Application of Adverse Outcome Pathways (AOPs) in Human Health and Ecotoxicology Capturing Divergent Consequences of Conserved Molecular Initiating Events via AOP Networks (Presentation)

EPA Science Inventory

The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making...

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.

Hidden treasures in "ancient" microarrays: gene-expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue.

PubMed

Kerkentzes, Konstantinos; Lagani, Vincenzo; Tsamardinos, Ioannis; Vyberg, Mogens; Røe, Oluf Dimitri

2014-01-01

Novel statistical methods and increasingly more accurate gene annotations can transform "old" biological data into a renewed source of knowledge with potential clinical relevance. Here, we provide an in silico proof-of-concept by extracting novel information from a high-quality mRNA expression dataset, originally published in 2001, using state-of-the-art bioinformatics approaches. The dataset consists of histologically defined cases of lung adenocarcinoma (AD), squamous (SQ) cell carcinoma, small-cell lung cancer, carcinoid, metastasis (breast and colon AD), and normal lung specimens (203 samples in total). A battery of statistical tests was used for identifying differential gene expressions, diagnostic and prognostic genes, enriched gene ontologies, and signaling pathways. Our results showed that gene expressions faithfully recapitulate immunohistochemical subtype markers, as chromogranin A in carcinoids, cytokeratin 5, p63 in SQ, and TTF1 in non-squamous types. Moreover, biological information with putative clinical relevance was revealed as potentially novel diagnostic genes for each subtype with specificity 93-100% (AUC = 0.93-1.00). Cancer subtypes were characterized by (a) differential expression of treatment target genes as TYMS, HER2, and HER3 and (b) overrepresentation of treatment-related pathways like cell cycle, DNA repair, and ERBB pathways. The vascular smooth muscle contraction, leukocyte trans-endothelial migration, and actin cytoskeleton pathways were overexpressed in normal tissue. Reanalysis of this public dataset displayed the known biological features of lung cancer subtypes and revealed novel pathways of potentially clinical importance. The findings also support our hypothesis that even old omics data of high quality can be a source of significant biological information when appropriate bioinformatics methods are used.

Developing and applying adverse outcome pathways: What you need to know

EPA Science Inventory

Adverse outcome pathways (AOPs) are a conceptual framework for organizing existing information concerning the predictive linkages between the initiation or early progression of a biological perturbation in an organism and the adverse outcome(s) of regulatory relevance (e.g., impa...

A three-tiered approach for linking pharmacokinetic ...

EPA Pesticide Factsheets

The power of the adverse outcome pathway (AOP) framework arises from its utilization of pathway-based data to describe the initial interaction of a chemical with a molecular target (molecular initiating event; (MIE), followed by a progression through a series of key events that lead to an adverse outcome relevant for regulatory purposes. The AOP itself is not chemical specific, thus providing the biological context necessary for interpreting high throughput (HT) toxicity screening results. Application of the AOP framework and HT predictions in ecological and human health risk assessment, however, requires the consideration of chemical-specific properties that influence external exposure doses and target tissue doses. To address this requirement, a three-tiered approach was developed to provide a workflow for connecting biology-based AOPs to biochemical-based pharmacokinetic properties (absorption, distribution, metabolism, excretion; ADME), and then to chemical/human activity-based exposure pathways. This approach included: (1) The power of the adverse outcome pathway (AOP) framework arisesfrom its utilization of pathway-based data to describe the initial interaction of a chemical with a molecular target (molecular initiating event; (MIE), followed by a progression through a series of key events that lead to an adverse outcome relevant for regulatory purposes. The AOP itself is not chemical specific, thus providing the biological context necessary for interpreti

Biological interpretation of genome-wide association studies using predicted gene functions.

PubMed

Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

2015-01-19

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

Real-Time Growth Kinetics Measuring Hormone Mimicry for ToxCast Chemicals in T‑47D Human Ductal Carcinoma Cells

EPA Science Inventory

High-throughput screening (HTS) assays capable of profiling thousands of environmentally relevant chemicals for in vitro biological activity provide useful information on the potential for disrupting endocrine pathways. Disruption of the estrogen signaling pathway has been implic...

Use of Adverse Outcome Pathways for Assessing Effects of the Fungicide Propiconazole on Fish Reproduction

EPA Science Inventory

Adverse outcome pathways (AOP) are used to describe the linkage of biological events from a molecular initiating point, to individual-level-endpoints relevant to risk assessment. This study was done to assess toxicity outcomes for the conazole fungicide propiconazole based on a p...

GPER (GPR30): A Nongenomic Receptor (GPCR) for Steroid Hormones with Implications for Cardiovascular Disease and Cancer.

PubMed

Feldman, Ross D; Limbird, Lee E

2017-01-06

Although the rapid effects of steroids, such as estrogen and aldosterone, were postulated originally to be nongenomic, it is now appreciated that activation of such signaling pathways via a steroid-acting G protein-coupled receptor, the G protein estrogen receptor (GPER), has important transcription-dependent outcomes in the regulation of cell growth and programmed cell death secondary to GPER-regulated second-messenger pathways. GPER is expressed ubiquitously and has diverse biological effects, including regulation of endocrine, immune, neuronal, and cardiovascular functions. Perhaps the most biologically important consequences of GPER activation are the regulation of cell growth, migration, and apoptotic cell death. These cell growth regulatory effects, important in cancer biology, are also relevant in the regulation of cardiac and vascular hypertrophy and in the response to ischemia. This review provides a summary of relevant findings of the impact of GPER regulation by either estradiol or aldosterone in in vitro model systems and extends those findings to in vivo studies of direct clinical relevance for development of GPER-directed agents for treatment of cancer and cardiovascular diseases associated with cellular proliferation.

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

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

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.

Biological interpretation of genome-wide association studies using predicted gene functions

PubMed Central

Pers, Tune H.; Karjalainen, Juha M.; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R.; Yang, Jian; Lui, Julian C.; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K.; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S.N.; Hirschhorn, Joel N.; Franke, Lude

2015-01-01

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. PMID:25597830

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

Informatics approaches in the Biological Characterization of ...

EPA Pesticide Factsheets

Adverse Outcome Pathways (AOPs) are a conceptual framework to characterize toxicity pathways by a series of mechanistic steps from a molecular initiating event to population outcomes. This framework helps to direct risk assessment research, for example by aiding in computational prioritization of chemicals, genes, and tissues relevant to an adverse health outcome. We have designed and implemented a computational workflow to access a wealth of public data relating genes, chemicals, diseases, pathways, and species, to provide a biological context for putative AOPs. We selected three AOP case studies: ER/Aromatase Antagonism Leading to Reproductive Dysfunction, AHR1 Activation Leading to Cardiotoxicity, and AChE Inhibition Leading to Acute Mortality, and deduced a taxonomic range of applicability for each AOP. We developed computational tools to automatically access and analyze the pathway activity of AOP-relevant protein orthologs, finding broad similarity among vertebrate species for the ER/Aromatase and AHR1 AOPs, and similarity extending to invertebrate animal species for AChE inhibition. Additionally, we used public gene expression data to find groups of highly co-expressed genes, and compared those groups across organisms. To interpret these findings at a higher level of biological organization, we created the AOPdb, a relational database that mines results from sources including NCBI, KEGG, Reactome, CTD, and OMIM. This multi-source database connects genes,

Applying Aggregate Exposure Pathway and Adverse Outcome ...

EPA Pesticide Factsheets

Hazard assessment for nanomaterials often involves applying in vitro dose-response data to estimate potential health risks that arise from exposure to products that contain nanomaterials. However, much uncertainty is inherent in relating bioactivities observed in an in vitro system to the perturbations of biological mechanisms that lead to apical adverse health outcomes in living organisms. The Adverse Outcome Pathway (AOP) framework addresses this uncertainty by acting as a scaffold onto which in vitro toxicity testing and other data can be arranged to aid in the interpretation of these results in terms of biologically-relevant responses, as an AOP connects an upstream molecular initiating event (MIE) to a downstream adverse outcome. In addition to hazard assessment, risk estimation also requires reconciling in vitro concentrations sufficient to produce bioactivity with in vivo concentrations that can trigger a MIE at the relevant biological target. Such target site exposures (TSEs) can be estimated by integrating pharmacokinetic considerations with environmental and exposure factors. Environmental and exposure data have been historically scattered in various resources, such as monitoring data for air pollutants or exposure models for specific chemicals. The Aggregate Exposure Pathway (AEP) framework is introduced to organize existing knowledge concerning biologically, chemically, and physically plausible, as well as empirically supported, links between the i

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

PubMed

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

PubMed

Pattaro, Cristian; Teumer, Alexander; Gorski, Mathias; Chu, Audrey Y; Li, Man; Mijatovic, Vladan; Garnaas, Maija; Tin, Adrienne; Sorice, Rossella; Li, Yong; Taliun, Daniel; Olden, Matthias; Foster, Meredith; Yang, Qiong; Chen, Ming-Huei; Pers, Tune H; Johnson, Andrew D; Ko, Yi-An; Fuchsberger, Christian; Tayo, Bamidele; Nalls, Michael; Feitosa, Mary F; Isaacs, Aaron; Dehghan, Abbas; d'Adamo, Pio; Adeyemo, Adebowale; Dieffenbach, Aida Karina; Zonderman, Alan B; Nolte, Ilja M; van der Most, Peter J; Wright, Alan F; Shuldiner, Alan R; Morrison, Alanna C; Hofman, Albert; Smith, Albert V; Dreisbach, Albert W; Franke, Andre; Uitterlinden, Andre G; Metspalu, Andres; Tonjes, Anke; Lupo, Antonio; Robino, Antonietta; Johansson, Åsa; Demirkan, Ayse; Kollerits, Barbara; Freedman, Barry I; Ponte, Belen; Oostra, Ben A; Paulweber, Bernhard; Krämer, Bernhard K; Mitchell, Braxton D; Buckley, Brendan M; Peralta, Carmen A; Hayward, Caroline; Helmer, Catherine; Rotimi, Charles N; Shaffer, Christian M; Müller, Christian; Sala, Cinzia; van Duijn, Cornelia M; Saint-Pierre, Aude; Ackermann, Daniel; Shriner, Daniel; Ruggiero, Daniela; Toniolo, Daniela; Lu, Yingchang; Cusi, Daniele; Czamara, Darina; Ellinghaus, David; Siscovick, David S; Ruderfer, Douglas; Gieger, Christian; Grallert, Harald; Rochtchina, Elena; Atkinson, Elizabeth J; Holliday, Elizabeth G; Boerwinkle, Eric; Salvi, Erika; Bottinger, Erwin P; Murgia, Federico; Rivadeneira, Fernando; Ernst, Florian; Kronenberg, Florian; Hu, Frank B; Navis, Gerjan J; Curhan, Gary C; Ehret, George B; Homuth, Georg; Coassin, Stefan; Thun, Gian-Andri; Pistis, Giorgio; Gambaro, Giovanni; Malerba, Giovanni; Montgomery, Grant W; Eiriksdottir, Gudny; Jacobs, Gunnar; Li, Guo; Wichmann, H-Erich; Campbell, Harry; Schmidt, Helena; Wallaschofski, Henri; Völzke, Henry; Brenner, Hermann; Kroemer, Heyo K; Kramer, Holly; Lin, Honghuang; Leach, I Mateo; Ford, Ian; Guessous, Idris; Rudan, Igor; Prokopenko, Inga; Borecki, Ingrid; Heid, Iris M; Kolcic, Ivana; Persico, Ivana; Jukema, J Wouter; Wilson, James F; Felix, Janine F; Divers, Jasmin; Lambert, Jean-Charles; Stafford, Jeanette M; Gaspoz, Jean-Michel; Smith, Jennifer A; Faul, Jessica D; Wang, Jie Jin; Ding, Jingzhong; Hirschhorn, Joel N; Attia, John; Whitfield, John B; Chalmers, John; Viikari, Jorma; Coresh, Josef; Denny, Joshua C; Karjalainen, Juha; Fernandes, Jyotika K; Endlich, Karlhans; Butterbach, Katja; Keene, Keith L; Lohman, Kurt; Portas, Laura; Launer, Lenore J; Lyytikäinen, Leo-Pekka; Yengo, Loic; Franke, Lude; Ferrucci, Luigi; Rose, Lynda M; Kedenko, Lyudmyla; Rao, Madhumathi; Struchalin, Maksim; Kleber, Marcus E; Cavalieri, Margherita; Haun, Margot; Cornelis, Marilyn C; Ciullo, Marina; Pirastu, Mario; de Andrade, Mariza; McEvoy, Mark A; Woodward, Mark; Adam, Martin; Cocca, Massimiliano; Nauck, Matthias; Imboden, Medea; Waldenberger, Melanie; Pruijm, Menno; Metzger, Marie; Stumvoll, Michael; Evans, Michele K; Sale, Michele M; Kähönen, Mika; Boban, Mladen; Bochud, Murielle; Rheinberger, Myriam; Verweij, Niek; Bouatia-Naji, Nabila; Martin, Nicholas G; Hastie, Nick; Probst-Hensch, Nicole; Soranzo, Nicole; Devuyst, Olivier; Raitakari, Olli; Gottesman, Omri; Franco, Oscar H; Polasek, Ozren; Gasparini, Paolo; Munroe, Patricia B; Ridker, Paul M; Mitchell, Paul; Muntner, Paul; Meisinger, Christa; Smit, Johannes H; Kovacs, Peter; Wild, Philipp S; Froguel, Philippe; Rettig, Rainer; Mägi, Reedik; Biffar, Reiner; Schmidt, Reinhold; Middelberg, Rita P S; Carroll, Robert J; Penninx, Brenda W; Scott, Rodney J; Katz, Ronit; Sedaghat, Sanaz; Wild, Sarah H; Kardia, Sharon L R; Ulivi, Sheila; Hwang, Shih-Jen; Enroth, Stefan; Kloiber, Stefan; Trompet, Stella; Stengel, Benedicte; Hancock, Stephen J; Turner, Stephen T; Rosas, Sylvia E; Stracke, Sylvia; Harris, Tamara B; Zeller, Tanja; Zemunik, Tatijana; Lehtimäki, Terho; Illig, Thomas; Aspelund, Thor; Nikopensius, Tiit; Esko, Tonu; Tanaka, Toshiko; Gyllensten, Ulf; Völker, Uwe; Emilsson, Valur; Vitart, Veronique; Aalto, Ville; Gudnason, Vilmundur; Chouraki, Vincent; Chen, Wei-Min; Igl, Wilmar; März, Winfried; Koenig, Wolfgang; Lieb, Wolfgang; Loos, Ruth J F; Liu, Yongmei; Snieder, Harold; Pramstaller, Peter P; Parsa, Afshin; O'Connell, Jeffrey R; Susztak, Katalin; Hamet, Pavel; Tremblay, Johanne; de Boer, Ian H; Böger, Carsten A; Goessling, Wolfram; Chasman, Daniel I; Köttgen, Anna; Kao, W H Linda; Fox, Caroline S

2016-01-21

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

PubMed Central

Pattaro, Cristian; Teumer, Alexander; Gorski, Mathias; Chu, Audrey Y.; Li, Man; Mijatovic, Vladan; Garnaas, Maija; Tin, Adrienne; Sorice, Rossella; Li, Yong; Taliun, Daniel; Olden, Matthias; Foster, Meredith; Yang, Qiong; Chen, Ming-Huei; Pers, Tune H.; Johnson, Andrew D.; Ko, Yi-An; Fuchsberger, Christian; Tayo, Bamidele; Nalls, Michael; Feitosa, Mary F.; Isaacs, Aaron; Dehghan, Abbas; d'Adamo, Pio; Adeyemo, Adebowale; Dieffenbach, Aida Karina; Zonderman, Alan B.; Nolte, Ilja M.; van der Most, Peter J.; Wright, Alan F.; Shuldiner, Alan R.; Morrison, Alanna C.; Hofman, Albert; Smith, Albert V.; Dreisbach, Albert W.; Franke, Andre; Uitterlinden, Andre G.; Metspalu, Andres; Tonjes, Anke; Lupo, Antonio; Robino, Antonietta; Johansson, Åsa; Demirkan, Ayse; Kollerits, Barbara; Freedman, Barry I.; Ponte, Belen; Oostra, Ben A.; Paulweber, Bernhard; Krämer, Bernhard K.; Mitchell, Braxton D.; Buckley, Brendan M.; Peralta, Carmen A.; Hayward, Caroline; Helmer, Catherine; Rotimi, Charles N.; Shaffer, Christian M.; Müller, Christian; Sala, Cinzia; van Duijn, Cornelia M.; Saint-Pierre, Aude; Ackermann, Daniel; Shriner, Daniel; Ruggiero, Daniela; Toniolo, Daniela; Lu, Yingchang; Cusi, Daniele; Czamara, Darina; Ellinghaus, David; Siscovick, David S.; Ruderfer, Douglas; Gieger, Christian; Grallert, Harald; Rochtchina, Elena; Atkinson, Elizabeth J.; Holliday, Elizabeth G.; Boerwinkle, Eric; Salvi, Erika; Bottinger, Erwin P.; Murgia, Federico; Rivadeneira, Fernando; Ernst, Florian; Kronenberg, Florian; Hu, Frank B.; Navis, Gerjan J.; Curhan, Gary C.; Ehret, George B.; Homuth, Georg; Coassin, Stefan; Thun, Gian-Andri; Pistis, Giorgio; Gambaro, Giovanni; Malerba, Giovanni; Montgomery, Grant W.; Eiriksdottir, Gudny; Jacobs, Gunnar; Li, Guo; Wichmann, H-Erich; Campbell, Harry; Schmidt, Helena; Wallaschofski, Henri; Völzke, Henry; Brenner, Hermann; Kroemer, Heyo K.; Kramer, Holly; Lin, Honghuang; Leach, I. Mateo; Ford, Ian; Guessous, Idris; Rudan, Igor; Prokopenko, Inga; Borecki, Ingrid; Heid, Iris M.; Kolcic, Ivana; Persico, Ivana; Jukema, J. Wouter; Wilson, James F.; Felix, Janine F.; Divers, Jasmin; Lambert, Jean-Charles; Stafford, Jeanette M.; Gaspoz, Jean-Michel; Smith, Jennifer A.; Faul, Jessica D.; Wang, Jie Jin; Ding, Jingzhong; Hirschhorn, Joel N.; Attia, John; Whitfield, John B.; Chalmers, John; Viikari, Jorma; Coresh, Josef; Denny, Joshua C.; Karjalainen, Juha; Fernandes, Jyotika K.; Endlich, Karlhans; Butterbach, Katja; Keene, Keith L.; Lohman, Kurt; Portas, Laura; Launer, Lenore J.; Lyytikäinen, Leo-Pekka; Yengo, Loic; Franke, Lude; Ferrucci, Luigi; Rose, Lynda M.; Kedenko, Lyudmyla; Rao, Madhumathi; Struchalin, Maksim; Kleber, Marcus E.; Cavalieri, Margherita; Haun, Margot; Cornelis, Marilyn C.; Ciullo, Marina; Pirastu, Mario; de Andrade, Mariza; McEvoy, Mark A.; Woodward, Mark; Adam, Martin; Cocca, Massimiliano; Nauck, Matthias; Imboden, Medea; Waldenberger, Melanie; Pruijm, Menno; Metzger, Marie; Stumvoll, Michael; Evans, Michele K.; Sale, Michele M.; Kähönen, Mika; Boban, Mladen; Bochud, Murielle; Rheinberger, Myriam; Verweij, Niek; Bouatia-Naji, Nabila; Martin, Nicholas G.; Hastie, Nick; Probst-Hensch, Nicole; Soranzo, Nicole; Devuyst, Olivier; Raitakari, Olli; Gottesman, Omri; Franco, Oscar H.; Polasek, Ozren; Gasparini, Paolo; Munroe, Patricia B.; Ridker, Paul M.; Mitchell, Paul; Muntner, Paul; Meisinger, Christa; Smit, Johannes H.; Abecasis, Goncalo R.; Adair, Linda S.; Alexander, Myriam; Altshuler, David; Amin, Najaf; Arking, Dan E.; Arora, Pankaj; Aulchenko, Yurii; Bakker, Stephan J. L.; Bandinelli, Stefania; Barroso, Ines; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Bis, Joshua C.; Boehnke, Michael; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bots, Michiel L.; Bragg-Gresham, Jennifer L.; Brand, Stefan-Martin; Brand, Eva; Braund, Peter S.; Brown, Morris J.; Burton, Paul R.; Casas, Juan P.; Caulfield, Mark J.; Chakravarti, Aravinda; Chambers, John C.; Chandak, Giriraj R.; Chang, Yen-Pei C.; Charchar, Fadi J.; Chaturvedi, Nish; Shin Cho, Yoon; Clarke, Robert; Collins, Francis S.; Collins, Rory; Connell, John M.; Cooper, Jackie A.; Cooper, Matthew N.; Cooper, Richard S.; Corsi, Anna Maria; Dörr, Marcus; Dahgam, Santosh; Danesh, John; Smith, George Davey; Day, Ian N. M.; Deloukas, Panos; Denniff, Matthew; Dominiczak, Anna F.; Dong, Yanbin; Doumatey, Ayo; Elliott, Paul; Elosua, Roberto; Erdmann, Jeanette; Eyheramendy, Susana; Farrall, Martin; Fava, Cristiano; Forrester, Terrence; Fowkes, F. Gerald R.; Fox, Ervin R.; Frayling, Timothy M.; Galan, Pilar; Ganesh, Santhi K.; Garcia, Melissa; Gaunt, Tom R.; Glazer, Nicole L.; Go, Min Jin; Goel, Anuj; Grässler, Jürgen; Grobbee, Diederick E.; Groop, Leif; Guarrera, Simonetta; Guo, Xiuqing; Hadley, David; Hamsten, Anders; Han, Bok-Ghee; Hardy, Rebecca; Hartikainen, Anna-Liisa; Heath, Simon; Heckbert, Susan R.; Hedblad, Bo; Hercberg, Serge; Hernandez, Dena; Hicks, Andrew A.; Hilton, Gina; Hingorani, Aroon D.; Bolton, Judith A Hoffman; Hopewell, Jemma C.; Howard, Philip; Humphries, Steve E.; Hunt, Steven C.; Hveem, Kristian; Ikram, M. Arfan; Islam, Muhammad; Iwai, Naoharu; Jarvelin, Marjo-Riitta; Jackson, Anne U.; Jafar, Tazeen H.; Janipalli, Charles S.; Johnson, Toby; Kathiresan, Sekar; Khaw, Kay-Tee; Kim, Hyung-Lae; Kinra, Sanjay; Kita, Yoshikuni; Kivimaki, Mika; Kooner, Jaspal S.; Kumar, M. J. Kranthi; Kuh, Diana; Kulkarni, Smita R.; Kumari, Meena; Kuusisto, Johanna; Kuznetsova, Tatiana; Laakso, Markku; Laan, Maris; Laitinen, Jaana; Lakatta, Edward G.; Langefeld, Carl D.; Larson, Martin G.; Lathrop, Mark; Lawlor, Debbie A.; Lawrence, Robert W.; Lee, Jong-Young; Lee, Nanette R.; Levy, Daniel; Li, Yali; Longstreth, Will T.; Luan, Jian'an; Lucas, Gavin; Ludwig, Barbara; Mangino, Massimo; Mani, K. Radha; Marmot, Michael G.; Mattace-Raso, Francesco U. S.; Matullo, Giuseppe; McArdle, Wendy L.; McKenzie, Colin A.; Meitinger, Thomas; Melander, Olle; Meneton, Pierre; Meschia, James F.; Miki, Tetsuro; Milaneschi, Yuri; Mohlke, Karen L.; Mooser, Vincent; Morken, Mario A.; Morris, Richard W.; Mosley, Thomas H.; Najjar, Samer; Narisu, Narisu; Newton-Cheh, Christopher; Nguyen, Khanh-Dung Hoang; Nilsson, Peter; Nyberg, Fredrik; O'Donnell, Christopher J.; Ogihara, Toshio; Ohkubo, Takayoshi; Okamura, Tomonori; Ong, RickTwee-Hee; Ongen, Halit; Onland-Moret, N. Charlotte; O'Reilly, Paul F.; Org, Elin; Orru, Marco; Palmas, Walter; Palmen, Jutta; Palmer, Lyle J.; Palmer, Nicholette D.; Parker, Alex N.; Peden, John F.; Peltonen, Leena; Perola, Markus; Pihur, Vasyl; Platou, Carl G. P.; Plump, Andrew; Prabhakaran, Dorairajan; Psaty, Bruce M.; Raffel, Leslie J.; Rao, Dabeeru C.; Rasheed, Asif; Ricceri, Fulvio; Rice, Kenneth M.; Rosengren, Annika; Rotter, Jerome I.; Rudock, Megan E.; Sõber, Siim; Salako, Tunde; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J.; Schwartz, Steven M.; Schwarz, Peter E. H.; Scott, Laura J.; Scott, James; Scuteri, Angelo; Sehmi, Joban S.; Seielstad, Mark; Seshadri, Sudha; Sharma, Pankaj; Shaw-Hawkins, Sue; Shi, Gang; Shrine, Nick R. G.; Sijbrands, Eric J. G.; Sim, Xueling; Singleton, Andrew; Sjögren, Marketa; Smith, Nicholas L.; Artigas, Maria Soler; Spector, Tim D.; Staessen, Jan A.; Stancakova, Alena; Steinle, Nanette I.; Strachan, David P.; Stringham, Heather M.; Sun, Yan V.; Swift, Amy J.; Tabara, Yasuharu; Tai, E-Shyong; Talmud, Philippa J.; Taylor, Andrew; Terzic, Janos; Thelle, Dag S.; Tobin, Martin D.; Tomaszewski, Maciej; Tripathy, Vikal; Tuomilehto, Jaakko; Tzoulaki, Ioanna; Uda, Manuela; Ueshima, Hirotsugu; Uiterwaal, Cuno S. P. M.; Umemura, Satoshi; van der Harst, Pim; van der Schouw, Yvonne T.; van Gilst, Wiek H.; Vartiainen, Erkki; Vasan, Ramachandran S.; Veldre, Gudrun; Verwoert, Germaine C.; Viigimaa, Margus; Vinay, D. G.; Vineis, Paolo; Voight, Benjamin F.; Vollenweider, Peter; Wagenknecht, Lynne E.; Wain, Louise V.; Wang, Xiaoling; Wang, Thomas J.; Wareham, Nicholas J.; Watkins, Hugh; Weder, Alan B.; Whincup, Peter H.; Wiggins, Kerri L.; Witteman, Jacqueline C. M.; Wong, Andrew; Wu, Ying; Yajnik, Chittaranjan S.; Yao, Jie; Young, J. H.; Zelenika, Diana; Zhai, Guangju; Zhang, Weihua; Zhang, Feng; Zhao, Jing Hua; Zhu, Haidong; Zhu, Xiaofeng; Zitting, Paavo; Zukowska-Szczechowska, Ewa; Okada, Yukinori; Wu, Jer-Yuarn; Gu, Dongfeng; Takeuchi, Fumihiko; Takahashi, Atsushi; Maeda, Shiro; Tsunoda, Tatsuhiko; Chen, Peng; Lim, Su-Chi; Wong, Tien-Yin; Liu, Jianjun; Young, Terri L.; Aung, Tin; Teo, Yik-Ying; Kim, Young Jin; Kang, Daehee; Chen, Chien-Hsiun; Tsai, Fuu-Jen; Chang, Li-Ching; Fann, S. -J. Cathy; Mei, Hao; Hixson, James E.; Chen, Shufeng; Katsuya, Tomohiro; Isono, Masato; Albrecht, Eva; Yamamoto, Kazuhiko; Kubo, Michiaki; Nakamura, Yusuke; Kamatani, Naoyuki; Kato, Norihiro; He, Jiang; Chen, Yuan-Tsong; Tanaka, Toshihiro; Reilly, Muredach P; Schunkert, Heribert; Assimes, Themistocles L.; Hall, Alistair; Hengstenberg, Christian; König, Inke R.; Laaksonen, Reijo; McPherson, Ruth; Thompson, John R.; Thorsteinsdottir, Unnur; Ziegler, Andreas; Absher, Devin; Chen, Li; Cupples13, L. Adrienne; Halperin, Eran; Li, Mingyao; Musunuru, Kiran; Preuss, Michael; Schillert, Arne; Thorleifsson, Gudmar; Wells, George A.; Holm, Hilma; Roberts, Robert; Stewart, Alexandre F. R.; Fortmann, Stephen; Go, Alan; Hlatky, Mark; Iribarren, Carlos; Knowles, Joshua; Myers, Richard; Quertermous, Thomas; Sidney, Steven; Risch, Neil; Tang, Hua; Blankenberg, Stefan; Schnabel, Renate; Sinning, Christoph; Lackner, Karl J.; Tiret, Laurence; Nicaud, Viviane; Cambien, Francois; Bickel, Christoph; Rupprecht, Hans J.; Perret, Claire; Proust, Carole; Münzel, Thomas F.; Barbalic, Maja; Chen, Ida Yii-Der; Demissie-Banjaw, Serkalem; Folsom, Aaron; Lumley, Thomas; Marciante, Kristin; Taylor, Kent D.; Volcik, Kelly; Gretarsdottir, Solveig; Gulcher, Jeffrey R.; Kong, Augustine; Stefansson, Kari; Thorgeirsson, Gudmundur; Andersen, Karl; Fischer, Marcus; Grosshennig, Anika; Linsel-Nitschke, Patrick; Stark, Klaus; Schreiber, Stefan; Aherrahrou, Zouhair; Bruse, Petra; Doering, Angela; Klopp, Norman; Diemert, Patrick; Loley, Christina; Medack, Anja; Nahrstedt, Janja; Peters, Annette; Wagner, Arnika K.; Willenborg, Christina; Böhm, Bernhard O.; Dobnig, Harald; Grammer, Tanja B.; Hoffmann, Michael M.; Meinitzer, Andreas; Winkelmann, Bernhard R.; Pilz, Stefan; Renner, Wilfried; Scharnagl, Hubert; Stojakovic, Tatjana; Tomaschitz, Andreas; Winkler, Karl; Guiducci, Candace; Burtt, Noel; Gabriel, Stacey B.; Dandona, Sonny; Jarinova, Olga; Qu, Liming; Wilensky, Robert; Matthai, William; Hakonarson, Hakon H.; Devaney, Joe; Burnett, Mary Susan; Pichard, Augusto D.; Kent, Kenneth M.; Satler, Lowell; Lindsay, Joseph M.; Waksman, Ron; Knouff, Christopher W.; Waterworth, Dawn M.; Walker, Max C.; Epstein, Stephen E.; Rader, Daniel J.; Nelson, Christopher P.; Wright, Benjamin J.; Balmforth, Anthony J.; Ball, Stephen G.; Loehr, Laura R.; Rosamond, Wayne D.; Benjamin, Emelia; Haritunians, Talin; Couper, David; Murabito, Joanne; Wang, Ying A.; Stricker, Bruno H.; Chang, Patricia P.; Willerson, James T.; Felix, Stephan B.; Watzinger, Norbert; Aragam, Jayashri; Zweiker, Robert; Lind, Lars; Rodeheffer, Richard J.; Greiser, Karin Halina; Deckers, Jaap W.; Stritzke, Jan; Ingelsson, Erik; Kullo, Iftikhar; Haerting, Johannes; Reffelmann, Thorsten; Redfield, Margaret M.; Werdan, Karl; Mitchell, Gary F.; Arnett, Donna K.; Gottdiener, John S.; Blettner, Maria; Friedrich, Nele; Kovacs, Peter; Wild, Philipp S.; Froguel, Philippe; Rettig, Rainer; Mägi, Reedik; Biffar, Reiner; Schmidt, Reinhold; Middelberg, Rita P. S.; Carroll, Robert J.; Penninx, Brenda W.; Scott, Rodney J.; Katz, Ronit; Sedaghat, Sanaz; Wild, Sarah H.; Kardia, Sharon L. R.; Ulivi, Sheila; Hwang, Shih-Jen; Enroth, Stefan; Kloiber, Stefan; Trompet, Stella; Stengel, Benedicte; Hancock, Stephen J.; Turner, Stephen T.; Rosas, Sylvia E.; Stracke, Sylvia; Harris, Tamara B.; Zeller, Tanja; Zemunik, Tatijana; Lehtimäki, Terho; Illig, Thomas; Aspelund, Thor; Nikopensius, Tiit; Esko, Tonu; Tanaka, Toshiko; Gyllensten, Ulf; Völker, Uwe; Emilsson, Valur; Vitart, Veronique; Aalto, Ville; Gudnason, Vilmundur; Chouraki, Vincent; Chen, Wei-Min; Igl, Wilmar; März, Winfried; Koenig, Wolfgang; Lieb, Wolfgang; Loos, Ruth J. F.; Liu, Yongmei; Snieder, Harold; Pramstaller, Peter P.; Parsa, Afshin; O'Connell, Jeffrey R.; Susztak, Katalin; Hamet, Pavel; Tremblay, Johanne; de Boer, Ian H.; Böger, Carsten A.; Goessling, Wolfram; Chasman, Daniel I.; Köttgen, Anna; Kao, W. H. Linda; Fox, Caroline S.

2016-01-01

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways. PMID:26831199

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

Whole-Exome Sequencing to Identify Novel Biological Pathways Associated With Infertility After Pelvic Inflammatory Disease.

PubMed

Taylor, Brandie D; Zheng, Xiaojing; Darville, Toni; Zhong, Wujuan; Konganti, Kranti; Abiodun-Ojo, Olayinka; Ness, Roberta B; O'Connell, Catherine M; Haggerty, Catherine L

2017-01-01

Ideal management of sexually transmitted infections (STI) may require risk markers for pathology or vaccine development. Previously, we identified common genetic variants associated with chlamydial pelvic inflammatory disease (PID) and reduced fecundity. As this explains only a proportion of the long-term morbidity risk, we used whole-exome sequencing to identify biological pathways that may be associated with STI-related infertility. We obtained stored DNA from 43 non-Hispanic black women with PID from the PID Evaluation and Clinical Health Study. Infertility was assessed at a mean of 84 months. Principal component analysis revealed no population stratification. Potential covariates did not significantly differ between groups. Sequencing kernel association test was used to examine associations between aggregates of variants on a single gene and infertility. The results from the sequencing kernel association test were used to choose "focus genes" (P < 0.01; n = 150) for subsequent Ingenuity Pathway Analysis to identify "gene sets" that are enriched in biologically relevant pathways. Pathway analysis revealed that focus genes were enriched in canonical pathways including, IL-1 signaling, P2Y purinergic receptor signaling, and bone morphogenic protein signaling. Focus genes were enriched in pathways that impact innate and adaptive immunity, protein kinase A activity, cellular growth, and DNA repair. These may alter host resistance or immunopathology after infection. Targeted sequencing of biological pathways identified in this study may provide insight into STI-related infertility.

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 analysis of autophagy in cancer therapy.

PubMed

Shi, Zheng; Li, Chun-yang; Zhao, Si; Yu, Yang; An, Na; Liu, Yong-xi; Wu, Chuan-fang; Yue, Bi-song; Bao, Jin-ku

2013-09-01

Autophagy, which degrades redundant or damaged cellular constituents, is intricately relevant to a variety of human diseases, most notably cancer. Autophagy exerts distinct effects on cancer initiation and progression, due to the intrinsic overlapping of autophagic and cancer signalling pathways. However, due to the complexity of cancer as a systemic disease, the fate of cancer cells is not decided by any one signalling pathway. Numerous autophagic inter-connectivity and cross-talk pathways need to be further clarified at a systems level. In this review, we propose a systems biology perspective for the comprehensive analysis of the autophagy-cancer network, focusing on systems biology analysis in autophagy and cancer therapy. Together, these analyses may not only improve our understanding on autophagy-cancer relationships, but also facilitate cancer drug discovery. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

PubMed Central

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-01-01

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. PMID:26019233

Psychological intervention and health outcomes among women treated for breast cancer: a review of stress pathways and biological mediators

PubMed Central

McGregor, Bonnie A.; Antoni, Michael H.

2009-01-01

Breast cancer is a common cancer among American women. The diagnosis, treatment, and the challenges of survivorship all have potential to increase women’s levels of distress to levels that might influence their adaptation and possibly the course of disease. Psychological distress can influence tumor progression via many different pathways (e.g., genetic changes, immune surveillance, pro-angiogenic processes). Psychological intervention has been shown to facilitate psychological adaptation to breast cancer. But can psychological intervention influence cancer relevant biological outcomes among breast cancer survivors? We review the literature on how psychological intervention can influence cancer-relevant biological outcomes among breast cancer patients. We limited the present review to randomized controlled trials reported in the past 6 years that tested the effects of psychological intervention on biological dependent variables among patients with non-metatstic breast cancer. There are data to suggest that psychological intervention can influence neuroendocrine (e.g. cortisol) and immune function indicators, especially lymphocyte proliferation and TH1 cytokine production. Future psychological intervention studies should also focus on more newly discovered stress-tumor pathways (e.g., neuroendocrine processes promoting tumor growth and metastasis) and follow larger cohorts of the most vulnerable patients over longer periods to evaluate the lasting effects of these interventions on health and quality of life and their underlying biobehavioral mechanisms. PMID:18778768

Applicability of a high-throughput shotgun plasma protein screening approach in understanding maternal biological pathways relevant to infant birth weight outcome.

PubMed

Kumarathasan, P; Vincent, R; Das, D; Mohottalage, S; Blais, E; Blank, K; Karthikeyan, S; Vuong, N Q; Arbuckle, T E; Fraser, W D

2014-04-04

There are reports linking maternal nutritional status, smoking and environmental chemical exposures to adverse pregnancy outcomes. However, biological bases for association between some of these factors and birth outcomes are yet to be established. The objective of this preliminary work is to test the capability of a new high-throughput shotgun plasma proteomic screening in identifying maternal changes relevant to pregnancy outcome. A subset of third trimester plasma samples (N=12) associated with normal and low-birth weight infants were fractionated, tryptic-digested and analyzed for global proteomic changes using a MALDI-TOF-TOF-MS methodology. Mass spectral data were mined for candidate biomarkers using bioinformatic and statistical tools. Maternal plasma profiles of cytokines (e.g. IL8, TNF-α), chemokines (e.g. MCP-1) and cardiovascular endpoints (e.g. ET-1, MMP-9) were analyzed by a targeted approach using multiplex protein array and HPLC-Fluorescence methods. Target and global plasma proteomic markers were used to identify protein interaction networks and maternal biological pathways relevant to low infant birth weight. Our results exhibited the potential to discriminate specific maternal physiologies relevant to risk of adverse birth outcomes. This proteomic approach can be valuable in understanding the impacts of maternal factors such as environmental contaminant exposures and nutrition on birth outcomes in future work. We demonstrate here the fitness of mass spectrometry-based shot-gun proteomics for surveillance of biological changes in mothers, and for adverse pathway analysis in combination with target biomarker information. This approach has potential for enabling early detection of mothers at risk for low infant birth weight and preterm birth, and thus early intervention for mitigation and prevention of adverse pregnancy outcomes. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes? Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Stochastic Kinetics on Networks: When Slow Is Fast

PubMed Central

2015-01-01

Most chemical and biological processes can be viewed as reaction networks in which different pathways often compete kinetically for transformation of substrates into products. An enzymatic process is an example of such phenomena when biological catalysts create new routes for chemical reactions to proceed. It is typically assumed that the general process of product formation is governed by the pathway with the fastest kinetics at all time scales. In contrast to the expectation, here we show theoretically that at time scales sufficiently short, reactions are predominantly determined by the shortest pathway (in the number of intermediate states), regardless of the average turnover time associated with each pathway. This universal phenomenon is demonstrated by an explicit calculation for a system with two competing reversible (or irreversible) pathways. The time scales that characterize this regime and its relevance for single-molecule experimental studies are also discussed. PMID:25140607

DNA Repair in Prostate Cancer: Biology and Clinical Implications.

PubMed

Mateo, Joaquin; Boysen, Gunther; Barbieri, Christopher E; Bryant, Helen E; Castro, Elena; Nelson, Pete S; Olmos, David; Pritchard, Colin C; Rubin, Mark A; de Bono, Johann S

2017-03-01

For more precise, personalized care in prostate cancer (PC), a new classification based on molecular features relevant for prognostication and treatment stratification is needed. Genomic aberrations in the DNA damage repair pathway are common in PC, particularly in late-stage disease, and may be relevant for treatment stratification. To review current knowledge on the prevalence and clinical significance of aberrations in DNA repair genes in PC, particularly in metastatic disease. A literature search up to July 2016 was conducted, including clinical trials and preclinical basic research studies. Keywords included DNA repair, BRCA, ATM, CRPC, prostate cancer, PARP, platinum, predictive biomarkers, and hereditary cancer. We review how the DNA repair pathway is relevant to prostate carcinogenesis and progression. Data on how this may be relevant to hereditary cancer and genetic counseling are included, as well as data from clinical trials of PARP inhibitors and platinum therapeutics in PC. Relevant studies have identified genomic defects in DNA repair in PCs in 20-30% of advanced castration-resistant PC cases, a proportion of which are germline aberrations and heritable. Phase 1/2 clinical trial data, and other supporting clinical data, support the development of PARP inhibitors and DNA-damaging agents in this molecularly defined subgroup of PC following success in other cancer types. These studies may be an opportunity to improve patient care with personalized therapeutic strategies. Key literature on how genomic defects in the DNA damage repair pathway are relevant for prostate cancer biology and clinical management is reviewed. Potential implications for future changes in patient care are discussed. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

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.

Analyzing cell fate control by cytokines through continuous single cell biochemistry.

PubMed

Rieger, Michael A; Schroeder, Timm

2009-10-01

Cytokines are important regulators of cell fates with high clinical and commercial relevance. However, despite decades of intense academic and industrial research, it proved surprisingly difficult to describe the biological functions of cytokines in a precise and comprehensive manner. The exact analysis of cytokine biology is complicated by the fact that individual cytokines control many different cell fates and activate a multitude of intracellular signaling pathways. Moreover, although activating different molecular programs, different cytokines can be redundant in their biological effects. In addition, cytokines with different biological effects can activate overlapping signaling pathways. This prospect article will outline the necessity of continuous single cell biochemistry to unravel the biological functions of molecular cytokine signaling. It focuses on potentials and limitations of recent technical developments in fluorescent time-lapse imaging and single cell tracking allowing constant long-term observation of molecules and behavior of single cells. (c) 2009 Wiley-Liss, Inc.

Use of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes (hiPSC-CMs) to Monitor Compound Effects on Cardiac Myocyte Signaling Pathways.

PubMed

Guo, Liang; Eldridge, Sandy; Furniss, Mike; Mussio, Jodie; Davis, Myrtle

2015-09-01

There is a need to develop mechanism-based assays to better inform risk of cardiotoxicity. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are rapidly gaining acceptance as a biologically relevant in vitro model for use in drug discovery and cardiotoxicity screens. Utilization of hiPSC-CMs for mechanistic investigations would benefit from confirmation of the expression and activity of cellular pathways that are known to regulate cardiac myocyte viability and function. This unit describes an approach to demonstrate the presence and function of signaling pathways in hiPSC-CMs and the effects of treatments on these pathways. We present a workflow that employs protocols to demonstrate protein expression and functional integrity of signaling pathway(s) of interest and to characterize biological consequences of signaling modulation. These protocols utilize a unique combination of structural, functional, and biochemical endpoints to interrogate compound effects on cardiomyocytes. Copyright © 2015 John Wiley & Sons, Inc.

Putative adverse outcome pathways relevant to neurotoxicity

PubMed Central

Bal-Price, Anna; Crofton, Kevin M.; Sachana, Magdalini; Shafer, Timothy J.; Behl, Mamta; Forsby, Anna; Hargreaves, Alan; Landesmann, Brigitte; Lein, Pamela J.; Louisse, Jochem; Monnet-Tschudi, Florianne; Paini, Alicia; Rolaki, Alexandra; Schrattenholz, André; Suñol, Cristina; van Thriel, Christoph; Whelan, Maurice; Fritsche, Ellen

2016-01-01

The Adverse Outcome Pathway (AOP) framework provides a template that facilitates understanding of complex biological systems and the pathways of toxicity that result in adverse outcomes (AOs). The AOP starts with an molecular initiating event (MIE) in which a chemical interacts with a biological target(s), followed by a sequential series of KEs, which are cellular, anatomical, and/or functional changes in biological processes, that ultimately result in an AO manifest in individual organisms and populations. It has been developed as a tool for a knowledge-based safety assessment that relies on understanding mechanisms of toxicity, rather than simply observing its adverse outcome. A large number of cellular and molecular processes are known to be crucial to proper development and function of the central (CNS) and peripheral nervous systems (PNS). However, there are relatively few examples of well-documented pathways that include causally linked MIEs and KEs that result in adverse outcomes in the CNS or PNS. As a first step in applying the AOP framework to adverse health outcomes associated with exposure to exogenous neurotoxic substances, the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) organized a workshop (March 2013, Ispra, Italy) to identify potential AOPs relevant to neurotoxic and developmental neurotoxic outcomes. Although the AOPs outlined during the workshop are not fully described, they could serve as a basis for further, more detailed AOP development and evaluation that could be useful to support human health risk assessment in a variety of ways. PMID:25605028

Hippo pathway - brief overview of its relevance in cancer.

