported here, we overcome the aforementioned limitations by using a synthetic biology approach to construct and functionally characterize a reversal of the β-oxidation cycle. This was achieved through the in vitro kinetic characterization of each functional unit of the core and termination pathways, followed by their in vivo assembly and functional characterization. With this approach, the four functional units of the core pathway, thiolase, 3-hydroxyacyl-CoA dehydrogenase, enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydratase, and acyl-CoA dehydrogenase/trans-enoyl-CoA reductase, were purified and kinetically characterized in vitro. When these four functional units were assembled in vivo in combination with thioesterases as the termination pathway, the synthesis of a variety of 4-C carboxylic acids from a one-turn functional reversal of the β-oxidation cycle was realized. The individual expression and modular construction of these well-defined core components exerted the majority of control over product formation, with only highly selective termination pathways resulting in shifts in product formation. Further control over product synthesis was demonstrated by overexpressing a long-chain thiolase that enables the operation of multiple turns of the reversal of the β-oxidation cycle and hence the synthesis of longer-chain carboxylic acids. The well-defined and self-contained nature of each functional unit makes the engineered reversal of the β-oxidation cycle "chassis neutral" and hence transferrable to the host of choice for efficient fuel or chemical production.

Leptospira interrogans causes quantitative and morphological disturbances in adherens junctions and other biological groups of proteins in human endothelial cells

PubMed Central

Sato, Hiromi

2017-01-01

Pathogenic Leptospira transmits from animals to humans, causing the zoonotic life-threatening infection called leptospirosis. This infection is reported worldwide with higher risk in tropical regions. Symptoms of leptospirosis range from mild illness to severe illness such as liver damage, kidney failure, respiratory distress, meningitis, and fatal hemorrhagic disease. Invasive species of Leptospira rapidly disseminate to multiple tissues where this bacterium damages host endothelial cells, increasing vascular permeability. Despite the burden in humans and animals, the pathogenic mechanisms of Leptospira infection remain to be elucidated. The pathogenic leptospires adhere to endothelial cells and permeabilize endothelial barriers in vivo and in vitro. In this study, human endothelial cells were infected with the pathogenic L. interrogans serovar Copenhageni or the saprophyte L. biflexa serovar Patoc to investigate morphological changes and other distinctive phenotypes of host cell proteins by fluorescence microscopy. Among those analyzed, 17 proteins from five biological classes demonstrated distinctive phenotypes in morphology and/or signal intensity upon infection with Leptospira. The affected biological groups include: 1) extracellular matrix, 2) intercellular adhesion molecules and cell surface receptors, 3) intracellular proteins, 4) cell-cell junction proteins, and 5) a cytoskeletal protein. Infection with the pathogenic strain most profoundly disturbed the biological structures of adherens junctions (VE-cadherin and catenins) and actin filaments. Our data illuminate morphological disruptions and reduced signals of cell-cell junction proteins and filamentous actin in L. interrogans-infected endothelial cells. In addition, Leptospira infection, regardless of pathogenic status, influenced other host proteins belonging to multiple biological classes. Our data suggest that this zoonotic agent may damage endothelial cells via multiple cascades or pathways including endothelial barrier damage and inflammation, potentially leading to vascular hyperpermeability and severe illness in vivo. This work provides new insights into the pathophysiological mechanisms of Leptospira infection. PMID:28750011

Leptospira interrogans causes quantitative and morphological disturbances in adherens junctions and other biological groups of proteins in human endothelial cells.

PubMed

Sato, Hiromi; Coburn, Jenifer

2017-07-01

Pathogenic Leptospira transmits from animals to humans, causing the zoonotic life-threatening infection called leptospirosis. This infection is reported worldwide with higher risk in tropical regions. Symptoms of leptospirosis range from mild illness to severe illness such as liver damage, kidney failure, respiratory distress, meningitis, and fatal hemorrhagic disease. Invasive species of Leptospira rapidly disseminate to multiple tissues where this bacterium damages host endothelial cells, increasing vascular permeability. Despite the burden in humans and animals, the pathogenic mechanisms of Leptospira infection remain to be elucidated. The pathogenic leptospires adhere to endothelial cells and permeabilize endothelial barriers in vivo and in vitro. In this study, human endothelial cells were infected with the pathogenic L. interrogans serovar Copenhageni or the saprophyte L. biflexa serovar Patoc to investigate morphological changes and other distinctive phenotypes of host cell proteins by fluorescence microscopy. Among those analyzed, 17 proteins from five biological classes demonstrated distinctive phenotypes in morphology and/or signal intensity upon infection with Leptospira. The affected biological groups include: 1) extracellular matrix, 2) intercellular adhesion molecules and cell surface receptors, 3) intracellular proteins, 4) cell-cell junction proteins, and 5) a cytoskeletal protein. Infection with the pathogenic strain most profoundly disturbed the biological structures of adherens junctions (VE-cadherin and catenins) and actin filaments. Our data illuminate morphological disruptions and reduced signals of cell-cell junction proteins and filamentous actin in L. interrogans-infected endothelial cells. In addition, Leptospira infection, regardless of pathogenic status, influenced other host proteins belonging to multiple biological classes. Our data suggest that this zoonotic agent may damage endothelial cells via multiple cascades or pathways including endothelial barrier damage and inflammation, potentially leading to vascular hyperpermeability and severe illness in vivo. This work provides new insights into the pathophysiological mechanisms of Leptospira infection.

Pathway Profiling and Rational Trial Design for Studies in Advanced Stage Cervical Carcinoma: A Review and a Perspective

PubMed Central

Scholl, Susy M. E.; Kenter, Gemma; Kurzeder, Christian; Beuzeboc, Philippe

2011-01-01

Multiple genetic abnormalities will have occurred in advanced cervical cancer and multiple targeting is likely to be needed to control tumor growth. To date, dominant therapeutic targets under scrutiny for cervical cancer treatment have been EGFR pathway and angiogenesis inhibition as well as anti-HPV vaccines. The potentially most effective targets to be blocked may be downstream from the membrane receptor or at the level of the nucleus. Alterations of the pathways involved in DNA repair and in checkpoint activations, as well as the specific site of HPV genome integration, appear worth assessing. For genetic mutational analysis, complete exon sequencing may become the norm in the future but at this stage frequent mutations (that matter) can be verified by PCR analysis. A precise documentation of relevant alterations of a large spectrum of protein biomarkers can be carried out by reverse phase protein array (RPPA) or by multiplex analysis. Clinical decision-making on the drug(s) of choice as a function of the biological alteration will need input from bio-informatics platforms as well as novel statistical designs. Endpoints are yet to be defined such as the loss (or reappearance) of a predictive biomarker. Single or dual targeting needs to be explored first in relevant preclinical animal and in xenograft models prior to clinical deployment. PMID:22091418

Transactional Pathways of Transgender Identity Development in Transgender and Gender Nonconforming Youth and Caregivers from the Trans Youth Family Study

PubMed Central

Katz-Wise, Sabra L.; Budge, Stephanie L.; Fugate, Ellen; Flanagan, Kaleigh; Touloumtzis, Currie; Rood, Brian; Perez-Brumer, Amaya; Leibowitz, Scott

2017-01-01

Background A growing body of research has examined transgender identity development, but no studies have investigated developmental pathways as a transactional process between youth and caregivers, incorporating perspectives from multiple family members. The aim of this study was to conceptualize pathways of transgender identity development using narratives from both transgender and gender nonconforming (TGN) youth and their cisgender (non-transgender) caregivers. Methods The sample included 16 families, with 16 TGN youth, ages 7–18 years, and 29 cisgender caregivers (N = 45 family members). TGN youth represented multiple gender identities, including trans boy (n = 9), trans girl (n = 5), gender fluid boy (n = 1), and girlish boy (n = 1). Caregivers included mothers (n = 17), fathers (n = 11), and one grandmother. Participants were recruited from LGBTQ community organizations and support networks for families with transgender youth in the Midwest, Northeast, and South regions of the United States. Each family member completed a one-time in-person semi-structured qualitative interview that included questions about transgender identity development. Results Analyses revealed seven overarching themes of transgender identity development, which were organized into a conceptual model: Trans identity development, sociocultural influences/societal discourse, biological influences, family adjustment/impact, stigma/cisnormativity, support/resources, and gender affirmation/actualization. Conclusions Findings underscore the importance of assessing developmental processes among TGN youth as transactional, impacting both youth and their caregivers. PMID:29527139

Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data.