PubMed

Zygulska, A L; Krzemieniecki, K; Pierzchalski, P

2017-06-01

The Hippo pathway is the major regulator of organ growth and proliferation. Described initially in Drosophila, it is now recognized as one of the most conserved molecular pathways in all metazoan. Recent studies have revealed the Hippo signalling pathway might contribute to tumorigenesis and cancer development. The core components of the Hippo pathway include the mammalian sterile 20-like kinases (MSTs), large tumour suppressor kinases (LATSs), the adaptor proteins Salvador homologue 1 (SAV1, also called WW45) and Mps One Binder kinase activator proteins. The major target of the Hippo core kinases is the mammalian transcriptional activator Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ). In cancer, the Hippo signalling is inactivated and YAP and TAZ are activated and free to translocate into the nucleus to promote cell proliferation. Nuclear YAP/TAZ activate or suppress transcription factors that regulate target genes involved in cell proliferation, tissue growth, control of organ size and shape or metastasis. The Hippo signalling pathway that controls the most important cellular processes like growth and division appears to be a very promising research subject in the field of cell biology and tissue engineering. It consists of elements that in the cell play the roles of tumour suppressors as well as oncogenes. This 'Janus like' - an opposite activity hidden within one and the same signalling pathway represents a significant obstacle for studying it. This property of the Hippo pathway is worth remembering, as it will appear several times during the discussion of its properties. Here, we will review certain data regarding biology of the Hippo signalling and its interplay with other prominent signalling pathways in the cell, its relevance in cancer development and therapies that might target elements of the Hippo pathway in most human cancers.

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.

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

A method for integrating and ranking the evidence for biochemical pathways by mining reactions from text

PubMed Central

Miwa, Makoto; Ohta, Tomoko; Rak, Rafal; Rowley, Andrew; Kell, Douglas B.; Pyysalo, Sampo; Ananiadou, Sophia

2013-01-01

Motivation: To create, verify and maintain pathway models, curators must discover and assess knowledge distributed over the vast body of biological literature. Methods supporting these tasks must understand both the pathway model representations and the natural language in the literature. These methods should identify and order documents by relevance to any given pathway reaction. No existing system has addressed all aspects of this challenge. Method: We present novel methods for associating pathway model reactions with relevant publications. Our approach extracts the reactions directly from the models and then turns them into queries for three text mining-based MEDLINE literature search systems. These queries are executed, and the resulting documents are combined and ranked according to their relevance to the reactions of interest. We manually annotate document-reaction pairs with the relevance of the document to the reaction and use this annotation to study several ranking methods, using various heuristic and machine-learning approaches. Results: Our evaluation shows that the annotated document-reaction pairs can be used to create a rule-based document ranking system, and that machine learning can be used to rank documents by their relevance to pathway reactions. We find that a Support Vector Machine-based system outperforms several baselines and matches the performance of the rule-based system. The success of the query extraction and ranking methods are used to update our existing pathway search system, PathText. Availability: An online demonstration of PathText 2 and the annotated corpus are available for research purposes at http://www.nactem.ac.uk/pathtext2/. Contact: makoto.miwa@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23813008

Pathway-based personalized analysis of cancer

PubMed Central

Drier, Yotam; Sheffer, Michal; Domany, Eytan

2013-01-01

We introduce Pathifier, an algorithm that infers pathway deregulation scores for each tumor sample on the basis of expression data. This score is determined, in a context-specific manner, for every particular dataset and type of cancer that is being investigated. The algorithm transforms gene-level information into pathway-level information, generating a compact and biologically relevant representation of each sample. We demonstrate the algorithm’s performance on three colorectal cancer datasets and two glioblastoma multiforme datasets and show that our multipathway-based representation is reproducible, preserves much of the original information, and allows inference of complex biologically significant information. We discovered several pathways that were significantly associated with survival of glioblastoma patients and two whose scores are predictive of survival in colorectal cancer: CXCR3-mediated signaling and oxidative phosphorylation. We also identified a subclass of proneural and neural glioblastoma with significantly better survival, and an EGF receptor-deregulated subclass of colon cancers. PMID:23547110

De Novo Characterization of the Spleen Transcriptome of the Large Yellow Croaker (Pseudosciaena crocea) and Analysis of the Immune Relevant Genes and Pathways Involved in the Antiviral Response

PubMed Central

Ding, Yang; Ao, Jingqun; Hu, Songnian; Chen, Xinhua

2014-01-01

The large yellow croaker (Pseudosciaena crocea) is an economically important marine fish in China. To understand the molecular basis for antiviral defense in this species, we used Illumia paired-end sequencing to characterize the spleen transcriptome of polyriboinosinic:polyribocytidylic acid [poly(I:C)]-induced large yellow croakers. The library produced 56,355,728 reads and assembled into 108,237 contigs. As a result, 15,192 unigenes were found from this transcriptome. Gene ontology analysis showed that 4,759 genes were involved in three major functional categories: biological process, cellular component, and molecular function. We further ascertained that numerous consensus sequences were homologous to known immune-relevant genes. Kyoto Encyclopedia of Genes and Genomes orthology mapping annotated 5,389 unigenes and identified numerous immune-relevant pathways. These immune-relevant genes and pathways revealed major antiviral immunity effectors, including but not limited to: pattern recognition receptors, adaptors and signal transducers, the interferons and interferon-stimulated genes, inflammatory cytokines and receptors, complement components, and B-cell and T-cell antigen activation molecules. Moreover, the partial genes of Toll-like receptor signaling pathway, RIG-I-like receptors signaling pathway, Janus kinase-Signal Transducer and Activator of Transcription (JAK-STAT) signaling pathway, and T-cell receptor (TCR) signaling pathway were found to be changed after poly(I:C) induction by real-time polymerase chain reaction (PCR) analysis, suggesting that these signaling pathways may be regulated by poly(I:C), a viral mimic. Overall, the antivirus-related genes and signaling pathways that were identified in response to poly(I:C) challenge provide valuable leads for further investigation of the antiviral defense mechanism in the large yellow croaker. PMID:24820969

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

PubMed

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-08-15

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. © The Author 2015. Published by Oxford University Press.

Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.

PubMed

Cox, Amanda J; Zhang, Ping; Evans, Tiffany J; Scott, Rodney J; Cripps, Allan W; West, Nicholas P

Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n=21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n=11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p<0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p<0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10 -8 ; AUC: 0.909, CR: 72.7%). These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

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.

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

Testing quantitative adverse outcome pathway predictions using aromatase inhibitors in female fathead minnows

EPA Science Inventory

To become more efficient and cost effective regulatory toxicology is increasingly averting from whole animal testing toward collecting data at lower levels of biological organization, through such means as in vitro high throughput screening (HTS) assays. When anchored to relevant...

Hyphae-specific genes HGC1, ALS3, HWP1, and ECE1 and relevant signaling pathways in Candida albicans.

PubMed

Fan, Yan; He, Hong; Dong, Yan; Pan, Hengbiao

2013-12-01

Fungal virulence mechanisms include adhesion to epithelia, morphogenesis, production of secretory hydrolytic enzymes, and phenotype switching, all of which contribute to the process of pathogenesis. A striking feature of the biology of Candida albicans is its ability to grow in yeast, pseudohyphal, and hyphal forms. The hyphal form plays an important role in causing disease, by invading epithelial cells and causing tissue damage. In this review, we illustrate some of the main hyphae-specific genes, namely HGC1, UME6, ALS3, HWP1, and ECE1, and their relevant and reversed signal transduction pathways in reactions stimulated by environmental factors, including pH, CO2, and serum.

Mouse models of ageing and their relevance to disease.

PubMed

Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

2016-12-01

Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

30 years of NF-κB: a blossoming of relevance to human pathobiology

PubMed Central

Zhang, Qian; Lenardo, Michael J.; Baltimore, David

2016-01-01

NF-κB was discovered thirty years ago as a rapidly inducible transcription factor. Since that time it has been found to have a broad role in gene induction in diverse cellular responses, particularly throughout the immune system. Here we summarize elaborate regulatory pathways involving this transcription factor and use recent discoveries in human genetic diseases to place specific proteins within their relevant medical and biological contexts. PMID:28086098

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.

Sex and gonadal hormones in mouse models of Alzheimer’s disease: what is relevant to the human condition?

PubMed Central

2012-01-01

Biologic sex and gonadal hormones matter in human aging and diseases of aging such as Alzheimer’s – and the importance of studying their influences relates directly to human health. The goal of this article is to review the literature to date on sex and hormones in mouse models of Alzheimer’s disease (AD) with an exclusive focus on interpreting the relevance of findings to the human condition. To this end, we highlight advances in AD and in sex and hormone biology, discuss what these advances mean for merging the two fields, review the current mouse model literature, raise major unresolved questions, and offer a research framework that incorporates human reproductive aging for future studies aimed at translational discoveries in this important area. Unraveling human relevant pathways in sex and hormone-based biology may ultimately pave the way to novel and urgently needed treatments for AD and other neurodegenerative diseases. PMID:23126652

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Advances in the understanding of the clinically relevant genetic pathways and molecular aspects of canine mammary tumours. Part 2: invasion, angiogenesis, metastasis and therapy.

PubMed

Santos, A A; Matos, A J F

2015-08-01

Significant advances have been made recently in the understanding of the molecular events and critical pathways associated with and driving cancer of the mammary gland in humans and dogs. The study of canine mammary tumour biology, particularly the interactions of neoplastic cells with stromal and immune cells, is crucial for the development of novel effective therapeutic agents and strategies. This second part of a two-part review discusses some of the latest advances in the understanding of the clinically relevant genetic and molecular pathways involved in metastasis and in the interactions between tumour and stromal cells, including inflammatory and immune cells, cancer-associated fibroblasts, and endothelial cells. Recent experimental data on the role of matrix-degrading proteases and angiogenic factors are also discussed. Finally, the clinical utility of different non-surgical therapeutic modalities is reviewed. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Systematic reconstruction of autism biology from massive genetic mutation profiles

PubMed Central

Zhang, Chaolin; Jiang, Yong-hui

2018-01-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3′,5′-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein–coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity. PMID:29651456

Systematic reconstruction of autism biology from massive genetic mutation profiles.

PubMed

Luo, Weijun; Zhang, Chaolin; Jiang, Yong-Hui; Brouwer, Cory R

2018-04-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3',5'-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein-coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity.

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.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

PubMed

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Applying NGS Data to Find Evolutionary Network Biomarkers from the Early and Late Stages of Hepatocellular Carcinoma

PubMed Central

Wu, Chia-Chou; Lin, Chih-Lung; Chen, Ting-Shou

2015-01-01

Hepatocellular carcinoma (HCC) is a major liver tumor (~80%), besides hepatoblastomas, angiosarcomas, and cholangiocarcinomas. In this study, we used a systems biology approach to construct protein-protein interaction networks (PPINs) for early-stage and late-stage liver cancer. By comparing the networks of these two stages, we found that the two networks showed some common mechanisms and some significantly different mechanisms. To obtain differential network structures between cancer and noncancer PPINs, we constructed cancer PPIN and noncancer PPIN network structures for the two stages of liver cancer by systems biology method using NGS data from cancer cells and adjacent noncancer cells. Using carcinogenesis relevance values (CRVs), we identified 43 and 80 significant proteins and their PPINs (network markers) for early-stage and late-stage liver cancer. To investigate the evolution of network biomarkers in the carcinogenesis process, a primary pathway analysis showed that common pathways of the early and late stages were those related to ordinary cancer mechanisms. A pathway specific to the early stage was the mismatch repair pathway, while pathways specific to the late stage were the spliceosome pathway, lysine degradation pathway, and progesterone-mediated oocyte maturation pathway. This study provides a new direction for cancer-targeted therapies at different stages. PMID:26366411

Exploring pathway interactions in insulin resistant mouse liver

PubMed Central

2011-01-01

Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341

Classification and Analysis of Regulatory Pathways Using Graph Property, Biochemical and Physicochemical Property, and Functional Property

PubMed Central

Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418

Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development.

PubMed

Fay, Kellie A; Villeneuve, Daniel L; Swintek, Joe; Edwards, Stephen W; Nelms, Mark D; Blackwell, Brett R; Ankley, Gerald T

2018-06-01

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 apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.

Expression Profiling Analysis Reveals Key MicroRNA-mRNA Interactions in Early Retinal Degeneration in Retinitis Pigmentosa.

PubMed

Anasagasti, Ander; Ezquerra-Inchausti, Maitane; Barandika, Olatz; Muñoz-Culla, Maider; Caffarel, María M; Otaegui, David; López de Munain, Adolfo; Ruiz-Ederra, Javier

2018-05-01

The aim of this study was to identify differentially expressed microRNAs (miRNAs) that might play an important role in the etiology of retinal degeneration in a genetic mouse model of retinitis pigmentosa (rd10 mice) at initial stages of the disease. miRNAs-mRNA interaction networks were generated for analysis of biological pathways involved in retinal degeneration. Of more than 1900 miRNAs analyzed, we selected 19 miRNAs on the basis of (1) a significant differential expression in rd10 retinas compared with control samples and (2) an inverse expression relationship with predicted mRNA targets involved in biological pathways relevant to retinal biology and/or degeneration. Seven of the selected miRNAs have been associated with retinal dystrophies, whereas, to our knowledge, nine have not been previously linked to any disease. This study contributes to our understanding of the etiology and progression of retinal degeneration.

Omics/systems biology and cancer cachexia.

PubMed

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

Knowledge Gaps in Rodent Pancreas Biology: Taking Human Pluripotent Stem Cell-Derived Pancreatic Beta Cells into Our Own Hands

PubMed Central

Santosa, Munirah Mohamad; Low, Blaise Su Jun; Pek, Nicole Min Qian; Teo, Adrian Kee Keong

2016-01-01

In the field of stem cell biology and diabetes, we and others seek to derive mature and functional human pancreatic β cells for disease modeling and cell replacement therapy. Traditionally, knowledge gathered from rodents is extended to human pancreas developmental biology research involving human pluripotent stem cells (hPSCs). While much has been learnt from rodent pancreas biology in the early steps toward Pdx1+ pancreatic progenitors, much less is known about the transition toward Ngn3+ pancreatic endocrine progenitors. Essentially, the later steps of pancreatic β cell development and maturation remain elusive to date. As a result, the most recent advances in the stem cell and diabetes field have relied upon combinatorial testing of numerous growth factors and chemical compounds in an arbitrary trial-and-error fashion to derive mature and functional human pancreatic β cells from hPSCs. Although this hit-or-miss approach appears to have made some headway in maturing human pancreatic β cells in vitro, its underlying biology is vaguely understood. Therefore, in this mini-review, we discuss some of these late-stage signaling pathways that are involved in human pancreatic β cell differentiation and highlight our current understanding of their relevance in rodent pancreas biology. Our efforts here unravel several novel signaling pathways that can be further studied to shed light on unexplored aspects of rodent pancreas biology. New investigations into these signaling pathways are expected to advance our knowledge in human pancreas developmental biology and to aid in the translation of stem cell biology in the context of diabetes treatments. PMID:26834702

Knowledge Gaps in Rodent Pancreas Biology: Taking Human Pluripotent Stem Cell-Derived Pancreatic Beta Cells into Our Own Hands.

PubMed

Santosa, Munirah Mohamad; Low, Blaise Su Jun; Pek, Nicole Min Qian; Teo, Adrian Kee Keong

2015-01-01

In the field of stem cell biology and diabetes, we and others seek to derive mature and functional human pancreatic β cells for disease modeling and cell replacement therapy. Traditionally, knowledge gathered from rodents is extended to human pancreas developmental biology research involving human pluripotent stem cells (hPSCs). While much has been learnt from rodent pancreas biology in the early steps toward Pdx1(+) pancreatic progenitors, much less is known about the transition toward Ngn3(+) pancreatic endocrine progenitors. Essentially, the later steps of pancreatic β cell development and maturation remain elusive to date. As a result, the most recent advances in the stem cell and diabetes field have relied upon combinatorial testing of numerous growth factors and chemical compounds in an arbitrary trial-and-error fashion to derive mature and functional human pancreatic β cells from hPSCs. Although this hit-or-miss approach appears to have made some headway in maturing human pancreatic β cells in vitro, its underlying biology is vaguely understood. Therefore, in this mini-review, we discuss some of these late-stage signaling pathways that are involved in human pancreatic β cell differentiation and highlight our current understanding of their relevance in rodent pancreas biology. Our efforts here unravel several novel signaling pathways that can be further studied to shed light on unexplored aspects of rodent pancreas biology. New investigations into these signaling pathways are expected to advance our knowledge in human pancreas developmental biology and to aid in the translation of stem cell biology in the context of diabetes treatments.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

PubMed

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

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...

Solution state nuclear magnetic resonance spectroscopy for biological metabolism and pathway intermediate analysis.

PubMed

Nealon, Gareth L; Howard, Mark J

2016-12-15

Using nuclear magnetic resonance (NMR) spectroscopy in the study of metabolism has been immensely popular in medical- and health-related research but has yet to be widely applied to more fundamental biological problems. This review provides some NMR background relevant to metabolism, describes why 1 H NMR spectra are complex as well as introducing relevant terminology and definitions. The applications and practical considerations of NMR metabolic profiling and 13 C NMR-based flux analyses are discussed together with the elegant 'enzyme trap' approach for identifying novel metabolic pathway intermediates. The importance of sample preparation and data analysis are also described and explained with reference to data precision and multivariate analysis to introduce researchers unfamiliar with NMR and metabolism to consider this technique for their research interests. Finally, a brief glance into the future suggests NMR-based metabolism has room to expand in the 21st century through new isotope labels, and NMR technologies and methodologies. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Next-generation sequencing analysis of gene regulation in the rat model of retinopathy of prematurity.

PubMed

Griffith, Rachel M; Li, Hu; Zhang, Nan; Favazza, Tara L; Fulton, Anne B; Hansen, Ronald M; Akula, James D

2013-08-01

The purpose of this study was to identify the genes, biochemical signaling pathways, and biological themes involved in the pathogenesis of retinopathy of prematurity (ROP). Next-generation sequencing (NGS) was performed on the RNA transcriptome of rats with the Penn et al. (Pediatr Res 36:724-731, 1994) oxygen-induced retinopathy model of ROP at the height of vascular abnormality, postnatal day (P) 19, and normalized to age-matched, room-air-reared littermate controls. Eight custom-developed pathways with potential relevance to known ROP sequelae were evaluated for significant regulation in ROP: The three major Wnt signaling pathways, canonical, planar cell polarity (PCP), and Wnt/Ca(2+); two signaling pathways mediated by the Rho GTPases RhoA and Cdc42, which are, respectively, thought to intersect with canonical and non-canonical Wnt signaling; nitric oxide signaling pathways mediated by two nitric oxide synthase (NOS) enzymes, neuronal (nNOS) and endothelial (eNOS); and the retinoic acid (RA) signaling pathway. Regulation of other biological pathways and themes was detected by gene ontology using the Kyoto Encyclopedia of Genes and Genomes and the NIH's Database for Annotation, Visualization, and Integrated Discovery's GO terms databases. Canonical Wnt signaling was found to be regulated, but the non-canonical PCP and Wnt/Ca(2+) pathways were not. Nitric oxide signaling, as measured by the activation of nNOS and eNOS, was also regulated, as was RA signaling. Biological themes related to protein translation (ribosomes), neural signaling, inflammation and immunity, cell cycle, and cell death were (among others) highly regulated in ROP rats. These several genes and pathways identified by NGS might provide novel targets for intervention in ROP.

Next Generation Sequencing Analysis of Gene Regulation in the Rat Model of Retinopathy of Prematurity

PubMed Central

Griffith, Rachel M.; Li, Hu; Zhang, Nan; Favazza, Tara L.; Fulton, Anne B.; Hansen, Ronald M.; Akula, James D.

2013-01-01

Purpose To identify the genes, biochemical signaling pathways and biological themes involved in the pathogenesis of retinopathy of prematurity (ROP). Methods Next-generation sequencing (NGS) was performed on the RNA transcriptome of rats with the Penn et al. (1994) oxygen-induced retinopathy (OIR) model of ROP at the height of vascular abnormality, postnatal day (P) 19, and normalized to age-matched, room-air-reared littermate controls. Eight custom developed pathways with potential relevance to known ROP sequelae were evaluated for significant regulation in ROP: The three major Wnt signaling pathways, canonical, planar cell polarity (PCP), and Wnt/Ca2+, two signaling pathways mediated by the Rho GTPases RhoA and Cdc42, which are respectively thought to intersect with canonical and noncanonical Wnt signaling, nitric oxide signaling pathways mediated by two nitrox oxide synthase (NOS) enzymes, neuronal (nNOS) and endothelial (eNOS), and the retinoic acid (RA) signaling pathway. Regulation of other biological pathways and themes were detected by gene ontology using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the NIH's Database for Annotation, Visualization and Integrated Discovery (DAVID)'s GO terms databases. Results Canonical Wnt signaling was found to be regulated, but the non-canonical PCP and Wnt/Ca2+ pathways were not. Nitric oxide (NO) signaling, as measured by the activation of nNOS eNOS, was also regulated, as was RA signaling. Biological themes related to protein translation (ribosomes), neural signaling, inflammation and immunity, cell cycle and cell death, were (among others) highly regulated in ROP rats. Conclusions These several genes and pathways identified by NGS might provide novel targets for intervention in ROP. PMID:23775346

Differentiating high priority pathway-based toxicity from non ...

EPA Pesticide Factsheets

The ToxCast chemical screening approach enables the rapid assessment of large numbers of chemicals for biological effects, primarily at the molecular level. Adverse outcome pathways (AOPs) offer a means to link biomolecular effects with potential adverse outcomes at the level of the individual or population, thus enhancing the utility of the ToxCast effort for hazard assessment. Thus, efforts are underway to develop AOPs relevant to the pathway perturbations detected in ToxCast assays. However, activity (?‘hits’) determined for chemical-assay pairs may reflect target-specific activity relevant to a molecular initiating event of an AOP, or more generalized cell stress and cytotoxicity-mediated effects. Previous work identified a ?‘cytotoxic burst’ phenomenon wherein large numbers of assays begin to respond at or near concentrations that elicit cytotoxicity. The concentration range at which the “burst” occurs is definable, statistically. Consequently, in order to focus AOP development on the ToxCast assay targetswhich are most sensitive and relevant to pathway-specific effects, we conducted a meta-analysis to identify which assays were frequently responding at concentrations well below the cytotoxic burst. Assays were ranked by the fraction of chemical hits below the burst concentration range compared to the number of chemicals tested, resulting in a preliminary list of potentially important, target-specific assays. After eliminating cytotoxicity a

Protective Mechanism of STAT3-siRNA on Cerebral Ischemia Injury

NASA Astrophysics Data System (ADS)

He, Jinting; Yang, Le; Liang, Wenzhao

2018-01-01

Nerve cells in ischemic brain injury will occur a series of complex signal transduction pathway changes and produce the corresponding biological function, thus affecting the central nervous system functionally different cells in the ischemic brain injury metabolism, division, Differentiation and death process, while changes in signal pathways also play an important role in the repair process of the post-ischemic nervous system. JAK/STAT pathway and vascular lesions have some relevance, but its exact mechanism after cerebral ischemia is not yet fully understood. This study is intended to further explore the JAK / STAT pathway in the functional site of STAT3 in neuronal ischemia Hypoxic injury and related molecular mechanisms, targeting these targets design intervention strategies to block the signal pathway, in order to provide a theoretical basis for the treatment of ischemic brain damage in this pathway.

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

Programmable genetic circuits for pathway engineering.

PubMed

Hoynes-O'Connor, Allison; Moon, Tae Seok

2015-12-01

Synthetic biology has the potential to provide decisive advances in genetic control of metabolic pathways. However, there are several challenges that synthetic biologists must overcome before this vision becomes a reality. First, a library of diverse and well-characterized sensors, such as metabolite-sensing or condition-sensing promoters, must be constructed. Second, robust programmable circuits that link input conditions with a specific gene regulation response must be developed. Finally, multi-gene targeting strategies must be integrated with metabolically relevant sensors and complex, robust logic. Achievements in each of these areas, which employ the CRISPR/Cas system, in silico modeling, and dynamic sensor-regulators, among other tools, provide a strong basis for future research. Overall, the future for synthetic biology approaches in metabolic engineering holds immense promise. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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.

The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life

PubMed Central

Chen, Lei; Lu, Jing; Kong, XiangYin; Huang, Tao; Li, HaiPeng

2016-01-01

A drug’s biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO) terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347), monoamine transmembrane transporter activity (GO:0008504), negative regulation of synaptic transmission (GO:0050805), neuroactive ligand-receptor interaction (hsa04080), serotonergic synapse (hsa04726), and linoleic acid metabolism (hsa00591), among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives. PMID:27780226

Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways.

PubMed

Pey, Jon; Valgepea, Kaspar; Rubio, Angel; Beasley, John E; Planes, Francisco J

2013-12-08

The study of cellular metabolism in the context of high-throughput -omics data has allowed us to decipher novel mechanisms of importance in biotechnology and health. To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling. We present here an in-silico framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in Escherichia coli. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed. A novel mathematical framework that determines functional pathways based on gene/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in Escherichia coli.

An ubiquitin-binding molecule can work as an inhibitor of ubiquitin processing enzymes and ubiquitin receptors.

PubMed

Nguyen, Thanh; Ho, Minh; Ghosh, Ambarnil; Kim, Truc; Yun, Sun Il; Lee, Seung Seo; Kim, Kyeong Kyu

2016-10-07

The ubiquitin pathway plays a critical role in regulating diverse biological processes, and its dysregulation is associated with various diseases. Therefore, it is important to have a tool that can control the ubiquitin pathway in order to improve understanding of this pathway and to develop therapeutics against relevant diseases. We found that Chicago Sky Blue 6B binds directly to the β-groove, a major interacting surface of ubiquitin. Hence, it could successfully inhibit the enzymatic activity of ubiquitin processing enzymes and the binding of ubiquitin to the CXCR4, a cell surface ubiquitin receptor. Furthermore, we demonstrated that this ubiquitin binding chemical could effectively suppress the ubiquitin induced cancer cell migration by blocking ubiquitin-CXCR4 interaction. Current results suggest that ubiquitin binding molecules can be developed as inhibitors of ubiquitin-protein interactions, which will have the value not only in unveiling the biological role of ubiquitin but also in treating related diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways

PubMed Central

Jo, Kyuri; Jung, Inuk; Moon, Ji Hwan; Kim, Sun

2016-01-01

Motivation: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. Results: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein–protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-Pathway map in time clock. TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. Availability and Implementation: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: sunkim.bioinfo@snu.ac.kr PMID:27307609

Expanding the horizons of microRNA bioinformatics.

PubMed

Huntley, Rachael P; Kramarz, Barbara; Sawford, Tony; Umrao, Zara; Kalea, Anastasia Z; Acquaah, Vanessa; Martin, Maria-Jesus; Mayr, Manuel; Lovering, Ruth C

2018-06-05

MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult for researchers to find and analyse microRNA-related experimental data and define further research projects. We are addressing this problem by providing two new bioinformatics datasets that contain experimentally verified functional information for mammalian microRNAs involved in cardiovascular-relevant, and other, processes. To date, our resource provides over 3,900 Gene Ontology annotations associated with almost 500 miRNAs from human, mouse and rat and over 2,200 experimentally validated miRNA:target interactions. We illustrate how this resource can be used to create miRNA-focused interaction networks with a biological context using the known biological role of miRNAs and the mRNAs they regulate, enabling discovery of associations between gene products, biological pathways and, ultimately, diseases. This data will be crucial in advancing the field of microRNA bioinformatics and will establish consistent datasets for reproducible functional analysis of microRNAs across all biological research areas. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Disease implication of hyper-Hippo signalling.

PubMed

Wang, Shu-Ping; Wang, Lan-Hsin

2016-10-01

The Hippo signalling pathway regulates cellular proliferation, apoptosis and differentiation, thus exerting profound effects on cellular homeostasis. Inhibition of Hippo signalling has been frequently implicated in human cancers, indicating a well-known tumour suppressor function of the Hippo pathway. However, it is less certain whether and how hyperactivation of the Hippo pathway affects biological outcome in living cells. This review describes current knowledge of the regulatory mechanisms of the Hippo pathway, mainly focusing on hyperactivation of the Hippo signalling nexus. The disease implications of hyperactivated Hippo signalling have also been discussed, including arrhythmogenic cardiomyopathy, Sveinsson's chorioretinal atrophy, Alzheimer's disease, amyotrophic lateral sclerosis and diabetes. By highlighting the significance of disease-relevant Hippo signalling activation, this review can offer exciting prospects to address the onset and potential reversal of Hippo-related disorders. © 2016 The Authors.

Disease implication of hyper-Hippo signalling

PubMed Central

Wang, Shu-Ping

2016-01-01

The Hippo signalling pathway regulates cellular proliferation, apoptosis and differentiation, thus exerting profound effects on cellular homeostasis. Inhibition of Hippo signalling has been frequently implicated in human cancers, indicating a well-known tumour suppressor function of the Hippo pathway. However, it is less certain whether and how hyperactivation of the Hippo pathway affects biological outcome in living cells. This review describes current knowledge of the regulatory mechanisms of the Hippo pathway, mainly focusing on hyperactivation of the Hippo signalling nexus. The disease implications of hyperactivated Hippo signalling have also been discussed, including arrhythmogenic cardiomyopathy, Sveinsson's chorioretinal atrophy, Alzheimer's disease, amyotrophic lateral sclerosis and diabetes. By highlighting the significance of disease-relevant Hippo signalling activation, this review can offer exciting prospects to address the onset and potential reversal of Hippo-related disorders. PMID:27805903

Expression Profiling Analysis Reveals Key MicroRNA–mRNA Interactions in Early Retinal Degeneration in Retinitis Pigmentosa

PubMed Central

Anasagasti, Ander; Ezquerra-Inchausti, Maitane; Barandika, Olatz; Muñoz-Culla, Maider; Caffarel, María M.; Otaegui, David; López de Munain, Adolfo

2018-01-01

Purpose The aim of this study was to identify differentially expressed microRNAs (miRNAs) that might play an important role in the etiology of retinal degeneration in a genetic mouse model of retinitis pigmentosa (rd10 mice) at initial stages of the disease. Methods miRNAs–mRNA interaction networks were generated for analysis of biological pathways involved in retinal degeneration. Results Of more than 1900 miRNAs analyzed, we selected 19 miRNAs on the basis of (1) a significant differential expression in rd10 retinas compared with control samples and (2) an inverse expression relationship with predicted mRNA targets involved in biological pathways relevant to retinal biology and/or degeneration. Seven of the selected miRNAs have been associated with retinal dystrophies, whereas, to our knowledge, nine have not been previously linked to any disease. Conclusions This study contributes to our understanding of the etiology and progression of retinal degeneration. PMID:29847644

Pyramidal neurovision architecture for vision machines

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1993-08-01

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

In silico epigenetics of metal exposure and subclinical atherosclerosis in middle aged men: pilot results from the Aragon Workers Health Study.

PubMed

Riffo-Campos, Angela L; Fuentes-Trillo, Azahara; Tang, Wan Y; Soriano, Zoraida; De Marco, Griselda; Rentero-Garrido, Pilar; Adam-Felici, Victoria; Lendinez-Tortajada, Veronica; Francesconi, Kevin; Goessler, Walter; Ladd-Acosta, Christine; Leon-Latre, Montse; Casasnovas, Jose A; Chaves, F Javier; Navas-Acien, Ana; Guallar, Eliseo; Tellez-Plaza, Maria

2018-06-05

We explored the association of metal levels with subclinical atherosclerosis and epigenetic changes in relevant biological pathways. Whole blood DNA Infinium Methylation 450 K data were obtained from 23 of 73 middle age men without clinically evident cardiovascular disease (CVD) who participated in the Aragon Workers Health Study in 2009 (baseline visit) and had available baseline urinary metals and subclinical atherosclerosis measures obtained in 2010-2013 (follow-up visit). The median metal levels were 7.36 µg g -1 , 0.33 µg g -1 , 0.11 µg g -1 and 0.07 µg g -1 , for arsenic (sum of inorganic and methylated species), cadmium, antimony and tungsten, respectively. Urine cadmium and tungsten were associated with femoral and carotid intima-media thickness, respectively (Pearson's r = 0.27; p = 0.03 in both cases). Among nearest genes to identified differentially methylated regions (DMRs), 46% of metal-DMR genes overlapped with atherosclerosis-DMR genes ( p < 0.001). Pathway enrichment analysis of atherosclerosis-DMR genes showed a role in inflammatory, metabolic and transport pathways. In in silico protein-to-protein interaction networks among proteins encoded by 162 and 108 genes attributed to atherosclerosis- and metal-DMRs, respectively, with proteins known to have a role in atherosclerosis pathways, we observed hub proteins in the network associated with both atherosclerosis and metal-DMRs (e.g. SMAD3 and NOP56 ), and also hub proteins associated with metal-DMRs only but with relevant connections with atherosclerosis effectors (e.g. SSTR5 , HDAC4 , AP2A2 , CXCL12 and SSTR4 ). Our integrative in silico analysis demonstrates the feasibility of identifying epigenomic regions linked to environmental exposures and potentially involved in relevant pathways for human diseases. While our results support the hypothesis that metal exposures can influence health due to epigenetic changes, larger studies are needed to confirm our pilot results.This article is part of a discussion meeting issue 'Frontiers in epigenetic chemical biology'. © 2018 The Author(s).

Relevance of the Axis Spermidine/eIF5A for Plant Growth and Development

PubMed Central

Belda-Palazón, Borja; Almendáriz, Carla; Martí, Esmeralda; Carbonell, Juan; Ferrando, Alejandro

2016-01-01

One key role of the essential polyamine spermidine in eukaryotes is to provide the 4-aminobutyl moiety group destined to the post-translational modification of a lysine in the highly conserved translation factor eIF5A. This modification is catalyzed by two sequential enzymatic steps leading to the activation of eIF5A by the conversion of one conserved lysine to the unusual amino acid hypusine. The active translation factor facilitates the sequence-specific translation of polyproline sequences that otherwise cause ribosome stalling. In spite of the well-characterized involvement of active eIF5A in the translation of proline repeat-rich proteins, its biological role has been recently elucidated only in mammals, and it is poorly described at the functional level in plants. Here we describe the alterations in plant growth and development caused by RNAi-mediated conditional genetic inactivation of the hypusination pathway in Arabidopsis thaliana by knocking-down the enzyme deoxyhypusine synthase. We have uncovered that spermidine-mediated activation of eIF5A by hypusination is involved in several aspects of plant biology such as the control of flowering time, the aerial and root architecture, and root hair growth. In addition this pathway is required for adaptation to challenging growth conditions such as high salt and high glucose medium and to elevated concentrations of the plant hormone ABA. We have also performed a bioinformatic analysis of polyproline-rich containing proteins as putative eIF5A targets to uncover their organization in clusters of protein networks to find molecular culprits for the disclosed phenotypes. This study represents a first attempt to provide a holistic view of the biological relevance of the spermidine-dependent hypusination pathway for plant growth and development. PMID:26973686

Deriving Signatures of In Vivo Toxicity Using Both Efficacy and Potency Information from In Vitro Assays: Evaluating Model Performance as a Function of Increasing Variability in Experimental Data

EPA Science Inventory

The US EPA ToxCast program aims to develop methods for mechanistically-based chemical prioritization using a suite of high throughput, in vitro assays that probe relevant biological pathways, and coupling them with statistical and machine learning methods that produce predictive ...

Reverse engineering the mechanical and molecular pathways in stem cell morphogenesis.

PubMed

Lu, Kai; Gordon, Richard; Cao, Tong

2015-03-01

The formation of relevant biological structures poses a challenge for regenerative medicine. During embryogenesis, embryonic cells differentiate into somatic tissues and undergo morphogenesis to produce three-dimensional organs. Using stem cells, we can recapitulate this process and create biological constructs for therapeutic transplantation. However, imperfect imitation of nature sometimes results in in vitro artifacts that fail to recapitulate the function of native organs. It has been hypothesized that developing cells may self-organize into tissue-specific structures given a correct in vitro environment. This proposition is supported by the generation of neo-organoids from stem cells. We suggest that morphogenesis may be reverse engineered to uncover its interacting mechanical pathway and molecular circuitry. By harnessing the latent architecture of stem cells, novel tissue-engineering strategies may be conceptualized for generating self-organizing transplants. Copyright © 2013 John Wiley & Sons, Ltd.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

Parameter space exploration within dynamic simulations of signaling networks.

PubMed

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

2013-02-01

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

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.

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biologics that inhibit the Th17 pathway and related cytokines to treat inflammatory disorders.

PubMed

Balato, Anna; Scala, Emanuele; Balato, Nicola; Caiazzo, Giuseppina; Di Caprio, Roberta; Monfrecola, Giuseppe; Raimondo, Annunziata; Lembo, Serena; Ayala, Fabio

2017-11-01

Advances in the understanding of TNF-α and IL-17 synergistic functions have recently led to the concept that patients who do not respond or who respond inadequately to TNF-α inhibitors may have IL-17-driven diseases, opening up the way for a new class of therapeutic development: Th17-inhibitors. Areas covered: In this review, the authors discuss the central role that the IL-23/Th17 axis plays in the pathogenesis of several inflammatory diseases, such as psoriasis, highlighting its position as a relevant therapeutic target. In particular, the authors start by giving a brief historical excursus on biologic agent development up until the success of TNF-α inhibitors, and continue with an overview of IL12/23 pathway inhibition. Next, they describe Th17 cell biology, focusing on the role of IL-17 in host defense and in human immune-inflammatory diseases, discussing the use and side effects of IL-17 inhibitors. Expert opinion: The IL-23/Th17 signaling pathway plays a central role in the pathogenesis of several inflammatory diseases, such as psoriasis. Recent data has demonstrated that biologics neutralizing IL-17 (ixekizumab, secukinumab) or its receptor (brodalumab) are highly effective with a positive safety profile in treating moderate to severe psoriasis, offering new treatment possibilities, especially for patients who do not respond adequately to anti-TNF-α therapies.

Adverse outcome pathways: a concise introduction for toxicologists

PubMed Central

Vergauwen, Lucia; Hengstler, Jan G.; Angrish, Michelle; Whelan, Maurice

2018-01-01

Adverse outcome pathways are designed to provide a clear-cut mechanistic representation of critical toxicological effects that propagate over different layers of biological organization from the initial interaction of a chemical with a molecular target to an adverse outcome at the individual or population level. Adverse outcome pathways are currently gaining momentum, especially in view of their many potential applications as pragmatic tools in the fields of human toxicology, ecotoxicology and risk assessment. A number of guidance documents, issued by the Organization for Economic Cooperation and Development, as well as landmark papers, outlining best practices to develop, assess and use adverse outcome pathways, have been published in the last few years. The present paper provides a synopsis of the main principles related to the adverse outcome pathway framework for the toxicologist less familiar with this area, followed by two case studies relevant for human toxicology and ecotoxicology. PMID:28660287

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.

Planar cell polarity pathway in vertebrate epidermal development, homeostasis and repair

PubMed Central

Dworkin, Sebastian; Jane, Stephen M

2011-01-01

The planar cell polarity (PCP) pathway plays a critical role in diverse developmental processes that require coordinated cellular movement, including neural tube closure and renal tubulogenesis. Recent studies have demonstrated that this pathway also has emerging relevance to the epidermis, as PCP signaling underpins many aspects of skin biology and pathology, including epidermal development, hair orientation, stem cell division and cancer. Coordinated cellular movement required for epidermal repair in mammals is also regulated by PCP signaling, and in this context, a new PCP gene encoding the developmental transcription factor Grainyhead-like 3 (Grhl3) is critical. This review focuses on the role that PCP signaling plays in the skin across a variety of epidermal functions and highlights perturbations that induce epidermal pathologies. PMID:22041517

Clinical and Biological Relevance of Genomic Heterogeneity in Chronic Lymphocytic Leukemia

PubMed Central

Friedman, Daphne R.; Lucas, Joseph E.; Weinberg, J. Brice

2013-01-01

Background Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients’ leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL. Methods To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups. Results Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes. Conclusions Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways. PMID:23468975

Clinical and biological relevance of genomic heterogeneity in chronic lymphocytic leukemia.

PubMed

Friedman, Daphne R; Lucas, Joseph E; Weinberg, J Brice

2013-01-01

Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients' leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL. To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups. Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes. Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways.

Contributions of DNA repair and damage response pathways to the non-linear genotoxic responses of alkylating agents

PubMed Central

Klapacz, Joanna; Pottenger, Lynn H.; Engelward, Bevin P.; Heinen, Christopher D.; Johnson, George E.; Clewell, Rebecca A.; Carmichael, Paul L.; Adeleye, Yeyejide; Andersen, Melvin E.

2016-01-01

From a risk assessment perspective, DNA-reactive agents are conventionally assumed to have genotoxic risks at all exposure levels, thus applying a linear extrapolation for low-dose responses. New approaches discussed here, including more diverse and sensitive methods for assessing DNA damage and DNA repair, strongly support the existence of measurable regions where genotoxic responses with increasing doses are insignificant relative to control. Model monofunctional alkylating agents have in vitro and in vivo datasets amenable to determination of points of departure (PoDs) for genotoxic effects. A session at the 2013 Society of Toxicology meeting provided an opportunity to survey the progress in understanding the biological basis of empirically-observed PoDs for DNA alkylating agents. Together with the literature published since, this review discusses cellular pathways activated by endogenous and exogenous alkylation DNA damage. Cells have evolved conserved processes that monitor and counteract a spontaneous steady-state level of DNA damage. The ubiquitous network of DNA repair pathways serves as the first line of defense for clearing of the DNA damage and preventing mutation. Other biological pathways discussed here that are activated by genotoxic stress include post-translational activation of cell cycle networks and transcriptional networks for apoptosis/cell death. The interactions of various DNA repair and DNA damage response pathways provide biological bases for the observed PoD behaviors seen with genotoxic compounds. Thus, after formation of DNA adducts, the activation of cellular pathways can lead to the avoidance a mutagenic outcome. The understanding of the cellular mechanisms acting within the low-dose region will serve to better characterize risks from exposures to DNA-reactive agents at environmentally-relevant concentrations. PMID:27036068

Contributions of DNA repair and damage response pathways to the non-linear genotoxic responses of alkylating agents.

PubMed

Klapacz, Joanna; Pottenger, Lynn H; Engelward, Bevin P; Heinen, Christopher D; Johnson, George E; Clewell, Rebecca A; Carmichael, Paul L; Adeleye, Yeyejide; Andersen, Melvin E

2016-01-01

From a risk assessment perspective, DNA-reactive agents are conventionally assumed to have genotoxic risks at all exposure levels, thus applying a linear extrapolation for low-dose responses. New approaches discussed here, including more diverse and sensitive methods for assessing DNA damage and DNA repair, strongly support the existence of measurable regions where genotoxic responses with increasing doses are insignificant relative to control. Model monofunctional alkylating agents have in vitro and in vivo datasets amenable to determination of points of departure (PoDs) for genotoxic effects. A session at the 2013 Society of Toxicology meeting provided an opportunity to survey the progress in understanding the biological basis of empirically-observed PoDs for DNA alkylating agents. Together with the literature published since, this review discusses cellular pathways activated by endogenous and exogenous alkylation DNA damage. Cells have evolved conserved processes that monitor and counteract a spontaneous steady-state level of DNA damage. The ubiquitous network of DNA repair pathways serves as the first line of defense for clearing of the DNA damage and preventing mutation. Other biological pathways discussed here that are activated by genotoxic stress include post-translational activation of cell cycle networks and transcriptional networks for apoptosis/cell death. The interactions of various DNA repair and DNA damage response pathways provide biological bases for the observed PoD behaviors seen with genotoxic compounds. Thus, after formation of DNA adducts, the activation of cellular pathways can lead to the avoidance of a mutagenic outcome. The understanding of the cellular mechanisms acting within the low-dose region will serve to better characterize risks from exposures to DNA-reactive agents at environmentally-relevant concentrations. Copyright © 2015 Elsevier B.V. All rights reserved.

TOXICITY TESTING IN THE 21ST CENTURY: A VISION AND A STRATEGY

PubMed Central

Krewski, Daniel; Acosta, Daniel; Andersen, Melvin; Anderson, Henry; Bailar, John C.; Boekelheide, Kim; Brent, Robert; Charnley, Gail; Cheung, Vivian G.; Green, Sidney; Kelsey, Karl T.; Kerkvliet, Nancy I.; Li, Abby A.; McCray, Lawrence; Meyer, Otto; Patterson, Reid D.; Pennie, William; Scala, Robert A.; Solomon, Gina M.; Stephens, Martin; Yager, James; Zeise, Lauren

2015-01-01

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology. PMID:20574894

Systems Toxicology: Real World Applications and Opportunities.

PubMed

Hartung, Thomas; FitzGerald, Rex E; Jennings, Paul; Mirams, Gary R; Peitsch, Manuel C; Rostami-Hodjegan, Amin; Shah, Imran; Wilks, Martin F; Sturla, Shana J

2017-04-17

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity.

Systems Toxicology: Real World Applications and Opportunities

PubMed Central

2017-01-01

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams (“big data”), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity. PMID:28362102

Exploring the pathways leading from disadvantage to end-stage renal disease for indigenous Australians.