PubMed

Aliper, Alexander; Plis, Sergey; Artemov, Artem; Ulloa, Alvaro; Mamoshina, Polina; Zhavoronkov, Alex

2016-07-05

Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics, and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solely based on their transcriptional profiles. We used the perturbation samples of 678 drugs across A549, MCF-7, and PC-3 cell lines from the LINCS Project and linked those to 12 therapeutic use categories derived from MeSH. To train the DNN, we utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled data set of samples perturbed with different concentrations of the drug for 6 and 24 hours. In both pathway and gene level classification, DNN achieved high classification accuracy and convincingly outperformed the support vector machine (SVM) model on every multiclass classification problem, however, models based on pathway level data performed significantly better. For the first time we demonstrate a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. We also propose using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development.

Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data

PubMed Central

Aliper, Alexander; Plis, Sergey; Artemov, Artem; Ulloa, Alvaro; Mamoshina, Polina; Zhavoronkov, Alex

2016-01-01

Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solely based on their transcriptional profiles. We used the perturbation samples of 678 drugs across A549, MCF‐7 and PC‐3 cell lines from the LINCS project and linked those to 12 therapeutic use categories derived from MeSH. To train the DNN, we utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled dataset of samples perturbed with different concentrations of the drug for 6 and 24 hours. In both gene and pathway level classification, DNN convincingly outperformed support vector machine (SVM) model on every multiclass classification problem, however, models based on a pathway level classification perform better. For the first time we demonstrate a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. We also propose using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development. PMID:27200455

Plant MetGenMAP: an integrative analysis system for plant systems biology

USDA-ARS?s Scientific Manuscript database

We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...

Role of dimethyl fumarate in oxidative stress of multiple sclerosis: A review.

PubMed

Suneetha, A; Raja Rajeswari, K

2016-04-15

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS affecting both white and grey matter. Inflammation and oxidative stress are also thought to promote tissue damage in multiple sclerosis. Recent data point at an important role of anti-oxidative pathways for tissue protection in chronic MS, particularly involving the transcription factor nuclear factor (erythroid-derived 2)-related factor 2 (Nrf2). Thus, novel therapeutics enhancing cellular resistance to free radicals could prove useful for MS treatment. Oxidative stress and anti-oxidative pathways are important players in MS pathophysiology and constitute a promising target for future MS therapy with dimethyl fumarate. The clinical utility of DMF in multiple sclerosis is being explored through phase III trials with BG-12, which is an oral therapeutic agent. Currently a wide research is going on to find out the exact mechanism of DMF, till date it is not clear. Based on strong signals of nephrotoxicity in non-humans and the theoretical risk of renal cell cancer from intracellular accumulation of fumarate, post-marketing study of a large population of patients will be necessary to fully assess the long-term safety of dimethyl fumarate. The current treatment goals are to shorten the duration and severity of relapses, prolong the time between relapses, and delay progression of disability. In this regard, dimethyl fumarate offers a promising alternative to orally administered fingolimod (GILENYA) or teriflunomide (AUBAGIO), which are currently marketed in the United States under FDA-mandated Risk Evaluation and Mitigation Strategy (REMS) programs because of serious safety concerns. More clinical experience with all three agents will be necessary to differentiate the tolerability of long-term therapy for patients diagnosed with multiple sclerosis. This write-up provides the detailed information of dimethyl fumarate in treating the neuro disease, multiple sclerosis and its mechanism involved via oxidative stress pathway. The rapid screening methods are also need to be developed to estimate DMF in biological samples to perform and proceed for further investigations. Copyright © 2016 Elsevier B.V. All rights reserved.

Protection of Momordica charantia polysaccharide against intracerebral hemorrhage-induced brain injury through JNK3 signaling pathway.

PubMed

Duan, Zhen-Zhen; Zhou, Xiao-Ling; Li, Yi-Hang; Zhang, Feng; Li, Feng-Ying; Su-Hua, Qi

2015-01-01

It has been well documented that Momordica charantia polysaccharide (MCP) has multiple biological effects such as immune enhancement, anti-oxidation and anti-cancer. However, the potential protective effects of MCP on stroke damage and its relative mechanisms remain unclear. Our present study demonstrated that MCP could scavenge reactive oxygen species (ROS) in intra-cerebral hemorrhage damage, significantly attenuating the neuronal death induced by thrombin in primary hippocampal neurons. Furthermore, we found that MCP prevented the activation of the c-Jun N-terminal protein kinase (JNK3), c-Jun and caspase-3, which was caused by the intra-cerebral hemorrhage injury. Taken together, our study demonstrated that MCP had a neuroprotective effect in response to intra-cerebral hemorrhage and its mechanisms involved the inhibition of JNK3 signaling pathway.

Atomic-level characterization of the structural dynamics of proteins.

PubMed

Shaw, David E; Maragakis, Paul; Lindorff-Larsen, Kresten; Piana, Stefano; Dror, Ron O; Eastwood, Michael P; Bank, Joseph A; Jumper, John M; Salmon, John K; Shan, Yibing; Wriggers, Willy

2010-10-15

Molecular dynamics (MD) simulations are widely used to study protein motions at an atomic level of detail, but they have been limited to time scales shorter than those of many biologically critical conformational changes. We examined two fundamental processes in protein dynamics--protein folding and conformational change within the folded state--by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equilibrium simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; separate simulations of the protein's constituent substructures shed light on possible determinants of this pathway. A 1-millisecond simulation of the folded protein BPTI reveals a small number of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.

Vitamin D and its effects on cardiovascular diseases: a comprehensive review

PubMed Central

Pérez-Hernández, Nonanzit; Aptilon-Duque, Gad; Nostroza-Hernández, María Cristina; Vargas-Alarcón, Gilberto; Rodríguez-Pérez, José Manuel; Blachman-Braun, Ruben

2016-01-01

Vitamin D is a molecule that is actively involved in multiple metabolic pathways. It is mostly known for its implications related to calcium metabolism. It has also been determined that it actively participates in the cardiovascular system, influencing blood pressure, coronary artery disease and other vascular diseases, such as heart failure and atrial fibrillation. Furthermore, it has been established that this vitamin is extensively involved in the regulation of both the renin angiotensin aldosterone system and the immune system. In this review, we present the different vitamin D metabolic pathways associated with the cardiovascular pathophysiology, and we include studies in animal and human models, as well as some of the controversies found in the literature. This review also incorporates an overview of the implications in the molecular biology and public health fields. PMID:27117316

Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

PubMed

Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

2012-12-01

Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

Synergistic Synthetic Biology: Units in Concert

PubMed Central

Trosset, Jean-Yves; Carbonell, Pablo

2013-01-01

Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications. PMID:25022769

Synergistic Synthetic Biology: Units in Concert.

PubMed

Trosset, Jean-Yves; Carbonell, Pablo

2013-01-01

Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications.

Candidate genes, pathways and mechanisms for alcoholism: an expanded convergent functional genomics approach.

PubMed

Rodd, Z A; Bertsch, B A; Strother, W N; Le-Niculescu, H; Balaraman, Y; Hayden, E; Jerome, R E; Lumeng, L; Nurnberger, J I; Edenberg, H J; McBride, W J; Niculescu, A B

2007-08-01

We describe a comprehensive translational approach for identifying candidate genes for alcoholism. The approach relies on the cross-matching of animal model brain gene expression data with human genetic linkage data, as well as human tissue data and biological roles data, an approach termed convergent functional genomics. An analysis of three animal model paradigms, based on inbred alcohol-preferring (iP) and alcohol-non-preferring (iNP) rats, and their response to treatments with alcohol, was used. A comprehensive analysis of microarray gene expression data from five key brain regions (frontal cortex, amygdala, caudate-putamen, nucleus accumbens and hippocampus) was carried out. The Bayesian-like integration of multiple independent lines of evidence, each by itself lacking sufficient discriminatory power, led to the identification of high probability candidate genes, pathways and mechanisms for alcoholism. These data reveal that alcohol has pleiotropic effects on multiple systems, which may explain the diverse neuropsychiatric and medical pathology in alcoholism. Some of the pathways identified suggest avenues for pharmacotherapy of alcoholism with existing agents, such as angiotensin-converting enzyme (ACE) inhibitors. Experiments we carried out in alcohol-preferring rats with an ACE inhibitor show a marked modulation of alcohol intake. Other pathways are new potential targets for drug development. The emergent overall picture is that physical and physiological robustness may permit alcohol-preferring individuals to withstand the aversive effects of alcohol. In conjunction with a higher reactivity to its rewarding effects, they may able to ingest enough of this nonspecific drug for a strong hedonic and addictive effect to occur.

Frameworks for organizing exposure and toxicity data - the Aggregate Exposure Pathway (AEP) and the Adverse Outcome Pathway (AOP)

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework organizes existing knowledge regarding a series of biological events, starting with a molecular initiating event (MIE) and ending at an adverse outcome. The AOP framework provides a biological context to interpret in vitro toxicity dat...

Transition model for ricin-aptamer interactions with multiple pathways and energy barriers

NASA Astrophysics Data System (ADS)

Wang, Bin; Xu, Bingqian

2014-02-01

We develop a transition model to interpret single-molecule ricin-aptamer interactions with multiple unbinding pathways and energy barriers measured by atomic force microscopy dynamic force spectroscopy. Molecular simulations establish the relationship between binding conformations and the corresponding unbinding pathways. Each unbinding pathway follows a Bell-Evans multiple-barrier model. Markov-type transition matrices are developed to analyze the redistribution of unbinding events among the pathways under different loading rates. Our study provides detailed information about complex behaviors in ricin-aptamer unbinding events.

Rapid construction of insulated genetic circuits via synthetic sequence-guided isothermal assembly

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

Torella, JP; Boehm, CR; Lienert, F

2013-12-28

In vitro recombination methods have enabled one-step construction of large DNA sequences from multiple parts. Although synthetic biological circuits can in principle be assembled in the same fashion, they typically contain repeated sequence elements such as standard promoters and terminators that interfere with homologous recombination. Here we use a computational approach to design synthetic, biologically inactive unique nucleotide sequences (UNSes) that facilitate accurate ordered assembly. Importantly, our designed UNSes make it possible to assemble parts with repeated terminator and insulator sequences, and thereby create insulated functional genetic circuits in bacteria and mammalian cells. Using UNS-guided assembly to construct repeating promoter-gene-terminatormore » parts, we systematically varied gene expression to optimize production of a deoxychromoviridans biosynthetic pathway in Escherichia coli. We then used this system to construct complex eukaryotic AND-logic gates for genomic integration into embryonic stem cells. Construction was performed by using a standardized series of UNS-bearing BioBrick-compatible vectors, which enable modular assembly and facilitate reuse of individual parts. UNS-guided isothermal assembly is broadly applicable to the construction and optimization of genetic circuits and particularly those requiring tight insulation, such as complex biosynthetic pathways, sensors, counters and logic gates.« less

Systems biology approach in Chlamydomonas reveals connections between copper nutrition and multiple metabolic steps.

PubMed

Castruita, Madeli; Casero, David; Karpowicz, Steven J; Kropat, Janette; Vieler, Astrid; Hsieh, Scott I; Yan, Weihong; Cokus, Shawn; Loo, Joseph A; Benning, Christoph; Pellegrini, Matteo; Merchant, Sabeeha S

2011-04-01

In this work, we query the Chlamydomonas reinhardtii copper regulon at a whole-genome level. Our RNA-Seq data simulation and analysis pipeline validated a 2-fold cutoff and 10 RPKM (reads per kilobase of mappable length per million mapped reads) (~1 mRNA per cell) to reveal 63 CRR1 targets plus another 86 copper-responsive genes. Proteomic and immunoblot analyses captured 25% of the corresponding proteins, whose abundance was also dependent on copper nutrition, validating transcriptional regulation as a major control mechanism for copper signaling in Chlamydomonas. The impact of copper deficiency on the expression of several O₂-dependent enzymes included steps in lipid modification pathways. Quantitative lipid profiles indicated increased polyunsaturation of fatty acids on thylakoid membrane digalactosyldiglycerides, indicating a global impact of copper deficiency on the photosynthetic apparatus. Discovery of a putative plastid copper chaperone and a membrane protease in the thylakoid suggest a mechanism for blocking copper utilization in the chloroplast. We also found an example of copper sparing in the N assimilation pathway: the replacement of copper amine oxidase by a flavin-dependent backup enzyme. Forty percent of the targets are previously uncharacterized proteins, indicating considerable potential for new discovery in the biology of copper.

The molecular biology of soft-tissue sarcomas and current trends in therapy.

PubMed

Quesada, Jorge; Amato, Robert

2012-01-01

Basic research in sarcoma models has been fundamental in the discovery of scientific milestones leading to a better understanding of the molecular biology of cancer. Yet, clinical research in sarcoma has lagged behind other cancers because of the multiple clinical and pathological entities that characterize sarcomas and their rarity. Sarcomas encompass a very heterogeneous group of tumors with diverse pathological and clinical overlapping characteristics. Molecular testing has been fundamental in the identification and better definition of more specific entities among this vast array of malignancies. A group of sarcomas are distinguished by specific molecular aberrations such as somatic mutations, intergene deletions, gene amplifications, reciprocal translocations, and complex karyotypes. These and other discoveries have led to a better understanding of the growth signals and the molecular pathways involved in the development of these tumors. These findings are leading to treatment strategies currently under intense investigation. Disruption of the growth signals is being targeted with antagonistic antibodies, tyrosine kinase inhibitors, and inhibitors of several downstream molecules in diverse molecular pathways. Preliminary clinical trials, supported by solid basic research and strong preclinical evidence, promises a new era in the clinical management of these broad spectrum of malignant tumors.

Transcriptome differences between enrofloxacin-resistant and enrofloxacin-susceptible strains of Aeromonas hydrophila.

PubMed

Zhu, Fengjiao; Yang, Zongying; Zhang, Yiliu; Hu, Kun; Fang, Wenhong

2017-01-01

Enrofloxacin is the most commonly used antibiotic to control diseases in aquatic animals caused by A. hydrophila. This study conducted de novo transcriptome sequencing and compared the global transcriptomes of enrofloxacin-resistant and enrofloxacin-susceptible strains. We got a total of 4,714 unigenes were assembled. Of these, 4,122 were annotated. A total of 3,280 unigenes were assigned to GO, 3,388 unigenes were classified into Cluster of Orthologous Groups of proteins (COG) using BLAST and BLAST2GO software, and 2,568 were mapped onto pathways using the Kyoto Encyclopedia of Gene and Genomes Pathway database. Furthermore, 218 unigenes were deemed to be DEGs. After enrofloxacin treatment, 135 genes were upregulated and 83 genes were downregulated. The GO terms biological process (126 genes) and metabolic process (136 genes) were the most enriched, and the terms for protein folding, response to stress, and SOS response were also significantly enriched. This study identified enrofloxacin treatment affects multiple biological functions of A. hydrophila. Enrofloxacin resistance in A. hydrophila is closely related to the reduction of intracellular drug accumulation caused by ABC transporters and increased expression of topoisomerase IV.

Transcriptome differences between enrofloxacin-resistant and enrofloxacin-susceptible strains of Aeromonas hydrophila

PubMed Central

Yang, Zongying; Zhang, Yiliu; Hu, Kun; Fang, Wenhong

2017-01-01

Enrofloxacin is the most commonly used antibiotic to control diseases in aquatic animals caused by A. hydrophila. This study conducted de novo transcriptome sequencing and compared the global transcriptomes of enrofloxacin-resistant and enrofloxacin-susceptible strains. We got a total of 4,714 unigenes were assembled. Of these, 4,122 were annotated. A total of 3,280 unigenes were assigned to GO, 3,388 unigenes were classified into Cluster of Orthologous Groups of proteins (COG) using BLAST and BLAST2GO software, and 2,568 were mapped onto pathways using the Kyoto Encyclopedia of Gene and Genomes Pathway database. Furthermore, 218 unigenes were deemed to be DEGs. After enrofloxacin treatment, 135 genes were upregulated and 83 genes were downregulated. The GO terms biological process (126 genes) and metabolic process (136 genes) were the most enriched, and the terms for protein folding, response to stress, and SOS response were also significantly enriched. This study identified enrofloxacin treatment affects multiple biological functions of A. hydrophila. Enrofloxacin resistance in A. hydrophila is closely related to the reduction of intracellular drug accumulation caused by ABC transporters and increased expression of topoisomerase IV. PMID:28708867

Autophagy in Measles Virus Infection.

PubMed

Rozières, Aurore; Viret, Christophe; Faure, Mathias

2017-11-24

Autophagy is a biological process that helps cells to recycle obsolete cellular components and which greatly contributes to maintaining cellular integrity in response to environmental stress factors. Autophagy is also among the first lines of cellular defense against invading microorganisms, including viruses. The autophagic destruction of invading pathogens, a process referred to as xenophagy, involves cytosolic autophagy receptors, such as p62/SQSTM1 (Sequestosome 1) or NDP52/CALCOCO2 (Nuclear Dot 52 KDa Protein/Calcium Binding And Coiled-Coil Domain 2), which bind to microbial components and target them towards growing autophagosomes for degradation. However, most, if not all, infectious viruses have evolved molecular tricks to escape from xenophagy. Many viruses even use autophagy, part of the autophagy pathway or some autophagy-associated proteins, to improve their infectious potential. In this regard, the measles virus, responsible for epidemic measles, has a unique interface with autophagy as the virus can induce multiple rounds of autophagy in the course of infection. These successive waves of autophagy result from distinct molecular pathways and seem associated with anti- and/or pro-measles virus consequences. In this review, we describe what the autophagy-measles virus interplay has taught us about both the biology of the virus and the mechanistic orchestration of autophagy.