PubMed

Cass, Alan; Cunningham, Joan; Snelling, Paul; Wang, Zhiqiang; Hoy, Wendy

2004-02-01

Indigenous Australians are disadvantaged, relative to other Australians, over a range of socio-economic and health measures. The age- and sex-adjusted incidence of end-stage renal disease (ESRD)--the irreversible preterminal phase of chronic renal failure--is almost nine times higher amongst Indigenous than it is amongst non-indigenous Australians. A striking gradient exists from urban to remote regions, where the standardised ESRD incidence is from 20 to more than 30 times the national incidence. We discuss the profound impact of renal disease on Indigenous Australians and their communities. We explore the linkages between disadvantage, often accompanied by geographic isolation, and both the initiation of renal disease, and its progression to ESRD. Purported explanations for the excess burden of renal disease in indigenous populations can be categorised as: primary renal disease explanations;genetic explanations;early development explanations; and socio-economic explanations. We discuss the strengths and weaknesses of these explanations and suggest a new hypothesis which integrates the existing evidence. We use this hypothesis to illuminate the pathways between disadvantage and the human biological processes which culminate in ESRD, and to propose prevention strategies across the life-course of Indigenous Australians to reduce their ESRD risk. Our hypothesis is likely to be relevant to an understanding of patterns of renal disease in other high-risk populations, particularly indigenous people in the developed world and people in developing countries. Furthermore, analogous pathways might be relevant to other chronic diseases, such as diabetes and cardiovascular disease. If we are able to confirm the various pathways from disadvantage to human biology, we will be better placed to advocate evidence-based interventions, both within and beyond the scope of the health-care system, to address the excess burden of renal and other chronic diseases among affected populations.

Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

PubMed

Ng; Wong

1999-01-01

We are entering a new era of research where the latest scientific discoveries are often first reported online and are readily accessible by scientists worldwide. This rapid electronic dissemination of research breakthroughs has greatly accelerated the current pace in genomics and proteomics research. The race to the discovery of a gene or a drug has now become increasingly dependent on how quickly a scientist can scan through voluminous amount of information available online to construct the relevant picture (such as protein-protein interaction pathways) as it takes shape amongst the rapidly expanding pool of globally accessible biological data (e.g. GENBANK) and scientific literature (e.g. MEDLINE). We describe a prototype system for automatic pathway discovery from on-line text abstracts, combining technologies that (1) retrieve research abstracts from online sources, (2) extract relevant information from the free texts, and (3) present the extracted information graphically and intuitively. Our work demonstrates that this framework allows us to routinely scan online scientific literature for automatic discovery of knowledge, giving modern scientists the necessary competitive edge in managing the information explosion in this electronic age.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

PubMed

Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

2010-10-07

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

PubMed Central

2010-01-01

Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease. PMID:20929581

Developing and applying the adverse outcome pathway ...

EPA Pesticide Factsheets

To support a paradigm shift in regulatory toxicology testing and risk assessment, the Adverse Outcome Pathway (AOP) concept has recently been proposed. This concept is similar to that for Mode of Action (MOA), describing a sequence of measurable key events triggered by a molecular initiating event in which a stressor interacts with a biological target. The resulting cascade of key events includes molecular, cellular, structural and functional changes in biological systems, resulting in a measurable adverse outcome. Thereby, an AOP ideally provides information relevant to chemical structure-activity relationships as a basis to predict effects for structurally similar compounds. AOPs could potentially also form the basis for qualitative and quantitative predictive modeling of the human adverse outcome resulting from molecular initiating or other key events for which higher-throughput testing methods are available or can be developed.A variety of cellular and molecular processes are known to be critical to normal function of the central (CNS) and peripheral nervous systems (PNS). Because of the biological and functional complexity of the CNS and PNS, it has been challenging to establish causative links and quantitative relationships between key events that comprise the pathways leading from chemical exposure to an adverse outcome in the nervous system. Following introduction of principles of the description and assessment of MOA and AOPs, examples of adverse out

A tiered approach for integrating exposure and dosimetry with ...

EPA Pesticide Factsheets

High-throughput (HT) risk screening approaches apply in vitro dose-response data to estimate potential health risks that arise from exposure to chemicals. However, much uncertainty is inherent in relating bioactivities observed in an in vitro system to the perturbations of biological mechanisms that lead to apical adverse health outcomes in living organisms. The chemical-agnostic Adverse Outcome Pathway (AOP) framework addresses this uncertainty by acting as a scaffold onto which pathway-based data can be arranged to aid in the understanding of in vitro toxicity testing results. In addition, risk estimation also requires reconciling chemical concentrations sufficient to produce bioactivity in vitro with concentrations that trigger a molecular initiating event (MIE) at the relevant biological target in vivo. Such target site exposures (TSEs) can be estimated using computational models to integrate exposure information with a chemical’s absorption, distribution, metabolism, and elimination (ADME) processes. In this presentation, the utility of a tiered approach for integrating exposure, ADME, and hazard into risk-based decision making will be demonstrated using several case studies, along with the investigation of how uncertainties in exposure and ADME might impact risk estimates. These case studies involve 1) identifying and prioritizing chemicals capable of altering biological pathways based on their potential to reach an in vivo target; 2) evaluating the infl

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

Recent advances in understanding the biology of marginal zone lymphoma

PubMed Central

Zucca, Emanuele

2018-01-01

There are three different marginal zone lymphomas (MZLs): the extranodal MZL of mucosa-associated lymphoid tissue (MALT) type (MALT lymphoma), the splenic MZL, and the nodal MZL. The three MZLs share common lesions and deregulated pathways but also present specific alterations that can be used for their differential diagnosis. Although trisomies of chromosomes 3 and 18, deletions at 6q23, deregulation of nuclear factor kappa B, and chromatin remodeling genes are frequent events in all of them, the three MZLs differ in the presence of recurrent translocations, mutations affecting the NOTCH pathway, and the transcription factor Kruppel like factor 2 ( KLF2) or the receptor-type protein tyrosine phosphatase delta ( PTPRD). Since a better understanding of the molecular events underlying each subtype may have practical relevance, this review summarizes the most recent and main advances in our understanding of the genetics and biology of MZLs. PMID:29657712

[3D structure of DKK1 indicates its involvement in both canonical and non-canonical Wnt pathways].

PubMed

Khalili, S; Rasaee, M J; Bamdad, T

2017-01-01

Dikkoppf-1 (DKK1) is an antagonist of the canonical Wnt signaling pathway. The importance of DKK1 as a diagnostic and therapeutic agent in a wide range of diseases along with its significance in a variety of biological processes accentuate the necessity to decipher its 3D structure that would pave the way towards the development of relevant selective inhibitors. A DKK1 structure model predicted by the Robetta server with structural refinements including a 10 ns molecular dynamics run was subjected to functional and docking analyses. We hypothesize that the N-terminal region of the DKK1 molecule could be functionally important for both canonical and noncanonical Wnt pathways. Moreover, it seems that DKK1 could be involved in interactions with the Frizzled receptors, leading to the activation of the Planar Cell Polarity (PCP) pathway (activation of Jun N-terminal kinase (JNK) Pathway) and Wnt/Ca^(2+) pathway (activation of CamKII).

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

Molecular Pharmacology of Malignant Pleural Mesothelioma: Challenges and Perspectives From Preclinical and Clinical Studies.

PubMed

Thellung, Stefano; Favoni, Roberto E; Würth, Roberto; Nizzari, Mario; Pattarozzi, Alessandra; Daga, Antonio; Florio, Tullio; Barbieri, Federica

2016-01-01

Malignant pleural mesothelioma (MPM) is one of the deadliest and most heterogeneous tumors, highly refractory to multimodal therapeutic approach, including surgery, chemo- and radiotherapy. Preclinical and clinical studies exploring the efficacy of drugs targeting tyrosine kinases, angiogenesis and histone deacetylases, did not fulfil the expected clinical benefits. Thus, novel molecular targets should be identified from a definite knowledge of the unique biology and most relevant transduction pathways of MPM cells. Cancer stem cells (CSCs) are a subset of malignant precursors responsible for initiation, progression, resistance to cytotoxic drugs, recurrence and metastatic diffusion of tumor cells. CSCs are putative driving factors for MPM development and contribute to its clinical and biological heterogeneity; hence, targeted eradication of CSCs represents an ineludible goal to counteract MPM aggressiveness. In this context, innovative preclinical models could be exploited to identify novel intracellular pathway inhibitors able to target CSC viability. Novel drug targets have been identified among key factors responsible for the oncogenic transformation of mesothelial cells, often directly induced by asbestos. These include mitogenic and anti-apoptotic signaling that may also be activated by autocrine and paracrine cytokine pathways controlling cell plasticity. Both signaling pathways affecting proto-oncogene and transcription factor expression, or genetic and epigenetic alterations, such as mutations in cell cycle genes and silencing of tumor suppressor genes, represent promising disease-specific targets. In this review we describe current knowledge of MPM cell biology, focusing on potential targets to be tested in pharmacological studies, and highlighting results and challenges of clinical translation.

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

Production of bulk chemicals via novel metabolic pathways in microorganisms.

PubMed

Shin, Jae Ho; Kim, Hyun Uk; Kim, Dong In; Lee, Sang Yup

2013-11-01

Metabolic engineering has been playing important roles in developing high performance microorganisms capable of producing various chemicals and materials from renewable biomass in a sustainable manner. Synthetic and systems biology are also contributing significantly to the creation of novel pathways and the whole cell-wide optimization of metabolic performance, respectively. In order to expand the spectrum of chemicals that can be produced biotechnologically, it is necessary to broaden the metabolic capacities of microorganisms. Expanding the metabolic pathways for biosynthesizing the target chemicals requires not only the enumeration of a series of known enzymes, but also the identification of biochemical gaps whose corresponding enzymes might not actually exist in nature; this issue is the focus of this paper. First, pathway prediction tools, effectively combining reactions that lead to the production of a target chemical, are analyzed in terms of logics representing chemical information, and designing and ranking the proposed metabolic pathways. Then, several approaches for potentially filling in the gaps of the novel metabolic pathway are suggested along with relevant examples, including the use of promiscuous enzymes that flexibly utilize different substrates, design of novel enzymes for non-natural reactions, and exploration of hypothetical proteins. Finally, strain optimization by systems metabolic engineering in the context of novel metabolic pathways constructed is briefly described. It is hoped that this review paper will provide logical ways of efficiently utilizing 'big' biological data to design and develop novel metabolic pathways for the production of various bulk chemicals that are currently produced from fossil resources. Copyright © 2012 Elsevier Inc. All rights reserved.

Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set

PubMed Central

Zhang, Jintao; Lushington, Gerald H.; Huan, Jun

2011-01-01

The NIH Molecular Libraries Initiative (MLI), launched in 2004 with initial goals of identifying chemical probes for characterizing gene function and druggability, has produced PubChem, a chemical genomics knowledgebase for fostering translation of basic research into new therapeutic strategies. This paper assesses progress toward these goals by evaluating MLI target novelty and propensity for undergoing biochemically or therapeutically relevant modulations and the degree of chemical diversity and biogenic bias inherent in the MLI screening set. Our analyses suggest that while MLI target selection has not yet been fully optimized for biochemical diversity, it covers biologically interesting pathway space that complements established drug targets. We find the MLI screening set to be chemically diverse and to have greater biogenic bias than comparable collections of commercially available compounds. Biogenic enhancements such as incorporation of more metabolite-like chemotypes are suggested. PMID:21568288

NO ICE HYDROGENATION: A SOLID PATHWAY TO NH{sub 2}OH FORMATION IN SPACE

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

Congiu, Emanuele; Dulieu, Francois; Chaabouni, Henda

2012-05-01

Icy dust grains in space act as catalytic surfaces onto which complex molecules form. These molecules are synthesized through exothermic reactions from precursor radicals and, mostly, hydrogen atom additions. Among the resulting products are species of biological relevance, such as hydroxylamine-NH{sub 2}OH-a precursor molecule in the formation of amino acids. In this Letter, laboratory experiments are described that demonstrate NH{sub 2}OH formation in interstellar ice analogs for astronomically relevant temperatures via successive hydrogenation reactions of solid nitric oxide (NO). Inclusion of the experimental results in an astrochemical gas-grain model proves the importance of a solid-state NO+H reaction channel as amore » starting point for prebiotic species in dark interstellar clouds and adds a new perspective to the way molecules of biological importance may form in space.« less

Acetylene-based pathways for prebiotic evolution on Titan

NASA Astrophysics Data System (ADS)

Abbas, O.; Schulze-Makuch, D.

2002-11-01

Due to Titan's reducing atmosphere and lack of an ozone shield, ionizing radiation penetrates the atmosphere creating ions, radicals and electrons that are highly reactive producing versatile chemical species on Titan's surface. We propose that the catalytic hydrogenation of photochemically produced acetylene may be used as simple metabolic pathway by organisms at or near Titan's surface. While the acetylene may undergo this reaction, it can also undertake several other multi-step synthetic schemes that eventually lead to the production of amino acids or other biologically important molecules. Four model synthetic schemes will be described, and their relevance in relation to prebiotic evolution on Earth is discussed.

Simulation and estimation of gene number in a biological pathway using almost complete saturation mutagenesis screening of haploid mouse cells.

PubMed

Tokunaga, Masahiro; Kokubu, Chikara; Maeda, Yusuke; Sese, Jun; Horie, Kyoji; Sugimoto, Nakaba; Kinoshita, Taroh; Yusa, Kosuke; Takeda, Junji

2014-11-24

Genome-wide saturation mutagenesis and subsequent phenotype-driven screening has been central to a comprehensive understanding of complex biological processes in classical model organisms such as flies, nematodes, and plants. The degree of "saturation" (i.e., the fraction of possible target genes identified) has been shown to be a critical parameter in determining all relevant genes involved in a biological function, without prior knowledge of their products. In mammalian model systems, however, the relatively large scale and labor intensity of experiments have hampered the achievement of actual saturation mutagenesis, especially for recessive traits that require biallelic mutations to manifest detectable phenotypes. By exploiting the recently established haploid mouse embryonic stem cells (ESCs), we present an implementation of almost complete saturation mutagenesis in a mammalian system. The haploid ESCs were mutagenized with the chemical mutagen N-ethyl-N-nitrosourea (ENU) and processed for the screening of mutants defective in various steps of the glycosylphosphatidylinositol-anchor biosynthetic pathway. The resulting 114 independent mutant clones were characterized by a functional complementation assay, and were shown to be defective in any of 20 genes among all 22 known genes essential for this well-characterized pathway. Ten mutants were further validated by whole-exome sequencing. The predominant generation of single-nucleotide substitutions by ENU resulted in a gene mutation rate proportional to the length of the coding sequence, which facilitated the experimental design of saturation mutagenesis screening with the aid of computational simulation. Our study enables mammalian saturation mutagenesis to become a realistic proposition. Computational simulation, combined with a pilot mutagenesis experiment, could serve as a tool for the estimation of the number of genes essential for biological processes such as drug target pathways when a positive selection of mutants is available.

Biology and Clinical Relevance of Acute Myeloid Leukemia Stem Cells.

PubMed

Reinisch, Andreas; Chan, Steven M; Thomas, Daniel; Majeti, Ravindra

2015-07-01

Evidence for the cancer stem cell model was first demonstrated in xenotransplanted blood and bone marrow samples from patients with acute myeloid leukemia (AML) almost two decades ago, supporting the concept that a rare clonal and mutated leukemic stem cell (LSC) population is sufficient to drive leukemic growth. The inability to eliminate LSCs with conventional therapies is thought to be the primary cause of disease relapse in AML patients, and as such, novel therapies with the ability to target this population are required to improve patient outcomes. An important step towards this goal is the identification of common immunophenotypic surface markers and biological properties that distinguish LSCs from normal hematopoietic stem and progenitor cells (HSPCs) across AML patients. This work has resulted in the development of a large number of potential LSC-selective therapies that target cell surface molecules, intracellular signaling pathways, and the bone marrow microenvironment. Here, we will review the basic biology, immunophenotypic detection, and clinical relevance of LSCs, as well as emerging biological and small-molecule strategies that either directly target LSCs or indirectly target these cells through modulation of their microenvironment. Copyright © 2015 Elsevier Inc. All rights reserved.

Formation of biologically relevant carboxylic acids during the gamma irradiation of acetic acid

NASA Technical Reports Server (NTRS)

Negron-Mendoza, A.; Ponnamperuma, C.

1976-01-01

Irradiation of aqueous solutions of acetic acid with gamma rays produced several carboxylic acids in small yield. Their identification was based on the technique of gas chromatography combined with mass spectrometry. Some of these acids are Krebs Cycle intermediates. Their simultaneous formation in experiments simulating the primitive conditions on the earth suggests that metabolic pathways may have had their origin in prebiotic chemical processes.

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.

JAKs and STATs in Immunoregulation and Immune-Mediated Disease

PubMed Central

O’Shea, John J.; Plenge, Robert

2012-01-01

Summary A landmark in cell biology, the discovery of the JAK-STAT pathway provided a simple mechanism for gene regulation that dramatically advanced our understanding of the action of hormones, interferons, colony stimulating factors, and interleukins. As we learn more about the complexities of immune responses, new insights into the functions of this pathway continue to be revealed, aided by technology that permits genomewide views. As we celebrate the 20th anniversary of the discovery of this paradigm in cell signaling, it is particularly edifying to see how this knowledge has rapidly been translated to human immune disease. Not only have genomewide association studies demonstrated that this pathway is highly relevant to human autoimmunity but targeting JAKs is now a reality in immune-mediated disease. PMID:22520847

Designing microarray and RNA-Seq experiments for greater systems biology discovery in modern plant genomics.

PubMed

Yang, Chuanping; Wei, Hairong

2015-02-01

Microarray and RNA-seq experiments have become an important part of modern genomics and systems biology. Obtaining meaningful biological data from these experiments is an arduous task that demands close attention to many details. Negligence at any step can lead to gene expression data containing inadequate or composite information that is recalcitrant for pattern extraction. Therefore, it is imperative to carefully consider experimental design before launching a time-consuming and costly experiment. Contemporarily, most genomics experiments have two objectives: (1) to generate two or more groups of comparable data for identifying differentially expressed genes, gene families, biological processes, or metabolic pathways under experimental conditions; (2) to build local gene regulatory networks and identify hierarchically important regulators governing biological processes and pathways of interest. Since the first objective aims to identify the active molecular identities and the second provides a basis for understanding the underlying molecular mechanisms through inferring causality relationships mediated by treatment, an optimal experiment is to produce biologically relevant and extractable data to meet both objectives without substantially increasing the cost. This review discusses the major issues that researchers commonly face when embarking on microarray or RNA-seq experiments and summarizes important aspects of experimental design, which aim to help researchers deliberate how to generate gene expression profiles with low background noise but with more interaction to facilitate novel biological discoveries in modern plant genomics. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

High Throughput Screening for Inhibitors of Mycobacterium tuberculosis H37Rv

PubMed Central

ANANTHAN, SUBRAMANIAM; FAALEOLEA, ELLEN R.; GOLDMAN, ROBERT C.; HOBRATH, JUDITH V.; KWONG, CECIL D.; LAUGHON, BARBARA E.; MADDRY, JOSEPH A.; MEHTA, ALKA; RASMUSSEN, LYNN; REYNOLDS, ROBERT C.; SECRIST, JOHN A.; SHINDO, NICE; SHOWE, DUSTIN N.; SOSA, MELINDA I.; SULING, WILLIAM J.; WHITE, E. LUCILE

2009-01-01

SUMMARY There is an urgent need for the discovery and development of new antitubercular agents that target new biochemical pathways and treat drug resistant forms of the disease. One approach to addressing this need is through high throughput screening of medicinally relevant libraries against the whole bacterium in order to discover a variety of new, active scaffolds that will stimulate new biological research and drug discovery. Through the Tuberculosis Antimicrobial Acquisition and Coordinating Facility (www.taacf.org), a large, medicinally relevant chemical library was screened against M. tuberculosis strain H37Rv. The screening methods and a medicinal chemistry analysis of the results are reported herein. PMID:19758845

Environmental chemicals and breast cancer: An updated review of epidemiological literature informed by biological mechanisms.

PubMed

Rodgers, Kathryn M; Udesky, Julia O; Rudel, Ruthann A; Brody, Julia Green

2018-01-01

Many common environmental chemicals are mammary gland carcinogens in animal studies, activate relevant hormonal pathways, or enhance mammary gland susceptibility to carcinogenesis. Breast cancer's long latency and multifactorial etiology make evaluation of these chemicals in humans challenging. For chemicals previously identified as mammary gland toxicants, we evaluated epidemiologic studies published since our 2007 review. We assessed whether study designs captured relevant exposures and disease features suggested by toxicological and biological evidence of genotoxicity, endocrine disruption, tumor promotion, or disruption of mammary gland development. We systematically searched the PubMed database for articles with breast cancer outcomes published in 2006-2016 using terms for 134 environmental chemicals, sources, or biomarkers of exposure. We critically reviewed the articles. We identified 158 articles. Consistent with experimental evidence, a few key studies suggested higher risk for exposures during breast development to dichlorodiphenyltrichloroethane (DDT), dioxins, perfluorooctane-sulfonamide (PFOSA), and air pollution (risk estimates ranged from 2.14 to 5.0), and for occupational exposure to solvents and other mammary carcinogens, such as gasoline components (risk estimates ranged from 1.42 to 3.31). Notably, one 50-year cohort study captured exposure to DDT during several critical windows for breast development (in utero, adolescence, pregnancy) and when this chemical was still in use. Most other studies did not assess exposure during a biologically relevant window or specify the timing of exposure. Few studies considered genetic variation, but the Long Island Breast Cancer Study Project reported higher breast cancer risk for polycyclic aromatic hydrocarbons (PAHs) in women with certain genetic variations, especially in DNA repair genes. New studies that targeted toxicologically relevant chemicals and captured biological hypotheses about genetic variants or windows of breast susceptibility added to evidence of links between environmental chemicals and breast cancer. However, many biologically relevant chemicals, including current-use consumer product chemicals, have not been adequately studied in humans. Studies are challenged to reconstruct exposures that occurred decades before diagnosis or access biological samples stored that long. Other problems include measuring rapidly metabolized chemicals and evaluating exposure to mixtures. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Metabolite damage and repair in metabolic engineering design.

PubMed

Sun, Jiayi; Jeffryes, James G; Henry, Christopher S; Bruner, Steven D; Hanson, Andrew D

2017-11-01

The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields, and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects. Copyright © 2017 International Metabolic Engineering Society. All rights reserved.

Integrated omics analysis of specialized metabolism in medicinal plants.

PubMed

Rai, Amit; Saito, Kazuki; Yamazaki, Mami

2017-05-01

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Application of Adverse Outcome Pathways (AOPs) in Human ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making. Because many fundamental molecular and cellular pathways are conserved across taxa, data from assays that screen chemicals for their ability to interact with specific biomolecular targets can often be credibly applied to a broad range of species, even if the apical outcomes of those perturbations may differ. Information concerning the different trajectories of adversity that molecular initiating events may take in different taxa, life stages, and sexes of organisms can be captured in the form of an AOP network. As an example, AOPs documenting divergent consequences of thyroid peroxidase (TPO) and deiodinase (DIO) inhibition in mammals, amphibians, and fish have been developed. These AOPs provide the foundation for using data from common in vitro assays for TPO or DIO activity to inform both human health and ecological risk assessments. They also provide the foundation for an integrated approach to testing and assessment, where available information and biological understanding can be integrated in order to formulate plausible and testable hypotheses which can be used to target in vivo testing on the endpoints of greatest concern. Application of this AOP knowledge in several different r

Application of adverse outcome pathways (AOPs) in human ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making. Because many fundamental molecular and cellular pathways are conserved across taxa, data from assays that screen chemicals for their ability to interact with specific biomolecular targets can often be credibly applied to a broad range of species, even if the apical outcomes of those perturbations may differ. Information concerning the different trajectories of adversity that molecular initiating events may take in different taxa, life stages, and sexes of organisms can be captured in the form of an AOP network. As an example, AOPs documenting divergent consequences of thyroid peroxidase (TPO) and deiodinase (DIO) inhibition in mammals, amphibians, and fish have been developed. These AOPs provide the foundation for using data from common in vitro assays for TPO or DIO activity to inform both human health and ecological risk assessments. They also provide the foundation for an integrated approach to testing and assessment, where available information and biological understanding can be integrated in order to formulate plausible and testable hypotheses which can be used to target in vivo testing on the endpoints of greatest concern. Application of this AOP knowledge in several different r

Metabolite damage and repair in metabolic engineering design

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

Sun, Jiayi; Jeffryes, James G.; Henry, Christopher S.

The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields,more » and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects.« less

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.

Glycyrrhizin, silymarin, and ursodeoxycholic acid regulate a common hepatoprotective pathway in HepG2 cells.

PubMed

Hsiang, Chien-Yun; Lin, Li-Jen; Kao, Shung-Te; Lo, Hsin-Yi; Chou, Shun-Ting; Ho, Tin-Yun

2015-07-15

Glycyrrhizin, silymarin, and ursodeoxycholic acid are widely used hepatoprotectants for the treatment of liver disorders, such as hepatitis C virus infection, primary biliary cirrhosis, and hepatocellular carcinoma. The gene expression profiles of HepG2 cells responsive to glycyrrhizin, silymarin, and ursodeoxycholic acid were analyzed in this study. HepG2 cells were treated with 25 µM hepatoprotectants for 24 h. Gene expression profiles of hepatoprotectants-treated cells were analyzed by oligonucleotide microarray in triplicates. Nuclear factor-κB (NF-κB) activities were assessed by luciferase assay. Among a total of 30,968 genes, 252 genes were commonly regulated by glycyrrhizin, silymarin, and ursodeoxycholic acid. These compounds affected the expression of genes relevant various biological pathways, such as neurotransmission, and glucose and lipid metabolism. Genes involved in hepatocarcinogenesis, apoptosis, and anti-oxidative pathways were differentially regulated by all compounds. Moreover, interaction networks showed that NF-κB might play a central role in the regulation of gene expression. Further analysis revealed that these hepatoprotectants inhibited NF-κB activities in a dose-dependent manner. Our data suggested that glycyrrhizin, silymarin, and ursodeoxycholic acid regulated the expression of genes relevant to apoptosis and oxidative stress in HepG2 cells. Moreover, the regulation by these hepatoprotectants might be relevant to the suppression of NF-κB activities. Copyright © 2015 Elsevier GmbH. All rights reserved.

Genome-wide expression profiling in the peripheral blood of patients with fibromyalgia

PubMed Central

Jones, Kim D.; Gelbart, Terri; Whisenant, Thomas C.; Waalen, Jill; Mondala, Tony S.; Iklé, David N.; Salomon, Daniel R.; Bennett, Robert M.; Kurian, Sunil M.

2016-01-01

Objective Fibromyalgia (FM) is a common pain disorder characterised by nociceptive dysregulation. The basic biology of FM is poorly understood. Herein we have used agnostic gene expression as a potential probe for informing its underlying biology and the development of a proof-of-concept diagnostic gene expression signature. Methods We analysed RNA expression in 70 FM patients and 70 healthy controls. The isolated RNA was amplified and hybridised to Affymetrix® Human Gene 1.1 ST Peg arrays. The data was analysed using Partek Genomics Suite v. 6.6. Results Fibromyalgia patients exhibited a differential expression of 421 genes (p<0.001), several relevant to pathways for pain processing, such as glutamine/glutamate signaling and axonal development. There was also an upregulation of several inflammatory pathways and downregulation of pathways related to hypersensitivity and allergy. Using rigorous diagnostic modeling strategies, we show “locked” gene signatures discovered on Training and Test cohorts, that have a mean Area Under the Curve (AUC) of 0.81 on randomised, independent external data cohorts. Lastly, we identified a subset of 10 probesets that provided a diagnostic sensitivity for FM of 95% and a specificity of 96%. We also show that the signatures for FM were very specific to FM rather than common FM comorbidities. Conclusion These findings provide new insights relevant to the pathogenesis of FM, and provide several testable hypotheses that warrant further exploration and also establish the foundation for a first blood-based molecular signature in FM that needs to be validated in larger cohorts of patients. PMID:27157394

Using space-based investigations to inform cancer research on Earth.

PubMed

Becker, Jeanne L; Souza, Glauco R

2013-05-01

Experiments conducted in the microgravity environment of space are not typically at the forefront of the mind of a cancer biologist. However, space provides physical conditions that are not achievable on Earth, as well as conditions that can be exploited to study mechanisms and pathways that control cell growth and function. Over the past four decades, studies have shown how exposure to microgravity alters biological processes that may be relevant to cancer. In this Review, we explore the influence of microgravity on cell biology, focusing on tumour cells grown in space together with work carried out using models in ground-based investigations.

Development of a pluripotent stem cell derived neuronal model to identify chemically induced pathway perturbations in relation to neurotoxicity: Effects of CREB pathway inhibition

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

Pistollato, Francesca; Louisse, Jochem; Scelfo, Bibiana

2014-10-15

According to the advocated paradigm shift in toxicology, acquisition of knowledge on the mechanisms underlying the toxicity of chemicals, such as perturbations of biological pathways, is of primary interest. Pluripotent stem cells (PSCs), such as human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs), offer a unique opportunity to derive physiologically relevant human cell types to measure molecular and cellular effects of such pathway modulations. Here we compared the neuronal differentiation propensity of hESCs and hiPSCs with the aim to develop novel hiPSC-based tools for measuring pathway perturbation in relation to molecular and cellular effects in vitro.more » Among other fundamental pathways, also, the cAMP responsive element binding protein (CREB) pathway was activated in our neuronal models and gave us the opportunity to study time-dependent effects elicited by chemical perturbations of the CREB pathway in relation to cellular effects. We show that the inhibition of the CREB pathway, using 2-naphthol-AS-E-phosphate (KG-501), induced an inhibition of neurite outgrowth and synaptogenesis, as well as a decrease of MAP2{sup +} neuronal cells. These data indicate that a CREB pathway inhibition can be related to molecular and cellular effects that may be relevant for neurotoxicity testing, and, thus, qualify the use of our hiPSC-derived neuronal model for studying chemical-induced neurotoxicity resulting from pathway perturbations. - Highlights: • HESCs derived neuronal cells serve as benchmark for iPSC based neuronal toxicity test development. • Comparisons between hESCs and hiPSCs demonstrated variability of the epigenetic state • CREB pathway modulation have been explored in relation to the neurotoxicant exposure KG-501 • hiPSC might be promising tools to translate theoretical AoPs into toxicological in vitro tests.« less

Biosimilars: biologics that meet patients' needs and healthcare economics.

PubMed

McCamish, Mark; Yoon, William; McKay, James

2016-09-01

Biologics have revolutionized medical care, yet uniform access to these effective medicines remains difficult due to the increasing costs of healthcare. As patent exclusivity on the early biologics wanes, regulatory and legal systems are adapting to bring competition to the field in the form of biosimilars. Biosimilars are biologics that offer the same clinical benefit in one or more of the same indications as the reference biologic drug and bring competition to the biologics space. Legislation creating a pathway resulting in the first US approvals of biosimilars has been in place since 2010, but the regulatory methodology and science of evaluating the sameness of two biologics has been in use for decades. The demonstration of biosimilarity is based on the "totality of the evidence" concept, in which all structural, functional, nonclinical, and clinical data for a biosimilar product are evaluated to show high similarity to the reference product. Clinical trials for biosimilars, therefore, are designed to confirm similarity, or discover clinically relevant differences between the reference product and the biosimilar, should differences exist. It is hoped that competition from biosimilars will drive biologic innovation and increase patient access to biologics.

Coherent nonlinear optical studies of elementary processes in biological complexes: diagrammatic techniques based on the wave function versus the density matrix

PubMed Central

Biggs, Jason D.; Voll, Judith A.; Mukamel, Shaul

2012-01-01

Two types of diagrammatic approaches for the design and simulation of nonlinear optical experiments (closed-time path loops based on the wave function and double-sided Feynman diagrams for the density matrix) are presented and compared. We give guidelines for the assignment of relevant pathways and provide rules for the interpretation of existing nonlinear experiments in carotenoids. PMID:22753822

Biomedically relevant circuit-design strategies in mammalian synthetic biology

PubMed Central

Bacchus, William; Aubel, Dominique; Fussenegger, Martin

2013-01-01

The development and progress in synthetic biology has been remarkable. Although still in its infancy, synthetic biology has achieved much during the past decade. Improvements in genetic circuit design have increased the potential for clinical applicability of synthetic biology research. What began as simple transcriptional gene switches has rapidly developed into a variety of complex regulatory circuits based on the transcriptional, translational and post-translational regulation. Instead of compounds with potential pharmacologic side effects, the inducer molecules now used are metabolites of the human body and even members of native cell signaling pathways. In this review, we address recent progress in mammalian synthetic biology circuit design and focus on how novel designs push synthetic biology toward clinical implementation. Groundbreaking research on the implementation of optogenetics and intercellular communications is addressed, as particularly optogenetics provides unprecedented opportunities for clinical application. Along with an increase in synthetic network complexity, multicellular systems are now being used to provide a platform for next-generation circuit design. PMID:24061539

Aggregate Exposure Pathways in Support of Risk Assessment

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

Tan, Yu-Mei; Leonard, Jeremy A.; Edwards, Stephen

Over time, risk assessment has shifted from establishing relationships between exposure to a single chemical and a resulting adverse health outcome, to evaluation of multiple chemicals and disease outcomes simultaneously. As a result, there is an increasing need to better understand the complex mechanisms that influence risk of chemical and non-chemical stressors, beginning at their source and ending at a biological endpoint relevant to human or ecosystem health risk assessment. Just as the Adverse Outcome Pathway (AOP) framework has emerged as a means of providing insight into mechanism-based toxicity, the exposure science community has seen the recent introduction of themore » Aggregate Exposure Pathway (AEP) framework. AEPs aid in making exposure data applicable to the FAIR (i.e., findable, accessible, interoperable, and reusable) principle, especially by (1) organizing continuous flow of disjointed exposure information;(2) identifying data gaps, to focus resources on acquiring the most relevant data; (3) optimizing use and repurposing of existing exposure data; and (4) facilitating interoperability among predictive models. Herein, we discuss integration of the AOP and AEP frameworks and how such integration can improve confidence in both traditional and cumulative risk assessment approaches.« less

Aggregate Exposure Pathways in Support of Risk Assessment

DOE PAGES

Tan, Yu-Mei; Leonard, Jeremy A.; Edwards, Stephen; ...

2018-03-29

Over time, risk assessment has shifted from establishing relationships between exposure to a single chemical and a resulting adverse health outcome, to evaluation of multiple chemicals and disease outcomes simultaneously. As a result, there is an increasing need to better understand the complex mechanisms that influence risk of chemical and non-chemical stressors, beginning at their source and ending at a biological endpoint relevant to human or ecosystem health risk assessment. Just as the Adverse Outcome Pathway (AOP) framework has emerged as a means of providing insight into mechanism-based toxicity, the exposure science community has seen the recent introduction of themore » Aggregate Exposure Pathway (AEP) framework. AEPs aid in making exposure data applicable to the FAIR (i.e., findable, accessible, interoperable, and reusable) principle, especially by (1) organizing continuous flow of disjointed exposure information;(2) identifying data gaps, to focus resources on acquiring the most relevant data; (3) optimizing use and repurposing of existing exposure data; and (4) facilitating interoperability among predictive models. Herein, we discuss integration of the AOP and AEP frameworks and how such integration can improve confidence in both traditional and cumulative risk assessment approaches.« less

Developing and applying the adverse outcome pathway concept for understanding and predicting neurotoxicity

PubMed Central

Bal-Price, Anna; Lein, Pamela J.; Keil, Kimberly P.; Sethi, Sunjay; Shafer, Timothy; Barenys, Marta; Fritsche, Ellen; Sachana, Magdalini; Meek, M.E. (Bette)

2016-01-01

The Adverse Outcome Pathway (AOP) concept has recently been proposed to support a paradigm shift in regulatory toxicology testing and risk assessment. This concept is similar to the Mode of Action (MOA), in that it describes a sequence of measurable key events triggered by a molecular initiating event in which a stressor interacts with a biological target. The resulting cascade of key events includes molecular, cellular, structural and functional changes in biological systems, resulting in a measurable adverse outcome. Thereby, an AOP ideally provides information relevant to chemical structure-activity relationships as a basis for predicting effects of structurally similar compounds. AOPs could potentially also form the basis for qualitative and quantitative predictive modeling of the human adverse outcome resulting from molecular initiating or other key events for which higher-throughput testing methods are available or can be developed. A variety of cellular and molecular processes are known to be critical for normal function of the central (CNS) and peripheral nervous systems (PNS). Because of the biological and functional complexity of the CNS and PNS, it has been challenging to establish causative links and quantitative relationships between key events that comprise the pathways leading from chemical exposure to an adverse outcome in the nervous system. Following introduction of the principles of MOA and AOPs, examples of potential or putative adverse outcome pathways specific for developmental or adult neurotoxicity are summarized and aspects of their assessment considered. Their possible application in developing mechanistically informed Integrated Approaches to Testing and Assessment (IATA) is also discussed. PMID:27212452

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.

The use of CD47-modified biomaterials to mitigate the immune response.

PubMed

Tengood, Jillian E; Levy, Robert J; Stachelek, Stanley J

2016-05-01

Addressing the aberrant interactions between immune cells and biomaterials represents an unmet need in biomaterial research. Although progress has been made in the development of bioinert coatings, identifying and targeting relevant cellular and molecular pathways can provide additional therapeutic strategies to address this major healthcare concern. To that end, we describe the immune inhibitory motif, receptor-ligand pairing of signal regulatory protein alpha and its cognate ligand CD47 as a potential signaling pathway to enhance biocompatibility. The goals of this article are to detail the known roles of CD47-signal regulatory protein alpha signal transduction pathway and to describe how immobilized CD47 can be used to mitigate the immune response to biomaterials. Current applications of CD47-modified biomaterials will also be discussed herein. © 2016 by the Society for Experimental Biology and Medicine.

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 Escherichia coli to overproduce aromatic amino acids and derived compounds.

PubMed

Rodriguez, Alberto; Martínez, Juan A; Flores, Noemí; Escalante, Adelfo; Gosset, Guillermo; Bolivar, Francisco

2014-09-09

The production of aromatic amino acids using fermentation processes with recombinant microorganisms can be an advantageous approach to reach their global demands. In addition, a large array of compounds with alimentary and pharmaceutical applications can potentially be synthesized from intermediates of this metabolic pathway. However, contrary to other amino acids and primary metabolites, the artificial channelling of building blocks from central metabolism towards the aromatic amino acid pathway is complicated to achieve in an efficient manner. The length and complex regulation of this pathway have progressively called for the employment of more integral approaches, promoting the merge of complementary tools and techniques in order to surpass metabolic and regulatory bottlenecks. As a result, relevant insights on the subject have been obtained during the last years, especially with genetically modified strains of Escherichia coli. By combining metabolic engineering strategies with developments in synthetic biology, systems biology and bioprocess engineering, notable advances were achieved regarding the generation, characterization and optimization of E. coli strains for the overproduction of aromatic amino acids, some of their precursors and related compounds. In this paper we review and compare recent successful reports dealing with the modification of metabolic traits to attain these objectives.

Amphiphilic gold nanoparticles as modulators of lipid membrane fusion

NASA Astrophysics Data System (ADS)

Tahir, Mukarram; Alexander-Katz, Alfredo

The fusion of lipid membranes is central to biological functions like inter-cellular transport and signaling and is coordinated by proteins of the soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) superfamily. We utilize molecular dynamics simulations to demonstrate that gold nanoparticles functionalized with a mixed-monolayer of hydrophobic and hydrophilic alkanethiol ligands can act as synthetic analogues of these fusion proteins and mediate lipid membrane fusion by catalyzing the formation of a toroidal stalk between adjacent membranes and enabling the formation of a fusion pore upon influx of Ca2+ into the exterior solvent. The fusion pathway enabled by these synthetic nanostructures is analogous to the regulated fast fusion pathway observed during synaptic vesicle fusion; it therefore provides novel physical insights into this important biological process while also being relevant in a number of single-cell therapeutic applications. Computational resources from NSF XSEDE contract TG-DMR130042. Financial support from DOE CSGF fellowship DE-FG02-97ER25308.

New insights about host response to smallpox using microarray data.

PubMed

Esteves, Gustavo H; Simoes, Ana C Q; Souza, Estevao; Dias, Rodrigo A; Ospina, Raydonal; Venancio, Thiago M

2007-08-24

Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems.

Positive affect and markers of inflammation: discrete positive emotions predict lower levels of inflammatory cytokines.

PubMed

Stellar, Jennifer E; John-Henderson, Neha; Anderson, Craig L; Gordon, Amie M; McNeil, Galen D; Keltner, Dacher

2015-04-01

Negative emotions are reliably associated with poorer health (e.g., Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002), but only recently has research begun to acknowledge the important role of positive emotions for our physical health (Fredrickson, 2003). We examine the link between dispositional positive affect and one potential biological pathway between positive emotions and health-proinflammatory cytokines, specifically levels of interleukin-6 (IL-6). We hypothesized that greater trait positive affect would be associated with lower levels of IL-6 in a healthy sample. We found support for this hypothesis across two studies. We also explored the relationship between discrete positive emotions and IL-6 levels, finding that awe, measured in two different ways, was the strongest predictor of lower levels of proinflammatory cytokines. These effects held when controlling for relevant personality and health variables. This work suggests a potential biological pathway between positive emotions and health through proinflammatory cytokines. (c) 2015 APA, all rights reserved).

Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks.

PubMed

Blatti, Charles; Sinha, Saurabh

2016-07-15

Analysis of co-expressed gene sets typically involves testing for enrichment of different annotations or 'properties' such as biological processes, pathways, transcription factor binding sites, etc., one property at a time. This common approach ignores any known relationships among the properties or the genes themselves. It is believed that known biological relationships among genes and their many properties may be exploited to more accurately reveal commonalities of a gene set. Previous work has sought to achieve this by building biological networks that combine multiple types of gene-gene or gene-property relationships, and performing network analysis to identify other genes and properties most relevant to a given gene set. Most existing network-based approaches for recognizing genes or annotations relevant to a given gene set collapse information about different properties to simplify (homogenize) the networks. We present a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types that preserve more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only these relevant properties. We then re-rank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork. We demonstrate the effectiveness of this algorithm for ranking genes related to Drosophila embryonic development and aggressive responses in the brains of social animals. DRaWR was implemented as an R package available at veda.cs.illinois.edu/DRaWR. blatti@illinois.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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.

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

An image analysis toolbox for high-throughput C. elegans assays

PubMed Central

Wählby, Carolina; Kamentsky, Lee; Liu, Zihan H.; Riklin-Raviv, Tammy; Conery, Annie L.; O’Rourke, Eyleen J.; Sokolnicki, Katherine L.; Visvikis, Orane; Ljosa, Vebjorn; Irazoqui, Javier E.; Golland, Polina; Ruvkun, Gary; Ausubel, Frederick M.; Carpenter, Anne E.

2012-01-01

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays of C. elegans for the study of diverse biological pathways relevant to human disease. PMID:22522656

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

Curcumin as a multifaceted compound against human papilloma virus infection and cervical cancers: A review of chemistry, cellular, molecular, and preclinical features.

PubMed

Teymouri, Manouchehr; Pirro, Matteo; Johnston, Thomas P; Sahebkar, Amirhosein

2017-05-06

Curcumin, the bioactive polyphenolic ingredient of turmeric, has been extensively studied for its effects on human papilloma virus (HPV) infection as well as primary and malignant squamous cervical cancers. HPV infections, especially those related to HPV 16 and 18 types, have been established as the leading cause of cervical cancer; however, there are also additional contributory factors involved in the etiopathogenesis of cervical cancers. Curcumin has emerged as having promising chemopreventive and anticancer effects against both HPV-related and nonrelated cervical cancers. In this review, we first discuss the biological relevance of curcumin and both its pharmacological effects and pharmaceutical considerations from a chemical point of view. Next, the signaling pathways that are modulated by curcumin and are relevant to the elimination of HPV infection and treatment of cervical cancer are discussed. We also present counter arguments regarding the effects of curcumin on signaling pathways and molecular markers dysregulated by benzo(a)pyrene (Bap), a carcinogen found in pathological cervical lesions of women who smoke frequently, and estradiol, as two important risk factors involved in persistent HPV-infection and cervical cancer. Finally, various strategies to enhance the pharmacological activity and pharmacokinetic characteristics of curcumin are discussed with examples of studies in experimental models of cervical cancer. © 2016 BioFactors, 43(3):331-346, 2017. © 2016 International Union of Biochemistry and Molecular Biology.

Relevance and Significance of Extraterrestrial Abiological Hydrocarbon Chemistry.

PubMed

Olah, George A; Mathew, Thomas; Prakash, G K Surya

2016-06-08

Astrophysical observations show similarity of observed abiological "organics"-i.e., hydrocarbons, their derivatives, and ions (carbocations and carbanions)-with studied terrestrial chemistry. Their formation pathways, their related extraterrestrial hydrocarbon chemistry originating from carbon and other elements after the Big Bang, their parent hydrocarbon and derivative (methane and methanol, respectively), and transportation of derived building blocks of life by meteorites or comets to planet Earth are discussed in this Perspective. Their subsequent evolution on Earth under favorable "Goldilocks" conditions led to more complex molecules and biological systems, and eventually to humans. The relevance and significance of extraterrestrial hydrocarbon chemistry to the limits of science in relation to the physical aspects of evolution on our planet Earth are also discussed.