Cofactors in the RNA World

NASA Technical Reports Server (NTRS)

Ditzler, Mark A.

2014-01-01

RNA world theories figure prominently in many scenarios for the origin and early evolution of life. These theories posit that RNA molecules played a much larger role in ancient biology than they do now, acting both as the dominant biocatalysts and as the repository of genetic information. Many features of modern RNA biology are potential examples of molecular fossils from an RNA world, such as the pervasive involvement of nucleotides in coenzymes, the existence of natural aptamers that bind these coenzymes, the existence of natural ribozymes, a biosynthetic pathway in which deoxynucleotides are produced from ribonucleotides, and the central role of ribosomal RNA in protein synthesis in the peptidyl transferase center of the ribosome. Here, we uses both a top-down approach that evaluates RNA function in modern biology and a bottom-up approach that examines the capacities of RNA independent of modern biology. These complementary approaches exploit multiple in vitro evolution techniques coupled with high-throughput sequencing and bioinformatics analysis. Together these complementary approaches advance our understanding of the most primitive organisms, their early evolution, and their eventual transition to modern biochemistry.

Queueing-Based Synchronization and Entrainment for Synthetic Gene Oscillators

NASA Astrophysics Data System (ADS)

Mather, William; Butzin, Nicholas; Hochendoner, Philip; Ogle, Curtis

Synthetic gene oscillators have been a major focus of synthetic biology research since the beginning of the field 15 years ago. They have proven to be useful both for biotechnological applications as well as a testing ground to significantly develop our understanding of the design principles behind synthetic and native gene oscillators. In particular, the principles governing synchronization and entrainment of biological oscillators have been explored using a synthetic biology approach. Our work combines experimental and theoretical approaches to specifically investigate how a bottleneck for protein degradation, which is present in most if not all existing synthetic oscillators, can be leveraged to robustly synchronize and entrain biological oscillators. We use both the terminology and mathematical tools of queueing theory to intuitively explain the role of this bottleneck in both synchronization and entrainment, which extends prior work demonstrating the usefulness of queueing theory in synthetic and native gene circuits. We conclude with an investigation of how synchronization and entrainment may be sensitive to the presence of multiple proteolytic pathways in a cell that couple weakly through crosstalk. This work was supported by NSF Grant #1330180.

Comparative proteomics analysis of apoptotic Spodoptera frugiperda cells during p35 knockout Autographa californica multiple nucleopolyhedrovirus infection.

PubMed

Yu, Qian; Xiong, Youhua; Liu, Jianliang; Wang, Qin; Qiu, Yuanxin; Wen, Dongling

2016-06-01

Infection with Autographa californica multiple nucleopolyhedrovirus (AcMNPV) mutants lacking a functional p35 gene can induce host cell apoptosis, which provides the possibility to use the potential of these viruses in the biological control of pest insects. Nonetheless, the proteomics or the protein changes of Spodoptera frugiperda (Sf9) cells infected with p35 knockout AcMNPV have not yet been studied. To further improve the use of AcMNPV, we set out to analyze the protein composition and protein changes of Sf9 cells of different infection stages by isobaric tag for relative and absolute quantification (iTRAQ) techniques. A total of 4004 sf9 proteins were identified by iTRAQ. After comparation of the significantly expressed 483 proteins from p35koAcMNPV-infected Sf9 cells and the significantly expressed 413 proteins from wtAcMNPV-infected Sf9 cells, we found that 226 proteins were specific to p35koAcMNPV-infected Sf9 cells. The 226 proteins were categorized according to GO classification for insects and were categorized into: biological processes, molecular functions and cellular components. Of interest, the most up-regulated proteins related to Epstein-Barr virus infection, RNA transport, Calcium signaling pathway, cGMP-PKG signaling pathway, oxidative phosphorylation and N-Glycan biosynthesis. Determination of the protein changes in p35 knockout AcMNPV-infected Sf9 cells would facilitate the better use of this virus-host cell interaction in pest insect control and other related fields. Copyright © 2016 Elsevier Inc. All rights reserved.

Enriched pathways for major depressive disorder identified from a genome-wide association study.

PubMed

Kao, Chung-Feng; Jia, Peilin; Zhao, Zhongming; Kuo, Po-Hsiu

2012-11-01

Major depressive disorder (MDD) has caused a substantial burden of disease worldwide with moderate heritability. Despite efforts through conducting numerous association studies and now, genome-wide association (GWA) studies, the success of identifying susceptibility loci for MDD has been limited, which is partially attributed to the complex nature of depression pathogenesis. A pathway-based analytic strategy to investigate the joint effects of various genes within specific biological pathways has emerged as a powerful tool for complex traits. The present study aimed to identify enriched pathways for depression using a GWA dataset for MDD. For each gene, we estimated its gene-wise p value using combined and minimum p value, separately. Canonical pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta were used. We employed four pathway-based analytic approaches (gene set enrichment analysis, hypergeometric test, sum-square statistic, sum-statistic). We adjusted for multiple testing using Benjamini & Hochberg's method to report significant pathways. We found 17 significantly enriched pathways for depression, which presented low-to-intermediate crosstalk. The top four pathways were long-term depression (p⩽1×10-5), calcium signalling (p⩽6×10-5), arrhythmogenic right ventricular cardiomyopathy (p⩽1.6×10-4) and cell adhesion molecules (p⩽2.2×10-4). In conclusion, our comprehensive pathway analyses identified promising pathways for depression that are related to neurotransmitter and neuronal systems, immune system and inflammatory response, which may be involved in the pathophysiological mechanisms underlying depression. We demonstrated that pathway enrichment analysis is promising to facilitate our understanding of complex traits through a deeper interpretation of GWA data. Application of this comprehensive analytic strategy in upcoming GWA data for depression could validate the findings reported in this study.

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

PubMed Central

Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

PubMed

Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants.

PubMed

van Baren, Marijke J; Bachy, Charles; Reistetter, Emily Nahas; Purvine, Samuel O; Grimwood, Jane; Sudek, Sebastian; Yu, Hang; Poirier, Camille; Deerinck, Thomas J; Kuo, Alan; Grigoriev, Igor V; Wong, Chee-Hong; Smith, Richard D; Callister, Stephen J; Wei, Chia-Lin; Schmutz, Jeremy; Worden, Alexandra Z

2016-03-31

Prasinophytes are widespread marine green algae that are related to plants. Cellular abundance of the prasinophyte Micromonas has reportedly increased in the Arctic due to climate-induced changes. Thus, studies of these unicellular eukaryotes are important for marine ecology and for understanding Viridiplantae evolution and diversification. We generated evidence-based Micromonas gene models using proteomics and RNA-Seq to improve prasinophyte genomic resources. First, sequences of four chromosomes in the 22 Mb Micromonas pusilla (CCMP1545) genome were finished. Comparison with the finished 21 Mb genome of Micromonas commoda (RCC299; named herein) shows they share ≤8,141 of ~10,000 protein-encoding genes, depending on the analysis method. Unlike RCC299 and other sequenced eukaryotes, CCMP1545 has two abundant repetitive intron types and a high percent (26 %) GC splice donors. Micromonas has more genus-specific protein families (19 %) than other genome sequenced prasinophytes (11 %). Comparative analyses using predicted proteomes from other prasinophytes reveal proteins likely related to scale formation and ancestral photosynthesis. Our studies also indicate that peptidoglycan (PG) biosynthesis enzymes have been lost in multiple independent events in select prasinophytes and plants. However, CCMP1545, polar Micromonas CCMP2099 and prasinophytes from other classes retain the entire PG pathway, like moss and glaucophyte algae. Surprisingly, multiple vascular plants also have the PG pathway, except the Penicillin-Binding Protein, and share a unique bi-domain protein potentially associated with the pathway. Alongside Micromonas experiments using antibiotics that halt bacterial PG biosynthesis, the findings highlight unrecognized phylogenetic complexity in PG-pathway retention and implicate a role in chloroplast structure or division in several extant Viridiplantae lineages. Extensive differences in gene loss and architecture between related prasinophytes underscore their divergence. PG biosynthesis genes from the cyanobacterial endosymbiont that became the plastid, have been selectively retained in multiple plants and algae, implying a biological function. Our studies provide robust genomic resources for emerging model algae, advancing knowledge of marine phytoplankton and plant evolution.