Volatile science? Metabolic engineering of terpenoids in plants.

PubMed

Aharoni, Asaph; Jongsma, Maarten A; Bouwmeester, Harro J

2005-12-01

Terpenoids are important for plant survival and also possess biological properties that are beneficial to humans. Here, we describe the state of the art in terpenoid metabolic engineering, showing that significant progress has been made over the past few years. Subcellular targeting of enzymes has demonstrated that terpenoid precursors in subcellular compartments are not as strictly separated as previously thought and that multistep pathway engineering is feasible, even across cell compartments. These engineered plants show that insect behavior is influenced by terpenoids. In the future, we expect rapid progress in the engineering of terpenoid production in plants. In addition to commercial applications, such transgenic plants should increase our understanding of the biological relevance of these volatile secondary metabolites.

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.

The PLOS ONE Synthetic Biology Collection: Six Years and Counting

PubMed Central

Peccoud, Jean; Isalan, Mark

2012-01-01

Since it was launched in 2006, PLOS ONE has published over fifty articles illustrating the many facets of the emerging field of synthetic biology. This article reviews these publications by organizing them into broad categories focused on DNA synthesis and assembly techniques, the development of libraries of biological parts, the use of synthetic biology in protein engineering applications, and the engineering of gene regulatory networks and metabolic pathways. Finally, we review articles that describe enabling technologies such as software and modeling, along with new instrumentation. In order to increase the visibility of this body of work, the papers have been assembled into the PLOS ONE Synthetic Biology Collection (www.ploscollections.org/synbio). Many of the innovative features of the PLOS ONE web site will help make this collection a resource that will support a lively dialogue between readers and authors of PLOS ONE synthetic biology papers. The content of the collection will be updated periodically by including relevant articles as they are published by the journal. Thus, we hope that this collection will continue to meet the publishing needs of the synthetic biology community. PMID:22916228

The PLOS ONE synthetic biology collection: six years and counting.

PubMed

Peccoud, Jean; Isalan, Mark

2012-01-01

Since it was launched in 2006, PLOS ONE has published over fifty articles illustrating the many facets of the emerging field of synthetic biology. This article reviews these publications by organizing them into broad categories focused on DNA synthesis and assembly techniques, the development of libraries of biological parts, the use of synthetic biology in protein engineering applications, and the engineering of gene regulatory networks and metabolic pathways. Finally, we review articles that describe enabling technologies such as software and modeling, along with new instrumentation. In order to increase the visibility of this body of work, the papers have been assembled into the PLOS ONE Synthetic Biology Collection (www.ploscollections.org/synbio). Many of the innovative features of the PLOS ONE web site will help make this collection a resource that will support a lively dialogue between readers and authors of PLOS ONE synthetic biology papers. The content of the collection will be updated periodically by including relevant articles as they are published by the journal. Thus, we hope that this collection will continue to meet the publishing needs of the synthetic biology community.

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

PubMed Central

Duell, Eric J.; Yu, Kai; Risch, Harvey A.; Olson, Sara H.; Kooperberg, Charles; Wolpin, Brian M.; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A.; Bueno-de-Mesquita, H. Bas; Fuchs, Charles S.; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N.; Holly, Elizabeth A.; Jacobs, Eric J.; Klein, Alison P.; LaCroix, Andrea; Mandelson, Margaret T.; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Buring, Julie E.; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J.; Cotterchio, Michelle; Gaziano, J.Michael; Giovannucci, Edward L.; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E.; Hoffman Bolton, Judith A.; Hunter, David J.; Hutchinson, Amy; Jacobs, Kevin B.; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C.; McWilliams, Robert R.; Mendelsohn, Julie B.; Patel, Alpa V.; Rabe, Kari G.; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Stolzenberg-Solomon, Rachael Z.

2012-01-01

Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H. pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer. PMID:22523087

AN OVERVIEW OF COMPUTATIONAL LIFE SCIENCE DATABASES & EXCHANGE FORMATS OF RELEVANCE TO CHEMICAL BIOLOGY RESEARCH

PubMed Central

Hall, Aaron Smalter; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2016-01-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities. PMID:22934944

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

PubMed

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

An overview of computational life science databases & exchange formats of relevance to chemical biology research.

PubMed

Smalter Hall, Aaron; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2013-03-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities.

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.

Benchmarking organic micropollutants in wastewater, recycled water and drinking water with in vitro bioassays.

PubMed

Escher, Beate I; Allinson, Mayumi; Altenburger, Rolf; Bain, Peter A; Balaguer, Patrick; Busch, Wibke; Crago, Jordan; Denslow, Nancy D; Dopp, Elke; Hilscherova, Klara; Humpage, Andrew R; Kumar, Anu; Grimaldi, Marina; Jayasinghe, B Sumith; Jarosova, Barbora; Jia, Ai; Makarov, Sergei; Maruya, Keith A; Medvedev, Alex; Mehinto, Alvine C; Mendez, Jamie E; Poulsen, Anita; Prochazka, Erik; Richard, Jessica; Schifferli, Andrea; Schlenk, Daniel; Scholz, Stefan; Shiraishi, Fujio; Snyder, Shane; Su, Guanyong; Tang, Janet Y M; van der Burg, Bart; van der Linden, Sander C; Werner, Inge; Westerheide, Sandy D; Wong, Chris K C; Yang, Min; Yeung, Bonnie H Y; Zhang, Xiaowei; Leusch, Frederic D L

2014-01-01

Thousands of organic micropollutants and their transformation products occur in water. Although often present at low concentrations, individual compounds contribute to mixture effects. Cell-based bioassays that target health-relevant biological endpoints may therefore complement chemical analysis for water quality assessment. The objective of this study was to evaluate cell-based bioassays for their suitability to benchmark water quality and to assess efficacy of water treatment processes. The selected bioassays cover relevant steps in the toxicity pathways including induction of xenobiotic metabolism, specific and reactive modes of toxic action, activation of adaptive stress response pathways and system responses. Twenty laboratories applied 103 unique in vitro bioassays to a common set of 10 water samples collected in Australia, including wastewater treatment plant effluent, two types of recycled water (reverse osmosis and ozonation/activated carbon filtration), stormwater, surface water, and drinking water. Sixty-five bioassays (63%) showed positive results in at least one sample, typically in wastewater treatment plant effluent, and only five (5%) were positive in the control (ultrapure water). Each water type had a characteristic bioanalytical profile with particular groups of toxicity pathways either consistently responsive or not responsive across test systems. The most responsive health-relevant endpoints were related to xenobiotic metabolism (pregnane X and aryl hydrocarbon receptors), hormone-mediated modes of action (mainly related to the estrogen, glucocorticoid, and antiandrogen activities), reactive modes of action (genotoxicity) and adaptive stress response pathway (oxidative stress response). This study has demonstrated that selected cell-based bioassays are suitable to benchmark water quality and it is recommended to use a purpose-tailored panel of bioassays for routine monitoring.

Biological monitoring of carcinogens: current status and perspectives.

PubMed

Pavanello, Sofia; Lotti, Marcello

2012-04-01

Biomonitoring exposures to carcinogens is common practice and a variety of biomarkers have been developed to assess both exposures and biochemical/biological effects. However, their clinical and preventive relevance is still uncertain. The understanding of cancer as a genetic disease has dramatically evolved during last decades, showing that cancer cell types acquire their characteristics with different strategies, time frames and microenvironments. Therefore, the place of current biomarkers within this complex scenario of gene-environment interactions leading to cancer cannot be defined. Reasons are manifold. Most studies assessed cancer risk on a group basis through snapshots taken at unknown time-points of the postulated chain of events. Little attention has been paid to the variety and variability of exposures, and no prospective study validated the indicators of biochemical/biological effects. New opportunities and suggestions for biomonitoring exposures to carcinogens could derive from exploring the exposome that combines exposures from all sources both external and internal. The discovery of new biomarkers and the identification of relevant gene-specific pathways could be achieved through metabolomic and genome-wide studies. In conclusion, it is possible to envisage personalized biomonitoring procedures, such as those already implemented in the context of nutrition and clinical oncology.

A biologically relevant method for considering patterns of oceanic retention in the Southern Ocean

NASA Astrophysics Data System (ADS)

Mori, Mao; Corney, Stuart P.; Melbourne-Thomas, Jessica; Klocker, Andreas; Sumner, Michael; Constable, Andrew

2017-12-01

Many marine species have planktonic forms - either during a larval stage or throughout their lifecycle - that move passively or are strongly influenced by ocean currents. Understanding these patterns of movement is important for informing marine ecosystem management and for understanding ecological processes generally. Retention of biological particles in a particular area due to ocean currents has received less attention than transport pathways, particularly for the Southern Ocean. We present a method for modelling retention time, based on the half-life for particles in a particular region, that is relevant for biological processes. This method uses geostrophic velocities at the ocean surface, derived from 23 years of satellite altimetry data (1993-2016), to simulate the advection of passive particles during the Southern Hemisphere summer season (from December to March). We assess spatial patterns in the retention time of passive particles and evaluate the processes affecting these patterns for the Indian sector of the Southern Ocean. Our results indicate that the distribution of retention time is related to bathymetric features and the resulting ocean dynamics. Our analysis also reveals a moderate level of consistency between spatial patterns of retention time and observations of Antarctic krill (Euphausia superba) distribution.

Tools of pathway reconstruction and production of economically relevant plant secondary metabolites in recombinant microorganisms.

PubMed

Dziggel, Clarissa; Schäfer, Holger; Wink, Michael

2017-01-01

Plant secondary metabolites exhibit a variety of biological activities and therefore serve as valuable therapeutics or flavoring compounds. However, the small amounts isolated from plants often cannot meet market demands. This led to the exploration of other, more profitable methods for their production, including plant cell culture systems, chemical synthesis and biotechnological production in microbial hosts. The biotechnological production can be pursued by reconstructing metabolic pathways in selected microbial systems. But due to their complexity, most of these pathways are not completely understood and require the expression of a multitude of genes in a foreign organism. Recently, next generation sequencing data and advances in gene silencing in plants allowed the elucidation of some biosynthetic pathways in more detail. Thus, the de novo production of some natural products, including morphine, strictosidine, artemisinin, taxol ® and resveratrol, in extensively engineered microbial hosts has become feasible. This review highlights the reconstruction of these pathways, missing pieces and novel techniques employed. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Is nanotechnology the key to unravel and engineer biological processes?

PubMed

Navarro, Melba; Planell, Josep A

2012-01-01

Regenerative medicine is an emerging field aiming to the development of new reparative strategies to treat degenerative diseases, injury, and trauma through developmental pathways in order to rebuild the architecture of the original injured organ and take over its functionality. Most of the processes and interactions involved in the regenerative process take place at subcellular scale. Nanotechnology provides the tools and technology not only to detect, to measure, or to image the interactions between the different biomolecules and biological entities, but also to control and guide the regenerative process. The relevance of nanotechnology for the development of regenerative medicine as well as an overview of the different tools that contribute to unravel and engineer biological systems are presented in this chapter. In addition, general data about the social impact and global investment in nanotechnology are provided.

Extraintestinal roles of bombesin-like peptides and their receptors: lung.

PubMed

Qin, Xiao-Qun; Qu, Xiangping

2013-02-01

Description of the recent findings of the biological roles of bombesin-like peptides and their receptors in lungs. Gastrin-releasing peptide (GRP) was involved in the airway inflammation in murine models of airway hyperreactivity. The circulating proGRP could serve as a valuable tumor marker for small-cell lung cancers, and the plasma level of proGRP is more stable compared with that of serum proGRP. Recent studies also shed light on the intracellular signaling pathways of bombesin receptor subtype-3 (BRS-3) activation in cultured human lung cancer cells. The relevant biology of BLPs and their receptors in lung cancers and other lung diseases still remains largely unknown. With the development of several highly specific BRS-3 agonists, recent studies provided some insights into the biological effects of BRS-3 in lungs.

Ars Moriendi; the art of dying well - new insights into the molecular pathways of necroptotic cell death.

PubMed

Murphy, James M; Silke, John

2014-02-01

When our time comes to die most people would probably opt for a quick, peaceful and painless exit. But the manner and timing are rarely under our direct control. Hence the Ars moriendi, literally, "The Art of Dying", two texts written in Latin around the 15th century that offered advice on how to die well according to the Christian ideals of the time. In contrast, for individual cells, the death process is frequently under their control and several signaling pathways that cause cell death, including apoptosis, pyroptosis and necroptosis, have been described. Furthermore the manner in which cells die can have good or bad consequences for the organism. In this review we will discuss how cells die via the necroptotic signaling pathway, with emphasis on recent structural work and place this work in a biological context by discussing relevant studies with knock-out animals.

Vascular endothelial growth factor inhibitor-induced hypertension: from pathophysiology to prevention and treatment based on long-acting nitric oxide donors.

PubMed

Kruzliak, Peter; Novák, Jan; Novák, Miroslav

2014-01-01

Hypertension is the most common adverse effect of the inhibitors of vascular endothelial growth factor (VEGF) pathway-based therapy (VEGF pathway inhibitors therapy, VPI therapy) in cancer patients. VPI includes monoclonal antibodies against VEGF, tyrosine kinase inhibitors, VEGF Traps, and so-called aptamers that may become clinically relevant in the future. All of these substances inhibit the VEGF pathway, which in turn causes a decrease in nitric oxide (NO) and an increase in blood pressure, with the consequent development of hypertension and its final events (e.g., myocardial infarction or stroke). To our knowledge, there is no current study on how to provide an optimal therapy for patients on VPI therapy with hypertension. This review summarizes the roles of VEGF and NO in vessel biology, provides an overview of VPI agents, and suggests a potential treatment procedure for patients with VPI-induced hypertension.

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

Molecular pathogenesis of splenic and nodal marginal zone lymphoma.

PubMed

Spina, Valeria; Rossi, Davide

Genomic studies have improved our understanding of the biological basis of splenic (SMZL) and nodal (NMZL) marginal zone lymphoma by providing a comprehensive and unbiased view of the genes/pathways that are deregulated in these diseases. Consistent with the physiological involvement of NOTCH, NF-κB, B-cell receptor and toll-like receptor signaling in mature B-cells differentiation into the marginal zone B-cells, many oncogenic mutations of genes involved in these pathways have been identified in SMZL and NMZL. Beside genetic lesions, also epigenetic and post-transcriptional modifications contribute to the deregulation of marginal zone B-cell differentiation pathways in SMZL and NMZL. This review describes the progress in understanding the molecular mechanism underlying SMZL and NMZL, including molecular and post-transcriptional modifications, and discusses how information gained from these efforts has provided new insights on potential targets of diagnostic, prognostic and therapeutic relevance in SMZL and NMZL. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular and comparative genetics of mental retardation.

PubMed Central

Inlow, Jennifer K; Restifo, Linda L

2004-01-01

Affecting 1-3% of the population, mental retardation (MR) poses significant challenges for clinicians and scientists. Understanding the biology of MR is complicated by the extraordinary heterogeneity of genetic MR disorders. Detailed analyses of >1000 Online Mendelian Inheritance in Man (OMIM) database entries and literature searches through September 2003 revealed 282 molecularly identified MR genes. We estimate that hundreds more MR genes remain to be identified. A novel test, in which we distributed unmapped MR disorders proportionately across the autosomes, failed to eliminate the well-known X-chromosome overrepresentation of MR genes and candidate genes. This evidence argues against ascertainment bias as the main cause of the skewed distribution. On the basis of a synthesis of clinical and laboratory data, we developed a biological functions classification scheme for MR genes. Metabolic pathways, signaling pathways, and transcription are the most common functions, but numerous other aspects of neuronal and glial biology are controlled by MR genes as well. Using protein sequence and domain-organization comparisons, we found a striking conservation of MR genes and genetic pathways across the approximately 700 million years that separate Homo sapiens and Drosophila melanogaster. Eighty-seven percent have one or more fruit fly homologs and 76% have at least one candidate functional ortholog. We propose that D. melanogaster can be used in a systematic manner to study MR and possibly to develop bioassays for therapeutic drug discovery. We selected 42 Drosophila orthologs as most likely to reveal molecular and cellular mechanisms of nervous system development or plasticity relevant to MR. PMID:15020472

Synthetic biology, inspired by synthetic chemistry.

PubMed

Malinova, V; Nallani, M; Meier, W P; Sinner, E K

2012-07-16

The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

The Importance of Transition Metals in the Expanding Network of Microbial Metabolism in the Archean Eon

NASA Astrophysics Data System (ADS)

Moore, E. K.; Jelen, B. I.; Giovannelli, D.; Prabhu, A.; Raanan, H.; Falkowski, P. G.

2017-12-01

Deep time changes in Earth surface redox conditions, particularly due to global oxygenation, has impacted the availability of different metals and substrates that are central in biology. Oxidoreductase proteins are molecular nanomachines responsible for all biological electron transfer processes across the tree of life. These enzymes largely contain transition metals in their active sites. Microbial metabolic pathways form a global network of electron transfer, which expanded throughout the Archean eon. Older metabolisms (sulfur reduction, methanogenesis, anoxygenic photosynthesis) accessed negative redox potentials, while later evolving metabolisms (oxygenic photosynthesis, nitrification/denitrification, aerobic respiration) accessed positive redox potentials. The incorporation of different transition metals facilitated biological innovation and the expansion of the network of microbial metabolism. Network analysis was used to examine the connections between microbial taxa, metabolic pathways, crucial metallocofactors, and substrates in deep time by incorporating biosignatures preserved in the geologic record. Nitrogen fixation and aerobic respiration have the highest level of betweenness among metabolisms in the network, indicating that the oldest metabolisms are not the most central. Fe has by far the highest betweenness among metals. Clustering analysis largely separates High Metal Bacteria (HMB), Low Metal Bacteria (LMB), and Archaea showing that simple un-weighted links between taxa, metabolism, and metals have phylogenetic relevance. On average HMB have the highest betweenness among taxa, followed by Archaea and LMB. There is a correlation between the number of metallocofactors and metabolic pathways in representative bacterial taxa, but Archaea do not follow this trend. In many cases older and more recently evolved metabolisms were clustered together supporting previous findings that proliferation of metabolic pathways is not necessarily chronological.

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

Evaluation of genome-wide association study results through development of ontology fingerprints

PubMed Central

Tsoi, Lam C.; Boehnke, Michael; Klein, Richard L.; Zheng, W. Jim

2009-01-01

Motivation: Genome-wide association (GWA) studies may identify multiple variants that are associated with a disease or trait. To narrow down candidates for further validation, quantitatively assessing how identified genes relate to a phenotype of interest is important. Results: We describe an approach to characterize genes or biological concepts (phenotypes, pathways, diseases, etc.) by ontology fingerprint—the set of Gene Ontology (GO) terms that are overrepresented among the PubMed abstracts discussing the gene or biological concept together with the enrichment p-value of these terms generated from a hypergeometric enrichment test. We then quantify the relevance of genes to the trait from a GWA study by calculating similarity scores between their ontology fingerprints using enrichment p-values. We validate this approach by correctly identifying corresponding genes for biological pathways with a 90% average area under the ROC curve (AUC). We applied this approach to rank genes identified through a GWA study that are associated with the lipid concentrations in plasma as well as to prioritize genes within linkage disequilibrium (LD) block. We found that the genes with highest scores were: ABCA1, lipoprotein lipase (LPL) and cholesterol ester transfer protein, plasma for high-density lipoprotein; low-density lipoprotein receptor, APOE and APOB for low-density lipoprotein; and LPL, APOA1 and APOB for triglyceride. In addition, we identified genes relevant to lipid metabolism from the literature even in cases where such knowledge was not reflected in current annotation of these genes. These results demonstrate that ontology fingerprints can be used effectively to prioritize genes from GWA studies for experimental validation. Contact: zhengw@musc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19349285

Apoptosis Gene Information System--AGIS.

PubMed

Sakharkar, Kishore R; Clement, Marie V; Chow, Vincent T K; Pervaiz, Shazib

2006-05-01

Genes implicated in apoptosis have great relevance to biology, medicine and oncology. Here, we describe a unique resource, Apoptosis Gene Information System (AGIS) that provides data for over 2400 genes involved directly or indirectly, in apoptotic pathways of more than 350 different organisms. The organization of this information system is based on the principle of one-gene, one record. AGIS will be updated on a six monthly basis as new information becomes available. AGIS can be accessed at: http://www.cellfate.org/AGIS/.

Thermophilic and alkaliphilic Actinobacteria: biology and potential applications

PubMed Central

Shivlata, L.; Satyanarayana, Tulasi

2015-01-01

Microbes belonging to the phylum Actinobacteria are prolific sources of antibiotics, clinically useful bioactive compounds and industrially important enzymes. The focus of the current review is on the diversity and potential applications of thermophilic and alkaliphilic actinobacteria, which are highly diverse in their taxonomy and morphology with a variety of adaptations for surviving and thriving in hostile environments. The specific metabolic pathways in these actinobacteria are activated for elaborating pharmaceutically, agriculturally, and biotechnologically relevant biomolecules/bioactive compounds, which find multifarious applications. PMID:26441937

Microfabrication of individual 200 microm diameter transdermal microconduits using high voltage pulsing in salicylic acid and benzoic acid.

PubMed

Ilic, L; Gowrishankar, T R; Vaughan, T E; Herndon, T O; Weaver, J C

2001-01-01

We describe an extension of semiconductor fabrication methods that creates individual approximately 200 microm diameter aqueous pathways through human stratum corneum at predetermined sites. Our hypothesis is that spatially localized electroporation of the multilamellar lipid bilayer membranes provides rapid delivery of salicylic acid to the keratin within corneocytes, leading to localized keratin disruption and then to a microconduit. A microconduit penetrating the isolated stratum corneum supports a volumetric flow of order 0.01 ml per s with a pressure difference of only 0.01 atm (about 10(2) Pa). This study provides a method for rapidly microengineering a pathway in the skin to interface future devices for transdermal drug delivery and sampling of biologically relevant fluids.

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.

Quantification of conjugated metabolites of drugs in biological matrices after the hydrolysis with β-glucuronidase and sufatase: a review of bio-analytical methods.

PubMed

Ding, Yue; Peng, Ming; Zhang, Tong; Tao, Jian-Sheng; Cai, Zhen-Zhen; Zhang, Yong

2013-10-01

Glucuronidation and sulfation represent two major pathways in phase II drug metabolism in humans and other mammalian species. The great majority of drugs, for example, polyphenols, flavonoids and anthraquinones, could be transformed into sulfated and glucuronidated conjugates simultaneously and extensively in vivo. The pharmacological activities of drug conjugations are normally decreased compared with those of their free forms. However, some drug conjugates may either bear biological activities themselves or serve as excellent sources of biologically active compounds. As the bioactivities of drugs are thought to be relevant to the kinetics of their conjugates, it is essential to study the pharmacokinetic behaviors of the conjugates in more detail. Unfortunately, the free forms of drugs cannot be detected directly in most cases if their glucuronides and sulfates are the predominant forms in biological samples. Nevertheless, an initial enzymatic hydrolysis step using β-glucuronidase and/or sulfatase is usually performed to convert the glucuronidated and/or sulfated conjugates to their free forms prior to the extraction, purification and other subsequent analysis steps in the literature. This review provides fundamental information on drug metabolism pathways, the bio-analytical strategies for the quantification of various drug conjugates, and the applications of the analytical methods to pharmacokinetic studies. Copyright © 2013 John Wiley & Sons, Ltd.

Systems biology of meridians, acupoints, and chinese herbs in disease.

PubMed

Lin, Li-Ling; Wang, Ya-Hui; Lai, Chi-Yu; Chau, Chan-Lao; Su, Guan-Chin; Yang, Chun-Yi; Lou, Shu-Ying; Chen, Szu-Kai; Hsu, Kuan-Hao; Lai, Yen-Ling; Wu, Wei-Ming; Huang, Jian-Long; Liao, Chih-Hsin; Juan, Hsueh-Fen

2012-01-01

Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM). They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.

Accelerating Adverse Outcome Pathway (AOP) development ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework is increasingly being adopted as a tool for organizing and summarizing the mechanistic information connecting molecular perturbations by environmental stressors with adverse outcomes relevant for ecological and human health outcomes. However, the conventional process for assembly of these AOPs is time and resource intensive, and has been a rate limiting step for AOP use and development. Therefore computational approaches to accelerate the process need to be developed. We previously developed a method for generating computationally predicted AOPs (cpAOPs) by association mining and integration of data from publicly available databases. In this work, a cpAOP network of ~21,000 associations was established between 105 phenotypes from TG-GATEs rat liver data from different time points (including microarray, pathological effects and clinical chemistry data), 994 REACTOME pathways, 688 High-throughput assays from ToxCast and 194 chemicals. A second network of 128,536 associations was generated by connecting 255 biological target genes from ToxCast to 4,980 diseases from CTD using either HT screening activity from ToxCast for 286 chemicals or CTD gene expression changes in response to 2,330 chemicals. Both networks were separately evaluated through manual extraction of disease-specific cpAOPs and comparison with expert curation of the relevant literature. By employing data integration strategies that involve the weighting of n

Pathways Impacted by Genomic Alterations in Pulmonary Carcinoid Tumors.

PubMed

Asiedu, Michael K; Thomas, Charles F; Dong, Jie; Schulte, Sandra C; Khadka, Prasidda; Sun, Zhifu; Kosari, Farhad; Jen, Jin; Molina, Julian; Vasmatzis, George; Kuang, Ray; Aubry, Marie Christine; Yang, Ping; Wigle, Dennis A

2018-04-01

Purpose: Pulmonary carcinoid tumors account for up to 5% of all lung malignancies in adults, comprise 30% of all carcinoid malignancies, and are defined histologically as typical carcinoid (TC) and atypical carcinoid (AC) tumors. The role of specific genomic alterations in the pathogenesis of pulmonary carcinoid tumors remains poorly understood. We sought to identify genomic alterations and pathways that are deregulated in these tumors to find novel therapeutic targets for pulmonary carcinoid tumors. Experimental Design: We performed integrated genomic analysis of carcinoid tumors comprising whole genome and exome sequencing, mRNA expression profiling and SNP genotyping of specimens from normal lung, TC and AC, and small cell lung carcinoma (SCLC) to fully represent the lung neuroendocrine tumor spectrum. Results: Analysis of sequencing data found recurrent mutations in cancer genes including ATP1A2, CNNM1, MACF1, RAB38, NF1, RAD51C, TAF1L, EPHB2, POLR3B , and AGFG1 The mutated genes are involved in biological processes including cellular metabolism, cell division cycle, cell death, apoptosis, and immune regulation. The top most significantly mutated genes were TMEM41B, DEFB127, WDYHV1, and TBPL1 Pathway analysis of significantly mutated and cancer driver genes implicated MAPK/ERK and amyloid beta precursor protein (APP) pathways whereas analysis of CNV and gene expression data suggested deregulation of the NF-κB and MAPK/ERK pathways. The mutation signature was predominantly C>T and T>C transitions with a minor contribution of T>G transversions. Conclusions: This study identified mutated genes affecting cancer relevant pathways and biological processes that could provide opportunities for developing targeted therapies for pulmonary carcinoid tumors. Clin Cancer Res; 24(7); 1691-704. ©2018 AACR . ©2018 American Association for Cancer Research.

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.

From the outside, from within: Biological and therapeutic relevance of signal transduction in T-cell acute lymphoblastic leukemia.

PubMed

Oliveira, Mariana L; Akkapeddi, Padma; Alcobia, Isabel; Almeida, Afonso R; Cardoso, Bruno A; Fragoso, Rita; Serafim, Teresa L; Barata, João T

2017-10-01

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological cancer that arises from clonal expansion of transformed T-cell precursors. In this review we summarize the current knowledge on the external stimuli and cell-intrinsic lesions that drive aberrant activation of pivotal, pro-tumoral intracellular signaling pathways in T-cell precursors, driving transformation, leukemia expansion, spread or resistance to therapy. In addition to their pathophysiological relevance, receptors and kinases involved in signal transduction are often attractive candidates for targeted drug development. As such, we discuss also the potential of T-ALL signaling players as targets for therapeutic intervention. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Control of seizures by ketogenic diet-induced modulation of metabolic pathways.

PubMed

Clanton, Ryan M; Wu, Guoyao; Akabani, Gamal; Aramayo, Rodolfo

2017-01-01

Epilepsy is too complex to be considered as a disease; it is more of a syndrome, characterized by seizures, which can be caused by a diverse array of afflictions. As such, drug interventions that target a single biological pathway will only help the specific individuals where that drug's mechanism of action is relevant to their disorder. Most likely, this will not alleviate all forms of epilepsy nor the potential biological pathways causing the seizures, such as glucose/amino acid transport, mitochondrial dysfunction, or neuronal myelination. Considering our current inability to test every individual effectively for the true causes of their epilepsy and the alarming number of misdiagnoses observed, we propose the use of the ketogenic diet (KD) as an effective and efficient preliminary/long-term treatment. The KD mimics fasting by altering substrate metabolism from carbohydrates to fatty acids and ketone bodies (KBs). Here, we underscore the need to understand the underlying cellular mechanisms governing the KD's modulation of various forms of epilepsy and how a diverse array of metabolites including soluble fibers, specific fatty acids, and functional amino acids (e.g., leucine, D-serine, glycine, arginine metabolites, and N-acetyl-cysteine) may potentially enhance the KD's ability to treat and reverse, not mask, these neurological disorders that lead to epilepsy.

Using Multiorder Time-Correlation Functions (TCFs) To Elucidate Biomolecular Reaction Pathways from Microsecond Single-Molecule Fluorescence Experiments.

PubMed

Phelps, Carey; Israels, Brett; Marsh, Morgan C; von Hippel, Peter H; Marcus, Andrew H

2016-12-29

Recent advances in single-molecule fluorescence imaging have made it possible to perform measurements on microsecond time scales. Such experiments have the potential to reveal detailed information about the conformational changes in biological macromolecules, including the reaction pathways and dynamics of the rearrangements involved in processes, such as sequence-specific DNA "breathing" and the assembly of protein-nucleic acid complexes. Because microsecond-resolved single-molecule trajectories often involve "sparse" data, that is, they contain relatively few data points per unit time, they cannot be easily analyzed using the standard protocols that were developed for single-molecule experiments carried out with tens-of-millisecond time resolution and high "data density." Here, we describe a generalized approach, based on time-correlation functions, to obtain kinetic information from microsecond-resolved single-molecule fluorescence measurements. This approach can be used to identify short-lived intermediates that lie on reaction pathways connecting relatively long-lived reactant and product states. As a concrete illustration of the potential of this methodology for analyzing specific macromolecular systems, we accompany the theoretical presentation with the description of a specific biologically relevant example drawn from studies of reaction mechanisms of the assembly of the single-stranded DNA binding protein of the T4 bacteriophage replication complex onto a model DNA replication fork.

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.

Platelet-rich plasma for regeneration of neural feedback pathways around dental implants: a concise review and outlook on future possibilities

PubMed Central

Huang, Yan; Bornstein, Michael M; Lambrichts, Ivo; Yu, Hai-Yang; Politis, Constantinus; Jacobs, Reinhilde

2017-01-01

Along with the development of new materials, advanced medical imaging and surgical techniques, osseointegrated dental implants are considered a successful and constantly evolving treatment modality for the replacement of missing teeth in patients with complete or partial edentulism. The importance of restoring the peripheral neural feedback pathway and thus repairing the lack of periodontal mechanoreceptors after tooth extraction has been highlighted in the literature. Nevertheless, regenerating the nerve fibers and reconstructing the neural feedback pathways around osseointegrated implants remain a challenge. Recent studies have provided evidence that platelet-rich plasma (PRP) therapy is a promising treatment for musculoskeletal injuries. Because of its high biological safety, convenience and usability, PRP therapy has gradually gained popularity in the clinical field. Although much remains to be learned, the growth factors from PRP might play key roles in peripheral nerve repair mechanisms. This review presents known growth factors contributing to the biological efficacy of PRP and illustrates basic and (pre-)clinical evidence regarding the use of PRP and its relevant products in peripheral nerve regeneration. In addition, the potential of local application of PRP for structural and functional recovery of injured peripheral nerves around dental implants is discussed. PMID:28282030

Formation of nucleobases in a Miller-Urey reducing atmosphere.

PubMed

Ferus, Martin; Pietrucci, Fabio; Saitta, Antonino Marco; Knížek, Antonín; Kubelík, Petr; Ivanek, Ondřej; Shestivska, Violetta; Civiš, Svatopluk

2017-04-25

The Miller-Urey experiments pioneered modern research on the molecular origins of life, but their actual relevance in this field was later questioned because the gas mixture used in their research is considered too reducing with respect to the most accepted hypotheses for the conditions on primordial Earth. In particular, the production of only amino acids has been taken as evidence of the limited relevance of the results. Here, we report an experimental work, combined with state-of-the-art computational methods, in which both electric discharge and laser-driven plasma impact simulations were carried out in a reducing atmosphere containing NH 3 + CO. We show that RNA nucleobases are synthesized in these experiments, strongly supporting the possibility of the emergence of biologically relevant molecules in a reducing atmosphere. The reconstructed synthetic pathways indicate that small radicals and formamide play a crucial role, in agreement with a number of recent experimental and theoretical results.

Formation of nucleobases in a Miller–Urey reducing atmosphere

PubMed Central

Ferus, Martin; Pietrucci, Fabio; Saitta, Antonino Marco; Knížek, Antonín; Kubelík, Petr; Ivanek, Ondřej; Shestivska, Violetta; Civiš, Svatopluk

2017-01-01

The Miller–Urey experiments pioneered modern research on the molecular origins of life, but their actual relevance in this field was later questioned because the gas mixture used in their research is considered too reducing with respect to the most accepted hypotheses for the conditions on primordial Earth. In particular, the production of only amino acids has been taken as evidence of the limited relevance of the results. Here, we report an experimental work, combined with state-of-the-art computational methods, in which both electric discharge and laser-driven plasma impact simulations were carried out in a reducing atmosphere containing NH3 + CO. We show that RNA nucleobases are synthesized in these experiments, strongly supporting the possibility of the emergence of biologically relevant molecules in a reducing atmosphere. The reconstructed synthetic pathways indicate that small radicals and formamide play a crucial role, in agreement with a number of recent experimental and theoretical results. PMID:28396441

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.

Combined metabonomic and quantitative real-time PCR analyses reveal systems metabolic changes in Jurkat T-cells treated with HIV-1 Tat protein.

PubMed

Liao, Wenting; Tan, Guangguo; Zhu, Zhenyu; Chen, Qiuli; Lou, Ziyang; Dong, Xin; Zhang, Wei; Pan, Wei; Chai, Yifeng

2012-11-02

HIV-1 Tat protein is released by infected cells and can affect bystander uninfected T cells and induce numerous biological responses which contribute to its pathogenesis. To elucidate the complex pathogenic mechanism, we conducted a comprehensive investigation on Tat protein-related extracellular and intracellular metabolic changes in Jurkat T-cells using combined gas chromatography-mass spectrometry (GC-MS), reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and a hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS)-based metabonomics approach. Quantitative real-time PCR (qRT-PCR) analyses were further employed to measure expressions of several relevant enzymes together with perturbed metabolic pathways. Combined metabonomic and qRT-PCR analyses revealed that HIV-1 Tat caused significant and comprehensive metabolic changes, as represented by significant changes of 37 metabolites and 10 relevant enzymes in HIV-1 Tat-treated cells. Using MetaboAnalyst 2.0, it was found that 11 pathways (Impact-value >0.10) among the regulated pathways were acutely perturbed, including sphingolipid metabolism, glycine, serine and threonine metabolism, pyruvate metabolism, inositol phosphate metabolism, arginine and proline metabolism, citrate cycle, phenylalanine metabolism, tryptophan metabolism, pentose phosphate pathway, glycerophospholipid metabolism, glycolysis or gluconeogenesis. These results provide metabolic evidence of the complex pathogenic mechanism of HIV-1 Tat protein as a "viral toxin", and would help obligate Tat protein as "an important target" for therapeutic intervention and vaccine development.

Identification of personalized dysregulated pathways in hepatocellular carcinoma.

PubMed

Li, Hong; Jiang, Xiumei; Zhu, Shengjie; Sui, Lihong

2017-04-01

Hepatocellular carcinoma (HCC) is the most common liver malignancy, and ranks the fifth most prevalent malignant tumors worldwide. In general, HCC are detected until the disease is at an advanced stage and may miss the best chance for treatment. Thus, elucidating the molecular mechanisms is critical to clinical diagnosis and treatment for HCC. The purpose of this study was to identify dysregulated pathways of great potential functional relevance in the progression of HCC. Microarray data of 72 pairs of tumor and matched non-tumor surrounding tissues of HCC were transformed to gene expression data. Differentially expressed genes (DEG) between patients and normal controls were identified using Linear Models for Microarray Analysis. Personalized dysregulated pathways were identified using individualized pathway aberrance score module. 169 differentially expressed genes (DEG) were obtained with |logFC|≥1.5 and P≤0.01. 749 dysregulated pathways were obtained with P≤0.01 in pathway statistics, and there were 93 DEG overlapped in the dysregulated pathways. After performing normal distribution analysis, 302 pathways with the aberrance probability≥0.5 were identified. By ranking pathway with aberrance probability, the top 20 pathways were obtained. Only three DEGs (TUBA1C, TPR, CDC20) were involved in the top 20 pathways. These personalized dysregulated pathways and overlapped genes may give new insights into the underlying biological mechanisms in the progression of HCC. Particular attention can be focused on them for further research. Copyright © 2017 Elsevier GmbH. All rights reserved.

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.

The genomic landscape of chronic lymphocytic leukaemia: biological and clinical implications.

PubMed

Strefford, Jonathan C

2015-04-01

Chronic lymphocytic leukaemia (CLL) remains at the forefront of the genetic analysis of human tumours, principally due its prevalence, protracted natural history and accessibility to suitable material for analysis. With the application of high-throughput genetic technologies, we have an unbridled view of the architecture of the CLL genome, including a comprehensive description of the copy number and mutational landscape of the disease, a detailed picture of clonal evolution during pathogenesis, and the molecular mechanisms that drive genomic instability and therapeutic resistance. This work has nuanced the prognostic importance of established copy number alterations, and identified novel prognostically relevant gene mutations that function within biological pathways that are attractive treatment targets. Herein, an overview of recent genomic discoveries will be reviewed, with associated biological and clinical implications, and a view into how clinical implementation may be facilitated. © 2014 John Wiley & Sons Ltd.

Insight into the contribution of isoprostanoids to the health effects of omega 3 PUFAs.

PubMed

Joumard-Cubizolles, Laurie; Lee, Jetty Chung-Yung; Vigor, Claire; Leung, Ho Hang; Bertrand-Michel, Justine; Galano, Jean-Marie; Mazur, André; Durand, Thierry; Gladine, Cecile

2017-11-01

Omega 3 polyunsaturated fatty acids have been reported to confer beneficial health effects notably in the field of cardiovascular and inflammatory diseases. The current knowledge suggests a significant portion of the effects of omega 3 polyunsaturated fatty acids are mediated by their oxygenated metabolites. This review attempts to cover the current literature about the contribution of specific omega 3 oxygenated metabolites, namely omega 3 isoprostanoids, which are produced through free-radical mediated oxidation. A special emphasis has been given to the most biologically relevant omega 3 polyunsaturated fatty acids namely the α-linolenic, eicosapentaenoic and docosahexaenoic acids. The review includes a comprehensive description of the biosynthetic pathways, a summary of studies related to the biological significance of omega 3 isoprostanoids as well as a critical description of analytical development in the field of omega 3 isoprostanoids profiling in biological samples. Copyright © 2017 Elsevier Inc. All rights reserved.

Diversity-oriented synthetic strategy for developing a chemical modulator of protein-protein interaction

NASA Astrophysics Data System (ADS)

Kim, Jonghoon; Jung, Jinjoo; Koo, Jaeyoung; Cho, Wansang; Lee, Won Seok; Kim, Chanwoo; Park, Wonwoo; Park, Seung Bum

2016-10-01

Diversity-oriented synthesis (DOS) can provide a collection of diverse and complex drug-like small molecules, which is critical in the development of new chemical probes for biological research of undruggable targets. However, the design and synthesis of small-molecule libraries with improved biological relevance as well as maximized molecular diversity represent a key challenge. Herein, we employ functional group-pairing strategy for the DOS of a chemical library containing privileged substructures, pyrimidodiazepine or pyrimidine moieties, as chemical navigators towards unexplored bioactive chemical space. To validate the utility of this DOS library, we identify a new small-molecule inhibitor of leucyl-tRNA synthetase-RagD protein-protein interaction, which regulates the amino acid-dependent activation of mechanistic target of rapamycin complex 1 signalling pathway. This work highlights that privileged substructure-based DOS strategy can be a powerful research tool for the construction of drug-like compounds to address challenging biological targets.

From bedside to cell biology: a century of history on lysosomal dysfunction.

PubMed

Coutinho, Maria Francisca; Matos, Liliana; Alves, Sandra

2015-01-15

Lysosomal storage disorders (LSDs) are a group of rare genetic diseases, generally caused by a deficiency of specific lysosomal enzymes, which results in abnormal accumulation of undegraded substrates. The first clinical reports describing what were later shown to be LSDs were published more than a hundred years ago. In general, the history and pathophysiology of LSDs has impacted on our current knowledge of lysosomal biology. Classically, depending on the nature of the substrates, LSDs can be divided into different subgroups. The mucopolysaccharidoses (MPSs) are those caused by impaired degradation of glycosaminoglycans (GAGs). Amongst LSDs, the MPSs are a major group of pathologies with crucial historical relevance, since their study has revealed important biological pathways and highlighted interconnecting pathological cascades which are still being unveiled nowadays. Here we review the major historical discoveries in the field of LSDs and their impact on basic cellular knowledge and practical applications. Attention will be focused on the MPSs, with occasional references to other LSDs. We will show as studies on the metabolic basis of this group of diseases have increased our knowledge of the complex degradative pathways associated with the lysosome and established the basis to the development of specific therapeutic approaches aiming at correcting or, at least ameliorating their associated phenotypes. Copyright © 2014 Elsevier B.V. All rights reserved.

Expert consensus paper on the use of Vedolizumab for the management of patients with moderate-to-severe Inflammatory Bowel Disease.

PubMed

Armuzzi, Alessandro; Gionchetti, Paolo; Daperno, Marco; Danese, Silvio; Orlando, Ambrogio; Lia Scribano, Maria; Vecchi, Maurizio; Rizzello, Fernando

2016-04-01

Crohn's Disease (CD) and Ulcerative Colitis (UC) are chronic, relapsing conditions resulting from uncontrolled inflammation of the intestinal mucosa. Both conditions are associated with significant disability and patients with CD face higher mortality rates compared to the general population. The increasing understanding of the immunological basis of the disease led to the introduction of biologic therapies targeting key pathways of the natural and adaptive immune response such as Tumor Necrosis Factor α (TNF-α) inhibitors and, more recently, integrin-receptor antagonists. Treatment with TNF-α inhibitors improved clinical and patient-reported outcomes for many patients who did not benefit from conventional therapy. However, a sizeable share of patients still face suboptimal outcomes due to primary or secondary therapy failure. With the introduction of VDZ, a biologic treatment targeting novel IBD-relevant biologic pathways, it is crucial to understand how to integrate such innovations into current clinical practice. To this end, a panel of 14 Italian experts in the management of IBD met for a roundtable discussion. Recommendations concerning the management of moderate-to-severe IBD based on experts' opinions and literature review are discussed in the present report. Copyright © 2016 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling

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

Cucinotta, Francis A

The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently, the transforming growth factor β (TGFβ)more » pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses, and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low-dose responses and cross-talk between the ATM and TGFβ pathways initiated by low- and high-LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to crosstalk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental approaches to apply to these problems using confocal microscopy and flow cytometry to detail changes at low dose/dose-rate in order to understand individual cell responses, and will establish our mathematical models based on the experimental findings resulting from changes in DNA repair, apoptosis and proliferation.« less

Systems Biology Model of Interactions Between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFbeta and ATM Signaling

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

O'Neill, Peter; Anderson, Jennifer

The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently the transforming growth factor β (TGFβ)more » pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low dose responses and cross-talk between the ATM and TGFβ pathways initiated by low and high LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to cross- talk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental approaches to apply to these problems using confocal microscopy and flow cytometry to detail changes at low dose/dose-rate in order to understand individual cell responses, and will establish our mathematical models based on the experimental findings resulting from changes in DNA repair, apoptosis and proliferation.« less

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

New insights about host response to smallpox using microarray data

PubMed Central

Esteves, Gustavo H; Simoes, Ana CQ; Souza, Estevao; Dias, Rodrigo A; Ospina, Raydonal; Venancio, Thiago M

2007-01-01

Background Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. Results We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Conclusion Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems. PMID:17718913

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation

PubMed Central

Hawes, Norman L.; Trantow, Colleen M.; Chang, Bo; John, Simon W.M.

2010-01-01

Summary Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among sixteen mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease. PMID:18715234

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation.

PubMed

Anderson, Michael G; Hawes, Norman L; Trantow, Colleen M; Chang, Bo; John, Simon W M

2008-10-01

Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among 16 mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease.

cPath: open source software for collecting, storing, and querying biological pathways.