The treatment of parental height as a biological factor in studies of birth weight and childhood growth

PubMed Central

Spencer, N; Logan, S

2002-01-01

Parental height is frequently treated as a biological variable in studies of birth weight and childhood growth. Elimination of social variables from multivariate models including parental height as a biological variable leads researchers to conclude that social factors have no independent effect on the outcome. This paper challenges the treatment of parental height as a biological variable, drawing on extensive evidence for the determination of adult height through a complex interaction of genetic and social factors. The paper firstly seeks to establish the importance of social factors in the determination of height. The methodological problems associated with treatment of parental height as a purely biological variable are then discussed, illustrated by data from published studies and by analysis of data from the 1958 National Childhood Development Study (NCDS). The paper concludes that a framework for studying pathways to pregnancy and childhood outcomes needs to take account of the complexity of the relation between genetic and social factors and be able to account for the effects of multiple risk factors acting cumulatively across time and across generations. Illustrations of these approaches are given using NCDS data. PMID:12193422

Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems.

PubMed

Lê Cao, Kim-Anh; Boitard, Simon; Besse, Philippe

2011-06-22

Variable selection on high throughput biological data, such as gene expression or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant information and, therefore, to better characterize diseases or assess genetic structure. There are different ways to perform variable selection in large data sets. Statistical tests are commonly used to identify differentially expressed features for explanatory purposes, whereas Machine Learning wrapper approaches can be used for predictive purposes. In the case of multiple highly correlated variables, another option is to use multivariate exploratory approaches to give more insight into cell biology, biological pathways or complex traits. A simple extension of a sparse PLS exploratory approach is proposed to perform variable selection in a multiclass classification framework. sPLS-DA has a classification performance similar to other wrapper or sparse discriminant analysis approaches on public microarray and SNP data sets. More importantly, sPLS-DA is clearly competitive in terms of computational efficiency and superior in terms of interpretability of the results via valuable graphical outputs. sPLS-DA is available in the R package mixOmics, which is dedicated to the analysis of large biological data sets.

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

[Advance in flavonoids biosynthetic pathway and synthetic biology].

PubMed

Zou, Li-Qiu; Wang, Cai-Xia; Kuang, Xue-Jun; Li, Ying; Sun, Chao

2016-11-01

Flavonoids are the valuable components in medicinal plants, which possess a variety of pharmacological activities, including anti-tumor, antioxidant and anti-inflammatory activities. There is an unambiguous understanding about flavonoids biosynthetic pathway, that is,2S-flavanones including naringenin and pinocembrin are the skeleton of other flavonoids and they can transform to other flavonoids through branched metabolic pathway. Elucidation of the flavonoids biosynthetic pathway lays a solid foundation for their synthetic biology. A few flavonoids have been produced in Escherichia coli or yeast with synthetic biological technologies, such as naringenin, pinocembrin and fisetin. Synthetic biology will provide a new way to get valuable flavonoids and promote the research and development of flavonoid drugs and health products, making flavonoids play more important roles in human diet and health. Copyright© by the Chinese Pharmaceutical Association.

Extracellular vesicle communication pathways as regulatory targets of oncogenic transformation.

PubMed

Choi, Dongsic; Lee, Tae Hoon; Spinelli, Cristiana; Chennakrishnaiah, Shilpa; D'Asti, Esterina; Rak, Janusz

2017-07-01

Pathogenesis of human cancers bridges intracellular oncogenic driver events and their impact on intercellular communication. Among multiple mediators of this 'pathological connectivity' the role of extracellular vesicles (EVs) and their subsets (exosomes, ectosomes, oncosomes) is of particular interest for several reasons. The release of EVs from cancer cells represents a unique mechanism of regulated expulsion of bioactive molecules, a process that also mediates cell-to-cell transfer of lipids, proteins, and nucleic acids. Biological effects of these processes have been implicated in several aspects of cancer-related pathology, including tumour growth, invasion, angiogenesis, metastasis, immunity and thrombosis. Notably, the emerging evidence suggests that oncogenic mutations may impact several aspects of EV-mediated cell-cell communication including: (i) EV release rate and protein content; (ii) molecular composition of cancer EVs; (iii) the inclusion of oncogenic and mutant macromolecules in the EV cargo; (iv) EV-mediated release of genomic DNA; (v) deregulation of mechanisms responsible for EV biogenesis (vesiculome) and (vi) mechanisms of EV uptake by cancer cells. Intriguingly, EV-mediated intercellular transfer of mutant and oncogenic molecules between subpopulations of cancer cells, their indolent counterparts and stroma may exert profound biological effects that often resemble (but are not tantamount to) oncogenic transformation, including changes in cell growth, clonogenicity and angiogenic phenotype, or cause cell stress and death. However, several biological barriers likely curtail a permanent horizontal transformation of normal cells through EV-mediated mechanisms. The ongoing analysis and targeting of EV-mediated intercellular communication pathways can be viewed as a new therapeutic paradigm in cancer, while the analysis of oncogenic cargo contained in EVs released from cancer cells into biofluids is being developed for clinical use as a biomarker and companion diagnostics. Indeed, studies are underway to further explore the multiple links between molecular causality in cancer and various aspects of cellular vesiculation. Copyright © 2017 Elsevier Ltd. All rights reserved.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525

Molecular and Genomic Alterations in Glioblastoma Multiforme.

PubMed

Crespo, Ines; Vital, Ana Louisa; Gonzalez-Tablas, María; Patino, María del Carmen; Otero, Alvaro; Lopes, María Celeste; de Oliveira, Catarina; Domingues, Patricia; Orfao, Alberto; Tabernero, Maria Dolores

2015-07-01

In recent years, important advances have been achieved in the understanding of the molecular biology of glioblastoma multiforme (GBM); thus, complex genetic alterations and genomic profiles, which recurrently involve multiple signaling pathways, have been defined, leading to the first molecular/genetic classification of the disease. In this regard, different genetic alterations and genetic pathways appear to distinguish primary (eg, EGFR amplification) versus secondary (eg, IDH1/2 or TP53 mutation) GBM. Such genetic alterations target distinct combinations of the growth factor receptor-ras signaling pathways, as well as the phosphatidylinositol 3-kinase/phosphatase and tensin homolog/AKT, retinoblastoma/cyclin-dependent kinase (CDK) N2A-p16(INK4A), and TP53/mouse double minute (MDM) 2/MDM4/CDKN2A-p14(ARF) pathways, in cells that present features associated with key stages of normal neurogenesis and (normal) central nervous system cell types. This translates into well-defined genomic profiles that have been recently classified by The Cancer Genome Atlas Consortium into four subtypes: classic, mesenchymal, proneural, and neural GBM. Herein, we review the most relevant genetic alterations of primary versus secondary GBM, the specific signaling pathways involved, and the overall genomic profile of this genetically heterogeneous group of malignant tumors. Copyright © 2015 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Detection of Pathways Affected by Positive Selection in Primate Lineages Ancestral to Humans

PubMed Central

Moretti, S.; Davydov, I.I.; Excoffier, L.

2017-01-01

Abstract Gene set enrichment approaches have been increasingly successful in finding signals of recent polygenic selection in the human genome. In this study, we aim at detecting biological pathways affected by positive selection in more ancient human evolutionary history. Focusing on four branches of the primate tree that lead to modern humans, we tested all available protein coding gene trees of the Primates clade for signals of adaptation in these branches, using the likelihood-based branch site test of positive selection. The results of these locus-specific tests were then used as input for a gene set enrichment test, where whole pathways are globally scored for a signal of positive selection, instead of focusing only on outlier “significant” genes. We identified signals of positive selection in several pathways that are mainly involved in immune response, sensory perception, metabolism, and energy production. These pathway-level results are highly significant, even though there is no functional enrichment when only focusing on top scoring genes. Interestingly, several gene sets are found significant at multiple levels in the phylogeny, but different genes are responsible for the selection signal in the different branches. This suggests that the same function has been optimized in different ways at different times in primate evolution. PMID:28333345

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Genome Engineering and Modification Toward Synthetic Biology for the Production of Antibiotics.

PubMed

Zou, Xuan; Wang, Lianrong; Li, Zhiqiang; Luo, Jie; Wang, Yunfu; Deng, Zixin; Du, Shiming; Chen, Shi

2018-01-01

Antibiotic production is often governed by large gene clusters composed of genes related to antibiotic scaffold synthesis, tailoring, regulation, and resistance. With the expansion of genome sequencing, a considerable number of antibiotic gene clusters has been isolated and characterized. The emerging genome engineering techniques make it possible towards more efficient engineering of antibiotics. In addition to genomic editing, multiple synthetic biology approaches have been developed for the exploration and improvement of antibiotic natural products. Here, we review the progress in the development of these genome editing techniques used to engineer new antibiotics, focusing on three aspects of genome engineering: direct cloning of large genomic fragments, genome engineering of gene clusters, and regulation of gene cluster expression. This review will not only summarize the current uses of genomic engineering techniques for cloning and assembly of antibiotic gene clusters or for altering antibiotic synthetic pathways but will also provide perspectives on the future directions of rebuilding biological systems for the design of novel antibiotics. © 2017 Wiley Periodicals, Inc.

Decoding the Heart through Next Generation Sequencing Approaches.

PubMed

Pawlak, Michal; Niescierowicz, Katarzyna; Winata, Cecilia Lanny

2018-06-07

: Vertebrate organs develop through a complex process which involves interaction between multiple signaling pathways at the molecular, cell, and tissue levels. Heart development is an example of such complex process which, when disrupted, results in congenital heart disease (CHD). This complexity necessitates a holistic approach which allows the visualization of genome-wide interaction networks, as opposed to assessment of limited subsets of factors. Genomics offers a powerful solution to address the problem of biological complexity by enabling the observation of molecular processes at a genome-wide scale. The emergence of next generation sequencing (NGS) technology has facilitated the expansion of genomics, increasing its output capacity and applicability in various biological disciplines. The application of NGS in various aspects of heart biology has resulted in new discoveries, generating novel insights into this field of study. Here we review the contributions of NGS technology into the understanding of heart development and its disruption reflected in CHD and discuss how emerging NGS based methodologies can contribute to the further understanding of heart repair.

Introducing memory and association mechanism into a biologically inspired visual model.

PubMed

Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

2014-09-01

A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

Ultraviolet germicidal irradiation and its effects on elemental distributions in mouse embryonic fibroblast cells in x-ray fluorescence microanalysis

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

Jin, Qiaoling; Vogt, Stefan; Lai, Barry

Rapidly-frozen hydrated (cryopreserved) specimens combined with cryo-scanning x-ray fluorescence microscopy provide an ideal approach for investigating elemental distributions in biological cells and tissues. However, because cryopreservation does not deactivate potentially infectious agents associated with Risk Group 2 biological materials, one must be concerned with contamination of expensive and complicated cryogenic x-ray microscopes when working with such materials. We employed ultraviolet germicidal irradiation to decontaminate previously cryopreserved cells under liquid nitrogen, and then investigated its effects on elemental distributions under both frozen hydrated and freeze dried states with x-ray fluorescence microscopy. We show that the contents and distributions of most biologicallymore » important elements remain nearly unchanged when compared with non-ultraviolet-irradiated counterparts, even after multiple cycles of ultraviolet germicidal irradiation and cryogenic x-ray imaging. This provides a potential pathway for rendering Risk Group 2 biological materials safe for handling in multiuser cryogenic x-ray microscopes without affecting the fidelity of the results.« less

The Effect of Hypoxia on Mesenchymal Stem Cell Biology

PubMed Central

Ejtehadifar, Mostafa; Shamsasenjan, Karim; Movassaghpour, Aliakbar; Akbarzadehlaleh, Parvin; Dehdilani, Nima; Abbasi, Parvaneh; Molaeipour, Zahra; Saleh, Mahshid

2015-01-01

Although physiological and pathological role of hypoxia have been appreciated in mammalians for decades however the cellular biology of hypoxia more clarified in the past 20 years. Discovery of the transcription factor hypoxia-inducible factor (HIF)-1, in the 1990s opened a new window to investigate the mechanisms behind hypoxia. In different cellular contexts HIF-1 activation show variable results by impacting various aspects of cell biology such as cell cycle, apoptosis, differentiation and etc. Mesenchymal stem cells (MSC) are unique cells which take important role in tissue regeneration. They are characterized by self-renewal capacity, multilineage potential, and immunosuppressive property. Like so many kind of cells, hypoxia induces different responses in MSCs by HIF- 1 activation. The activation of this molecule changes the growth, multiplication, differentiation and gene expression profile of MSCs in their niche by a complex of signals. This article briefly discusses the most important effects of hypoxia in growth kinetics, signalling pathways, cytokine secretion profile and expression of chemokine receptors in different conditions. PMID:26236651

Ultraviolet germicidal irradiation and its effects on elemental distributions in mouse embryonic fibroblast cells in x-ray fluorescence microanalysis

DOE PAGES

Jin, Qiaoling; Vogt, Stefan; Lai, Barry; ...

2015-02-23

Rapidly-frozen hydrated (cryopreserved) specimens combined with cryo-scanning x-ray fluorescence microscopy provide an ideal approach for investigating elemental distributions in biological cells and tissues. However, because cryopreservation does not deactivate potentially infectious agents associated with Risk Group 2 biological materials, one must be concerned with contamination of expensive and complicated cryogenic x-ray microscopes when working with such materials. We employed ultraviolet germicidal irradiation to decontaminate previously cryopreserved cells under liquid nitrogen, and then investigated its effects on elemental distributions under both frozen hydrated and freeze dried states with x-ray fluorescence microscopy. We show that the contents and distributions of most biologicallymore » important elements remain nearly unchanged when compared with non-ultraviolet-irradiated counterparts, even after multiple cycles of ultraviolet germicidal irradiation and cryogenic x-ray imaging. This provides a potential pathway for rendering Risk Group 2 biological materials safe for handling in multiuser cryogenic x-ray microscopes without affecting the fidelity of the results.« less

Moonlighting proteins in cancer.

PubMed

Min, Kyung-Won; Lee, Seong-Ho; Baek, Seung Joon

2016-01-01

Since the 1980s, growing evidence suggested that the cellular localization of proteins determined their activity and biological functions. In a classical view, a protein is characterized by the single cellular compartment where it primarily resides and functions. It is now believed that when proteins appear in different subcellular locations, the cells surpass the expected activity of proteins given the same genomic information to fulfill complex biological behavior. Many proteins are recognized for having the potential to exist in multiple locations in cells. Dysregulation of translocation may cause cancer or contribute to poorer cancer prognosis. Thus, quantitative and comprehensive assessment of dynamic proteins and associated protein movements could be a promising indicator in determining cancer prognosis and efficiency of cancer treatment and therapy. This review will summarize these so-called moonlighting proteins, in terms of a coupled intracellular cancer signaling pathway. Determination of the detailed biological intracellular and extracellular transit and regulatory activity of moonlighting proteins permits a better understanding of cancer and identification of potential means of molecular intervention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Intersections of lung progenitor cells, lung disease and lung cancer.

PubMed

Kim, Carla F

2017-06-30

The use of stem cell biology approaches to study adult lung progenitor cells and lung cancer has brought a variety of new techniques to the field of lung biology and has elucidated new pathways that may be therapeutic targets in lung cancer. Recent results have begun to identify the ways in which different cell populations interact to regulate progenitor activity, and this has implications for the interventions that are possible in cancer and in a variety of lung diseases. Today's better understanding of the mechanisms that regulate lung progenitor cell self-renewal and differentiation, including understanding how multiple epigenetic factors affect lung injury repair, holds the promise for future better treatments for lung cancer and for optimising the response to therapy in lung cancer. Working between platforms in sophisticated organoid culture techniques, genetically engineered mouse models of injury and cancer, and human cell lines and specimens, lung progenitor cell studies can begin with basic biology, progress to translational research and finally lead to the beginnings of clinical trials. Copyright ©ERS 2017.

COX-2 in cancer: Gordian knot or Achilles heel?

PubMed Central

Stasinopoulos, Ioannis; Shah, Tariq; Penet, Marie-France; Krishnamachary, Balaji; Bhujwalla, Zaver M.

2013-01-01

The networks of blood and lymphatic vessels and of the extracellular matrix and their cellular and structural components, that are collectively termed the tumor microenvironment, are frequently co-opted and shaped by cancer cells to survive, invade, and form distant metastasis. With an enviable capacity to adapt to continually changing environments, cancer represents the epitome of functional chaos, a stark contrast to the hierarchical and organized differentiation processes that dictate the development and life of biological organisms. The consequences of changing landscapes such as hypoxia and acidic extracellular pH in and around tumors create a cascade of changes in multiple pathways and networks that become apparent only several years later as recurrence and metastasis. These molecular and phenotypic changes, several of which are mediated by COX-2, approach the complexities of a “Gordian Knot.” We review evidence from our studies and from literature suggesting that cyclooxygenase-2 (COX-2) biology presents a nodal point in cancer biology and an “Achilles heel” of COX-2-dependent tumors. PMID:23579438

Lysophosphatidic acid as a lipid mediator with multiple biological actions.