PubMed

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-11-13

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.

t4 Workshop Report*

PubMed Central

Kleensang, Andre; Maertens, Alexandra; Rosenberg, Michael; Fitzpatrick, Suzanne; Lamb, Justin; Auerbach, Scott; Brennan, Richard; Crofton, Kevin M.; Gordon, Ben; Fornace, Albert J.; Gaido, Kevin; Gerhold, David; Haw, Robin; Henney, Adriano; Ma’ayan, Avi; McBride, Mary; Monti, Stefano; Ochs, Michael F.; Pandey, Akhilesh; Sharan, Roded; Stierum, Rob; Tugendreich, Stuart; Willett, Catherine; Wittwehr, Clemens; Xia, Jianguo; Patton, Geoffrey W.; Arvidson, Kirk; Bouhifd, Mounir; Hogberg, Helena T.; Luechtefeld, Thomas; Smirnova, Lena; Zhao, Liang; Adeleye, Yeyejide; Kanehisa, Minoru; Carmichael, Paul; Andersen, Melvin E.; Hartung, Thomas

2014-01-01

Summary Despite wide-spread consensus on the need to transform toxicology and risk assessment in order to keep pace with technological and computational changes that have revolutionized the life sciences, there remains much work to be done to achieve the vision of toxicology based on a mechanistic foundation. A workshop was organized to explore one key aspect of this transformation – the development of Pathways of Toxicity (PoT) as a key tool for hazard identification based on systems biology. Several issues were discussed in depth in the workshop: The first was the challenge of formally defining the concept of a PoT as distinct from, but complementary to, other toxicological pathway concepts such as mode of action (MoA). The workshop came up with a preliminary definition of PoT as “A molecular definition of cellular processes shown to mediate adverse outcomes of toxicants”. It is further recognized that normal physiological pathways exist that maintain homeostasis and these, sufficiently perturbed, can become PoT. Second, the workshop sought to define the adequate public and commercial resources for PoT information, including data, visualization, analyses, tools, and use-cases, as well as the kinds of efforts that will be necessary to enable the creation of such a resource. Third, the workshop explored ways in which systems biology approaches could inform pathway annotation, and which resources are needed and available that can provide relevant PoT information to the diverse user communities. PMID:24127042

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

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.

Pathways and therapeutic targets in melanoma

PubMed Central

Shtivelman, Emma; Davies, Michael A.; Hwu, Patrick; Yang, James; Lotem, Michal; Oren, Moshe; Flaherty, Keith T.; Fisher, David E.

2014-01-01

This review aims to summarize the current knowledge of molecular pathways and their clinical relevance in melanoma. Metastatic melanoma was a grim diagnosis, but in recent years tremendous advances have been made in treatments. Chemotherapy provided little benefit in these patients, but development of targeted and new immune approaches made radical changes in prognosis. This would not have happened without remarkable advances in understanding the biology of disease and tremendous progress in the genomic (and other “omics”) scale analyses of tumors. The big problems facing the field are no longer focused exclusively on the development of new treatment modalities, though this is a very busy area of clinical research. The focus shifted now to understanding and overcoming resistance to targeted therapies, and understanding the underlying causes of the heterogeneous responses to immune therapy. PMID:24743024

Plasma membrane wounding and repair in pulmonary diseases.

PubMed

Cong, Xiaofei; Hubmayr, Rolf D; Li, Changgong; Zhao, Xiaoli

2017-03-01

Various pathophysiological conditions such as surfactant dysfunction, mechanical ventilation, inflammation, pathogen products, environmental exposures, and gastric acid aspiration stress lung cells, and the compromise of plasma membranes occurs as a result. The mechanisms necessary for cells to repair plasma membrane defects have been extensively investigated in the last two decades, and some of these key repair mechanisms are also shown to occur following lung cell injury. Because it was theorized that lung wounding and repair are involved in the pathogenesis of acute respiratory distress syndrome (ARDS) and idiopathic pulmonary fibrosis (IPF), in this review, we summarized the experimental evidence of lung cell injury in these two devastating syndromes and discuss relevant genetic, physical, and biological injury mechanisms, as well as mechanisms used by lung cells for cell survival and membrane repair. Finally, we discuss relevant signaling pathways that may be activated by chronic or repeated lung cell injury as an extension of our cell injury and repair focus in this review. We hope that a holistic view of injurious stimuli relevant for ARDS and IPF could lead to updated experimental models. In addition, parallel discussion of membrane repair mechanisms in lung cells and injury-activated signaling pathways would encourage research to bridge gaps in current knowledge. Indeed, deep understanding of lung cell wounding and repair, and discovery of relevant repair moieties for lung cells, should inspire the development of new therapies that are likely preventive and broadly effective for targeting injurious pulmonary diseases. Copyright © 2017 the American Physiological Society.

Alternative end-joining pathway(s): bricolage at DNA breaks.

PubMed

Frit, Philippe; Barboule, Nadia; Yuan, Ying; Gomez, Dennis; Calsou, Patrick

2014-05-01

To cope with DNA double strand break (DSB) genotoxicity, cells have evolved two main repair pathways: homologous recombination which uses homologous DNA sequences as repair templates, and non-homologous Ku-dependent end-joining involving direct sealing of DSB ends by DNA ligase IV (Lig4). During the last two decades a third player most commonly named alternative end-joining (A-EJ) has emerged, which is defined as any Ku- or Lig4-independent end-joining process. A-EJ increasingly appears as a highly error-prone bricolage on DSBs and despite expanding exploration, it still escapes full characterization. In the present review, we discuss the mechanism and regulation of A-EJ as well as its biological relevance under physiological and pathological situations, with a particular emphasis on chromosomal instability and cancer. Whether or not it is a genuine DSB repair pathway, A-EJ is emerging as an important cellular process and understanding A-EJ will certainly be a major challenge for the coming years. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

The role of apoptosis in respiratory diseases.

PubMed

Pierce, Janet D; Pierce, Jana; Stremming, Stephanie; Fakhari, Mahtab; Clancy, Richard L

2007-01-01

The purpose of this article is to define apoptosis and describe how this cellular pathway is relevant to the pathogenesis of different respiratory diseases. This will assist clinical nurse specialists in understanding how new drugs and therapies inhibit and stimulate apoptotic pathways. Clinical nurse specialists need to expand their knowledge concerning the role of apoptosis so that they can better expand their spheres of influence. The 4 stages of apoptosis are discussed, as well as the various apoptotic pathways involved with asthma, emphysema, and acute respiratory distress syndrome that promote and inhibit apoptosis in patients. It is crucial for clinical nurse specialists to know what apoptosis is and how it relates to different pathophysiologic states. The challenge facing clinical nurse specialists is how to be kept informed and current concerning molecular and cellular mechanisms that are important in the practice setting. Strategies needed to maintain expertise include acquiring new knowledge, developing new skills, and changing attitudes about molecular biology. Apoptosis must become a significant part of any health professionals' continuing educational program because it has been recognized as the pathway to most any disease. Clinical nurse specialists who understand apoptosis and its pathways can use this knowledge to aid in the prevention and treatment of respiratory diseases.

Biological therapy targeting the IL-23/IL-17 axis in inflammatory bowel disease.

PubMed

Verstockt, Bram; Van Assche, Gert; Vermeire, Séverine; Ferrante, Marc

2017-01-01

As many inflammatory bowel disease (IBD) patients do not benefit from long-term anti-tumour necrosis factor treatment, new anti-inflammatories are urgently needed. After the discovery of the interleukin (IL) 23/17 axis being pivotal in IBD pathogenesis, many different compounds were developed, targeting different components within this pathway. Areas covered: A literature search to March 2016 was performed to identify the most relevant reports on the role of the IL-23/IL-17 axis in IBD and on the different molecules targeting this pathway. First, the authors briefly summarize the immunology of the IL-23/IL-17 pathway to elucidate the mode of action of all different agents. Second, they describe all different molecules targeting this pathway. Besides discussing efficacy and safety data, they also explore immunogenicity, exposure during pregnancy and pharmacokinetics. Expert opinion: A new era in IBD treatment has recently been initiated: besides immunomodulators and TNF-antagonists, anti-adhesion molecules and monoclonal antibodies targeting the IL-23/IL-17 pathway have been developed. Biomarkers for personalized medicine are urgently needed. This therapeutic (r)evolution will further improve disease-related and patient-reported outcome, though a lot of questions should still be addressed in future years.

Pivotal role of the muscle-contraction pathway in cryptorchidism and evidence for genomic connections with cardiomyopathy pathways in RASopathies.

PubMed

Cannistraci, Carlo V; Ogorevc, Jernej; Zorc, Minja; Ravasi, Timothy; Dovc, Peter; Kunej, Tanja

2013-02-14

Cryptorchidism is the most frequent congenital disorder in male children; however the genetic causes of cryptorchidism remain poorly investigated. Comparative integratomics combined with systems biology approach was employed to elucidate genetic factors and molecular pathways underlying testis descent. Literature mining was performed to collect genomic loci associated with cryptorchidism in seven mammalian species. Information regarding the collected candidate genes was stored in MySQL relational database. Genomic view of the loci was presented using Flash GViewer web tool (http://gmod.org/wiki/Flashgviewer/). DAVID Bioinformatics Resources 6.7 was used for pathway enrichment analysis. Cytoscape plug-in PiNGO 1.11 was employed for protein-network-based prediction of novel candidate genes. Relevant protein-protein interactions were confirmed and visualized using the STRING database (version 9.0). The developed cryptorchidism gene atlas includes 217 candidate loci (genes, regions involved in chromosomal mutations, and copy number variations) identified at the genomic, transcriptomic, and proteomic level. Human orthologs of the collected candidate loci were presented using a genomic map viewer. The cryptorchidism gene atlas is freely available online: http://www.integratomics-time.com/cryptorchidism/. Pathway analysis suggested the presence of twelve enriched pathways associated with the list of 179 literature-derived candidate genes. Additionally, a list of 43 network-predicted novel candidate genes was significantly associated with four enriched pathways. Joint pathway analysis of the collected and predicted candidate genes revealed the pivotal importance of the muscle-contraction pathway in cryptorchidism and evidence for genomic associations with cardiomyopathy pathways in RASopathies. The developed gene atlas represents an important resource for the scientific community researching genetics of cryptorchidism. The collected data will further facilitate development of novel genetic markers and could be of interest for functional studies in animals and human. The proposed network-based systems biology approach elucidates molecular mechanisms underlying co-presence of cryptorchidism and cardiomyopathy in RASopathies. Such approach could also aid in molecular explanation of co-presence of diverse and apparently unrelated clinical manifestations in other syndromes.

cPath: open source software for collecting, storing, and querying biological pathways

PubMed Central

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-01-01

Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041

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.

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

The Biological Clock: A Pivotal Hub in Non-alcoholic Fatty Liver Disease Pathogenesis

PubMed Central

Mazzoccoli, Gianluigi; De Cosmo, Salvatore; Mazza, Tommaso

2018-01-01

Non-alcoholic fatty liver disease (NAFLD) is the most frequent hepatic pathology in the Western world and may evolve into steatohepatitis (NASH), increasing the risk of cirrhosis, portal hypertension and hepatocellular carcinoma. NAFLD derives from the accumulation of hepatic fat due to discrepant free fatty acid metabolism. Other factors contributing to this are deranged nutrients and bile acids fluxes as well as alterations in nuclear receptors, hormones, and intermediary metabolites, which impact on signaling pathways involved in metabolism and inflammation. Autophagy and host gut-microbiota interplay are also relevant to NAFLD pathogenesis. Notably, liver metabolic pathways and bile acid synthesis as well as autophagic and immune/inflammatory processes all show circadian patterns driven by the biological clock. Gut microbiota impacts on the biological clock, at the same time as the appropriate timing of metabolic fluxes, hormone secretion, bile acid turnover, autophagy and inflammation with behavioural cycles of fasting/feeding and sleeping/waking is required to circumvent hepatosteatosis, indicating significant interactions of the gut and circadian processes in NAFLD pathophysiology. Several time-related factors and processes interplay in NAFLD development, with the biological clock proposed to act as a network level hub. Deranged physiological rhythms (chronodisruption) may also play a role in liver steatosis pathogenesis. The current article reviews how the circadian clock circuitry intimately interacts with several mechanisms involved in the onset of hepatosteatosis and its progression to NASH, thereby contributing to the global NAFLD epidemic. PMID:29662454

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.

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

Wnt/β-Catenin Signaling in Liver Development, Homeostasis, and Pathobiology

PubMed Central

Russell, Jacquelyn O.; Monga, Satdarshan P.

2018-01-01

The liver is an organ that performs a multitude of functions, and its health is pertinent and indispensable to survival. Thus, the cellular and molecular machinery driving hepatic functions is of utmost relevance. The Wnt signaling pathway is one such signaling cascade that enables hepatic homeostasis and contributes to unique hepatic attributes such as metabolic zonation and regeneration. The Wnt/β-catenin pathway plays a role in almost every facet of liver biology. Furthermore, its aberrant activation is also a hallmark of various hepatic pathologies. In addition to its signaling function, β-catenin also plays a role at adherens junctions. Wnt/β-catenin signaling also influences the function of many different cell types. Due to this myriad of functions, Wnt/β-catenin signaling is complex, context-dependent, and highly regulated. In this review, we discuss the Wnt/β-catenin signaling pathway, its role in cell-cell adhesion and liver function, and the cell type–specific roles of Wnt/β-catenin signaling as it relates to liver physiology and pathobiology. PMID:29125798

Identification of genes involved in the biology of atypical teratoid/rhabdoid tumours using Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Jeibmann, Astrid; Eikmeier, Kristin; Linge, Anna; Kool, Marcel; Koos, Björn; Schulz, Jacqueline; Albrecht, Stefanie; Bartelheim, Kerstin; Frühwald, Michael C.; Pfister, Stefan M.; Paulus, Werner; Hasselblatt, Martin

2014-06-01

Atypical teratoid/rhabdoid tumours (AT/RT) are malignant brain tumours. Unlike most other human brain tumours, AT/RT are characterized by inactivation of one single gene, SMARCB1. SMARCB1 is a member of the evolutionarily conserved SWI/SNF chromatin remodelling complex, which has an important role in the control of cell differentiation and proliferation. Little is known, however, about the pathways involved in the oncogenic effects of SMARCB1 inactivation, which might also represent targets for treatment. Here we report a comprehensive genetic screen in the fruit fly that revealed several genes not yet associated with loss of snr1, the Drosophila homologue of SMARCB1. We confirm the functional role of identified genes (including merlin, kibra and expanded, known to regulate hippo signalling pathway activity) in human rhabdoid tumour cell lines and AT/RT tumour samples. These results demonstrate that fly models can be employed for the identification of clinically relevant pathways in human cancer.

Transcriptomic Responses During Early Development Following Arsenic Exposure in Western Clawed Frogs, Silurana tropicalis.

PubMed

Zhang, Jing; Koch, Iris; Gibson, Laura A; Loughery, Jennifer R; Martyniuk, Christopher J; Button, Mark; Caumette, Guilhem; Reimer, Kenneth J; Cullen, William R; Langlois, Valerie S

2015-12-01

Arsenic compounds are widespread environmental contaminants and exposure elicits serious health issues, including early developmental anomalies. Depending on the oxidation state, the intermediates of arsenic metabolism interfere with a range of subcellular events, but the fundamental molecular events that lead to speciation-dependent arsenic toxicity are not fully elucidated. This study therefore assesses the impact of arsenic exposure on early development by measuring speciation and gene expression profiles in the developing Western clawed frog (Silurana tropicalis) larvae following the environmental relevant 0.5 and 1 ppm arsenate exposure. Using HPLC-ICP-MS, arsenate, dimethylarsenic acid, arsenobetaine, arsenocholine, and tetramethylarsonium ion were detected. Microarray and pathway analyses were utilized to characterize the comprehensive transcriptomic responses to arsenic exposure. Clustering analysis of expression data showed distinct gene expression patterns in arsenate treated groups when compared with the control. Pathway enrichment revealed common biological themes enriched in both treatments, including cell signal transduction, cell survival, and developmental pathways. Moreover, the 0.5 ppm exposure led to the enrichment of pathways and biological processes involved in arsenic intake or efflux, as well as histone remodeling. These compensatory responses are hypothesized to be responsible for maintaining an in-body arsenic level comparable to control animals. With no appreciable changes observed in malformation and mortality between control and exposed larvae, this is the first study to suggest that the underlying transcriptomic regulations related to signal transduction, cell survival, developmental pathways, and histone remodeling may contribute to maintaining ongoing development while coping with the potential arsenic toxicity in S. tropicalis during early development. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Methane to bioproducts: the future of the bioeconomy?

PubMed

Pieja, Allison J; Morse, Molly C; Cal, Andrew J

2017-12-01

Methanotrophs have been studied since the 1970s, but interest has increased tremendously in recent years due to their potential to transform methane into valuable bioproducts. The vast quantity of available methane and the low price of methane as natural gas have helped to spur this interest. The most well-studied, biologically-derived products from methane include methanol, polyhydroxyalkanoates, and single cell protein. However, many other high-interest chemicals such as biofuels or high-value products such as ectoine could be made industrially relevant through metabolic engineering. Although challenges must be overcome to achieve commercialization of biologically manufactured methane-to-products, taking a holistic view of the production process or radically re-imagining pathways could lead to a future bioeconomy with methane as the primary feedstock. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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

Cellular processes involved in human epidermal cells exposed to extremely low frequency electric fields.

PubMed

Collard, J-F; Hinsenkamp, M

2015-05-01

We observed on different tissues and organisms a biological response after exposure to pulsed low frequency and low amplitude electric or electromagnetic fields but the precise mechanism of cell response remains unknown. The aim of this publication is to understand, using bioinformatics, the biological relevance of processes involved in the modification of gene expression. The list of genes analyzed was obtained after microarray protocol realized on cultures of human epidermal explants growing on deepidermized human skin exposed to a pulsed low frequency electric field. The directed acyclic graph on a WebGestalt Gene Ontology module shows six categories under the biological process root: "biological regulation", "cellular process", "cell proliferation", "death", "metabolic process" and "response to stimulus". Enriched derived categories are coherent with the type of in vitro culture, the stimulation protocol or with the previous results showing a decrease of cell proliferation and an increase of differentiation. The Kegg module on WebGestalt has highlighted "cell cycle" and "p53 signaling pathway" as significantly involved. The Kegg website brings out interactions between FoxO, MAPK, JNK, p53, p38, PI3K/Akt, Wnt, mTor or NF-KappaB. Some genes expressed by the stimulation are known to have an exclusive function on these pathways. Analyses performed with Pathway Studio linked cell proliferation, cell differentiation, apoptosis, cell cycle, mitosis, cell death etc. with our microarrays results. Medline citation generated by the software and the fold change variation confirms a diminution of the proliferation, activation of the differentiation and a less well-defined role of apoptosis or wound healing. Wnt and DKK functional classes, DKK1, MACF1, ATF3, MME, TXNRD1, and BMP-2 genes proposed in previous publications after a manual analysis are also highlighted with other genes after Pathway Studio automatic procedure. Finally, an analysis conducted on a list of genes characterized by an accelerated regulation after extremely low frequency pulsed stimulation also confirms their role in the processes of cell proliferation and differentiation. Bioinformatics approach allows in-depth research, without the bias of pre-selection, on cellular processes involved in a huge gene list. Copyright © 2015 Elsevier Inc. All rights reserved.

Twenty-five years after "Wingspread"- Environmental endocrine disruptors (EDCs) and human health.

PubMed

Gray, Leon Earl

2017-04-01

The aim of this paper is to provide the reader with a view of the Endocrine Disruptor Chemical (EDC) research field and its relevance to human health. My perspective is from working on the effects of EDCs that act via the androgen (A) or estrogen (E) signaling pathways in a regulatory agency for the last four decades with the objective of producing data that risk assessors could use to reduce the uncertainty in risk assessment. In vitro and in vivo data from our studies has contributed to regulatory agencies decision-making since the 1990s (https://www3.epa.gov/pesticides/chem_search/cleared_reviews/csr_PC-113201_7-Apr-98_238.pdf). From the start, we were evaluating the utility of in vitro and short-term in vivo effects to predict the adverse effects in developing animals [1; 2]. This approach has expanded greatly to include what is now known as Adverse Outcome Pathways (AOP) and networks (AOPn) [3; 4]. The AOP framework for the effects of chemicals that disrupt androgen signaling during sexual differentiation of the fetal male rat provides biological context for extrapolating mechanistic information from in vitro and in vivo assays in rodents to other species including humans. Such an approach has biological validity because the E and A pathways are highly conserved in vertebrates, including humans and laboratory animals.

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

The Impact of Biosampling Procedures on Molecular Data Interpretation*

PubMed Central

Sköld, Karl; Alm, Henrik; Scholz, Birger

2013-01-01

The separation between biological and technical variation without extensive use of technical replicates is often challenging, particularly in the context of different forms of protein and peptide modifications. Biosampling procedures in the research laboratory are easier to conduct within a shorter time frame and under controlled conditions as compared with clinical sampling, with the latter often having issues of reproducibility. But is the research laboratory biosampling really less variable? Biosampling introduces within minutes rapid tissue-specific changes in the cellular microenvironment, thus inducing a range of different pathways associated with cell survival. Biosampling involves hypoxia and, depending on the circumstances, hypothermia, circumstances for which there are evolutionarily conserved defense strategies in the range of species and also are relevant for the range of biomedical conditions. It remains unclear to what extent such adaptive processes are reflected in different biosampling procedures or how important they are for the definition of sample quality. Lately, an increasing number of comparative studies on different biosampling approaches, post-mortem effects and pre-sampling biological state, have investigated such immediate early biosampling effects. Commonalities between biosampling effects and a range of ischemia/reperfusion- and hypometabolism/anoxia-associated biological phenomena indicate that even small variations in post-sampling time intervals are likely to introduce a set of nonrandom and tissue-specific effects of experimental importance (both in vivo and in vitro). This review integrates the information provided by these comparative studies and discusses how an adaptive biological perspective in biosampling procedures may be relevant for sample quality issues. PMID:23382104

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...

Transcriptional profiling identifies the long noncoding RNA plasmacytoma variant translocation (PVT1) as a novel regulator of the asthmatic phenotype in human airway smooth muscle.

PubMed

Austin, Philip J; Tsitsiou, Eleni; Boardman, Charlotte; Jones, Simon W; Lindsay, Mark A; Adcock, Ian M; Chung, Kian Fan; Perry, Mark M

2017-03-01

The mechanism underlying nonsevere and severe asthma remains unclear, although it is commonly associated with increased airway smooth muscle (ASM) mass. Long noncoding RNAs (lncRNAs) are known to be important in regulating healthy primary airway smooth muscle cells (ASMCs), whereas changed expression has been observed in CD8 T cells from patients with severe asthma. Primary ASMCs were isolated from healthy subjects (n = 9) and patients classified as having nonsevere (n = 9) or severe (n = 9) asthma. ASMCs were exposed to dexamethasone and FCS. mRNA and lncRNA expression was measured by using a microarray and quantitative real-time PCR. Bioinformatic analysis was used to examine relevant biological pathways. Finally, the lncRNA plasmacytoma variant translocation 1 (PVT1) was inhibited by transfection of primary ASMCs with small interfering RNAs, and the effect on ASMC phenotype was examined. The mRNA expression profile was significantly different between patient groups after exposure to dexamethasone and FCS, and these were associated with biological pathways that might be relevant to the pathogenesis of asthma, including cellular proliferation and pathways associated with glucocorticoid activity. We also observed a significant change in lncRNA expression, yet the expression of only one lncRNA (PVT1) is decreased in patients with corticosteroid-sensitive nonsevere asthma and increased in patients with corticosteroid-insensitive severe asthma. Subsequent targeting studies demonstrated the importance of this lncRNA in controlling both proliferation and IL-6 release in ASMCs from patients with severe asthma. lncRNAs are associated with the aberrant phenotype observed in ASMCs from asthmatic patients. Targeting PVT1 might be effective in reducing airway remodeling in asthmatic patients. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Suppression of NF-κB signal pathway by NLRC3-like protein in stony coral Acropora aculeus under heat stress.

PubMed

Zhou, Zhi; Wu, Yibo; Zhang, Chengkai; Li, Can; Chen, Guangmei; Yu, Xiaopeng; Shi, Xiaowei; Xu, Yanlai; Wang, Lingui; Huang, Bo

2017-08-01

Heat stress is the most common factor for coral bleaching, which has increased both in frequency and severity due to global warming. In the present study, the stony coral Acropora aculeus was subjected to acute heat stress and entire transcriptomes were sequenced via the next generation sequencing platform. Four paired-end libraries were constructed and sequenced in two groups, including a control and a heat stress group. A total of 120,319,751 paired-end reads with lengths of 2 × 100 bp were assembled and 55,021 coral-derived genes were obtained. After read mapping and abundance estimation, 9110 differentially expressed genes were obtained in the comparison between the control and heat stress group, including 4465 significantly upregulated and 4645 significantly downregulated genes. Twenty-three GO terms in the Biological Process category were overrepresented for significantly upregulated genes, and divided into six groups according to their relationship. These three groups were related to the NF-κB signal pathway, and the remaining three groups were relevant for pathogen response, immunocyte activation and protein ubiquitination. Forty-three common genes were found in four GO terms, which were directly related to the NF-κB signal pathway. These included 2 NACHT, LRR, PYD domains-containing protein, 5 nucleotide-binding oligomerization domain-containing protein, 29 NLRC3-like protein, 4 NLRC5-like protein, and 3 uncharacterized protein. For significantly downregulated genes, 27 overrepresented GO terms were found in the Biological Process category, which were relevant to protein ubiquitination and ATP metabolism. Our results indicate that heat stress suppressed the immune response level via the NLRC3-like protein, the fine-tuning of protein turnover activity, and ATP metabolism. This might disrupt the balance of coral-zooxanthellae symbiosis and result in the bleaching of the coral A. aculeus. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Functional relevance of protein glycosylation to the pro-inflammatory effects of extracellular matrix metalloproteinase inducer (EMMPRIN) on monocytes/macrophages.

PubMed

Ge, Heng; Yuan, Wei; Liu, Jidong; He, Qing; Ding, Song; Pu, Jun; He, Ben

2015-01-01

Extracellular matrix metalloproteinase inducer (EMMPRIN) is an important pro-inflammatory protein involved in the cellular functions of monocytes/macrophages. We have hypothesized that high-level heterogeneousness of protein glycosylation of EMMPRIN may have functional relevance to its biological effects and affect the inflammatory activity of monocytes/macrophages. The glycosylation patterns of EMMPRIN expressed by monocytes/macrophages (THP-1 cells) in response to different extracellular stimuli were observed, and the structures of different glycosylation forms were identified. After the purification of highly- and less-glycosylated proteins respectively, the impacts of different glycosylation forms on the pro-inflammatory effects of EMMPRIN were examined in various aspects, such as cell adhesion to endothelial cells, cell migrations, cytokine expression, and activation of inflammatory signalling pathway. 1) It was mainly the highly-glycosylated form of EMMPRIN (HG-EMMPRIN) that increased after being exposed to inflammatory signals (PMA and H2O2). 2) Glycosylation of EMMPRIN in monocytes/macrophages led to N-linked-glycans being added to the protein, with the HG form containing complex-type glycans and the less-glycosylated form (LG) the simple type. 3) Only the HG-EMMPRIN but not the LG-EMMPRIN exhibited pro-inflammatory effects and stimulated inflammatory activities of the monocytes/macrophages (i.e., activation of ERK1/2 and NF-κB pathway, enhanced monocyte-endothelium adhesion, cell migration and matrix metalloproteinase -9 expression). Post-transcriptional glycosylation represents an important mechanism that determines the biological effects of EMMPRIN in monocytes/macrophages. Glycosylation of EMMPRIN may serve as a potential target for regulating the inflammatory activities of monocytes/macrophages.

Signalling Network Construction for Modelling Plant Defence Response

PubMed Central

Miljkovic, Dragana; Stare, Tjaša; Mozetič, Igor; Podpečan, Vid; Petek, Marko; Witek, Kamil; Dermastia, Marina; Lavrač, Nada; Gruden, Kristina

2012-01-01

Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for modelling other biological systems, given that an adequate vocabulary is provided. PMID:23272172

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.

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.

Adapting biomarker technologies to adverse outcome ...

EPA Pesticide Factsheets

Adverse outcome pathways (AOP) research is a relatively new concept in human systems biology for assessing the molecular level linkage from an initiating (chemical) event that could lead to a disease state. Although most implementations of AOPs are based on liquids analyses, there are now new technologies being considered derived from the broad field of breath research, especially in applications of gas-phase analysis and instrumentation. The ultimate goal is to discover disease progressions in human or animal systems, identify them at the molecular or cellular level, and then choose analytes that can distinctly define the presence of a particular path (Ankley et al. 2010, Villeneuve et al. 2014). Once such in vivo pathways are identified, then in vitro assays can be developed for streamlined testing of chemical effects without additional human or animal based studies (Pleil et al. 2012). Recent work has focused on discovery analysis in breath, or other biological media, wherein as many as possible compounds are cataloged and then linked to their biochemical source as exogenous (external), endogenous (internal) or from the microbiome (Pleil et al. 2013a, de Lacy Costello 2014, Pleil et al. 2013b, Trefz et al. 2013, Pleil et al. 2014). Such research lays the groundwork for identifying compounds from systems biology that might be relevant for developing AOPs for in vitro research. The National Exposure Research Laboratory’s (NERL’s) Human Exposure and Atm

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

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

PubMed Central

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-01-01

Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways. PMID:18764936

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

PubMed

Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

The use of 'Omics technology to rationally improve industrial mammalian cell line performance.

PubMed

Lewis, Amanda M; Abu-Absi, Nicholas R; Borys, Michael C; Li, Zheng Jian

2016-01-01

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development. © 2015 Wiley Periodicals, Inc.

Identification of the fitness determinants of budding yeast on a natural substrate.

PubMed

Filteau, Marie; Charron, Guillaume; Landry, Christian R

2017-04-01

The budding yeasts are prime models in genomics and cell biology, but the ecological factors that determine their success in non-human-associated habitats is poorly understood. In North America Saccharomyces yeasts are present on the bark of deciduous trees, where they feed on bark and sap exudates. In the North East, Saccharomyces paradoxus is found on maples, which makes maple sap a natural substrate for this species. We measured growth rates of S. paradoxus natural isolates on maple sap and found variation along a geographical gradient not explained by the inherent variation observed under optimal laboratory conditions. We used a functional genomic screen to reveal the ecologically relevant genes and conditions required for optimal growth in this substrate. We found that the allantoin degradation pathway is required for optimal growth in maple sap, in particular genes necessary for allantoate utilization, which we demonstrate is the major nitrogen source available to yeast in this environment. Growth with allantoin or allantoate as the sole nitrogen source recapitulated the variation in growth rates in maple sap among strains. We also show that two lineages of S. paradoxus display different life-history traits on allantoin and allantoate media, highlighting the ecological relevance of this pathway.

MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

PubMed Central

Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

2014-01-01

Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow. PMID:24266674

A G Protein-biased Designer G Protein-coupled Receptor Useful for Studying the Physiological Relevance of Gq/11-dependent Signaling Pathways.

PubMed

Hu, Jianxin; Stern, Matthew; Gimenez, Luis E; Wanka, Lizzy; Zhu, Lu; Rossi, Mario; Meister, Jaroslawna; Inoue, Asuka; Beck-Sickinger, Annette G; Gurevich, Vsevolod V; Wess, Jürgen

2016-04-08

Designerreceptorsexclusivelyactivated by adesignerdrug (DREADDs) are clozapine-N-oxide-sensitive designer G protein-coupled receptors (GPCRs) that have emerged as powerful novel chemogenetic tools to study the physiological relevance of GPCR signaling pathways in specific cell types or tissues. Like endogenous GPCRs, clozapine-N-oxide-activated DREADDs do not only activate heterotrimeric G proteins but can also trigger β-arrestin-dependent (G protein-independent) signaling. To dissect the relative physiological relevance of G protein-mediatedversusβ-arrestin-mediated signaling in different cell types or physiological processes, the availability of G protein- and β-arrestin-biased DREADDs would be highly desirable. In this study, we report the development of a mutationally modified version of a non-biased DREADD derived from the M3muscarinic receptor that can activate Gq/11with high efficacy but lacks the ability to interact with β-arrestins. We also demonstrate that this novel DREADD is activein vivoand that cell type-selective expression of this new designer receptor can provide novel insights into the physiological roles of G protein (Gq/11)-dependentversusβ-arrestin-dependent signaling in hepatocytes. Thus, this novel Gq/11-biased DREADD represents a powerful new tool to study the physiological relevance of Gq/11-dependent signaling in distinct tissues and cell types, in the absence of β-arrestin-mediated cellular effects. Such studies should guide the development of novel classes of functionally biased ligands that show high efficacy in various pathophysiological conditions but display a reduced incidence of side effects. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Strawberry tannins inhibit IL-8 secretion in a cell model of gastric inflammation.

PubMed

Fumagalli, Marco; Sangiovanni, Enrico; Vrhovsek, Urska; Piazza, Stefano; Colombo, Elisa; Gasperotti, Mattia; Mattivi, Fulvio; De Fabiani, Emma; Dell'Agli, Mario

2016-09-01

In the present study we chemically profiled tannin-enriched extracts from strawberries and tested their biological properties in a cell model of gastric inflammation. The chemical and biological features of strawberry tannins after in vitro simulated gastric digestion were investigated as well. The anti-inflammatory activities of pure strawberry tannins were assayed to get mechanistic insights. Tannin-enriched extracts from strawberries inhibit IL-8 secretion in TNFα-treated human gastric epithelial cells by dampening the NF-κB signaling. In vitro simulated gastric digestion slightly affected the chemical composition and the biological properties of strawberry tannins. By using pure compounds, we found that casuarictin may act as a pure NF-κB inhibitor while agrimoniin inhibits IL-8 secretion also acting on other biological targets; in our system procyanidin B1 prevents the TNFα-induced effects without interfering with the NF-κB pathway. We conclude that strawberry tannins, even after in vitro simulated gastric digestion, exert anti-inflammatory activities at nutritionally relevant concentrations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

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

Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.

Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significancemore » analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.« less

Evolving Concepts of Asthma

PubMed Central

Ray, Anuradha; Wenzel, Sally E.

2015-01-01

Our understanding of asthma has evolved over time from a singular disease to a complex of various phenotypes, with varied natural histories, physiologies, and responses to treatment. Early therapies treated most patients with asthma similarly, with bronchodilators and corticosteroids, but these therapies had varying degrees of success. Similarly, despite initial studies that identified an underlying type 2 inflammation in the airways of patients with asthma, biologic therapies targeted toward these type 2 pathways were unsuccessful in all patients. These observations led to increased interest in phenotyping asthma. Clinical approaches, both biased and later unbiased/statistical approaches to large asthma patient cohorts, identified a variety of patient characteristics, but they also consistently identified the importance of age of onset of disease and the presence of eosinophils in determining clinically relevant phenotypes. These paralleled molecular approaches to phenotyping that developed an understanding that not all patients share a type 2 inflammatory pattern. Using biomarkers to select patients with type 2 inflammation, repeated trials of biologics directed toward type 2 cytokine pathways saw newfound success, confirming the importance of phenotyping in asthma. Further research is needed to clarify additional clinical and molecular phenotypes, validate predictive biomarkers, and identify new areas for possible interventions. PMID:26161792

Genome-wide association study identifies 74 loci associated with educational attainment

PubMed Central

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

Genome-wide association study identifies 74 loci associated with educational attainment.

PubMed

Okbay, Aysu; Beauchamp, Jonathan P; Fontana, Mark Alan; Lee, James J; Pers, Tune H; Rietveld, Cornelius A; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S Fleur W; Oskarsson, Sven; Pickrell, Joseph K; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H; Pina Concas, Maria; Derringer, Jaime; Furlotte, Nicholas A; Galesloot, Tessel E; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M; Harris, Sarah E; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E; Kaasik, Kadri; Kalafati, Ioanna P; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J; deLeeuw, Christiaan; Lind, Penelope A; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B; van der Most, Peter J; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E; Shi, Jianxin; Smith, Albert V; Poot, Raymond A; St Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A; Campbell, Harry; Cappuccio, Francesco P; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans, David M; Faul, Jessica D; Feitosa, Mary F; Forstner, Andreas J; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V; Harris, Tamara B; Heath, Andrew C; Hocking, Lynne J; Holliday, Elizabeth G; Homuth, Georg; Horan, Michael A; Hottenga, Jouke-Jan; de Jager, Philip L; Joshi, Peter K; Jugessur, Astanand; Kaakinen, Marika A; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A L M; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J; Lebreton, Maël P; Levinson, Douglas F; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C M; Loukola, Anu; Madden, Pamela A; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E; Marques-Vidal, Pedro; Meddens, Gerardus A; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W; Myhre, Ronny; Nelson, Christopher P; Nyholt, Dale R; Ollier, William E R; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L; Petrovic, Katja E; Porteous, David J; Räikkönen, Katri; Ring, Susan M; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J; Smith, Blair H; Smith, Jennifer A; Staessen, Jan A; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J A; Venturini, Cristina; Vinkhuyzen, Anna A E; Völker, Uwe; Völzke, Henry; Vonk, Judith M; Vozzi, Diego; Waage, Johannes; Ware, Erin B; Willemsen, Gonneke; Attia, John R; Bennett, David A; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I; Borecki, Ingrid B; Bültmann, Ute; Chabris, Christopher F; Cucca, Francesco; Cusi, Daniele; Deary, Ian J; Dedoussis, George V; van Duijn, Cornelia M; Eriksson, Johan G; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J F; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L R; Lehtimäki, Terho; Lehrer, Steven F; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W J H; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A; Samani, Nilesh J; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I A; Spector, Tim D; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tiemeier, Henning; Tung, Joyce Y; Uitterlinden, André G; Vitart, Veronique; Vollenweider, Peter; Weir, David R; Wilson, James F; Wright, Alan F; Conley, Dalton C; Krueger, Robert F; Davey Smith, George; Hofman, Albert; Laibson, David I; Medland, Sarah E; Meyer, Michelle N; Yang, Jian; Johannesson, Magnus; Visscher, Peter M; Esko, Tõnu; Koellinger, Philipp D; Cesarini, David; Benjamin, Daniel J

2016-05-26

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Genomic pathway analysis reveals that EZH2 and HDAC4 represent mutually exclusive epigenetic pathways across human cancers

PubMed Central

2013-01-01

Background Alterations in epigenetic marks, including methylation or acetylation, are common in human cancers. For many epigenetic pathways, however, direct measures of activity are unknown, making their role in various cancers difficult to assess. Gene expression signatures facilitate the examination of patterns of epigenetic pathway activation across and within human cancer types allowing better understanding of the relationships between these pathways. Methods We used Bayesian regression to generate gene expression signatures from normal epithelial cells before and after epigenetic pathway activation. Signatures were applied to datasets from TCGA, GEO, CaArray, ArrayExpress, and the cancer cell line encyclopedia. For TCGA data, signature results were correlated with copy number variation and DNA methylation changes. GSEA was used to identify biologic pathways related to the signatures. Results We developed and validated signatures reflecting downstream effects of enhancer of zeste homolog 2(EZH2), histone deacetylase(HDAC) 1, HDAC4, sirtuin 1(SIRT1), and DNA methyltransferase 2(DNMT2). By applying these signatures to data from cancer cell lines and tumors in large public repositories, we identify those cancers that have the highest and lowest activation of each of these pathways. Highest EZH2 activation is seen in neuroblastoma, hepatocellular carcinoma, small cell lung cancer, and melanoma, while highest HDAC activity is seen in pharyngeal cancer, kidney cancer, and pancreatic cancer. Across all datasets studied, activation of both EZH2 and HDAC4 is significantly underrepresented. Using breast cancer and glioblastoma as examples to examine intrinsic subtypes of particular cancers, EZH2 activation was highest in luminal breast cancers and proneural glioblastomas, while HDAC4 activation was highest in basal breast cancer and mesenchymal glioblastoma. EZH2 and HDAC4 activation are associated with particular chromosome abnormalities: EZH2 activation with aberrations in genes from the TGF and phosphatidylinositol pathways and HDAC4 activation with aberrations in inflammatory and chemokine related genes. Conclusion Gene expression patterns can reveal the activation level of epigenetic pathways. Epigenetic pathways define biologically relevant subsets of human cancers. EZH2 activation and HDAC4 activation correlate with growth factor signaling and inflammation, respectively, and represent two distinct states for cancer cells. This understanding may allow us to identify targetable drivers in these cancer subsets. PMID:24079712

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.

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.

Tox21 Enricher: Web-based Chemical/Biological Functional Annotation Analysis Tool Based on Tox21 Toxicity Screening Platform.

PubMed

Hur, Junguk; Danes, Larson; Hsieh, Jui-Hua; McGregor, Brett; Krout, Dakota; Auerbach, Scott

2018-05-01

The US Toxicology Testing in the 21st Century (Tox21) program was established to develop more efficient and human-relevant toxicity assessment methods. The Tox21 program screens >10,000 chemicals using quantitative high-throughput screening (qHTS) of assays that measure effects on toxicity pathways. To date, more than 70 assays have yielded >12 million concentration-response curves. The patterns of activity across assays can be used to define similarity between chemicals. Assuming chemicals with similar activity profiles have similar toxicological properties, we may infer toxicological properties based on its neighbourhood. One approach to inference is chemical/biological annotation enrichment analysis. Here, we present Tox21 Enricher, a web-based chemical annotation enrichment tool for the Tox21 toxicity screening platform. Tox21 Enricher identifies over-represented chemical/biological annotations among lists of chemicals (neighbourhoods), facilitating the identification of the toxicological properties and mechanisms in the chemical set. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

A semantic web ontology for small molecules and their biological targets.

PubMed

Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

2010-05-24

A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

A Practical Look at the Chemistry and Biology of Hydrogen Sulfide

PubMed Central

2012-01-01

Abstract Significance: Hydrogen sulfide (H2S) is garnering increasing interest as a biologically relevant signaling molecule. The effects of H2S have now been observed in virtually every organ system and numerous physiological processes. Recent Advances: These studies have not only opened a new field of “gasotransmitter” biology, they have also led to the development of synthetic H2S “donating” compounds with the potential to be parlayed into a variety of therapeutic applications. Critical Issues: Often lost in the exuberance of this new field is a critical examination or understanding of practical aspects of H2S chemistry and biology. This is especially notable in the areas of handling and measuring H2S, evaluating biosynthetic and metabolic pathways, and separating physiological from pharmacological responses. Future Directions: This brief review describes some of the pitfalls in H2S chemistry and biology that can lead or have already led to misleading or erroneous conclusions. The intent is to allow individuals entering or already in this burgeoning field to critically analyze the literature and to assist them in the design of future experiments. Antioxid. Redox Signal. 17, 32–44. PMID:22074253

Brain processing of biologically relevant odors in the awake rat, as revealed by manganese-enhanced MRI.

PubMed

Lehallier, Benoist; Rampin, Olivier; Saint-Albin, Audrey; Jérôme, Nathalie; Ouali, Christian; Maurin, Yves; Bonny, Jean-Marie

2012-01-01

So far, an overall view of olfactory structures activated by natural biologically relevant odors in the awake rat is not available. Manganese-enhanced MRI (MEMRI) is appropriate for this purpose. While MEMRI has been used for anatomical labeling of olfactory pathways, functional imaging analyses have not yet been performed beyond the olfactory bulb. Here, we have used MEMRI for functional imaging of rat central olfactory structures and for comparing activation maps obtained with odors conveying different biological messages. Odors of male fox feces and of chocolate flavored cereals were used to stimulate conscious rats previously treated by intranasal instillation of manganese (Mn). MEMRI activation maps showed Mn enhancement all along the primary olfactory cortex. Mn enhancement elicited by male fox feces odor and to a lesser extent that elicited by chocolate odor, differed from that elicited by deodorized air. This result was partly confirmed by c-Fos immunohistochemistry in the piriform cortex. By providing an overall image of brain structures activated in awake rats by odorous stimulation, and by showing that Mn enhancement is differently sensitive to different stimulating odors, the present results demonstrate the interest of MEMRI for functional studies of olfaction in the primary olfactory cortex of laboratory small animals, under conditions close to natural perception. Finally, the factors that may cause the variability of the MEMRI signal in response to different odor are discussed.

PolySearch2: a significantly improved text-mining system for discovering associations between human diseases, genes, drugs, metabolites, toxins and more.