PubMed

Aikawa, Shizu; Hashimoto, Takafumi; Kano, Kuniyuki; Aoki, Junken

2015-02-01

Lysophosphatidic acid (LPA) is one of the simplest glycerophospholipids with one fatty acid chain and a phosphate group as a polar head. Although LPA had been viewed just as a metabolic intermediate in de novo lipid synthetic pathways, it has recently been paid much attention as a lipid mediator. LPA exerts many kinds of cellular processes, such as cell proliferation and smooth muscle contraction, through cognate G protein-coupled receptors. Because lipids are not coded by the genome directly, it is difficult to know their patho- and physiological roles. However, recent studies have identified several key factors mediating the biological roles of LPA, such as receptors and producing enzymes. In addition, studies of transgenic and gene knockout animals for these LPA-related genes, have revealed the biological significance of LPA. In this review we will summarize recent advances in the studies of LPA production and its roles in both physiological and pathological conditions. © The Authors 2014. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

Recent Advances in CRISPR-Cas9 Genome Editing Technology for Biological and Biomedical Investigations.

PubMed

Singh, Vijai; Gohil, Nisarg; Ramírez García, Robert; Braddick, Darren; Fofié, Christian Kuete

2018-01-01

The Type II CRISPR-Cas9 system is a simple, efficient, and versatile tool for targeted genome editing in a wide range of organisms and cell types. It continues to gain more scientific interest and has established itself as an extremely powerful technology within our synthetic biology toolkit. It works upon a targeted site and generates a double strand breaks that become repaired by either the NHEJ or the HDR pathway, modifying or permanently replacing the genomic target sequences of interest. These can include viral targets, single-mutation genetic diseases, and multiple-site corrections for wide scale disease states, offering the potential to manage and cure some of mankind's most persistent biomedical menaces. Here, we present the developing progress and future potential of CRISPR-Cas9 in biological and biomedical investigations, toward numerous therapeutic, biomedical, and biotechnological applications, as well as some of the challenges within. J. Cell. Biochem. 119: 81-94, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Biological technologies for the remediation of co-contaminated soil.

PubMed

Ye, Shujing; Zeng, Guangming; Wu, Haipeng; Zhang, Chang; Dai, Juan; Liang, Jie; Yu, Jiangfang; Ren, Xiaoya; Yi, Huan; Cheng, Min; Zhang, Chen

2017-12-01

Compound contamination in soil, caused by unreasonable waste disposal, has attracted increasing attention on a global scale, particularly since multiple heavy metals and/or organic pollutants are entering natural ecosystem through human activities, causing an enormous threat. The remediation of co-contaminated soil is more complicated and difficult than that of single contamination, due to the disparate remediation pathways utilized for different types of pollutants. Several modern remediation technologies have been developed for the treatment of co-contaminated soil. Biological remediation technologies, as the eco-friendly methods, have received widespread concern due to soil improvement besides remediation. This review summarizes the application of biological technologies, which contains microbial technologies (function microbial remediation and composting or compost addition), biochar, phytoremediation technologies, genetic engineering technologies and biochemical technologies, for the remediation of co-contaminated soil with heavy metals and organic pollutants. Mechanisms of these technologies and their remediation efficiencies are also reviewed. Based on this study, this review also identifies the future research required in this field.

Data-Driven Discovery of Extravasation Pathway in Circulating Tumor Cells

PubMed Central

Yadavalli, S.; Jayaram, S.; Manda, S. S.; Madugundu, A. K.; Nayakanti, D. S.; Tan, T. Z.; Bhat, R.; Rangarajan, A.; Chatterjee, A.; Gowda, H.; Thiery, J. P.; Kumar, P.

2017-01-01

Circulating tumor cells (CTCs) play a crucial role in cancer dissemination and provide a promising source of blood-based markers. Understanding the spectrum of transcriptional profiles of CTCs and their corresponding regulatory mechanisms will allow for a more robust analysis of CTC phenotypes. The current challenge in CTC research is the acquisition of useful clinical information from the multitude of high-throughput studies. To gain a deeper understanding of CTC heterogeneity and identify genes, pathways and processes that are consistently affected across tumors, we mined the literature for gene expression profiles in CTCs. Through in silico analysis and the integration of CTC-specific genes, we found highly significant biological mechanisms and regulatory processes acting in CTCs across various cancers, with a particular enrichment of the leukocyte extravasation pathway. This pathway appears to play a pivotal role in the migration of CTCs to distant metastatic sites. We find that CTCs from multiple cancers express both epithelial and mesenchymal markers in varying amounts, which is suggestive of dynamic and hybrid states along the epithelial-mesenchymal transition (EMT) spectrum. Targeting the specific molecular nodes to monitor disease and therapeutic control of CTCs in real time will likely improve the clinical management of cancer progression and metastases. PMID:28262832

The role of nutraceuticals in the regulation of Wnt and Hedgehog signaling in cancer

PubMed Central

Li, Yiwei; Wang, Zhiwei; Kong, Dejuan

2010-01-01

Multiple cellular signaling pathways have been involved in the processes of cancer cell invasion and metastasis. Among many signaling pathways, Wnt and Hedgehog (Hh) signaling pathways are critically involved in embryonic development, in the biology of cancer stem cells (CSCs) and in the acquisition of epithelial to mesenchymal transition (EMT), and thus this article will remain focused on Wnt and Hh signaling. Since CSCs and EMT are also known to be responsible for cancer cell invasion and metastasis, the Wnt and Hedgehog signaling pathways are also intimately associated with cancer invasion and metastasis. Emerging evidence suggests the beneficial role of chemopreventive agents commonly known as nutraceutical in cancer. Among many such agents, soy isoflavones, curcumin, green tea polyphenols, 3,3′-diindolylmethane, resveratrol, lycopene, vitamin D, etc. have been found to prevent, reverse, or delay the carcinogenic process. Interestingly, these agents have also shown to prevent or delay the progression of cancer, which could in part be due to their ability to attack CSCs or EMT-type cells by attenuating the Wnt and Hedgehog signaling pathways. In this review, we summarize the current state of our knowledge on the role of Wnt and Hedgehog signaling pathways, and their targeted inactivation by chemopreventive agents (nutraceuticals) for the prevention of tumor progression and/or treatment of human malignancies. PMID:20711635

Natural health products that inhibit angiogenesis: a potential source for investigational new agents to treat cancer—Part 1

PubMed Central

Sagar, S.M.; Yance, D.; Wong, R.K.

2006-01-01

An integrative approach for managing a patient with cancer should target the multiple biochemical and physiologic pathways that support tumour development and minimize normal-tissue toxicity. Angiogenesis is a key process in the promotion of cancer. Many natural health products that inhibit angiogenesis also manifest other anticancer activities. The present article focuses on products that have a high degree of anti-angiogenic activity, but it also describes some of the many other actions of these agents that can inhibit tumour progression and reduce the risk of metastasis. Natural health products target molecular pathways other than angiogenesis, including epidermal growth factor receptor, the HER2/neu gene, the cyclooxygenase-2 enzyme, the nuclear factor kappa-B transcription factor, the protein kinases, the Bcl-2 protein, and coagulation pathways. The herbs that are traditionally used for anticancer treatment and that are anti-angiogenic through multiple interdependent processes (including effects on gene expression, signal processing, and enzyme activities) include Artemisia annua (Chinese wormwood), Viscum album (European mistletoe), Curcuma longa (curcumin), Scutellaria baicalensis (Chinese skullcap), resveratrol and proanthocyanidin (grape seed extract), Magnolia officinalis (Chinese magnolia tree), Camellia sinensis (green tea), Ginkgo biloba, quercetin, Poria cocos, Zingiber officinalis (ginger), Panax ginseng, Rabdosia rubescens hora (Rabdosia), and Chinese destagnation herbs. Quality assurance of appropriate extracts is essential prior to embarking upon clinical trials. More data are required on dose–response, appropriate combinations, and potential toxicities. Given the multiple effects of these agents, their future use for cancer therapy probably lies in synergistic combinations. During active cancer therapy, they should generally be evaluated in combination with chemotherapy and radiation. In this role, they act as modifiers of biologic response or as adaptogens, potentially enhancing the efficacy of the conventional therapies. PMID:17576437

SLEPR: A Sample-Level Enrichment-Based Pathway Ranking Method — Seeking Biological Themes through Pathway-Level Consistency

PubMed Central

Yi, Ming; Stephens, Robert M.

2008-01-01

Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data. PMID:18818771

Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology.

PubMed

Krafty, Robert T; Rosen, Ori; Stoffer, David S; Buysse, Daniel J; Hall, Martica H

2017-01-01

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach exibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed.

Caenorhabditis elegans, a Biological Model for Research in Toxicology.