PubMed

Liu, Yifeng; Liang, Yongjie; Wishart, David

2015-07-01

PolySearch2 (http://polysearch.ca) is an online text-mining system for identifying relationships between biomedical entities such as human diseases, genes, SNPs, proteins, drugs, metabolites, toxins, metabolic pathways, organs, tissues, subcellular organelles, positive health effects, negative health effects, drug actions, Gene Ontology terms, MeSH terms, ICD-10 medical codes, biological taxonomies and chemical taxonomies. PolySearch2 supports a generalized 'Given X, find all associated Ys' query, where X and Y can be selected from the aforementioned biomedical entities. An example query might be: 'Find all diseases associated with Bisphenol A'. To find its answers, PolySearch2 searches for associations against comprehensive collections of free-text collections, including local versions of MEDLINE abstracts, PubMed Central full-text articles, Wikipedia full-text articles and US Patent application abstracts. PolySearch2 also searches 14 widely used, text-rich biological databases such as UniProt, DrugBank and Human Metabolome Database to improve its accuracy and coverage. PolySearch2 maintains an extensive thesaurus of biological terms and exploits the latest search engine technology to rapidly retrieve relevant articles and databases records. PolySearch2 also generates, ranks and annotates associative candidates and present results with relevancy statistics and highlighted key sentences to facilitate user interpretation. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

PolySearch2: a significantly improved text-mining system for discovering associations between human diseases, genes, drugs, metabolites, toxins and more

PubMed Central

Liu, Yifeng; Liang, Yongjie; Wishart, David

2015-01-01

PolySearch2 (http://polysearch.ca) is an online text-mining system for identifying relationships between biomedical entities such as human diseases, genes, SNPs, proteins, drugs, metabolites, toxins, metabolic pathways, organs, tissues, subcellular organelles, positive health effects, negative health effects, drug actions, Gene Ontology terms, MeSH terms, ICD-10 medical codes, biological taxonomies and chemical taxonomies. PolySearch2 supports a generalized ‘Given X, find all associated Ys’ query, where X and Y can be selected from the aforementioned biomedical entities. An example query might be: ‘Find all diseases associated with Bisphenol A’. To find its answers, PolySearch2 searches for associations against comprehensive collections of free-text collections, including local versions of MEDLINE abstracts, PubMed Central full-text articles, Wikipedia full-text articles and US Patent application abstracts. PolySearch2 also searches 14 widely used, text-rich biological databases such as UniProt, DrugBank and Human Metabolome Database to improve its accuracy and coverage. PolySearch2 maintains an extensive thesaurus of biological terms and exploits the latest search engine technology to rapidly retrieve relevant articles and databases records. PolySearch2 also generates, ranks and annotates associative candidates and present results with relevancy statistics and highlighted key sentences to facilitate user interpretation. PMID:25925572

Gamma irradiation of isocitric and citric acid in aqueous solution: Relevance in prebiotic chemistry

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

Negrón-Mendoza, A., E-mail: negron@nucleares.unam.mx; Ramos-Bernal, S.

The radiation chemistry of hydroxy acids like citric and isocitric acids is rather scarce, even though they are crucial compounds in biological systems and for food irradiation. The aim of this work is to study the radiolytic behavior of these acids focused on the interconversion induced by radiation of citric and isocitric acid into other members of the Krebs cycle. The results showed that among the products formed were succinic, malonic, malic and other acids related to metabolic pathways, and these results are correlated with its possible role in chemical evolution processes.

Simulation for Authentic Learning in Informal Education

PubMed Central

Dupuis, Jason; Ludwig-Palit, DeDee

2016-01-01

In 2011, the Museum of Science and Industry in Chicago, Illinois embarked on the creation of a program that allows middle and high school students to explore community health issues using human patient simulation. MedLab was created to engage students in an authentic exploration of medical science, biology, and human anatomy, with a particular focus on how these fields apply to learners’ lives. The program content is made relevant through an emphasis on personal health, community health, and medical science career pathways. This article explores the development, implementation, use of technology, and outcomes of MedLab. PMID:27980372

Simulation for Authentic Learning in Informal Education.

PubMed

Dupuis, Jason; Ludwig-Palit, DeDee

2016-01-01

In 2011, the Museum of Science and Industry in Chicago, Illinois embarked on the creation of a program that allows middle and high school students to explore community health issues using human patient simulation. MedLab was created to engage students in an authentic exploration of medical science, biology, and human anatomy, with a particular focus on how these fields apply to learners' lives. The program content is made relevant through an emphasis on personal health, community health, and medical science career pathways. This article explores the development, implementation, use of technology, and outcomes of MedLab.

MicroRNA-mediated regulation of glutathione and methionine metabolism and its relevance for liver disease.

PubMed

Lu, Shelly C; Mato, José M; Espinosa-Diez, Cristina; Lamas, Santiago

2016-11-01

The discovery of the microRNA (miRNA) family of small RNAs as fundamental regulators of post-transcriptional gene expression has fostered research on their importance in every area of biology and clinical medicine. In the particular area of liver metabolism and disease, miRNAs are gaining increasing importance. By focusing on two fundamental hepatic biosynthetic pathways, glutathione and methionine, we review recent advances on the comprehension of the role of miRNAs in liver pathophysiology and more specifically of models of hepatic cholestasis/fibrosis and hepatocellular carcinoma. Copyright © 2016 Elsevier Inc. All rights reserved.

MicroRNA-mediated regulation of glutathione and methionine metabolism and its relevance for liver disease

PubMed Central

Lu, Shelly C.; Mato, José M.; Espinosa-Diez, Cristina; Lamas, Santiago

2017-01-01

The discovery of the microRNA (miRNA) family of small RNAs as fundamental regulators of post-transcriptional gene expression has fostered research on their importance in every area of biology and clinical medicine. In the particular area of liver metabolism and disease, miRNAs are gaining increasing importance. By focusing on two fundamental hepatic biosynthetic pathways, glutathione and methionine, we review recent advances on the comprehension of the role of miRNAs in liver pathophysiology and more specifically of models of hepatic cholestasis/fibrosis and hepatocellular carcinoma. PMID:27033954

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.

Molecular and genetic bases of pancreatic cancer.

PubMed

Vaccaro, Vanja; Gelibter, Alain; Bria, Emilio; Iapicca, Pierluigi; Cappello, Paola; Di Modugno, Francesca; Pino, Maria Simona; Nuzzo, Carmen; Cognetti, Francesco; Novelli, Francesco; Nistico, Paola; Milella, Michele

2012-06-01

Pancreatic cancer remains a formidable challenge for oncologists and patients alike. Despite intensive efforts, attempts at improving survival in the past 15 years, particularly in advanced disease, have failed. This is true even with the introduction of molecularly targeted agents, chosen on the basis of their action on pathways that were supposedly important in pancreatic cancer development and progression: indeed, with the notable exception of the epidermal growth factor receptor (EGFR) inhibitor erlotinib, that has provided a minimal survival improvement when added to gemcitabine, other agents targeting EGFR, matrix metallo-proteases, farnesyl transferase, or vascular endothelial growth factor have not succeeded in improving outcomes over standard gemcitabine monotherapy for a variety of different reasons. However, recent developments in the molecular epidemiology of pancreatic cancer and an ever evolving understanding of the molecular mechanisms underlying pancreatic cancer initiation and progression raise renewed hope to find novel, relevant therapeutic targets that could be pursued in the clinical setting. In this review we focus on molecular epidemiology of pancreatic cancer, epithelial-to-mesenchymal transition and its influence on sensitivity to EGFR-targeted approaches, apoptotic pathways, hypoxia-related pathways, developmental pathways (such as the hedgehog and Notch pathways), and proteomic analysis as keys to a better understanding of pancreatic cancer biology and, most importantly, as a source of novel molecular targets to be exploited therapeutically.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

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

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Aqueous pathways dominate permeation of solutes across Pisum sativum seed coats and mediate solute transport via diffusion and bulk flow of water.

PubMed

Niemann, Sylvia; Burghardt, Markus; Popp, Christian; Riederer, Markus

2013-05-01

The permeability of seed coats to solutes either of biological or anthropogenic origin plays a major role in germination, seedling growth and seed treatment by pesticides. An experimental set-up was designed for investigating the mechanisms of seed coat permeation, which allows steady-state experiments with isolated seed coats of Pisum sativum. Permeances were measured for a set of organic model compounds with different physicochemical properties and sizes. The results show that narrow aqueous pathways dominate the diffusion of solutes across pea seed coats, as indicated by a correlation of permeances with the molecular sizes of the compounds instead of their lipophilicity. Further indicators for an aqueous pathway are small size selectivity and a small effect of temperature on permeation. The application of an osmotic water potential gradient across isolated seed coats leads to an increase in solute transfer, indicating that the aqueous pathways form a water-filled continuum across the seed coat allowing the bulk flow of water. Thus, the uptake of organic solutes across pea testae has two components: (1) by diffusion and (2) by bulk water inflow, which, however, is relevant only during imbibition. © 2012 Blackwell Publishing Ltd.

Skp1 Independent Function of Cdc53/Cul1 in F-box Protein Homeostasis.

PubMed

Mathur, Radhika; Yen, James L; Kaiser, Peter

2015-12-01

Abundance of substrate receptor subunits of Cullin-RING ubiquitin ligases (CRLs) is tightly controlled to maintain the full repertoire of CRLs. Unbalanced levels can lead to sequestration of CRL core components by a few overabundant substrate receptors. Numerous diseases, including cancer, have been associated with misregulation of substrate receptor components, particularly for the largest class of CRLs, the SCF ligases. One relevant mechanism that controls abundance of their substrate receptors, the F-box proteins, is autocatalytic ubiquitylation by intact SCF complex followed by proteasome-mediated degradation. Here we describe an additional pathway for regulation of F-box proteins on the example of yeast Met30. This ubiquitylation and degradation pathway acts on Met30 that is dissociated from Skp1. Unexpectedly, this pathway required the cullin component Cdc53/Cul1 but was independent of the other central SCF component Skp1. We demonstrated that this non-canonical degradation pathway is critical for chromosome stability and effective defense against heavy metal stress. More importantly, our results assign important biological functions to a sub-complex of cullin-RING ligases that comprises Cdc53/Rbx1/Cdc34, but is independent of Skp1.

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 ...

Treating children with inflammatory bowel disease: Current and new perspectives

PubMed Central

Guariso, Graziella; Gasparetto, Marco

2017-01-01

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gut characterised by alternating periods of remission and relapse. Whilst the mechanism underlying this disease is yet to be fully understood, old and newer generation treatments can only target selected pathways of this complex inflammatory process. This narrative review aims to provide an update on the most recent advances in treatment of paediatric IBD. A MEDLINE search was conducted using “paediatric inflammatory bowel disease”, “paediatric Crohn’s disease”, “paediatric ulcerative colitis”, “treatment”, “therapy”, “immunosuppressant”, “biologic”, “monitoring” and “biomarkers” as key words. Clinical trials, systematic reviews, and meta-analyses published between 2014 and 2016 were selected. Studies referring to earlier periods were also considered in case the data was relevant to our scope. Major advances have been achieved in monitoring the individual metabolism, toxicity and response to relevant medications in IBD including thiopurines and biologics. New biologics acting on novel mechanisms such as selective interference with lymphocyte trafficking are emerging treatment options. Current research is investing in the development of reliable prognostic biomarkers, aiming to move towards personalised treatments targeted to individual patients. PMID:28852307

Higher order visual input to the mushroom bodies in the bee, Bombus impatiens.

PubMed

Paulk, Angelique C; Gronenberg, Wulfila

2008-11-01

To produce appropriate behaviors based on biologically relevant associations, sensory pathways conveying different modalities are integrated by higher-order central brain structures, such as insect mushroom bodies. To address this function of sensory integration, we characterized the structure and response of optic lobe (OL) neurons projecting to the calyces of the mushroom bodies in bees. Bees are well known for their visual learning and memory capabilities and their brains possess major direct visual input from the optic lobes to the mushroom bodies. To functionally characterize these visual inputs to the mushroom bodies, we recorded intracellularly from neurons in bumblebees (Apidae: Bombus impatiens) and a single neuron in a honeybee (Apidae: Apis mellifera) while presenting color and motion stimuli. All of the mushroom body input neurons were color sensitive while a subset was motion sensitive. Additionally, most of the mushroom body input neurons would respond to the first, but not to subsequent, presentations of repeated stimuli. In general, the medulla or lobula neurons projecting to the calyx signaled specific chromatic, temporal, and motion features of the visual world to the mushroom bodies, which included sensory information required for the biologically relevant associations bees form during foraging tasks.

Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways.

PubMed

Chen, Lei; Zhang, Yu-Hang; Wang, ShaoPeng; Zhang, YunHua; Huang, Tao; Cai, Yu-Dong

2017-01-01

Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

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

PubMed

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

2018-01-01

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

It takes two-coincidence coding within the dual olfactory pathway of the honeybee.

PubMed

Brill, Martin F; Meyer, Anneke; Rössler, Wolfgang

2015-01-01

To rapidly process biologically relevant stimuli, sensory systems have developed a broad variety of coding mechanisms like parallel processing and coincidence detection. Parallel processing (e.g., in the visual system), increases both computational capacity and processing speed by simultaneously coding different aspects of the same stimulus. Coincidence detection is an efficient way to integrate information from different sources. Coincidence has been shown to promote associative learning and memory or stimulus feature detection (e.g., in auditory delay lines). Within the dual olfactory pathway of the honeybee both of these mechanisms might be implemented by uniglomerular projection neurons (PNs) that transfer information from the primary olfactory centers, the antennal lobe (AL), to a multimodal integration center, the mushroom body (MB). PNs from anatomically distinct tracts respond to the same stimulus space, but have different physiological properties, characteristics that are prerequisites for parallel processing of different stimulus aspects. However, the PN pathways also display mirror-imaged like anatomical trajectories that resemble neuronal coincidence detectors as known from auditory delay lines. To investigate temporal processing of olfactory information, we recorded PN odor responses simultaneously from both tracts and measured coincident activity of PNs within and between tracts. Our results show that coincidence levels are different within each of the two tracts. Coincidence also occurs between tracts, but to a minor extent compared to coincidence within tracts. Taken together our findings support the relevance of spike timing in coding of olfactory information (temporal code).

Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci

PubMed Central

Zhao, Yuqi; Chen, Jing; Freudenberg, Johannes M.; Meng, Qingying; Rajpal, Deepak K.; Yang, Xia

2017-01-01

Objective Recent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations. Approach and Results We devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks. Conclusions Our data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD. PMID:26966275

Interleukins and their signaling pathways in the Reactome biological pathway database.

PubMed

Jupe, Steve; Ray, Keith; Roca, Corina Duenas; Varusai, Thawfeek; Shamovsky, Veronica; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-04-01

There is a wealth of biological pathway information available in the scientific literature, but it is spread across many thousands of publications. Alongside publications that contain definitive experimental discoveries are many others that have been dismissed as spurious, found to be irreproducible, or are contradicted by later results and consequently now considered controversial. Many descriptions and images of pathways are incomplete stylized representations that assume the reader is an expert and familiar with the established details of the process, which are consequently not fully explained. Pathway representations in publications frequently do not represent a complete, detailed, and unambiguous description of the molecules involved; their precise posttranslational state; or a full account of the molecular events they undergo while participating in a process. Although this might be sufficient to be interpreted by an expert reader, the lack of detail makes such pathways less useful and difficult to understand for anyone unfamiliar with the area and of limited use as the basis for computational models. Reactome was established as a freely accessible knowledge base of human biological pathways. It is manually populated with interconnected molecular events that fully detail the molecular participants linked to published experimental data and background material by using a formal and open data structure that facilitates computational reuse. These data are accessible on a Web site in the form of pathway diagrams that have descriptive summaries and annotations and as downloadable data sets in several formats that can be reused with other computational tools. The entire database and all supporting software can be downloaded and reused under a Creative Commons license. Pathways are authored by expert biologists who work with Reactome curators and editorial staff to represent the consensus in the field. Pathways are represented as interactive diagrams that include as much molecular detail as possible and are linked to literature citations that contain supporting experimental details. All newly created events undergo a peer-review process before they are added to the database and made available on the associated Web site. New content is added quarterly. The 63rd release of Reactome in December 2017 contains 10,996 human proteins participating in 11,426 events in 2,179 pathways. In addition, analytic tools allow data set submission for the identification and visualization of pathway enrichment and representation of expression profiles as an overlay on Reactome pathways. Protein-protein and compound-protein interactions from several sources, including custom user data sets, can be added to extend pathways. Pathway diagrams and analytic result displays can be downloaded as editable images, human-readable reports, and files in several standard formats that are suitable for computational reuse. Reactome content is available programmatically through a REpresentational State Transfer (REST)-based content service and as a Neo4J graph database. Signaling pathways for IL-1 to IL-38 are hierarchically classified within the pathway "signaling by interleukins." The classification used is largely derived from Akdis et al. The addition to Reactome of a complete set of the known human interleukins, their receptors, and established signaling pathways linked to annotations of relevant aspects of immune function provides a significant computationally accessible resource of information about this important family. This information can be extended easily as new discoveries become accepted as the consensus in the field. A key aim for the future is to increase coverage of gene expression changes induced by interleukin signaling. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Autophagy as a Therapeutic Target in Cardiovascular Disease

PubMed Central

Nemchenko, Andriy; Chiong, Mario; Turer, Aslan; Lavandero, Sergio; Hill, Joseph A.

2011-01-01

The epidemic of heart failure continues apace, and development of novel therapies with clinical efficacy has lagged. Now, important insights into the molecular circuitry of cardiovascular autophagy have raised the prospect that this cellular pathway of protein quality control may be a target of clinical relevance. Whereas basal levels of autophagy are required for cell survival, excessive levels – or perhaps distinct forms of autophagic flux – contribute to disease pathogenesis. Our challenge will be to distinguish mechanisms that drive adaptive versus maladaptive autophagy and to manipulate those pathways for therapeutic gain. Recent evidence suggests this may be possible. Here, we review the fundamental biology of autophagy and its role in a variety of forms of cardiovascular disease. We discuss ways in which this evolutionarily conserved catabolic mechanism can be manipulated, discuss studies presently underway in heart disease, and provide our perspective on where this exciting field may lead in the future. PMID:21723289

Barriers to the use of genetic information for the development of new epilepsy treatments.

PubMed

Ferraro, Thomas N

2016-01-01

Genetic analysis is providing new information on the biological basis of epilepsy at a rapid pace; this article identifies factors acting as major barriers to use of these data for therapy development. Disease heterogeneity is a primary obstacle since so many genes can cause or predispose to epilepsy and the clinical presentation of epilepsy is so diverse, thus making it difficult to define the most therapeutically relevant targets. Further, many epilepsy genes affect brain development, an observation that represents a barrier unto itself given the challenge of reversing or preventing genetically mediated alterations of brain pathway formation. Finally, the lack of appropriate models for testing new therapies is also recognized as a fundamental limitation. Overcoming these barriers will be aided by full characterization of the genetic landscape of epilepsy, elucidation of key pathway points for therapeutic intervention and creation of unique experimental models to validate results.

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...

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

Use of comparative genomics approaches to characterize interspecies differences in response to environmental chemicals: Challenges, opportunities, and research needs

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

Burgess-Herbert, Sarah L., E-mail: sarah.burgess@alum.mit.edu; Euling, Susan Y.

A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionarymore » biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended.« less

A critical analysis of the biological impacts of plasticizers on wildlife

PubMed Central

Oehlmann, Jörg; Schulte-Oehlmann, Ulrike; Kloas, Werner; Jagnytsch, Oana; Lutz, Ilka; Kusk, Kresten O.; Wollenberger, Leah; Santos, Eduarda M.; Paull, Gregory C.; Van Look, Katrien J. W.; Tyler, Charles R.

2009-01-01

This review provides a critical analysis of the biological effects of the most widely used plasticizers, including dibutyl phthalate, diethylhexyl phthalate, dimethyl phthalate, butyl benzyl phthalate and bisphenol A (BPA), on wildlife, with a focus on annelids (both aquatic and terrestrial), molluscs, crustaceans, insects, fish and amphibians. Moreover, the paper provides novel data on the biological effects of some of these plasticizers in invertebrates, fish and amphibians. Phthalates and BPA have been shown to affect reproduction in all studied animal groups, to impair development in crustaceans and amphibians and to induce genetic aberrations. Molluscs, crustaceans and amphibians appear to be especially sensitive to these compounds, and biological effects are observed at environmentally relevant exposures in the low ng l−1 to µg l−1 range. In contrast, most effects in fish (except for disturbance in spermatogenesis) occur at higher concentrations. Most plasticizers appear to act by interfering with the functioning of various hormone systems, but some phthalates have wider pathways of disruption. Effect concentrations of plasticizers in laboratory experiments coincide with measured environmental concentrations, and thus there is a very real potential for effects of these chemicals on some wildlife populations. The most striking gaps in our current knowledge on the impacts of plasticizers on wildlife are the lack of data for long-term exposures to environmentally relevant concentrations and their ecotoxicity when part of complex mixtures. Furthermore, the hazard of plasticizers has been investigated in annelids, molluscs and arthropods only, and given the sensitivity of some invertebrates, effects assessments are warranted in other invertebrate phyla. PMID:19528055

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

Genetic engineering and sustainable production of ornamentals: current status and future directions.

PubMed

Lütken, Henrik; Clarke, Jihong Liu; Müller, Renate

2012-07-01

Through the last decades, environmentally and health-friendly production methods and conscientious use of resources have become crucial for reaching the goal of a more sustainable plant production. Protection of the environment requires careful consumption of limited resources and reduction of chemicals applied during production of ornamental plants. Numerous chemicals used in modern plant production have negative impacts on human health and are hazardous to the environment. In Europe, several compounds have lost their approval and further legal restrictions can be expected. This review presents the more recent progress of genetic engineering in ornamental breeding, delivers an overview of the biological background of the used technologies and critically evaluates the usefulness of the strategies to obtain improved ornamental plants. First, genetic engineering is addressed as alternative to growth retardants, comprising recombinant DNA approaches targeting relevant hormone pathways, e.g. the gibberellic acid (GA) pathway. A reduced content of active GAs causes compact growth and can be facilitated by either decreased anabolism, increased catabolism or altered perception. Moreover, compactness can be accomplished by using a natural transformation approach without recombinant DNA technology. Secondly, metabolic engineering approaches targeting elements of the ethylene signal transduction pathway are summarized as a possible alternative to avoid the use of chemical ethylene inhibitors. In conclusion, molecular breeding approaches are dealt with in a way allowing a critical biological assessment and enabling the scientific community and public to put genetic engineering of ornamental plants into a perspective regarding their usefulness in plant breeding.

Application of Sparse Linear Discriminant Analysis and Elastic Net for Diagnosis of IgA Nephropathy: Statistical and Biological Viewpoints

PubMed

Mohammadi Majd, Tahereh; Kalantari, Shiva; Raeisi Shahraki, Hadi; Nafar, Mohsen; Almasi, Afshin; Samavat, Shiva; Parvin, Mahmoud; Hashemian, Amirhossein

2018-03-10

IgA nephropathy (IgAN) is the most common primary glomerulonephritis diagnosed based on renal biopsy. Mesangial IgA deposits along with the proliferation of mesangial cells are the histologic hallmark of IgAN. Non-invasive diagnostic tools may help to prompt diagnosis and therapy. The discovery of potential and reliable urinary biomarkers for diagnosis of IgAN depends on applying robust and suitable models. Applying two multivariate modeling methods on a urine proteomic dataset obtained from IgAN patients, and comparison of the results of these methods were the purpose of this study. Two models were constructed for urinary protein profiles of 13 patients and 8 healthy individuals, based on sparse linear discriminant analysis (SLDA) and elastic net regression methods. A panel of selected biomarkers with the best coefficients were proposed and further analyzed for biological relevance using functional annotation and pathway analysis. Transferrin, α1-antitrypsin, and albumin fragments were the most important up-regulated biomarkers, while fibulin-5, YIP1 family member 3, prasoposin, and osteopontin were the most important down-regulated biomarkers. Pathway analysis revealed that complement and coagulation cascades and extracellular matrix-receptor interaction pathways impaired in the pathogenesis of IgAN. SLDA and elastic net had an equal importance for diagnosis of IgAN and were useful methods for exploring and processing proteomic data. In addition, the suggested biomarkers are reliable candidates for further validation to non-invasive diagnose of IgAN based on urine examination.

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

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.

Identification of hub subnetwork based on topological features of genes in breast cancer

PubMed Central

ZHUANG, DA-YONG; JIANG, LI; HE, QING-QING; ZHOU, PENG; YUE, TAO

2015-01-01

The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer. PMID:25573623

Differential Effect of Active Smoking on Gene Expression in Male and Female Smokers

PubMed Central

Paul, Sunirmal; Amundson, Sally A

2015-01-01

Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has remained unknown. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different sex-specific responses to the stress of smoking. Using whole genome microarray gene expression profiling, we found that a substantial number of oxidant related genes were expressed in both male and female smokers, however, smoking-responsive genes did indeed differ greatly between male and female smokers. Gene set enrichment analysis (GSEA) against reference oncogenic signature gene sets identified a large number of oncogenic pathway gene-sets that were significantly altered in female smokers compared to male smokers. In addition, functional annotation with Ingenuity Pathway Analysis (IPA) identified smoking-correlated genes associated with biological functions in male and female smokers that are directly relevant to well-known smoking related pathologies. However, these relevant biological functions were strikingly overrepresented in female smokers compared to male smokers. IPA network analysis with the functional categories of immune and inflammatory response gene products suggested potential interactions between smoking response and female hormones. Our results demonstrate a striking dichotomy between male and female gene expression responses to smoking. This is the first genome-wide expression study to compare the sex-specific impacts of smoking at a molecular level and suggests a novel potential connection between sex hormone signaling and smoking-induced diseases in female smokers. PMID:25621181

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures.

PubMed

Grafström, Roland C; Nymark, Penny; Hongisto, Vesa; Spjuth, Ola; Ceder, Rebecca; Willighagen, Egon; Hardy, Barry; Kaski, Samuel; Kohonen, Pekka

2015-11-01

This paper outlines the work for which Roland Grafström and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafström laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety. 2015 FRAME.

Conserved steroid hormone homology converges on NFκB to modulate inflammation in asthma

PubMed Central

Payne, Asha S.; Freishtat, Robert J.

2012-01-01

Asthma is a complex, multifactorial disease comprising multiple different subtypes, rather than a single disease entity [1], yet has a consistent clinical phenotype: recurring episodes of chest tightness, wheezing, and difficulty breathing. Despite the complex pathogenesis of asthma, steroid hormones (e.g. glucocorticoids) are ubiquitous in the acute and chronic management of all types of asthma. Overall, steroid hormones are a class of widely-relevant, biologically-active compounds originating from cholesterol and altered in a stepwise fashion, but maintain a basic 17-carbon, 4-ring structure. Steroids are lipophilic molecules that diffuse readily through cell membranes to directly and/or indirectly affect gene transcription. In addition, they employ rapid, non-genomic actions to affect cellular products. Steroid hormones are comprised of several groups (including glucocorticoids, sex steroid hormones, and secosteroids) with critical divergent biological and physiological functions relevant to health and disease. However, the conserved homology of steroid hormone molecules, receptors, and signaling pathways suggest that each of these is part of dynamic system of hormone interaction, likely involving overlap of downstream signaling mechanisms. Therefore, we will review the similarities and differences of these three groups of steroid hormones (i.e. glucocorticoids, sex steroid hormones, and secosteroids), identifying NFκB as a common inflammatory mediator. Despite our understanding of the impact of individual steroids (e.g. glucocorticoids, sex steroids and secosteroids) on asthma, research has yet to explain the interplay of the dynamic system in which these hormones function. To do so, there needs to be better understanding of the interplay of classical, non-classical, and non-genomic steroid hormone function. However, clues from the conserved homology steroid hormone structure and function and signaling pathways, offer insight into a possible model of steroid hormone regulation of inflammation in asthma through common NFκB-mediated downstream events. PMID:22183120

Functional Relevance of Protein Glycosylation to the Pro-Inflammatory Effects of Extracellular Matrix Metalloproteinase Inducer (EMMPRIN) on Monocytes/Macrophages

PubMed Central

Ge, Heng; Yuan, Wei; Liu, Jidong; He, Qing; Ding, Song; Pu, Jun; He, Ben

2015-01-01

Background and Objective Extracellular matrix metalloproteinase inducer (EMMPRIN) is an important pro-inflammatory protein involved in the cellular functions of monocytes/macrophages. We have hypothesized that high-level heterogeneousness of protein glycosylation of EMMPRIN may have functional relevance to its biological effects and affect the inflammatory activity of monocytes/macrophages. Methods The glycosylation patterns of EMMPRIN expressed by monocytes/macrophages (THP-1 cells) in response to different extracellular stimuli were observed, and the structures of different glycosylation forms were identified. After the purification of highly- and less-glycosylated proteins respectively, the impacts of different glycosylation forms on the pro-inflammatory effects of EMMPRIN were examined in various aspects, such as cell adhesion to endothelial cells, cell migrations, cytokine expression, and activation of inflammatory signalling pathway. Results 1) It was mainly the highly-glycosylated form of EMMPRIN (HG-EMMPRIN) that increased after being exposed to inflammatory signals (PMA and H2O2). 2) Glycosylation of EMMPRIN in monocytes/macrophages led to N-linked-glycans being added to the protein, with the HG form containing complex-type glycans and the less-glycosylated form (LG) the simple type. 3) Only the HG-EMMPRIN but not the LG-EMMPRIN exhibited pro-inflammatory effects and stimulated inflammatory activities of the monocytes/macrophages (i.e., activation of ERK1/2 and NF-κB pathway, enhanced monocyte-endothelium adhesion, cell migration and matrix metalloproteinase -9 expression). Conclusions Post-transcriptional glycosylation represents an important mechanism that determines the biological effects of EMMPRIN in monocytes/macrophages. Glycosylation of EMMPRIN may serve as a potential target for regulating the inflammatory activities of monocytes/macrophages. PMID:25658763

Commentary on "The Cerebellar System and What it Signifies from a Biological Perspective: A Communication by Christofredo Jakob (1866-1956) Before the Society of Neurology and Psychiatry of Buenos Aires, December 1938".

PubMed

Tzouma, Anny; Margulies, Daniel S; Triarhou, Lazaros C

2016-08-01

This commentary highlights a "cerebellar classic" by a pioneer of neurobiology, Christfried Jakob. Jakob discussed the connectivity between the cerebellum and mesencephalic, diencephalic, and telencephalic structures in an evolutionary, developmental, and histophysiological perspective. He proposed three evolutionary morphofunctional stages, the archicerebellar, paleocerebellar, and neocerebellar; he attributed the reduced cerebellospinal connections in humans, compared to other primates, to the perfection of the rubrolenticular and thalamocortical systems and the intense ascending pathways to the red nucleus in exchange for the more elementary descending efferent pathways. Jakob hypothesized the convergence of cerebellar pathways in associative cortical regions, insisting on the intimate collaboration of the cerebellum with the frontal lobe. The extensive lines of communication between regions throughout the association cortex substantiate Jakob's intuition and begin to outline the mechanisms for substantial cerebellar involvement in functions beyond the purely motor domain. Atop a foundation of anatomical and phylogenetic mastery, Jakob conceived ideas that were noteworthy, timely, and have much relevance to our current thinking on cerebellar structure and function.

Why We Should Create Artificial Offspring: Meaning and the Collective Afterlife.

PubMed

Danaher, John

2017-07-03

This article argues that the creation of artificial offspring could make our lives more meaningful (i.e. satisfy more meaning-relevant conditions of value). By 'artificial offspring' I mean beings that we construct, with a mix of human and non-human-like qualities. Robotic artificial intelligences are paradigmatic examples of the form. There are two reasons for thinking that the creation of such beings could make our lives more meaningful and valuable. The first is that the existence of a collective afterlife-i.e. a set of human-like lives that continue after we die-is likely to be an important source and sustainer of meaning in our present lives (Scheffler in Death and the afterlife, OUP, Oxford, 2013). The second is that the creation of artificial offspring provides a plausible and potentially better pathway to a collective afterlife than the traditional biological pathway (i.e. there are reasons to favour this pathway and there are no good defeaters to trying it out). Both of these arguments are defended from a variety of objections and misunderstandings.

What amyloidoses may tell us about normal protein folding: The Alzheimer's disease story

NASA Astrophysics Data System (ADS)

Teplow, David B.

2002-03-01

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder characterized by severe neuronal injury and death. A prominent histopathologic feature of AD is disseminated parenchymal and vascular amyloid deposition. The fibrils in these deposits are composed of the amyloid β-protein (Aβ), a peptide of 4 kDa mass. In vitro and in vivo studies of Aβ fibril formation have shown that both oligomeric and polymeric Aβ assemblies have neurotoxic activity. Understanding how these assemblies form thus could be of direct therapeutic relevance. However, the aggregation and fibril-forming propensities of Aβ have complicated structure determination. Nevertheless, careful morphologic, spectroscopic, protein chemical, and physiologic analyses of the time-dependent changes in Aβ conformation, assembly state, and biological activity which occur during fibrillogenesis have significantly advanced our understanding of this clinically important process. Here, I will discuss recent findings about the pathway(s) of Aβ folding and assembly and about key structural features of Aβ which control the associated kinetics. Interestingly, the amyloidogenic folding pathway of Aβ is in some respects the mirror image of that through which natively folded amyloidogenic proteins proceed.

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.

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...

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

PubMed

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-11-07

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

PubMed Central

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-01-01

Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444

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

High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes

PubMed Central

Hidalgo, Marta R.; Cubuk, Cankut; Amadoz, Alicia; Salavert, Francisco; Carbonell-Caballero, José; Dopazo, Joaquin

2017-01-01

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions. PMID:28042959

Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses.

PubMed

Painter, Jodie N; O'Mara, Tracy A; Morris, Andrew P; Cheng, Timothy H T; Gorman, Maggie; Martin, Lynn; Hodson, Shirley; Jones, Angela; Martin, Nicholas G; Gordon, Scott; Henders, Anjali K; Attia, John; McEvoy, Mark; Holliday, Elizabeth G; Scott, Rodney J; Webb, Penelope M; Fasching, Peter A; Beckmann, Matthias W; Ekici, Arif B; Hein, Alexander; Rübner, Matthias; Hall, Per; Czene, Kamila; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Lambrechts, Diether; Amant, Frederic; Annibali, Daniela; Depreeuw, Jeroen; Vanderstichele, Adriaan; Goode, Ellen L; Cunningham, Julie M; Dowdy, Sean C; Winham, Stacey J; Trovik, Jone; Hoivik, Erling; Werner, Henrica M J; Krakstad, Camilla; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Tham, Emma; Mints, Miriam; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Pharoah, Paul D P; Dunning, Alison M; Dennis, Joe; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Zondervan, Krina T; Nyholt, Dale R; MacGregor, Stuart; Montgomery, Grant W; Tomlinson, Ian; Easton, Douglas F; Thompson, Deborah J; Spurdle, Amanda B

2018-05-01

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (r g  = 0.23, P = 9.3 × 10 -3 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10 -3 ) and concordance in effect direction (P = 2.0 × 10 -3 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10 -5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10 -8 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Structure-guided discovery of the metabolite carboxy-SAM that modulates tRNA function.

PubMed

Kim, Jungwook; Xiao, Hui; Bonanno, Jeffrey B; Kalyanaraman, Chakrapani; Brown, Shoshana; Tang, Xiangying; Al-Obaidi, Nawar F; Patskovsky, Yury; Babbitt, Patricia C; Jacobson, Matthew P; Lee, Young-Sam; Almo, Steven C

2013-06-06

The identification of novel metabolites and the characterization of their biological functions are major challenges in biology. X-ray crystallography can reveal unanticipated ligands that persist through purification and crystallization. These adventitious protein-ligand complexes provide insights into new activities, pathways and regulatory mechanisms. We describe a new metabolite, carboxy-S-adenosyl-l-methionine (Cx-SAM), its biosynthetic pathway and its role in transfer RNA modification. The structure of CmoA, a member of the SAM-dependent methyltransferase superfamily, revealed a ligand consistent with Cx-SAM in the catalytic site. Mechanistic analyses showed an unprecedented role for prephenate as the carboxyl donor and the involvement of a unique ylide intermediate as the carboxyl acceptor in the CmoA-mediated conversion of SAM to Cx-SAM. A second member of the SAM-dependent methyltransferase superfamily, CmoB, recognizes Cx-SAM and acts as a carboxymethyltransferase to convert 5-hydroxyuridine into 5-oxyacetyl uridine at the wobble position of multiple tRNAs in Gram-negative bacteria, resulting in expanded codon-recognition properties. CmoA and CmoB represent the first documented synthase and transferase for Cx-SAM. These findings reveal new functional diversity in the SAM-dependent methyltransferase superfamily and expand the metabolic and biological contributions of SAM-based biochemistry. These discoveries highlight the value of structural genomics approaches in identifying ligands within the context of their physiologically relevant macromolecular binding partners, and in revealing their functions.

De novo characterization of the pine aphid Cinara pinitabulaeformis Zhang et Zhang transcriptome and analysis of genes relevant to pesticides

PubMed Central

Rebeca, Carballar-Lejarazú; Zhu, Xiaoli; Guo, Yajie; Lin, Qiannan; Hu, Xia; Wang, Rong; Liang, Guanghong; Guan, Xiong

2017-01-01

The pine aphid Cinara pinitabulaeformis Zhang et Zhang is the main pine pest in China, it causes pine needles to produce dense dew (honeydew) which can lead to sooty mold (black filamentous saprophytic ascomycetes). Although common chemical and physical strategies are used to prevent the disease caused by C. pinitabulaeformis Zhang et Zhang, new strategies based on biological and/or genetic approaches are promising to control and eradicate the disease. However, there is no information about genomics, proteomics or transcriptomics to allow the design of new control strategies for this pine aphid. We used next generation sequencing technology to sequence the transcriptome of C. pinitabulaeformis Zhang et Zhang and built a transcriptome database. We identified 80,259 unigenes assigned for Gene Ontology (GO) terms and information for a total of 11,609 classified unigenes was obtained in the Clusters of Orthologous Groups (COGs). A total of 10,806 annotated unigenes were analyzed to identify the represented biological pathways, among them 8,845 unigenes matched with 228 KEGG pathways. In addition, our data describe propagative viruses, nutrition-related genes, detoxification related molecules, olfactory related receptors, stressed-related protein, putative insecticide resistance genes and possible insecticide targets. Moreover, this study provides valuable information about putative insecticide resistance related genes and for the design of new genetic/biological based strategies to manage and control C. pinitabulaeformis Zhang et Zhang populations. PMID:28570707

Physicochemical and biological characterization of single-walled and double-walled carbon nanotubes in biological media.

PubMed

Liu, Wen-Te; Bien, Mauo-Ying; Chuang, Kai-Jen; Chang, Ta-Yuan; Jones, Tim; BéruBé, Kelly; Lalev, Georgi; Tsai, Dai-Hua; Chuang, Hsiao-Chi; Cheng, Tsun-Jen

2014-09-15

To study the toxicity of nanoparticles under relevant conditions, it is important to reproducibly disperse nanoparticles in biological media in in vitro and in vivo studies. Here, single-walled nanotubes (SWNTs) and double-walled nanotubes (DWNTs) were physicochemically and biologically characterized when dispersed in phosphate-buffered saline (PBS) and bovine serum albumin (BSA). BSA-SWNT/DWNT interaction resulted in a reduction of aggregation and an increase in particle stabilization. Based on the protein sequence coverage and protein binding results, DWNTs exhibited higher protein binding than SWNTs. SWNT and DWNT suspensions in the presence of BSA increased interleukin-6 (IL-6) levels and reduced tumor necrosis factor-alpha (TNF-α) levels in A549 cells as compared to corresponding samples in the absence of BSA. We next determined the effects of SWNTs and DWNTs on pulmonary protein modification using bronchoalveolar lavage fluid (BALF) as a surrogate collected form BALB/c mice. The BALF proteins bound to SWNTs (13 proteins) and DWNTs (11 proteins), suggesting that these proteins were associated with blood coagulation pathways. Lastly, we demonstrated the importance of physicochemical and biological alterations of SWNTs and DWNTs when dispersed in biological media, since protein binding may result in the misinterpretation of in vitro results and the activation of protein-regulated biological responses. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

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

PubMed

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

2015-11-01

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

Comparison of the perceived relevance of oral biology reported by students and interns of a Pakistani dental college.

PubMed

Farooq, I; Ali, S

2014-11-01

The purpose of this study was to analyse and compare the perceived relevance of oral biology with dentistry as reported by dental students and interns and to investigate the most popular teaching approach and learning resource. A questionnaire aiming to ask about the relevance of oral biology to dentistry, most popular teaching method and learning resource was utilised in this study. Study groups encompassed second-year dental students who had completed their course and dental interns. The data were obtained and analysed statistically. The overall response rate for both groups was 60%. Both groups reported high relevance of oral biology to dentistry. Perception of dental interns regarding the relevance of oral biology to dentistry was higher than that of students. Both groups identified student presentations as the most important teaching method. Amongst the most important learning resources, textbooks were considered most imperative by interns, whereas lecture handouts received the highest importance score by students. Dental students and interns considered oral biology to be relevant to dentistry, although greater relevance was reported by interns. Year-wise advancement in dental education and training improves the perception of the students about the relevance of oral biology to dentistry. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Student perception of relevance of biology content to everyday life: A study in higher education biology courses

NASA Astrophysics Data System (ADS)

Himschoot, Agnes Rose

The purpose of this mixed method case study was to examine the effects of methods of instruction on students' perception of relevance in higher education non-biology majors' courses. Nearly ninety percent of all students in a liberal arts college are required to take a general biology course. It is proposed that for many of those students, this is the last science course they will take for life. General biology courses are suspected of discouraging student interest in biology with large enrollment, didactic instruction, covering a huge amount of content in one semester, and are charged with promoting student disengagement with biology by the end of the course. Previous research has been aimed at increasing student motivation and interest in biology as measured by surveys and test results. Various methods of instruction have been tested and show evidence of improved learning gains. This study focused on students' perception of relevance of biology content to everyday life and the methods of instruction that increase it. A quantitative survey was administered to assess perception of relevance pre and post instruction over three topics typically taught in a general biology course. A second quantitative survey of student experiences during instruction was administered to identify methods of instruction used in the course lecture and lab. While perception of relevance dropped in the study, qualitative focus groups provided insight into the surprising results by identifying topics that are more relevant than the ones chosen for the study, conveying the affects of the instructor's personal and instructional skills on student engagement, explanation of how active engagement during instruction promotes understanding of relevance, the roll of laboratory in promoting students' understanding of relevance as well as identifying external factors that affect student engagement. The study also investigated the extent to which gender affected changes in students' perception of relevance. The results of this study will inform instructors' pedagogical and logistical choices in the design and implementation of higher education biology courses for non-biology majors. Recommendations for future research will include refining the study to train instructors in methods of instruction that promote student engagement as well as to identify biology topics that are more relevant to students enrolled in non-major biology courses.

Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

PubMed Central

Vitali, Francesca; Marini, Simone; Balli, Martina; Grosemans, Hanne; Sampaolesi, Maurilio; Lussier, Yves A.; Cusella De Angelis, Maria Gabriella; Bellazzi, Riccardo

2017-01-01

The molecular mechanisms underlying tissue regeneration and wound healing are still poorly understood despite their importance. In this paper we develop a bioinformatics approach, combining biology and network theory to drive experiments for better understanding the genetic underpinnings of wound healing mechanisms and for selecting potential drug targets. We start by selecting literature-relevant genes in murine wound healing, and inferring from them a Protein-Protein Interaction (PPI) network. Then, we analyze the network to rank wound healing-related genes according to their topological properties. Lastly, we perform a procedure for in-silico simulation of a treatment action in a biological pathway. The findings obtained by applying the developed pipeline, including gene expression analysis, confirms how a network-based bioinformatics method is able to prioritize candidate genes for in vitro analysis, thus speeding up the understanding of molecular mechanisms and supporting the discovery of potential drug targets. PMID:28635674

Boron nitride nanotubes as vehicles for intracellular delivery of fluorescent drugs and probes.

PubMed

Niskanen, Jukka; Zhang, Issan; Xue, Yanming; Golberg, Dmitri; Maysinger, Dusica; Winnik, Françoise M

2016-01-01

To evaluate the response of cells to boron nitride nanotubes (BNNTs) carrying fluorescent probes or drugs in their inner channel by assessment of the cellular localization of the fluorescent cargo, evaluation of the in vitro release and biological activity of a drug (curcumin) loaded in BNNTs. Cells treated with curcumin-loaded BNNTs and stimulated with lipopolysaccharide were assessed for nitric oxide release and stimulation of IL-6 and TNF-α. The cellular trafficking of two cell-permeant dyes and a non-cell-permeant dye loaded within BNNTs was imaged. BNNTs loaded with up to 13 wt% fluorophores were internalized by cells and controlled release of curcumin triggered cellular pathways associated with the known anti-inflammatory effects of the drug. The overall findings indicate that BNNTs can function as nanocarriers of biologically relevant probes/drugs allowing one to examine/control their local intracellular localization and biochemical effects, leading the way to applications as intracellular nanosensors.

Exams disadvantage women in introductory biology

PubMed Central

Cotner, Sehoya

2017-01-01

The gender gap in STEM fields has prompted a great deal of discussion, but what factors underlie performance deficits remain poorly understood. We show that female students underperformed on exams compared to their male counterparts across ten large introductory biology course sections in fall 2016 (N > 1500 students). Females also reported higher levels of test anxiety and course-relevant science interest. Results from mediation analyses revealed an intriguing pattern: for female students only, and regardless of their academic standing, test anxiety negatively impacted exam performance, while interest in the course-specific science topics increased exam performance. Thus, instructors seeking equitable classrooms can aim to decrease test anxiety and increase student interest in science course content. We provide strategies for mitigating test anxiety and suggestions for alignment of course content with student interest, with the hope of successfully reimagining the STEM pathway as one that is equally accessible to all. PMID:29049334

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...

Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine

PubMed Central

Chen, Xiao-Wu; Di, Yuan Ming; Zhang, Jian; Zhou, Zhi-Wei; Li, Chun Guang; Zhou, Shu-Feng

2012-01-01

Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis), which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer's disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach. PMID:23213296

RNA-seq Analysis Reveals Unique Transcriptome Signatures in Systemic Lupus Erythematosus Patients with Distinct Autoantibody Specificities

PubMed Central

Rai, Richa; Chauhan, Sudhir Kumar; Singh, Vikas Vikram; Rai, Madhukar; Rai, Geeta

2016-01-01

Systemic lupus erythematosus (SLE) patients exhibit immense heterogeneity which is challenging from the diagnostic perspective. Emerging high throughput sequencing technologies have been proved to be a useful platform to understand the complex and dynamic disease processes. SLE patients categorised based on autoantibody specificities are reported to have differential immuno-regulatory mechanisms. Therefore, we performed RNA-seq analysis to identify transcriptomics of SLE patients with distinguished autoantibody specificities. The SLE patients were segregated into three subsets based on the type of autoantibodies present in their sera (anti-dsDNA+ group with anti-dsDNA autoantibody alone; anti-ENA+ group having autoantibodies against extractable nuclear antigens (ENA) only, and anti-dsDNA+ENA+ group having autoantibodies to both dsDNA and ENA). Global transcriptome profiling for each SLE patients subsets was performed using Illumina® Hiseq-2000 platform. The biological relevance of dysregulated transcripts in each SLE subsets was assessed by ingenuity pathway analysis (IPA) software. We observed that dysregulation in the transcriptome expression pattern was clearly distinct in each SLE patients subsets. IPA analysis of transcripts uniquely expressed in different SLE groups revealed specific biological pathways to be affected in each SLE subsets. Multiple cytokine signaling pathways were specifically dysregulated in anti-dsDNA+ patients whereas Interferon signaling was predominantly dysregulated in anti-ENA+ patients. In anti-dsDNA+ENA+ patients regulation of actin based motility by Rho pathway was significantly affected. The granulocyte gene signature was a common feature to all SLE subsets; however, anti-dsDNA+ group showed relatively predominant expression of these genes. Dysregulation of Plasma cell related transcripts were higher in anti-dsDNA+ and anti-ENA+ patients as compared to anti-dsDNA+ ENA+. Association of specific canonical pathways with the uniquely expressed transcripts in each SLE subgroup indicates that specific immunological disease mechanisms are operative in distinct SLE patients’ subsets. This ‘sub-grouping’ approach could further be useful for clinical evaluation of SLE patients and devising targeted therapeutics. PMID:27835693

Comparison of transcripts in Phalaenopsis bellina and Phalaenopsis equestris (Orchidaceae) flowers to deduce monoterpene biosynthesis pathway.

PubMed

Hsiao, Yu-Yun; Tsai, Wen-Chieh; Kuoh, Chang-Sheng; Huang, Tian-Hsiang; Wang, Hei-Chia; Wu, Tian-Shung; Leu, Yann-Lii; Chen, Wen-Huei; Chen, Hong-Hwa

2006-07-13

Floral scent is one of the important strategies for ensuring fertilization and for determining seed or fruit set. Research on plant scents has hampered mainly by the invisibility of this character, its dynamic nature, and complex mixtures of components that are present in very small quantities. Most progress in scent research, as in other areas of plant biology, has come from the use of molecular and biochemical techniques. Although volatile components have been identified in several orchid species, the biosynthetic pathways of orchid flower fragrance are far from understood. We investigated how flower fragrance was generated in certain Phalaenopsis orchids by determining the chemical components of the floral scent, identifying floral expressed-sequence-tags (ESTs), and deducing the pathways of floral scent biosynthesis in Phalaneopsis bellina by bioinformatics analysis. The main chemical components in the P. bellina flower were shown by gas chromatography-mass spectrometry to be monoterpenoids, benzenoids and phenylpropanoids. The set of floral scent producing enzymes in the biosynthetic pathway from glyceraldehyde-3-phosphate (G3P) to geraniol and linalool were recognized through data mining of the P. bellina floral EST database (dbEST). Transcripts preferentially expressed in P. bellina were distinguished by comparing the scent floral dbEST to that of a scentless species, P. equestris, and included those encoding lipoxygenase, epimerase, diacylglycerol kinase and geranyl diphosphate synthase. In addition, EST filtering results showed that transcripts encoding signal transduction and Myb transcription factors and methyltransferase, in addition to those for scent biosynthesis, were detected by in silico hybridization of the P. bellina unigene database against those of the scentless species, rice and Arabidopsis. Altogether, we pinpointed 66% of the biosynthetic steps from G3P to geraniol, linalool and their derivatives. This systems biology program combined chemical analysis, genomics and bioinformatics to elucidate the scent biosynthesis pathway and identify the relevant genes. It integrates the forward and reverse genetic approaches to knowledge discovery by which researchers can study non-model plants.

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.

Proteolytic systems and AMP-activated protein kinase are critical targets of acute myeloid leukemia therapeutic approaches

PubMed Central

Pereira, Olga; Sampaio-Marques, Belém; Paiva, Artur; Correia-Neves, Margarida; Castro, Isabel; Ludovico, Paula

2015-01-01

The therapeutic strategies against acute myeloid leukemia (AML) have hardly been modified over four decades. Although resulting in a favorable outcome in young patients, older individuals, the most affected population, do not respond adequately to therapy. Intriguingly, the mechanisms responsible for AML cells chemoresistance/susceptibility are still elusive. Mounting evidence has shed light on the relevance of proteolytic systems (autophagy and ubiquitin-proteasome system, UPS), as well as the AMPK pathway, in AML biology and treatment, but their exact role is still controversial. Herein, two AML cell lines (HL-60 and KG-1) were exposed to conventional chemotherapeutic agents (cytarabine and/or doxorubicin) to assess the relevance of autophagy and UPS on AML cells’ response to antileukemia drugs. Our results clearly showed that the antileukemia agents target both proteolytic systems and the AMPK pathway. Doxorubicin enhanced UPS activity while drugs’ combination blocked autophagy specifically on HL-60 cells. In contrast, KG-1 cells responded in a more subtle manner to the drugs tested consistent with the higher UPS activity of these cells. In addition, the data demonstrates that autophagy may play a protective role depending on AML subtype. Specific modulators of autophagy and UPS are, therefore, promising targets for combining with standard therapeutic interventions in some AML subtypes. PMID:25537507

Identification of the fitness determinants of budding yeast on a natural substrate

PubMed Central

Filteau, Marie; Charron, Guillaume; Landry, Christian R

2017-01-01

The budding yeasts are prime models in genomics and cell biology, but the ecological factors that determine their success in non-human-associated habitats is poorly understood. In North America Saccharomyces yeasts are present on the bark of deciduous trees, where they feed on bark and sap exudates. In the North East, Saccharomyces paradoxus is found on maples, which makes maple sap a natural substrate for this species. We measured growth rates of S. paradoxus natural isolates on maple sap and found variation along a geographical gradient not explained by the inherent variation observed under optimal laboratory conditions. We used a functional genomic screen to reveal the ecologically relevant genes and conditions required for optimal growth in this substrate. We found that the allantoin degradation pathway is required for optimal growth in maple sap, in particular genes necessary for allantoate utilization, which we demonstrate is the major nitrogen source available to yeast in this environment. Growth with allantoin or allantoate as the sole nitrogen source recapitulated the variation in growth rates in maple sap among strains. We also show that two lineages of S. paradoxus display different life-history traits on allantoin and allantoate media, highlighting the ecological relevance of this pathway. PMID:27935595

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.

MicroRNA profiling reveals dysregulated microRNAs and their target gene regulatory networks in cemento-ossifying fibroma.

PubMed

Pereira, Thaís Dos Santos Fontes; Brito, João Artur Ricieri; Guimarães, André Luiz Sena; Gomes, Carolina Cavaliéri; de Lacerda, Júlio Cesar Tanos; de Castro, Wagner Henriques; Coimbra, Roney Santos; Diniz, Marina Gonçalves; Gomez, Ricardo Santiago

2018-01-01

Cemento-ossifying fibroma (COF) is a benign fibro-osseous neoplasm of uncertain pathogenesis, and its treatment results in morbidity. MicroRNAs (miRNA) are small non-coding RNAs that regulate gene expression and may represent therapeutic targets. The purpose of the study was to generate a comprehensive miRNA profile of COF compared to normal bone. Additionally, the most relevant pathways and target genes of differentially expressed miRNA were investigated by in silico analysis. Nine COF and ten normal bone samples were included in the study. miRNA profiling was carried out by using TaqMan® OpenArray® Human microRNA panel containing 754 validated human miRNAs. We identified the most relevant miRNAs target genes through the leader gene approach, using STRING and Cytoscape software. Pathways enrichment analysis was performed using DIANA-miRPath. Eleven miRNAs were downregulated (hsa-miR-95-3p, hsa-miR-141-3p, hsa-miR-205-5p, hsa-miR-223-3p, hsa-miR-31-5p, hsa-miR-944, hsa-miR-200b-3p, hsa-miR-135b-5p, hsa-miR-31-3p, hsa-miR-223-5p and hsa-miR-200c-3p), and five were upregulated (hsa-miR-181a-5p, hsa-miR-181c-5p, hsa-miR-149-5p, hsa-miR-138-5p and hsa-miR-199a-3p) in COF compared to normal bone. Eighteen common target genes were predicted, and the leader genes approach identified the following genes involved in human COF: EZH2, XIAP, MET and TGFBR1. According to the biology of bone and COF, the most relevant KEGG pathways revealed by enrichment analysis were proteoglycans in cancer, miRNAs in cancer, pathways in cancer, p53-, PI3K-Akt-, FoxO- and TGF-beta signalling pathways, which were previously found to be differentially regulated in bone neoplasms, odontogenic tumours and osteogenesis. miRNA dysregulation occurs in COF, and EZH2, XIAP, MET and TGFBR1 are potential targets for functional analysis validation. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Computational Model Predicting Disruption of Blood Vessel Development

PubMed Central

Kleinstreuer, Nicole; Dix, David; Rountree, Michael; Baker, Nancy; Sipes, Nisha; Reif, David; Spencer, Richard; Knudsen, Thomas

2013-01-01

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. PMID:23592958

Exploring Genetic, Genomic, and Phenotypic Data at the Rat Genome Database

PubMed Central

Laulederkind, Stanley J. F.; Hayman, G. Thomas; Wang, Shur-Jen; Lowry, Timothy F.; Nigam, Rajni; Petri, Victoria; Smith, Jennifer R.; Dwinell, Melinda R.; Jacob, Howard J.; Shimoyama, Mary

2013-01-01

The laboratory rat, Rattus norvegicus, is an important model of human health and disease, and experimental findings in the rat have relevance to human physiology and disease. The Rat Genome Database (RGD, http://rgd.mcw.edu) is a model organism database that provides access to a wide variety of curated rat data including disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components for genes, quantitative trait loci, and strains. We present an overview of the database followed by specific examples that can be used to gain experience in employing RGD to explore the wealth of functional data available for the rat. PMID:23255149

Cancer heterogeneity: origins and implications for genetic association studies

PubMed Central

Urbach, Davnah; Lupien, Mathieu; Karagas, Margaret R.; Moore, Jason H.

2012-01-01

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant difficult. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goal of identifying targetable disease pathways and successfully treating individual patients. PMID:22858414

Biological, environmental, and social influences on childhood obesity.

PubMed

Campbell, M Karen

2016-01-01

The prevalence of childhood obesity has increased globally over the past three decades, with evidence of recent leveling off in developed countries. Reduction in the, currently high, prevalence of obesity will require a full understanding of the biological and social pathways to obesity in order to develop appropriately targeted prevention strategies in early life. Determinants of childhood obesity include individual level factors, including biological, social, and behavioral risks, acting within the influence of the child's family environment, which is, in turn, imbedded in the context of the community environment. These influences act across childhood, with suggestions of early critical periods of biological and behavioral plasticity. There is evidence of sex and gender differences in the responses of boys and girls to their environments. The evidence that determinants of childhood obesity act at many levels and at different stages of childhood is of policy relevance to those planning early health promotion and primary prevention programs as it suggests the need to address the individual, the family, the physical environment, the social environment, and social policy. The purpose of this narrative review is to summarize current, and emerging, literature in a multilevel, life course framework.

Systematic review of interleukin-12, interleukin-17, and interleukin-23 pathway inhibitors for the treatment of moderate-to-severe chronic plaque psoriasis: ustekinumab, briakinumab, tildrakizumab, guselkumab, secukinumab, ixekizumab, and brodalumab.

PubMed

Tausend, William; Downing, Christopher; Tyring, Stephen

2014-01-01

Monoclonal antibodies known as biologic agents specifically targeted against interleukin-12 (IL-12), interleukin-17A (IL-17), and interleukin-23 (IL-23) have been the focus of research for moderate-to-severe chronic plaque psoriasis in recent years. To discuss the immune-mediated model of psoriasis and to summarize current knowledge of the clinical efficacy and safety of new biologic agents for moderate-to-severe chronic plaque psoriasis. The PubMed database was searched for relevant articles on ustekinumab, briakinumab, tildrakizumab (MK-322), guselkumab, secukinumab, ixekizumab, and brodalumab published between January 2005 and July 2013. Fifty-five articles were identified. These studies suggest that the biologic agents specifically targeting IL-12, IL-17, and IL-23 are efficacious and safe in the treatment of moderate-to-severe psoriasis in adults. Current data from clinical trials suggest that biologic agents targeting IL-12, IL-17, and IL-23 are safe and efficacious drugs for use in moderate-to-severe chronic plaque psoriasis. Long-term data still need to be established.

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...

OCT imaging of craniofacial anatomy in xenopus embryos (Conference Presentation)

NASA Astrophysics Data System (ADS)

Deniz, Engin; Jonas, Stephan M.; Griffin, John; Hooper, Michael C.; Choma, Michael A.; Khokha, Mustafa K.

2016-03-01

The etiology of craniofacial defects is incompletely understood. The ability to obtain large amounts of gene sequence data from families affected by craniofacial defects is opening up new ways to understand molecular genetic etiological factors. One important link between gene sequence data and clinical relevance is biological research into candidate genes and molecular pathways. We present our recent research using OCT as a nondestructive phenotyping modality of craniofacial morphology in Xenopus embryos, an important animal model for biological research in gene and pathway discovery. We define 2D and 3D scanning protocols for a standardized approach to craniofacial imaging in Xenopus embryos. We define standard views and planar reconstructions for visualizing normal anatomy and landmarks. We compare these views and reconstructions to traditional histopathology using alcian blue staining. In addition to being 3D, nondestructive, and having much faster throughout, OCT can identify craniofacial features that are lost during traditional histopathological preparation. We also identify quantitative morphometric parameters to define normative craniofacial anatomy. We also note that craniofacial and cardiac defects are not infrequently present in the same patient (e.g velocardiofacial syndrome). Given that OCT excels at certain aspects of cardiac imaging in Xenopus embryos, our work highlights the potential of using OCT and Xenopus to study molecular genetic factors that impact both cardiac and craniofacial development.

Insights into the structural biology of G-protein coupled receptors impacts drug design for central nervous system neurodegenerative processes

PubMed Central

Dalet, Farfán-García Eunice; Guadalupe, Trujillo-Ferrara José; María del Carmen, Castillo-Hernández; Humberto, Guerra-Araiza Christian; Antonio, Soriano-Ursúa Marvin

2013-01-01

In the last few years, there have been important new insights into the structural biology of G-protein coupled receptors. It is now known that allosteric binding sites are involved in the affinity and selectivity of ligands for G-protein coupled receptors, and that signaling by these receptors involves both G-protein dependent and independent pathways. The present review outlines the physiological and pharmacological implications of this perspective for the design of new drugs to treat disorders of the central nervous system. Specifically, new possibilities are explored in relation to allosteric and orthosteric binding sites on dopamine receptors for the treatment of Parkinson's disease, and on muscarinic receptors for Alzheimer's disease. Future research can seek to identify ligands that can bind to more than one site on the same receptor, or simultaneously bind to two receptors and form a dimer. For example, the design of bivalent drugs that can reach homo/hetero-dimers of D2 dopamine receptor holds promise as a relevant therapeutic strategy for Parkinson's disease. Regarding the treatment of Alzheimer's disease, the design of dualsteric ligands for mono-oligomeric rinic receptors could increase therapeutic effectiveness by generating potent compounds that could activate more than one signaling pathway. PMID:25206539

Purines: forgotten mediators in traumatic brain injury.

PubMed

Jackson, Edwin K; Boison, Detlev; Schwarzschild, Michael A; Kochanek, Patrick M

2016-04-01

Recently, the topic of traumatic brain injury has gained attention in both the scientific community and lay press. Similarly, there have been exciting developments on multiple fronts in the area of neurochemistry specifically related to purine biology that are relevant to both neuroprotection and neurodegeneration. At the 2105 meeting of the National Neurotrauma Society, a session sponsored by the International Society for Neurochemistry featured three experts in the field of purine biology who discussed new developments that are germane to both the pathomechanisms of secondary injury and development of therapies for traumatic brain injury. This included presentations by Drs. Edwin Jackson on the novel 2',3'-cAMP pathway in neuroprotection, Detlev Boison on adenosine in post-traumatic seizures and epilepsy, and Michael Schwarzschild on the potential of urate to treat central nervous system injury. This mini review summarizes the important findings in these three areas and outlines future directions for the development of new purine-related therapies for traumatic brain injury and other forms of central nervous system injury. In this review, novel therapies based on three emerging areas of adenosine-related pathobiology in traumatic brain injury (TBI) were proposed, namely, therapies targeting 1) the 2',3'-cyclic adenosine monophosphate (cAMP) pathway, 2) adenosine deficiency after TBI, and 3) augmentation of urate after TBI. © 2016 International Society for Neurochemistry.

Shaping long-term primate development: Telomere length trajectory as an indicator of early maternal maltreatment and predictor of future physiologic regulation.

PubMed

Drury, Stacy S; Howell, Brittany R; Jones, Christopher; Esteves, Kyle; Morin, Elyse; Schlesinger, Reid; Meyer, Jerrold S; Baker, Kate; Sanchez, Mar M

2017-12-01

The molecular, neurobiological, and physical health impacts of child maltreatment are well established, yet mechanistic pathways remain inadequately defined. Telomere length (TL) decline is an emerging molecular indicator of stress exposure with definitive links to negative health outcomes in maltreated individuals. The multiple confounders endemic to human maltreatment research impede the identification of causal pathways. This study leverages a unique randomized, cross-foster, study design in a naturalistic translational nonhuman primate model of infant maltreatment. At birth, newborn macaques were randomly assigned to either a maltreating or a competent control mother, balancing for sex, biological mother parenting history, and social rank. Offspring TL was measured longitudinally across the first 6 months of life (infancy) from peripheral blood. Hair cortisol accumulation was also determined at 6, 12, and 18 months of age. TL decline was greater in animals randomized to maltreatment, but also interacted with biological mother group. Shorter TL at 6 months was associated with higher mean cortisol levels through 18 months (juvenile period) when controlling for relevant covariates. These results suggest that even under the equivalent social, nutritional, and environmental conditions feasible in naturalistic translational nonhuman primate models, early adverse caregiving results in lasting molecular scars that foreshadow elevated health risk and physiologic dysregulation.

A new network representation of the metabolism to detect chemical transformation modules.

PubMed

Sorokina, Maria; Medigue, Claudine; Vallenet, David

2015-11-14

Metabolism is generally modeled by directed networks where nodes represent reactions and/or metabolites. In order to explore metabolic pathway conservation and divergence among organisms, previous studies were based on graph alignment to find similar pathways. Few years ago, the concept of chemical transformation modules, also called reaction modules, was introduced and correspond to sequences of chemical transformations which are conserved in metabolism. We propose here a novel graph representation of the metabolic network where reactions sharing a same chemical transformation type are grouped in Reaction Molecular Signatures (RMS). RMS were automatically computed for all reactions and encode changes in atoms and bonds. A reaction network containing all available metabolic knowledge was then reduced by an aggregation of reaction nodes and edges to obtain a RMS network. Paths in this network were explored and a substantial number of conserved chemical transformation modules was detected. Furthermore, this graph-based formalism allows us to define several path scores reflecting different biological conservation meanings. These scores are significantly higher for paths corresponding to known metabolic pathways and were used conjointly to build association rules that should predict metabolic pathway types like biosynthesis or degradation. This representation of metabolism in a RMS network offers new insights to capture relevant metabolic contexts. Furthermore, along with genomic context methods, it should improve the detection of gene clusters corresponding to new metabolic pathways.

Muscle dysfunction in chronic obstructive pulmonary disease: update on causes and biological findings

PubMed Central

Pascual, Sergi; Casadevall, Carme; Orozco-Levi, Mauricio; Barreiro, Esther

2015-01-01

Respiratory and/or limb muscle dysfunction, which are frequently observed in chronic obstructive pulmonary disease (COPD) patients, contribute to their disease prognosis irrespective of the lung function. Muscle dysfunction is caused by the interaction of local and systemic factors. The key deleterious etiologic factors are pulmonary hyperinflation for the respiratory muscles and deconditioning secondary to reduced physical activity for limb muscles. Nonetheless, cigarette smoke, systemic inflammation, nutritional abnormalities, exercise, exacerbations, anabolic insufficiency, drugs and comorbidities also seem to play a relevant role. All these factors modify the phenotype of the muscles, through the induction of several biological phenomena in patients with COPD. While respiratory muscles improve their aerobic phenotype (percentage of oxidative fibers, capillarization, mitochondrial density, enzyme activity in the aerobic pathways, etc.), limb muscles exhibit the opposite phenotype. In addition, both muscle groups show oxidative stress, signs of damage and epigenetic changes. However, fiber atrophy, increased number of inflammatory cells, altered regenerative capacity; signs of apoptosis and autophagy, and an imbalance between protein synthesis and breakdown are rather characteristic features of the limb muscles, mostly in patients with reduced body weight. Despite that significant progress has been achieved in the last decades, full elucidation of the specific roles of the target biological mechanisms involved in COPD muscle dysfunction is still required. Such an achievement will be crucial to adequately tackle with this relevant clinical problem of COPD patients in the near-future. PMID:26623119

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.

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...

Silk-polypyrrole biocompatible actuator performance under biologically relevant conditions

NASA Astrophysics Data System (ADS)

Hagler, Jo'elen; Peterson, Ben; Murphy, Amanda; Leger, Janelle

Biocompatible actuators that are capable of controlled movement and can function under biologically relevant conditions are of significant interest in biomedical fields. Previously, we have demonstrated that a composite material of silk biopolymer and the conducting polymer polypyrrole (PPy) can be formed into a bilayer device that can bend under applied voltage. Further, these silk-PPy composites can generate forces comparable to human muscle (>0.1 MPa) making them ideal candidates for interfacing with biological tissues. Here silk-PPy composite films are tested for performance under biologically relevant conditions including exposure to a complex protein serum and biologically relevant temperatures. Free-end bending actuation performance, current response, force generation and, mass degradation were investigated . Preliminary results show that when exposed to proteins and biologically relevant temperatures, these silk-PPy composites show minimal degradation and are able to generate forces and conduct currents comparable to devices tested under standard conditions. NSF.

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

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

Signaling Pathways Regulating Redox Balance in Cancer Metabolism

PubMed Central

De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

2018-01-01

The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells’ demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions. PMID:29740540

Signaling Pathways Regulating Redox Balance in Cancer Metabolism.

PubMed

De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

2018-01-01

The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells' demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions.

A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Servos, Jörg; Werner, Alexandra; Koch, Ina; Osiewacz, Heinz D

2013-01-01

Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

Engineering of a modular and synthetic phosphoketolase pathway for photosynthetic production of acetone from CO2 in Synechococcus elongatus PCC 7942 under light and aerobic condition.

PubMed

Chwa, Jun-Won; Kim, Wook Jin; Sim, Sang Jun; Um, Youngsoon; Woo, Han Min

2016-08-01

Capture and conversion of CO2 to valuable chemicals is intended to answer global challenges on environmental issues, climate change and energy security. Engineered cyanobacteria have been enabled to produce industry-relevant chemicals from CO2 . However, the final products from cyanobacteria have often been mixed with fermented metabolites during dark fermentation. In this study, our engineering of Synechococcus elongatus PCC 7942 enabled continuous conversion of CO2 to volatile acetone as sole product. This process occurred during lighted, aerobic culture via both ATP-driven malonyl-CoA synthesis pathway and heterologous phosphoketolase (PHK)-phosphotransacetylase (Pta) pathway. Because of strong correlations between the metabolic pathways of acetate and acetone, supplying the acetyl-CoA directly from CO2 in the engineered strain, led to sole production of acetone (22.48 mg/L ± 1.00) without changing nutritional constraints, and without an anaerobic shift. Our engineered S. elongatus strains, designed for acetone production, could be modified to create biosolar cell factories for sustainable photosynthetic production of acetyl-CoA-derived biochemicals. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Dysregulated cellular functions and cell stress pathways provide critical cues for activating and targeting natural killer cells to transformed and infected cells.

PubMed

Raulet, David H; Marcus, Assaf; Coscoy, Laurent

2017-11-01

Natural killer (NK) cells recognize and kill cancer cells and infected cells by engaging cell surface ligands that are induced preferentially or exclusively on these cells. These ligands are recognized by activating receptors on NK cells, such as NKG2D. In addition to activation by cell surface ligands, the acquisition of optimal effector activity by NK cells is driven in vivo by cytokines and other signals. This review addresses a developing theme in NK cell biology: that NK-activating ligands on cells, and the provision of cytokines and other signals that drive high effector function in NK cells, are driven by abnormalities that arise from transformation or the infected state. The pathways include genomic damage, which causes self DNA to be exposed in the cytosol of affected cells, where it activates the DNA sensor cGAS. The resulting signaling induces NKG2D ligands and also mobilizes NK cell activation. Other key pathways that regulate NKG2D ligands include PI-3 kinase activation, histone acetylation, and the integrated stress response. This review summarizes the roles of these pathways and their relevance in both viral infections and cancer. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Proteasomal Ubiquitin Receptor RPN-10 Controls Sex Determination in Caenorhabditis elegans

PubMed Central

Shimada, Masumi; Kanematsu, Kenji; Tanaka, Keiji; Yokosawa, Hideyoshi

2006-01-01

The ubiquitin-binding RPN-10 protein serves as a ubiquitin receptor that delivers client proteins to the 26S proteasome. Although ubiquitin recognition is an essential step for proteasomal destruction, deletion of the rpn-10 gene in yeast does not influence viability, indicating redundancy of the substrate delivery pathway. However, their specificity and biological relevance in higher eukaryotes is still enigmatic. We report herein that knockdown of the rpn-10 gene, but not any other proteasome subunit genes, sexually transforms hermaphrodites to females by eliminating hermaphrodite spermatogenesis in Caenorhabditis elegans. The feminization phenotype induced by deletion of the rpn-10 gene was rescued by knockdown of tra-2, one of sexual fate decision genes promoting female development, and its downstream target tra-1, indicating that the TRA-2–mediated sex determination pathway is crucial for the Δrpn-10–induced sterile phenotype. Intriguingly, we found that co-knockdown of rpn-10 and functionally related ubiquitin ligase ufd-2 overcomes the germline-musculinizing effect of fem-3(gf). Furthermore, TRA-2 proteins accumulated in rpn-10-defective worms. Our results show that the RPN-10–mediated ubiquitin pathway is indispensable for control of the TRA-2–mediated sex-determining pathway. PMID:17050737

Learning Biological Networks via Bootstrapping with Optimized GO-based Gene Similarity

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

Taylor, Ronald C.; Sanfilippo, Antonio P.; McDermott, Jason E.

2010-08-02

Microarray gene expression data provide a unique information resource for learning biological networks using "reverse engineering" methods. However, there are a variety of cases in which we know which genes are involved in a given pathology of interest, but we do not have enough experimental evidence to support the use of fully-supervised/reverse-engineering learning methods. In this paper, we explore a novel semi-supervised approach in which biological networks are learned from a reference list of genes and a partial set of links for these genes extracted automatically from PubMed abstracts, using a knowledge-driven bootstrapping algorithm. We show how new relevant linksmore » across genes can be iteratively derived using a gene similarity measure based on the Gene Ontology that is optimized on the input network at each iteration. We describe an application of this approach to the TGFB pathway as a case study and show how the ensuing results prove the feasibility of the approach as an alternate or complementary technique to fully supervised methods.« less

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

The therapeutic use of the relaxation response in stress-related diseases.

PubMed

Esch, Tobias; Fricchione, Gregory L; Stefano, George B

2003-02-01

The objective of this work was to investigate a possible (therapeutic) connection between the relaxation response (RR) and stress-related diseases. Further, common underlying molecular mechanisms and autoregulatory pathways were examined. For the question of (patho)physiology and significance of RR techniques in the treatment of stress-related diseases, we analyzed peer-reviewed references only. The RR has been shown to be an appropriate and relevant therapeutic tool to counteract several stress-related disease processes and certain health-restrictions, particularly in certain immunological, cardiovascular, and neurodegenerative diseases/mental disorders. Further, common underlying molecular mechanisms may exist that represent a connection between the stress response, pathophysiological findings in stress-related diseases, and physiological changes/autoregulatory pathways described in the RR. Here, constitutive or low-output nitric oxide (NO) production may be involved in a protective or ameliorating context, whereas inducible, high-output NO release may facilitate detrimental disease processes. In mild or early disease states, a high degree of biological and physiological flexibility may still be possible (dynamic balance). Here, the therapeutic use of RR techniques may be considered particularly relevant, and the observable (beneficial) effects may be exerted via activation of constitutive NO pathways. RR techniques, regularly part of professional stress management or mind/body medical settings, represent an important tool to be added to therapeutic strategies dealing with stress-related diseases. Moreover, as part of 'healthy' life-style modifications, they may serve primary (or secondary) prevention. Further studies are necessary to elucidate the complex physiology underlying the RR and its impact upon stress-related disease states.

In silico database screening of potential targets and pathways of compounds contained in plants used for psoriasis vulgaris.

PubMed

May, Brian H; Deng, Shiqiang; Zhang, Anthony L; Lu, Chuanjian; Xue, Charlie C L

2015-09-01

Reviews and meta-analyses of clinical trials identified plants used as traditional medicines (TMs) that show promise for psoriasis. These include Rehmannia glutinosa, Camptotheca acuminata, Indigo naturalis and Salvia miltiorrhiza. Compounds contained in these TMs have shown activities of relevance to psoriasis in experimental models. To further investigate the likely mechanisms of action of the multiple compounds in these TMs, we undertook a computer-based in silico investigation of the proteins known to be regulated by these compounds and their associated biological pathways. The proteins reportedly regulated by compounds in these four TMs were identified using the HIT (Herbal Ingredients' Targets) database. The resultant data were entered into the PANTHER (Protein ANnotation THrough Evolutionary Relationship) database to identify the pathways in which the proteins could be involved. The study identified 237 compounds in the TMs and these retrieved 287 proteins from HIT. These proteins identified 59 pathways in PANTHER with most proteins being located in the Apoptosis, Angiogenesis, Inflammation mediated by chemokine and cytokine, Gonadotropin releasing hormone receptor, and/or Interleukin signaling pathways. All four TMs contained compounds that had regulating effects on Apoptosis regulator BAX, Apoptosis regulator Bcl-2, Caspase-3, Tumor necrosis factor (TNF) or Prostaglandin G/H synthase 2 (COX2). The main proteins and pathways are primarily related to inflammation, proliferation and angiogenesis which are all processes involved in psoriasis. Experimental studies have reported that certain compounds from these TMs can regulate the expression of proteins involved in each of these pathways.

[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.

Doctoral conceptual thresholds in cellular and molecular biology

NASA Astrophysics Data System (ADS)

Feldon, David F.; Rates, Christopher; Sun, Chongning

2017-12-01

In the biological sciences, very little is known about the mechanisms by which doctoral students acquire the skills they need to become independent scientists. In the postsecondary biology education literature, identification of specific skills and effective methods for helping students to acquire them are limited to undergraduate education. To establish a foundation from which to investigate the developmental trajectory of biologists' research skills, it is necessary to identify those skills which are integral to doctoral study and distinct from skills acquired earlier in students' educational pathways. In this context, the current study engages the framework of threshold concepts to identify candidate skills that are both obstacles and significant opportunities for developing proficiency in conducting research. Such threshold concepts are typically characterised as transformative, integrative, irreversible, and challenging. The results from interviews and focus groups with current and former doctoral students in cellular and molecular biology suggest two such threshold concepts relevant to their subfield: the first is an ability to effectively engage primary research literature from the biological sciences in a way that is critical without dismissing the value of its contributions. The second is the ability to conceptualise appropriate control conditions necessary to design and interpret the results of experiments in an efficient and effective manner for research in the biological sciences as a discipline. Implications for prioritising and sequencing graduate training experiences are discussed on the basis of the identified thresholds.

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

PubMed

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

2017-03-01

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

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.

GeneTopics - interpretation of gene sets via literature-driven topic models

PubMed Central

2013-01-01

Background Annotation of a set of genes is often accomplished through comparison to a library of labelled gene sets such as biological processes or canonical pathways. However, this approach might fail if the employed libraries are not up to date with the latest research, don't capture relevant biological themes or are curated at a different level of granularity than is required to appropriately analyze the input gene set. At the same time, the vast biomedical literature offers an unstructured repository of the latest research findings that can be tapped to provide thematic sub-groupings for any input gene set. Methods Our proposed method relies on a gene-specific text corpus and extracts commonalities between documents in an unsupervised manner using a topic model approach. We automatically determine the number of topics summarizing the corpus and calculate a gene relevancy score for each topic allowing us to eliminate non-specific topics. As a result we obtain a set of literature topics in which each topic is associated with a subset of the input genes providing directly interpretable keywords and corresponding documents for literature research. Results We validate our method based on labelled gene sets from the KEGG metabolic pathway collection and the genetic association database (GAD) and show that the approach is able to detect topics consistent with the labelled annotation. Furthermore, we discuss the results on three different types of experimentally derived gene sets, (1) differentially expressed genes from a cardiac hypertrophy experiment in mice, (2) altered transcript abundance in human pancreatic beta cells, and (3) genes implicated by GWA studies to be associated with metabolite levels in a healthy population. In all three cases, we are able to replicate findings from the original papers in a quick and semi-automated manner. Conclusions Our approach provides a novel way of automatically generating meaningful annotations for gene sets that are directly tied to relevant articles in the literature. Extending a general topic model method, the approach introduced here establishes a workflow for the interpretation of gene sets generated from diverse experimental scenarios that can complement the classical approach of comparison to reference gene sets. PMID:24564875

Biotin Switch Assays for Quantitation of Reversible Cysteine Oxidation.

PubMed

Li, R; Kast, J

2017-01-01

Thiol groups in protein cysteine residues can be subjected to different oxidative modifications by reactive oxygen/nitrogen species. Reversible cysteine oxidation, including S-nitrosylation, S-sulfenylation, S-glutathionylation, and disulfide formation, modulate multiple biological functions, such as enzyme catalysis, antioxidant, and other signaling pathways. However, the biological relevance of reversible cysteine oxidation is typically underestimated, in part due to the low abundance and high reactivity of some of these modifications, and the lack of methods to enrich and quantify them. To facilitate future research efforts, this chapter describes detailed procedures to target the different modifications using mass spectrometry-based biotin switch assays. By switching the modification of interest to a biotin moiety, these assays leverage the high affinity between biotin and avidin to enrich the modification. The use of stable isotope labeling and a range of selective reducing agents facilitate the quantitation of individual as well as total reversible cysteine oxidation. The biotin switch assay has been widely applied to the quantitative analysis of S-nitrosylation in different disease models and is now also emerging as a valuable research tool for other oxidative cysteine modifications, highlighting its relevance as a versatile, robust strategy for carrying out in-depth studies in redox proteomics. © 2017 Elsevier Inc. All rights reserved.

Stress and the psyche-brain-immune network in psychiatric diseases based on psychoneuroendocrineimmunology: a concise review.

PubMed

Bottaccioli, Anna Giulia; Bottaccioli, Francesco; Minelli, Andrea

2018-05-15

In the last decades, psychoneuroendocrineimmunology research has made relevant contributions to the fields of neuroscience, psychobiology, epigenetics, molecular biology, and clinical research by studying the effect of stress on human health and highlighting the close interrelations between psyche, brain, and bodily systems. It is now well recognized that chronic stress can alter the physiological cross-talk between brain and biological systems, leading to long-lasting maladaptive effects (allostatic overload) on the nervous, immune, endocrine, and metabolic systems, which compromises stress resiliency and health. Stressful conditions in early life have been associated with profound alterations in cortical and subcortical brain regions involved in emotion regulation and the salience network, showing relevant overlap with different psychiatric conditions. This paper provides a summary of the available literature concerning the notable effects of stress on the brain and immune system. We highlight the role of epigenetics as a mechanistic pathway mediating the influences of the social and physical environment on brain structure and connectivity, the immune system, and psycho-physical health in psychiatric diseases. We also summarize the evidence regarding the effects of stress management techniques (mainly psychotherapy and meditation practice) on clinical outcomes, brain neurocircuitry, and immune-inflammatory network in major psychiatric diseases. © 2018 New York Academy of Sciences.

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information.

PubMed

Safo, Sandra E; Li, Shuzhao; Long, Qi

2018-03-01

Integrative analysis of high dimensional omics data is becoming increasingly popular. At the same time, incorporating known functional relationships among variables in analysis of omics data has been shown to help elucidate underlying mechanisms for complex diseases. In this article, our goal is to assess association between transcriptomic and metabolomic data from a Predictive Health Institute (PHI) study that includes healthy adults at a high risk of developing cardiovascular diseases. Adopting a strategy that is both data-driven and knowledge-based, we develop statistical methods for sparse canonical correlation analysis (CCA) with incorporation of known biological information. Our proposed methods use prior network structural information among genes and among metabolites to guide selection of relevant genes and metabolites in sparse CCA, providing insight on the molecular underpinning of cardiovascular disease. Our simulations demonstrate that the structured sparse CCA methods outperform several existing sparse CCA methods in selecting relevant genes and metabolites when structural information is informative and are robust to mis-specified structural information. Our analysis of the PHI study reveals that a number of gene and metabolic pathways including some known to be associated with cardiovascular diseases are enriched in the set of genes and metabolites selected by our proposed approach. © 2017, The International Biometric Society.

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.

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

Nicotinamide Inhibits Vasculogenic Mimicry, an Alternative Vascularization Pathway Observed in Highly Aggressive Melanoma

PubMed Central

Shalmon, Bruria; Kubi, Adva; Treves, Avraham J.; Shapira-Frommer, Ronnie; Avivi, Camilla; Ortenberg, Rona; Ben-Ami, Eytan; Schachter, Jacob; Besser, Michal J.; Markel, Gal

2013-01-01

Vasculogenic mimicry (VM) describes functional vascular channels composed only of tumor cells and its presence predicts poor prognosis in melanoma patients. Inhibition of this alternative vascularization pathway might be of clinical importance, especially as several anti-angiogenic therapies targeting endothelial cells are largely ineffective in melanoma. We show the presence of VM structures histologically in a series of human melanoma lesions and demonstrate that cell cultures derived from these lesions form tubes in 3D cultures ex vivo. We tested the ability of nicotinamide, the amide form of vitamin B3 (niacin), which acts as an epigenetic gene regulator through unique cellular pathways, to modify VM. Nicotinamide effectively inhibited the formation of VM structures and destroyed already formed ones, in a dose-dependent manner. Remarkably, VM formation capacity remained suppressed even one month after the complete withdrawal of Nicotimamid. The inhibitory effect of nicotinamide on VM formation could be at least partially explained by a nicotinamide-driven downregulation of vascular endothelial cadherin (VE-Cadherin), which is known to have a central role in VM. Further major changes in the expression profile of hundreds of genes, most of them clustered in biologically-relevant clusters, were observed. In addition, nicotinamide significantly inhibited melanoma cell proliferation, but had an opposite effect on their invasion capacity. Cell cycle analysis indicated moderate changes in apoptotic indices. Therefore, nicotinamide could be further used to unravel new biological mechanisms that drive VM and tumor progression. Targeting VM, especially in combination with anti-angiogenic strategies, is expected to be synergistic and might yield substantial anti neoplastic effects in a variety of malignancies. PMID:23451174

SIGNALING PATHWAYS IN MELANOSOME BIOGENESIS AND PATHOLOGY

PubMed Central

Schiaffino, Maria Vittoria

2010-01-01

Melanosomes are the specialized intracellular organelles of pigment cells devoted to the synthesis, storage and transport of melanin pigments, which are responsible for most visible pigmentation in mammals and other vertebrates. As a direct consequence, any genetic mutation resulting in alteration of melanosomal function, either because affecting pigment cell survival, migration and differentiation, or because interfering with melanosome biogenesis, transport and transfer to keratinocytes, is immediately translated into color variations of skin, fur, hair or eyes. Thus, over one hundred genes and proteins have been identified as pigmentary determinants in mammals, providing us with a deep understanding of this biological system, which functions by using mechanisms and processes that have parallels in other tissues and organs. In particular, many genes implicated in melanosome biogenesis have been characterized, so that melanosomes represent an incredible source of information and a model for organelles belonging to the secretory pathway. Furthermore, the function of melanosomes can be associated with common physiological phenotypes, such as variation of pigmentation among individuals, and with rare pathological conditions, such as albinism, characterized by severe visual defects. Among the most relevant mechanisms operating in melanosome biogenesis are the signal transduction pathways mediated by two peculiar G protein-coupled receptors: the melanocortin-1 receptor (MC1R), involved in the fair skin/red hair phenotype and skin cancer; and OA1 (GPR143), whose loss-of-function results in X-linked ocular albinism. This review will focus on the most recent novelties regarding the functioning of these two receptors, by highlighting emerging signaling mechanisms and general implications for cell biology and pathology. PMID:20381640

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

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.

PubMed

Dowell, Karen G; Simons, Allen K; Bai, Hao; Kell, Braden; Wang, Zack Z; Yun, Kyuson; Hibbs, Matthew A

2014-05-01

Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1,100 conditions) and 62 mouse studies (~2.4 million data points collected under 1,085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and reverse transcriptase polymerase chain reaction (RT-PCR) validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g., POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g., threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g., leukemia inhibitory factor (LIF)-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated fibroblast growth factor in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation. © 2013 AlphaMed Press.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

PubMed Central

Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N

2010-01-01

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960

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.

A network model of genomic hormone interactions underlying dementia and its translational validation through serendipitous off-target effect

PubMed Central

2013-01-01

Background While the majority of studies have focused on the association between sex hormones and dementia, emerging evidence supports the role of other hormone signals in increasing dementia risk. However, due to the lack of an integrated view on mechanistic interactions of hormone signaling pathways associated with dementia, molecular mechanisms through which hormones contribute to the increased risk of dementia has remained unclear and capacity of translating hormone signals to potential therapeutic and diagnostic applications in relation to dementia has been undervalued. Methods Using an integrative knowledge- and data-driven approach, a global hormone interaction network in the context of dementia was constructed, which was further filtered down to a model of convergent hormone signaling pathways. This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis. Translational validation of the model was performed using the proposed novel mechanism discovery approach based on ‘serendipitous off-target effects’. Results Our results reveal the existence of a well-connected hormone interaction network underlying dementia. Seven hormone signaling pathways converge at the core of the hormone interaction network, which are shown to be mechanistically linked to the risk of dementia. Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions. Validation of the model through serendipitous off-target effects suggests that hormone signaling pathways substantially contribute to the pathogenesis of dementia. Conclusions The integrated network model of hormone interactions underlying dementia may serve as an initial translational platform for identifying potential therapeutic targets and candidate biomarkers for dementia-spectrum disorders such as Alzheimer’s disease. PMID:23885764

Early Induction of NRF2 Antioxidant Pathway by RHBDF2 Mediates Rapid Cutaneous Wound Healing

PubMed Central

Hosur, Vishnu; Burzenski, Lisa M.; Stearns, Timothy M.; Farley, Michelle L.; Sundberg, John P.; Wiles, Michael V.; Shultz, Leonard D.

2017-01-01

Rhomboid family protein RHBDF2, an upstream regulator of the epidermal growth factor (EGF) receptor signaling, has been implicated in cutaneous wound healing. However, the underlying molecular mechanisms are still emerging. In humans, a gain-of-function mutation in the RHBDF2 gene accelerates cutaneous wound healing in an EGFR-dependent manner. Likewise, a gain-of-function mutation in the mouse Rhbdf2 gene (Rhbdf2cub/cub) shows a regenerative phenotype (rapid ear-hole closure) resulting from constitutive activation of the EGFR pathway. Because the RHBDF2-regulated EGFR pathway is relevant to cutaneous wound healing in humans, we used Rhbdf2cub/cub mice to investigate the biological networks and pathways leading to accelerated ear-hole closure, with the goal of identifying therapeutic targets potentially effective in promoting wound healing in humans. Comparative transcriptome analysis of ear pinna tissue from Rhbdf2cub/cub and Rhbdf2+/+ mice at 0h, 15 min, 2h, and 24h post-wounding revealed an early induction of the nuclear factor E2-related factor 2 (NRF2)-mediated anti-oxidative pathway (0h and 15 min), followed by the integrin-receptor aggregation pathway (2h) as early-stage events immediately and shortly after wounding in Rhbdf2cub/cub mice. Additionally, we observed genes enriched for the Fc fragment of the IgG receptor IIIa (FCGR3A)-mediated phagocytosis pathway 24h post-wounding. Although cutaneous wound repair in healthy individuals is generally non-problematic, it can be severely impaired due to aging, diabetes, and chronic inflammation. This study suggests that activation of the NRF2-antioxidant pathway by rhomboid protein RHBDF2 might be beneficial in treating chronic non-healing wounds. PMID:28268192

Early induction of NRF2 antioxidant pathway by RHBDF2 mediates rapid cutaneous wound healing.