PubMed

Tejeda-Benitez, Lesly; Olivero-Verbel, Jesus

2016-01-01

Caenorhabditis elegans is a nematode of microscopic size which, due to its biological characteristics, has been used since the 1970s as a model for research in molecular biology, medicine, pharmacology, and toxicology. It was the first animal whose genome was completely sequenced and has played a key role in the understanding of apoptosis and RNA interference. The transparency of its body, short lifespan, ability to self-fertilize and ease of culture are advantages that make it ideal as a model in toxicology. Due to the fact that some of its biochemical pathways are similar to those of humans, it has been employed in research in several fields. C. elegans' use as a biological model in environmental toxicological assessments allows the determination of multiple endpoints. Some of these utilize the effects on the biological functions of the nematode and others use molecular markers. Endpoints such as lethality, growth, reproduction, and locomotion are the most studied, and usually employ the wild type Bristol N2 strain. Other endpoints use reporter genes, such as green fluorescence protein, driven by regulatory sequences from other genes related to different mechanisms of toxicity, such as heat shock, oxidative stress, CYP system, and metallothioneins among others, allowing the study of gene expression in a manner both rapid and easy. These transgenic strains of C. elegans represent a powerful tool to assess toxicity pathways for mixtures and environmental samples, and their numbers are growing in diversity and selectivity. However, other molecular biology techniques, including DNA microarrays and MicroRNAs have been explored to assess the effects of different toxicants and samples. C. elegans has allowed the assessment of neurotoxic effects for heavy metals and pesticides, among those more frequently studied, as the nematode has a very well defined nervous system. More recently, nanoparticles are emergent pollutants whose toxicity can be explored using this nematode. Overall, almost every type of known toxicant has been tested with this animal model. In the near future, the available knowledge on the life cycle of C. elegans should allow more studies on reproduction and transgenerational toxicity for newly developed chemicals and materials, facilitating their introduction in the market. The great diversity of endpoints and possibilities of this animal makes it an easy first-choice for rapid toxicity screening or to detail signaling pathways involved in mechanisms of toxicity.

Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.

PubMed

Wang, W; Huang, S; Hou, W; Liu, Y; Fan, Q; He, A; Wen, Y; Hao, J; Guo, X; Zhang, F

2017-10-01

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data METHOD: We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients' BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10 -4 for LS and 2.7 × 10 -2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10 -4 for femoral necks and 2.6 × 10 -2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article : W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572-576. © 2017 Wang et al.

Photoisomerization and photoionization of the photoactive yellow protein chromophore in solution.

PubMed

Larsen, Delmar S; Vengris, Mikas; van Stokkum, Ivo H M; van der Horst, Michael A; de Weerd, Frank L; Hellingwerf, Klaas J; van Grondelle, Rienk

2004-04-01

Dispersed pump-dump-probe spectroscopy has the ability to characterize and identify the underlying ultrafast dynamical processes in complicated chemical and biological systems. This technique builds on traditional pump-probe techniques by exploring both ground- and excited-state dynamics and characterizing the connectivity between constituent transient states. We have used the dispersed pump-dump-probe technique to investigate the ground-state dynamics and competing excited-state processes in the excitation-induced ultrafast dynamics of thiomethyl p-coumaric acid, a model chromophore for the photoreceptor photoactive yellow protein. Our results demonstrate the parallel formation of two relaxation pathways (with multiple transient states) that jointly lead to two different types of photochemistry: cis-trans isomerization and detachment of a hydrated electron. The relative transition rates and quantum yields of both pathways have been determined. We find that the relaxation of the photoexcited chromophores involves multiple, transient ground-state intermediates and the chromophore in solution does not generate persistent photoisomerized products, but instead undergoes photoionization resulting in the generation of detached electrons and radicals. These results are of great value in interpreting the more complex dynamical changes in the optical properties of the photoactive yellow protein.

Photoisomerization and Photoionization of the Photoactive Yellow Protein Chromophore in Solution

PubMed Central

Larsen, Delmar S.; Vengris, Mikas; van Stokkum, Ivo H. M.; van der Horst, Michael A.; de Weerd, Frank L.; Hellingwerf, Klaas J.; van Grondelle, Rienk

2004-01-01

Dispersed pump-dump-probe spectroscopy has the ability to characterize and identify the underlying ultrafast dynamical processes in complicated chemical and biological systems. This technique builds on traditional pump-probe techniques by exploring both ground- and excited-state dynamics and characterizing the connectivity between constituent transient states. We have used the dispersed pump-dump-probe technique to investigate the ground-state dynamics and competing excited-state processes in the excitation-induced ultrafast dynamics of thiomethyl p-coumaric acid, a model chromophore for the photoreceptor photoactive yellow protein. Our results demonstrate the parallel formation of two relaxation pathways (with multiple transient states) that jointly lead to two different types of photochemistry: cis-trans isomerization and detachment of a hydrated electron. The relative transition rates and quantum yields of both pathways have been determined. We find that the relaxation of the photoexcited chromophores involves multiple, transient ground-state intermediates and the chromophore in solution does not generate persistent photoisomerized products, but instead undergoes photoionization resulting in the generation of detached electrons and radicals. These results are of great value in interpreting the more complex dynamical changes in the optical properties of the photoactive yellow protein. PMID:15041690

Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications

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

Torella, JP; Lienert, F; Boehm, CR

2014-08-07

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts, and they hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies-for example, repeated terminator and insulator sequences-that complicate recombination-based assembly. We and others have recently developed DNA assembly methods, which we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked withmore » UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly assembled constructs, or into high-quality combinatorial libraries in only 2-3 d. If the DNA parts must be generated from scratch, an additional 2-5 d are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques.« less

Unique nucleotide sequence (UNS)-guided assembly of repetitive DNA parts for synthetic biology applications

PubMed Central

Torella, Joseph P.; Lienert, Florian; Boehm, Christian R.; Chen, Jan-Hung; Way, Jeffrey C.; Silver, Pamela A.

2016-01-01

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts and hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies — for example repeated terminator and insulator sequences — that complicate recombination-based assembly. We and others have recently developed DNA assembly methods that we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked with UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly-assembled constructs, or into high-quality combinatorial libraries in only 2–3 days. If the DNA parts must be generated from scratch, an additional 2–5 days are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques. PMID:25101822

Pathway Distiller - multisource biological pathway consolidation

PubMed Central

2012-01-01

Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636

Pathway Distiller - multisource biological pathway consolidation.

PubMed

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

Beyond Tracking: Multiple Pathways to College, Career, and Civic Participation

ERIC Educational Resources Information Center

Oakes, Jeannie, Ed.; Saunders, Marisa, Ed.

2008-01-01

"Beyond Tracking" responds to the a sobering assessment of American high schools by delineating and promoting an innovative and well-defined notion of multiple pathways. The book's authors clearly distinguish their use of the term "multiple pathways" from any updated version of the tracking system that marked so many American high schools during…

Chronic Inflammation: Accelerator of Biological Aging.

PubMed

Fougère, Bertrand; Boulanger, Eric; Nourhashémi, Fati; Guyonnet, Sophie; Cesari, Matteo

2017-09-01

Biological aging is characterized by a chronic low-grade inflammation level. This chronic phenomenon has been named "inflamm-aging" and is a highly significant risk factor for morbidity and mortality in the older persons. The most common theories of inflamm-aging include redox stress, mitochondrial dysfunction, glycation, deregulation of the immune system, hormonal changes, epigenetic modifications, and dysfunction telomere attrition. Inflamm-aging plays a role in the initiation and progression of age-related diseases such as type II diabetes, Alzheimer's disease, cardiovascular disease, frailty, sarcopenia, osteoporosis, and cancer. This review will cover the identification of pathways that control age-related inflammation across multiple systems and its potential causal role in contributing to adverse health outcomes. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

PubMed

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

PubMed

Li, Chaoxing; Liu, Li; Dinu, Valentin

2018-01-01

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

Multiple oxygen entry pathways in globin proteins revealed by intrinsic pathway identification method

NASA Astrophysics Data System (ADS)

Takayanagi, Masayoshi; Kurisaki, Ikuo; Nagaoka, Masataka

2015-12-01

Each subunit of human hemoglobin (HbA) stores an oxygen molecule (O2) in the binding site (BS) cavity near the heme group. The BS is buried in the interior of the subunit so that there is a debate over the O2 entry pathways from solvent to the BS; histidine gate or multiple pathways. To elucidate the O2 entry pathways, we executed ensemble molecular dynamics (MD) simulations of T-state tetramer HbA in high concentration O2 solvent to simulate spontaneous O2 entry from solvent into the BS. By analyzing 128 independent 8 ns MD trajectories by intrinsic pathway identification by clustering (IPIC) method, we found 141 and 425 O2 entry events into the BS of the α and β subunits, respectively. In both subunits, we found that multiple O2 entry pathways through inside cavities play a significant role for O2 entry process of HbA. The rate constants of O2 entry estimated from the MD trajectories correspond to the experimentally observed values. In addition, by analyzing monomer myoglobin, we verified that the high O2 concentration condition can reproduce the ratios of each multiple pathway in the one-tenth lower O2 concentration condition. These indicate the validity of the multiple pathways obtained in our MD simulations.