PubMed

Hosur, Vishnu; Burzenski, Lisa M; Stearns, Timothy M; Farley, Michelle L; Sundberg, John P; Wiles, Michael V; Shultz, Leonard D

2017-04-01

Rhomboid family protein RHBDF2, an upstream regulator of the epidermal growth factor (EGF) receptor signaling, has been implicated in cutaneous wound healing. However, the underlying molecular mechanisms are still emerging. In humans, a gain-of-function mutation in the RHBDF2 gene accelerates cutaneous wound healing in an EGFR-dependent manner. Likewise, a gain-of-function mutation in the mouse Rhbdf2 gene (Rhbdf2 cub/cub ) shows a regenerative phenotype (rapid ear-hole closure) resulting from constitutive activation of the EGFR pathway. Because the RHBDF2-regulated EGFR pathway is relevant to cutaneous wound healing in humans, we used Rhbdf2 cub/cub mice to investigate the biological networks and pathways leading to accelerated ear-hole closure, with the goal of identifying therapeutic targets potentially effective in promoting wound healing in humans. Comparative transcriptome analysis of ear pinna tissue from Rhbdf2 cub/cub and Rhbdf2 +/+ mice at 0h, 15min, 2h, and 24h post-wounding revealed an early induction of the nuclear factor E2-related factor 2 (NRF2)-mediated anti-oxidative pathway (0h and 15min), followed by the integrin-receptor aggregation pathway (2h) as early-stage events immediately and shortly after wounding in Rhbdf2 cub/cub mice. Additionally, we observed genes enriched for the Fc fragment of the IgG receptor IIIa (FCGR3A)-mediated phagocytosis pathway 24h post-wounding. Although cutaneous wound repair in healthy individuals is generally non-problematic, it can be severely impaired due to aging, diabetes, and chronic inflammation. This study suggests that activation of the NRF2-antioxidant pathway by rhomboid protein RHBDF2 might be beneficial in treating chronic non-healing wounds. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

Beltrame, Luca; Calura, Enrica; Popovici, Razvan R; Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-08-01

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. 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. 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.

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.

2-Keto acids based biosynthesis pathways for renewable fuels and chemicals.

PubMed

Tashiro, Yohei; Rodriguez, Gabriel M; Atsumi, Shota

2015-03-01

Global energy and environmental concerns have driven the development of biological chemical production from renewable sources. Biological processes using microorganisms are efficient and have been traditionally utilized to convert biomass (i.e., glucose) to useful chemicals such as amino acids. To produce desired fuels and chemicals with high yield and rate, metabolic pathways have been enhanced and expanded with metabolic engineering and synthetic biology approaches. 2-Keto acids, which are key intermediates in amino acid biosynthesis, can be converted to a wide range of chemicals. 2-Keto acid pathways were engineered in previous research efforts and these studies demonstrated that 2-keto acid pathways have high potential for novel metabolic routes with high productivity. In this review, we discuss recently developed 2-keto acid-based pathways.

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

PubMed Central

Milacic, Marija; Haw, Robin; Rothfels, Karen; Wu, Guanming; Croft, David; Hermjakob, Henning; D’Eustachio, Peter; Stein, Lincoln

2012-01-01

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics. PMID:24213504

Ligand-Specific Transcriptional Mechanisms Underlie Aryl Hydrocarbon Receptor-Mediated Developmental Toxicity of Oxygenated PAHs

PubMed Central

Goodale, B. C.; La Du, J.; Tilton, S. C.; Sullivan, C. M.; Bisson, W. H.; Waters, K. M.; Tanguay, R. L.

2015-01-01

Polycyclic aromatic hydrocarbons (PAHs) are priority environmental contaminants that exhibit mutagenic, carcinogenic, proinflammatory, and teratogenic properties. Oxygen-substituted PAHs (OPAHs) are formed during combustion processes and via phototoxidation and biological degradation of parent (unsubstituted) PAHs. Despite their prevalence both in contaminated industrial sites and in urban air, OPAH mechanisms of action in biological systems are relatively understudied. Like parent PAHs, OPAHs exert structure-dependent mutagenic activities and activation of the aryl hydrocarbon receptor (AHR) and cytochrome p450 metabolic pathway. Four-ring OPAHs 1,9-benz-10-anthrone (BEZO) and benz(a)anthracene-7,12-dione (7,12-B[a]AQ) cause morphological aberrations and induce markers of oxidative stress in developing zebrafish with similar potency, but only 7,12-B[a]AQ induces robust Cyp1a protein expression. We investigated the role of the AHR in mediating the toxicity of BEZO and 7,12-B[a]AQ, and found that knockdown of AHR2 rescued developmental effects caused by both compounds. Using RNA-seq and molecular docking, we identified transcriptional responses that precede developmental toxicity induced via differential interaction with AHR2. Redox-homeostasis genes were affected similarly by these OPAHs, while 7,12-B[a]AQ preferentially activated phase 1 metabolism and BEZO uniquely decreased visual system genes. Analysis of biological functions and upstream regulators suggests that BEZO is a weak AHR agonist, but interacts with other transcriptional regulators to cause developmental toxicity in an AHR-dependent manner. Identifying ligand-dependent AHR interactions and signaling pathways is essential for understanding toxicity of this class of environmentally relevant compounds. PMID:26141390

Principles for developing animal models of military PTSD

PubMed Central

Daskalakis, Nikolaos P.; Yehuda, Rachel

2014-01-01

The extent to which animal studies can be relevant to military posttraumatic stress disorder (PTSD) continues to be a matter of discussion. Some features of the clinical syndrome are more easily modeled than others. In the animal literature, a great deal of attention is focused on modeling the characteristics of military exposures and their impact on measurable behaviors and biological parameters. There are many issues to consider regarding the ecological validity of predator, social defeat or immobilization stress to combat-related experience. In contrast, less attention has been paid to individual variation following these exposures. Such variation is critical to understand how individual differences in the response to military trauma exposure may result to PTSD or resilience. It is important to consider potential differences in biological findings when comparing extremely exposed to non-exposed animals, versus those that result from examining individual differences. Animal models of military PTSD are also critical in advancing efforts in clinical treatment. In an ideal translational approach to study deployment related outcomes, information from humans and animals, blood and brain, should be carefully considered in tandem, possibly even computed simultaneously, to identify molecules, pathways and networks that are likely to be the key drivers of military PTSD symptoms. With the use novel biological methodologies (e.g., optogenetics) in the animal models, critical genes and pathways can be tuned up or down (rather than over-expressed or ablated completely) in discrete brain regions. Such techniques together with pre-and post-deployment human imaging will accelerate the identification of novel pharmacological and non-pharmacological intervention strategies. PMID:25206946

The Co-regulation Data Harvester: Automating gene annotation starting from a transcriptome database

NASA Astrophysics Data System (ADS)

Tsypin, Lev M.; Turkewitz, Aaron P.

Identifying co-regulated genes provides a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, a process much slower than genome sequencing per se. Tetrahymena thermophila, a unicellular eukaryote, has been a useful model organism and has a fully sequenced but sparsely annotated genome. One important resource for studying this organism has been an online transcriptomic database. We have developed an automated approach to gene annotation in the context of transcriptome data in T. thermophila, called the Co-regulation Data Harvester (CDH). Beginning with a gene of interest, the CDH identifies co-regulated genes by accessing the Tetrahymena transcriptome database. It then identifies their closely related genes (orthologs) in other organisms by using reciprocal BLAST searches. Finally, it collates the annotations of those orthologs' functions, which provides the user with information to help predict the cellular role of the initial query. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

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

Unraveling the response of plant cells to cytotoxic saponins

PubMed Central

Balestrazzi, Alma; Macovei, Anca; Tava, Aldo; Avato, Pinarosa; Raimondi, Elena

2011-01-01

A wide range of pharmacological properties are ascribed to natural saponins, in addition to their biological activities against herbivores, plant soil-borne pathogens and pests. As for animal cells, the cytotoxicity and the chemopreventive role of saponins are mediated by a complex network of signal transduction pathways which include reactive oxygen species (ROS) and nitric oxide (NO). The involvement of other relevant components of the saponin-related signaling routes, such as the Tumor Necrosis Factor (TNF)α, the interleukin (IL)-6 and the Nuclear Transcription FactorκB (NFκB), has been highlighted in animal cells. By contrast, information concerning the response of plant cells to saponins and the related signal transduction pathways is almost missing. To date, there are only a few common features which link plant and animal cells in their response to saponins, such as the early burst in ROS and NO production and the induction of metallothioneins (MTs), small cysteine-rich, metal-binding proteins. This aspect is discussed in the present paper in view of the recent hypothesis that MTs and NO are part of a novel signal transduction pathway participating in the cell response to oxidative stress. PMID:21673512

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

PubMed

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

2018-01-01

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

NF-κB deregulation in splenic marginal zone lymphoma.

PubMed

Spina, Valeria; Rossi, Davide

2016-08-01

Splenic marginal zone lymphoma is a rare mature B-cell malignancy involving the spleen, bone marrow and blood. Over the past years, the rapid expansion of sequencing technologies allowing the genome-wide assessment of genomic, epigenetic and transcriptional changes has revolutionized our understanding of the biological basis of splenic marginal zone lymphoma by providing a comprehensive and unbiased view of the genes/pathways that are deregulated in this disease. NF-κB is a family of transcription factors that plays critical roles in development, survival, and activation of B lymphocytes. Consistent with the physiological involvement of NF-κB signalling in proliferation and commitment of mature B-cells to the marginal zone of the spleen, many oncogenic mutations involved in constitutive activation of the NF-κB pathway were recently identified in splenic marginal zone lymphoma. This review describes the progress in understanding the mechanism of NF-κB activation in splenic marginal zone lymphoma, including molecular, epigenetic and post-transcriptional modifications of NF-κB genes and of upstream pathways, and discusses how information gained from these efforts has provided new insights on potential targets of diagnostic, prognostic and therapeutic relevance for splenic marginal zone lymphoma. Copyright © 2016. Published by Elsevier Ltd.

Disruptive environmental chemicals and cellular mechanisms that confer resistance to cell death

PubMed Central

Narayanan, Kannan Badri; Ali, Manaf; Barclay, Barry J.; Cheng, Qiang (Shawn); D’Abronzo, Leandro; Dornetshuber-Fleiss, Rita; Ghosh, Paramita M.; Gonzalez Guzman, Michael J.; Lee, Tae-Jin; Leung, Po Sing; Li, Lin; Luanpitpong, Suidjit; Ratovitski, Edward; Rojanasakul, Yon; Romano, Maria Fiammetta; Romano, Simona; Sinha, Ranjeet K.; Yedjou, Clement; Al-Mulla, Fahd; Al-Temaimi, Rabeah; Amedei, Amedeo; Brown, Dustin G.; Ryan, Elizabeth P.; Colacci, Anna Maria; Hamid, Roslida A.; Mondello, Chiara; Raju, Jayadev; Salem, Hosni K.; Woodrick, Jordan; Scovassi, A.Ivana; Singh, Neetu; Vaccari, Monica; Roy, Rabindra; Forte, Stefano; Memeo, Lorenzo; Kim, Seo Yun; Bisson, William H.; Lowe, Leroy; Park, Hyun Ho

2015-01-01

Cell death is a process of dying within biological cells that are ceasing to function. This process is essential in regulating organism development, tissue homeostasis, and to eliminate cells in the body that are irreparably damaged. In general, dysfunction in normal cellular death is tightly linked to cancer progression. Specifically, the up-regulation of pro-survival factors, including oncogenic factors and antiapoptotic signaling pathways, and the down-regulation of pro-apoptotic factors, including tumor suppressive factors, confers resistance to cell death in tumor cells, which supports the emergence of a fully immortalized cellular phenotype. This review considers the potential relevance of ubiquitous environmental chemical exposures that have been shown to disrupt key pathways and mechanisms associated with this sort of dysfunction. Specifically, bisphenol A, chlorothalonil, dibutyl phthalate, dichlorvos, lindane, linuron, methoxychlor and oxyfluorfen are discussed as prototypical chemical disruptors; as their effects relate to resistance to cell death, as constituents within environmental mixtures and as potential contributors to environmental carcinogenesis. PMID:26106145

LKB1 and lung cancer: more than the usual suspects.

PubMed

Shah, Usman; Sharpless, Norman E; Hayes, D Neil

2008-05-15

Often, the problem in cancer research is figuring out how a gene or pathway works in regulating cellular transformation. The question of what RAS activates or PTEN inhibits have been classic dilemmas of modern cancer biology. In these cases, biochemical and genetic studies have provided us with a fairly clear picture of the cancer relevant functions of these genes. For LKB1, a more recently identified human tumor suppressor gene, however, the problem is different. This serine-threonine kinase that is conserved from yeast to mammals seems to play a role in many diverse cellular pathways. Therefore, although elegant functional and genetic approaches have established critical roles for LKB1 in the regulation of metabolism, motility, polarity, and the cell cycle, the role(s) responsible for its true tumor suppressor function(s) is unknown. One is reminded of an Agatha Christie murder mystery where nearly every character in the book has reason to be suspected of committing the crime-there are too many suspects for how LKB1 might repress lung cancer.

Tyrosine Phosphorylation in Toll-Like Receptor Signaling

PubMed Central

Chattopadhyay, Saurabh; Sen, Ganes C.

2014-01-01

There is a wealth of knowledge about how different Ser/Thr protein kinases participate in Toll-like receptor (TLR) signaling. In many cases, we know the identities of the Ser/Thr residues of various components of the TLR-signaling pathways that are phosphorylated, the functional consequences of the phosphorylation and the responsible protein kinases. In contrast, the analysis of Tyr-phosphorylation of TLRs and their signaling proteins is currently incomplete, because several existing analyses are not systematic or they do not rely on robust experimental data. Nevertheless, it is clear that many TLRs require, for signaling, ligand-dependent phosphorylation of specific Tyr residues in their cytoplasmic domains; the list includes TLR2, TLR3, TLR4, TLR5, TLR8 and TLR9. In this article, we discuss the current status of knowledge on the effect of Tyr-phosphorylation of TLRs and their signaling proteins on their biochemical and biological functions, the possible identities of the relevant protein tyrosine kinases (PTKs) and the nature of regulations of PTK-mediated activation of TLR signaling pathways. PMID:25022196

Extrinsic control of Wnt signaling in the intestine.

PubMed

Koch, Stefan

The canonical Wnt/β-catenin signaling pathway is a central regulator of development and tissue homeostasis. In the intestine, Wnt signaling is primarily known as the principal organizer of epithelial stem cell identity and proliferation. Within the last decade, numerous scientific breakthroughs have shed light on epithelial self-organization in the gut, and organoids are now routinely used to study stem cell biology and intestinal pathophysiology. The contribution of non-epithelial cells to Wnt signaling in the gut has received less attention. However, there is mounting evidence that stromal cells are a rich source of Wnt pathway activators and inhibitors, which can dynamically shape Wnt signaling to control epithelial proliferation and restitution. Elucidating the extent and mechanisms of paracrine Wnt signaling in the intestine has the potential to broaden our understanding of epithelial homeostasis, and may be of particular relevance for disorders such as inflammatory bowel diseases and colitis-associated cancers. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Signaling pathway deregulation and molecular alterations across pediatric medulloblastomas.

PubMed

Lhermitte, B; Blandin, A F; Coca, A; Guerin, E; Durand, A; Entz-Werlé, N

2018-05-15

Medulloblastomas (MBs) account for 15% of brain tumors in children under the age of 15. To date, the overall 5-year survival rate for all children is only around 60%. Recent advances in cancer genomics have led to a fundamental change in medulloblastoma classification and is evolving along with the genomic discoveries, allowing to regularly reclassify this disease. The previous molecular classification defined 4 groups (WNT-activated MB, SHH-activated MB and the groups 3 and 4 characterized partially by NMYC and MYC driven MBs). This stratification moved forward recently to better define these groups and their correlation to outcome. This new stratification into 7 novel subgroups was helpful to lay foundations and complementary data on the understanding regarding molecular pathways and gene mutations underlying medulloblastoma biology. This review was aimed at answering the recent key questions on MB genomics and go further in the relevance of those genes in MB development as well as in their targeted therapies. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Differential epigenome-wide DNA methylation patterns in childhood obesity-associated asthma

PubMed Central

Rastogi, Deepa; Suzuki, Masako; Greally, John M.

2013-01-01

While DNA methylation plays a role in T-helper (Th) cell maturation, its potential dysregulation in the non-atopic Th1-polarized systemic inflammation observed in obesity-associated asthma is unknown. We studied DNA methylation epigenome-wide in peripheral blood mononuclear cells (PBMCs) from 8 obese asthmatic pre-adolescent children and compared it to methylation in PBMCs from 8 children with asthma alone, obesity alone and healthy controls. Differentially methylated loci implicated certain biologically relevant molecules and pathways. PBMCs from obese asthmatic children had distinctive DNA methylation patterns, with decreased promoter methylation of CCL5, IL2RA and TBX21, genes encoding proteins linked with Th1 polarization, and increased promoter methylation of FCER2, a low-affinity receptor for IgE, and of TGFB1, inhibitor of Th cell activation. T-cell signaling and macrophage activation were the two primary pathways that were selectively hypomethylated in obese asthmatics. These findings suggest that dysregulated DNA methylation is associated with non-atopic inflammation observed in pediatric obesity-associated asthma. PMID:23857381

β-Catenin transcriptional activity is minimal in canine osteosarcoma and its targeted inhibition results in minimal changes to cell line behaviour.

PubMed

Piskun, Caroline M; Stein, Timothy J

2016-06-01

Canine osteosarcoma (OS) is an aggressive malignancy associated with poor outcomes. Therapeutic improvements are likely to develop from an improved understanding of signalling pathways contributing to OS development and progression. The Wnt signalling pathway is of interest for its role in osteoblast differentiation, its dysregulation in numerous cancer types, and the relative frequency of cytoplasmic accumulation of β-catenin in canine OS. This study aimed to determine the biological impact of inhibiting canonical Wnt signalling in canine OS, by utilizing either β-catenin siRNA or a dominant-negative T-cell factor (TCF) construct. There were no consistent, significant changes in cell line behaviour with either method compared to parental cell lines. Interestingly, β-catenin transcriptional activity was three-fold higher in normal canine primary osteoblasts compared to canine OS cell lines. These results suggest canonical Wnt signalling is minimally active in canine OS and its targeted inhibition is not a relevant therapeutic strategy. © 2013 John Wiley & Sons Ltd.

FMM: a web server for metabolic pathway reconstruction and comparative analysis.

PubMed

Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

2009-07-01

Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

PubMed Central

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. PMID:29666752

Identifying relevant group of miRNAs in cancer using fuzzy mutual information.

PubMed

Pal, Jayanta Kumar; Ray, Shubhra Sankar; Pal, Sankar K

2016-04-01

MicroRNAs (miRNAs) act as a major biomarker of cancer. All miRNAs in human body are not equally important for cancer identification. We propose a methodology, called FMIMS, which automatically selects the most relevant miRNAs for a particular type of cancer. In FMIMS, miRNAs are initially grouped by using a SVM-based algorithm; then the group with highest relevance is determined and the miRNAs in that group are finally ranked for selection according to their redundancy. Fuzzy mutual information is used in computing the relevance of a group and the redundancy of miRNAs within it. Superiority of the most relevant group to all others, in deciding normal or cancer, is demonstrated on breast, renal, colorectal, lung, melanoma and prostate data. The merit of FMIMS as compared to several existing methods is established. While 12 out of 15 selected miRNAs by FMIMS corroborate with those of biological investigations, three of them viz., "hsa-miR-519," "hsa-miR-431" and "hsa-miR-320c" are possible novel predictions for renal cancer, lung cancer and melanoma, respectively. The selected miRNAs are found to be involved in disease-specific pathways by targeting various genes. The method is also able to detect the responsible miRNAs even at the primary stage of cancer. The related code is available at http://www.jayanta.droppages.com/FMIMS.html .

A guide for building biological pathways along with two case studies: hair and breast development.

PubMed

Trindade, Daniel; Orsine, Lissur A; Barbosa-Silva, Adriano; Donnard, Elisa R; Ortega, J Miguel

2015-03-01

Genomic information is being underlined in the format of biological pathways. Building these biological pathways is an ongoing demand and benefits from methods for extracting information from biomedical literature with the aid of text-mining tools. Here we hopefully guide you in the attempt of building a customized pathway or chart representation of a system. Our manual is based on a group of software designed to look at biointeractions in a set of abstracts retrieved from PubMed. However, they aim to support the work of someone with biological background, who does not need to be an expert on the subject and will play the role of manual curator while designing the representation of the system, the pathway. We therefore illustrate with two challenging case studies: hair and breast development. They were chosen for focusing on recent acquisitions of human evolution. We produced sub-pathways for each study, representing different phases of development. Differently from most charts present in current databases, we present detailed descriptions, which will additionally guide PESCADOR users along the process. The implementation as a web interface makes PESCADOR a unique tool for guiding the user along the biointeractions, which will constitute a novel pathway. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Construction and engineering of large biochemical pathways via DNA assembler

PubMed Central

Shao, Zengyi; Zhao, Huimin

2015-01-01

Summary DNA assembler enables rapid construction and engineering of biochemical pathways in a one-step fashion by exploitation of the in vivo homologous recombination mechanism in Saccharomyces cerevisiae. It has many applications in pathway engineering, metabolic engineering, combinatorial biology, and synthetic biology. Here we use two examples including the zeaxanthin biosynthetic pathway and the aureothin biosynthetic gene cluster to describe the key steps in the construction of pathways containing multiple genes using the DNA assembler approach. Methods for construct design, pathway assembly, pathway confirmation, and functional analysis are shown. The protocol for fine genetic modifications such as site-directed mutagenesis for engineering the aureothin gene cluster is also illustrated. PMID:23996442

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.

The expression of antibiotic resistance genes in antibiotic-producing bacteria.

PubMed

Mak, Stefanie; Xu, Ye; Nodwell, Justin R

2014-08-01

Antibiotic-producing bacteria encode antibiotic resistance genes that protect them from the biologically active molecules that they produce. The expression of these genes needs to occur in a timely manner: either in advance of or concomitantly with biosynthesis. It appears that there have been at least two general solutions to this problem. In many cases, the expression of resistance genes is tightly linked to that of antibiotic biosynthetic genes. In others, the resistance genes can be induced by their cognate antibiotics or by intermediate molecules from their biosynthetic pathways. The regulatory mechanisms that couple resistance to antibiotic biosynthesis are mechanistically diverse and potentially relevant to the origins of clinical antibiotic resistance. © 2014 John Wiley & Sons Ltd.

The Genetics and Epigenetics of Kidney Development

PubMed Central

Patel, Sanjeevkumar R.; Dressler, Gregory R.

2013-01-01

The development of the mammalian kidney has been studied at the genetic, biochemical, and cell biological level for more than 40 years. As such, detailed mechanisms governing early patterning, cell lineages, and inductive interactions are well described. How genes interact to specify the renal epithelial cells of the nephrons and how this specification is relevant to maintaining normal renal function is discussed. Implicit in the development of the kidney are epigenetic mechanisms that mark renal cell types and connect certain developmental regulatory factors to chromatin modifications that control gene expression patterns and cellular physiology. In adults, such regulatory factors and their epigenetic pathways may function in regeneration and may be disturbed in disease processes. PMID:24011574

Precision Dentistry in Early Childhood: The Central Role of Genomics.

PubMed

Divaris, Kimon

2017-07-01

Pediatric oral health is determined by the interaction of environmental factors and genetic influences. This is the case for early childhood caries, the most common disease of childhood. The complexity of exogenous-environmental factors interacting with innate biological predispositions results in a continuum of normal variation, as well as oral health and disease outcomes. Optimal oral health and care or precision dentistry warrants comprehensive understanding of these influences and tools enabling intervention on modifiable factors. This article reviews the current knowledge of the genomic basis of pediatric oral health and highlights known and postulated mechanistic pathways of action relevant to early childhood caries. Copyright © 2017 Elsevier Inc. All rights reserved.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

Fuzzy mutual information based grouping and new fitness function for PSO in selection of miRNAs in cancer.

PubMed

Pal, Jayanta Kumar; Ray, Shubhra Sankar; Pal, Sankar K

2017-10-01

MicroRNAs (miRNA) are one of the important regulators of cell division and also responsible for cancer development. Among the discovered miRNAs, not all are important for cancer detection. In this regard a fuzzy mutual information (FMI) based grouping and miRNA selection method (FMIGS) is developed to identify the miRNAs responsible for a particular cancer. First, the miRNAs are ranked and divided into several groups. Then the most important group is selected among the generated groups. Both the steps viz., ranking of miRNAs and selection of the most relevant group of miRNAs, are performed using FMI. Here the number of groups is automatically determined by the grouping method. After the selection process, redundant miRNAs are removed from the selected set of miRNAs as per user's necessity. In a part of the investigation we proposed a FMI based particle swarm optimization (PSO) method for selecting relevant miRNAs, where FMI is used as a fitness function to determine the fitness of the particles. The effectiveness of FMIGS and FMI based PSO is tested on five data sets and their efficiency in selecting relevant miRNAs are demonstrated. The superior performance of FMIGS to some existing methods are established and the biological significance of the selected miRNAs is observed by the findings of the biological investigation and publicly available pathway analysis tools. The source code related to our investigation is available at http://www.jayanta.droppages.com/FMIGS.html. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biological Conversion of Sugars to Hydrocarbons Technology Pathway

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

Davis, R.; Biddy, M.; Tan, E.

2013-03-01

This technology pathway case investigates the biological conversion of biomass-derived sugars to hydrocarbon biofuels, utilizing data from recent literature references and information consistent with recent pilot-scale demonstrations at NREL. Technical barriers and key research needs have been identified that should be pursued for the pathway to become competitive with petroleum-derived gasoline-, diesel-, and jet-range hydrocarbon blendstocks.

Deciphering the biological effects of acupuncture treatment modulating multiple metabolism pathways.

PubMed

Zhang, Aihua; Yan, Guangli; Sun, Hui; Cheng, Weiping; Meng, Xiangcai; Liu, Li; Xie, Ning; Wang, Xijun

2016-02-16

Acupuncture is an alternative therapy that is widely used to treat various diseases. However, detailed biological interpretation of the acupuncture stimulations is limited. We here used metabolomics and proteomics technology, thereby identifying the serum small molecular metabolites into the effect and mechanism pathways of standardized acupuncture treatments at 'Zusanli' acupoint which was the most often used acupoint in previous reports. Comprehensive overview of serum metabolic profiles during acupuncture stimulation was investigated. Thirty-four differential metabolites were identified in serum metabolome and associated with ten metabolism pathways. Importantly, we have found that high impact glycerophospholipid metabolism, fatty acid metabolism, ether lipid metabolism were acutely perturbed by acupuncture stimulation. As such, these alterations may be useful to clarify the biological mechanism of acupuncture stimulation. A series of differentially expressed proteins were identified and such effects of acupuncture stimulation were found to play a role in transport, enzymatic activity, signaling pathway or receptor interaction. Pathway analysis further revealed that most of these proteins were found to play a pivotal role in the regulation of multiple metabolism pathways. It demonstrated that the metabolomics coupled with proteomics as a powerful approach for potential applications in understanding the biological effects of acupuncture stimulation.

Fluid shear promotes chondrosarcoma cell invasion by activating matrix metalloproteinase 12 via IGF-2 and VEGF signaling pathways

PubMed Central

Wang, P; Chen, S-H; Hung, W-C; Paul, C; Zhu, F; Guan, P-P; Huso, DL; Kontrogianni-Konstantopoulos, A; Konstantopoulos, K

2015-01-01

Interstitial fluid flow in and around the tumor tissue is a physiologically relevant mechanical signal that regulates intracellular signaling pathways throughout the tumor. Yet, the effects of interstitial flow and associated fluid shear stress on the tumor cell function have been largely overlooked. Using in vitro bioengineering models in conjunction with molecular cell biology tools, we found that fluid shear (2 dyn/cm2) markedly upregulates matrix metalloproteinase 12 (MMP-12) expression and its activity in human chondrosarcoma cells. MMP-12 expression is induced in human chondrocytes during malignant transformation. However, the signaling pathway regulating MMP-12 expression and its potential role in human chondrosarcoma cell invasion and metastasis have yet to be delineated. We discovered that fluid shear stress induces the synthesis of insulin growth factor-2 (IGF-2) and vascular endothelial growth factor (VEGF) B and D, which in turn transactivate MMP-12 via PI3-K, p38 and JNK signaling pathways. IGF-2-, VEGF-B- or VEGF-D-stimulated chondrosarcoma cells display markedly higher migratory and invasive potentials in vitro, which are blocked by inhibiting MMP-12, PI3-K, p38 or JNK activity. Moreover, recombinant human MMP-12 or MMP-12 overexpression can potentiate chondrosarcoma cell invasion in vitro and the lung colonization in vivo. By reconstructing and delineating the signaling pathway regulating MMP-12 activation, potential therapeutic strategies that interfere with chondrosarcoma cell invasion may be identified. PMID:25435370

Fluid shear promotes chondrosarcoma cell invasion by activating matrix metalloproteinase 12 via IGF-2 and VEGF signaling pathways.

PubMed

Wang, P; Chen, S-H; Hung, W-C; Paul, C; Zhu, F; Guan, P-P; Huso, D L; Kontrogianni-Konstantopoulos, A; Konstantopoulos, K

2015-08-27

Interstitial fluid flow in and around the tumor tissue is a physiologically relevant mechanical signal that regulates intracellular signaling pathways throughout the tumor. Yet, the effects of interstitial flow and associated fluid shear stress on the tumor cell function have been largely overlooked. Using in vitro bioengineering models in conjunction with molecular cell biology tools, we found that fluid shear (2 dyn/cm(2)) markedly upregulates matrix metalloproteinase 12 (MMP-12) expression and its activity in human chondrosarcoma cells. MMP-12 expression is induced in human chondrocytes during malignant transformation. However, the signaling pathway regulating MMP-12 expression and its potential role in human chondrosarcoma cell invasion and metastasis have yet to be delineated. We discovered that fluid shear stress induces the synthesis of insulin growth factor-2 (IGF-2) and vascular endothelial growth factor (VEGF) B and D, which in turn transactivate MMP-12 via PI3-K, p38 and JNK signaling pathways. IGF-2-, VEGF-B- or VEGF-D-stimulated chondrosarcoma cells display markedly higher migratory and invasive potentials in vitro, which are blocked by inhibiting MMP-12, PI3-K, p38 or JNK activity. Moreover, recombinant human MMP-12 or MMP-12 overexpression can potentiate chondrosarcoma cell invasion in vitro and the lung colonization in vivo. By reconstructing and delineating the signaling pathway regulating MMP-12 activation, potential therapeutic strategies that interfere with chondrosarcoma cell invasion may be identified.

Associations of genetic risk scores based on adult adiposity pathways with childhood growth and adiposity measures.

PubMed

Monnereau, Claire; Vogelezang, Suzanne; Kruithof, Claudia J; Jaddoe, Vincent W V; Felix, Janine F

2016-08-18

Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures. We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models. A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area. A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards.

PathwayAccess: CellDesigner plugins for pathway databases.

PubMed

Van Hemert, John L; Dickerson, Julie A

2010-09-15

CellDesigner provides a user-friendly interface for graphical biochemical pathway description. Many pathway databases are not directly exportable to CellDesigner models. PathwayAccess is an extensible suite of CellDesigner plugins, which connect CellDesigner directly to pathway databases using respective Java application programming interfaces. The process is streamlined for creating new PathwayAccess plugins for specific pathway databases. Three PathwayAccess plugins, MetNetAccess, BioCycAccess and ReactomeAccess, directly connect CellDesigner to the pathway databases MetNetDB, BioCyc and Reactome. PathwayAccess plugins enable CellDesigner users to expose pathway data to analytical CellDesigner functions, curate their pathway databases and visually integrate pathway data from different databases using standard Systems Biology Markup Language and Systems Biology Graphical Notation. Implemented in Java, PathwayAccess plugins run with CellDesigner version 4.0.1 and were tested on Ubuntu Linux, Windows XP and 7, and MacOSX. Source code, binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv.

Scoring and ranking of metabolic trees to computationally ...

EPA Pesticide Factsheets

Increasing awareness about endocrine disrupting chemicals (EDCs) in the environment has driven concern about their potential impact on human health and wildlife. Tens of thousands of natural and synthetic xenobiotics are presently in commerce with little to no toxicity data and therefore uncertainty about their impact on estrogen receptor (ER) signaling pathways and other toxicity endpoints. As such, there is a need for strategies that make use of available data to prioritize chemicals for testing. One of the major achievements within the EPA’s Endocrine Disruptor Screening Program (EDSP), was the network model combining 18 ER in vitro assays from ToxCast to predict in vivo estrogenic activity. This model overcomes the limitations of single in vitro assays at different steps of the ER pathway. However, it lacks many relevant features required to estimate safe exposure levels and the composite assays do not consider the complex metabolic processes that might produce bioactive entities in a living system. This problem is typically addressed using in vivo assays. The aim of this work is to design a computational and in vitro approach to prioritize compounds and perform a quantitative safety assessment. To this end, we pursue a tiered approach taking into account bioactivity and bioavailability of chemicals and their metabolites using a human uterine epithelial cell (Ishikawa)-based assay. This biologically relevant fit-for-purpose assay was designed to quantitati

SeqAPASS: Sequence alignment to predict across-species ...

EPA Pesticide Factsheets

Efforts to shift the toxicity testing paradigm from whole organism studies to those focused on the initiation of toxicity and relevant pathways have led to increased utilization of in vitro and in silico methods. Hence the emergence of high through-put screening (HTS) programs, such as U.S. EPA ToxCast, and application of the adverse outcome pathway (AOP) framework for identifying and defining biological key events triggered upon perturbation of molecular initiating events and leading to adverse outcomes occuring at a level of organization relevant for risk assessment [1]. With these recent initiatives to harness the power of “the pathway” in describing and evaluating toxicity comes the need to extrapolate data beyond the model species. Sequence alignment to predict across-species susceptibilty (SeqAPASS) is a web-based tool that allows the user to begin to understand how broadly HTS data or AOP constructs may plausibly be extrapolated across species, while describing the relative intrinsic susceptibiltiy of different taxa to chemicals with known modes of action (e.g., pharmaceuticals and pesticides). The tool rapidly and strategically assesses available molecular target information to describe protein sequence similarity at the primary amino acid sequence, conserved domain, and individual amino acid residue levels. This in silico approach to species extrapolation was designed to automate and streamline the relatively complex and time-consuming process of co

TRYCAT pathways link peripheral inflammation, nicotine, somatization and depression in the etiology and course of Parkinson's disease.

PubMed

Anderson, George; Maes, Michael

2014-02-01

Increased depression, somatization, gut inflammation and wider peripheral inflammation are all associated with the early stages of Parkinson's disease (PD). Classically such concurrent conditions have been viewed as "comorbidities", driven by high levels of stress in a still poorly understood and treated disorder. Here we review the data on how oxidative and nitrosative stress in association with immuno-inflammatory responses, drives alteration in tryptophan catabolites, including kynurenine, kynurenic acid and quinolinic acid that drive not only the 'comorbidities" of PD but also important processes in the etiology and course of PD per se. The induction of indoleamine 2,3-dioxygenase, leading to the driving of tryptophan into neuroregulatory tryptophan catabolite products and away from serotonin and melatonin production, has significant implications for understanding the role of nicotine, melatonin, and caffeine in regulating PD susceptibility. Tryptophan catabolite pathway activation will also regulate blood-brain barrier permeability, glia and mast cell reactivity as well as wider innate and adaptive immune cell responses, all relevant to the course of PD. As such, the "comorbidities" of PD such as depression, somatization and peripheral inflammatory disorders can all be conceptualized as being an intricate part of the biological underpinnings of both the etiology and course of PD. As a consequence, the data reviewed here has treatment implications; relevant to both the course of PD and in the management of L-DOPA induced dyskinesias.

BIOREL: the benchmark resource to estimate the relevance of the gene networks.

PubMed

Antonov, Alexey V; Mewes, Hans W

2006-02-06

The progress of high-throughput methodologies in functional genomics has lead to the development of statistical procedures to infer gene networks from various types of high-throughput data. However, due to the lack of common standards, the biological significance of the results of the different studies is hard to compare. To overcome this problem we propose a benchmark procedure and have developed a web resource (BIOREL), which is useful for estimating the biological relevance of any genetic network by integrating different sources of biological information. The associations of each gene from the network are classified as biologically relevant or not. The proportion of genes in the network classified as "relevant" is used as the overall network relevance score. Employing synthetic data we demonstrated that such a score ranks the networks fairly in respect to the relevance level. Using BIOREL as the benchmark resource we compared the quality of experimental and theoretically predicted protein interaction data.

Imaging HIV-1 Tat Trafficking and Interactions by Engineered Green-Fluorescent-Protein Tagging

NASA Astrophysics Data System (ADS)

Beltram, Fabio

2002-03-01

The direct monitoring of protein function in live cells under physiologically relevant conditions is one of the most powerful and innovative methodologies for proteomics. Efficient florescent probes fully compatible with human-cell expression are the fundamental tools for these studies and their optimization opens the way to resolution at the single-protein level. Biological events involving protein pairs are also directly accessible thanks to tuning of protein-tag spectral properties and production of complementary pairs. Such pairs are characterized by overlapping absorption (for the acceptor tag) and emission (for the donor tag) spectra. By tagging the proteins of interest with acceptor and donor molecules, protein interaction can be directly visualized by FRET, fluorescent resonant energy transfer. In this talk we shall present the design by molecular dynamics calculations and the application of optimized green fluorescent proteins to the study of the human immunodeficiency virus HIV-1 proteomics. In particular trafficking and cellular interactions of HIV-1 transactivator protein Tat in live human cells will be presented. Tat localization and complex internalization pathways of exogenous molecules will be presented thanks to the peculiar optical properties of mutated GFPs. Cellular protein partners and subcellular interaction sites will be identified and directly visualized. The relevance of such results and of advanced spectroscopic and imaging techniques for a new level of understanding of biological processes and its significance for advancement in molecular biology will be underlined. A. Marcello et al., J. Biol. Chem. 276, 39220 (2001). R. Cinelli et al., Appl. Phys. Lett. 79, 3353 (2001).

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

PubMed Central

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

2016-01-01

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

Goal-Directed Visual Processing Differentially Impacts Human Ventral and Dorsal Visual Representations

PubMed Central

2017-01-01

Recent studies have challenged the ventral/“what” and dorsal/“where” two-visual-processing-pathway view by showing the existence of “what” and “where” information in both pathways. Is the two-pathway distinction still valid? Here, we examined how goal-directed visual information processing may differentially impact visual representations in these two pathways. Using fMRI and multivariate pattern analysis, in three experiments on human participants (57% females), by manipulating whether color or shape was task-relevant and how they were conjoined, we examined shape-based object category decoding in occipitotemporal and parietal regions. We found that object category representations in all the regions examined were influenced by whether or not object shape was task-relevant. This task effect, however, tended to decrease as task-relevant and irrelevant features were more integrated, reflecting the well-known object-based feature encoding. Interestingly, task relevance played a relatively minor role in driving the representational structures of early visual and ventral object regions. They were driven predominantly by variations in object shapes. In contrast, the effect of task was much greater in dorsal than ventral regions, with object category and task relevance both contributing significantly to the representational structures of the dorsal regions. These results showed that, whereas visual representations in the ventral pathway are more invariant and reflect “what an object is,” those in the dorsal pathway are more adaptive and reflect “what we do with it.” Thus, despite the existence of “what” and “where” information in both visual processing pathways, the two pathways may still differ fundamentally in their roles in visual information representation. SIGNIFICANCE STATEMENT Visual information is thought to be processed in two distinctive pathways: the ventral pathway that processes “what” an object is and the dorsal pathway that processes “where” it is located. This view has been challenged by recent studies revealing the existence of “what” and “where” information in both pathways. Here, we found that goal-directed visual information processing differentially modulates shape-based object category representations in the two pathways. Whereas ventral representations are more invariant to the demand of the task, reflecting what an object is, dorsal representations are more adaptive, reflecting what we do with the object. Thus, despite the existence of “what” and “where” information in both pathways, visual representations may still differ fundamentally in the two pathways. PMID:28821655

Molecular biology of pancreatic cancer: how useful is it in clinical practice?

PubMed

Sakorafas, George H; Smyrniotis, Vasileios

2012-07-10

During the recent two decades dramatic advances of molecular biology allowed an in-depth understanding of pancreatic carcinogenesis. It is currently accepted that pancreatic cancer has a genetic component. The real challenge is now how these impressive advances could be used in clinical practice. To critically present currently available data regarding clinical application of molecular biology in pancreatic cancer. Reports about clinical implications of molecular biology in patients with pancreatic cancer were retrieved from PubMed. These reports were selected on the basis of their clinical relevance, and the data of their publication (preferentially within the last 5 years). Emphasis was placed on reports investigating diagnostic, prognostic, and therapeutic implications. Molecular biology can be used to identify individuals at high-risk for pancreatic cancer development. Intensive surveillance is indicated in these patients to detect pancreatic neoplasia ideally at a preinvasive stage, when curative resection is still possible. Molecular biology can also be used in the diagnosis of pancreatic cancer, with molecular analysis on samples of biologic material, such as serum or plasma, duodenal fluid or preferentially pure pancreatic juice, pancreatic cells or tissue, and stools. Molecular indices have also prognostic significance. Finally, molecular biology may have therapeutic implications by using various therapeutic approaches, such as antiangiogenic factors, purine synthesis inhibitors, matrix metalloproteinase inhibitors, factors modulating tumor-stroma interaction, inactivation of the hedgehog pathway, gene therapy, oncolytic viral therapy, immunotherapy (both passive as well as active) etc. Molecular biology may have important clinical implications in patients with pancreatic cancer and represents one of the most active areas on cancer research. Hopefully clinical applications of molecular biology in pancreatic cancer will expand in the future, improving the effectiveness of treatment and prognosis of patients with pancreatic cancer. 

Biomimetic modelling.

PubMed Central

Vincent, Julian F V

2003-01-01

Biomimetics is seen as a path from biology to engineering. The only path from engineering to biology in current use is the application of engineering concepts and models to biological systems. However, there is another pathway: the verification of biological mechanisms by manufacture, leading to an iterative process between biology and engineering in which the new understanding that the engineering implementation of a biological system can bring is fed back into biology, allowing a more complete and certain understanding and the possibility of further revelations for application in engineering. This is a pathway as yet unformalized, and one that offers the possibility that engineers can also be scientists. PMID:14561351

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

A systematic approach to infer biological relevance and biases of gene network structures.

PubMed

Antonov, Alexey V; Tetko, Igor V; Mewes, Hans W

2006-01-10

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.

De Novo Transcriptomic Analysis of Peripheral Blood Lymphocytes from the Chinese Goose: Gene Discovery and Immune System Pathway Description

PubMed Central

Tariq, Mansoor; Chen, Rong; Yuan, Hongyu; Liu, Yanjie; Wu, Yanan; Wang, Junya; Xia, Chun

2015-01-01

Background The Chinese goose is one of the most economically important poultry birds and is a natural reservoir for many avian viruses. However, the nature and regulation of the innate and adaptive immune systems of this waterfowl species are not completely understood due to limited information on the goose genome. Recently, transcriptome sequencing technology was applied in the genomic studies focused on novel gene discovery. Thus, this study described the transcriptome of the goose peripheral blood lymphocytes to identify immunity relevant genes. Principal Findings De novo transcriptome assembly of the goose peripheral blood lymphocytes was sequenced by Illumina-Solexa technology. In total, 211,198 unigenes were assembled from the 69.36 million cleaned reads. The average length, N50 size and the maximum length of the assembled unigenes were 687 bp, 1,298 bp and 18,992 bp, respectively. A total of 36,854 unigenes showed similarity by BLAST search against the NCBI non-redundant (Nr) protein database. For functional classification, 163,161 unigenes were comprised of three Gene Ontology (Go) categories and 67 subcategories. A total of 15,334 unigenes were annotated into 25 eukaryotic orthologous groups (KOGs) categories. Kyoto Encyclopedia of Genes and Genomes (KEGG) database annotated 39,585 unigenes into six biological functional groups and 308 pathways. Among the 2,757 unigenes that participated in the 15 immune system KEGG pathways, 125 of the most important immune relevant genes were summarized and analyzed by STRING analysis to identify gene interactions and relationships. Moreover, 10 genes were confirmed by PCR and analyzed. Of these 125 unigenes, 109 unigenes, approximately 87%, were not previously identified in the goose. Conclusion This de novo transcriptome analysis could provide important Chinese goose sequence information and highlights the value of new gene discovery, pathways investigation and immune system gene identification, and comparison with other avian species as useful tools to understand the goose immune system. PMID:25816068

Lessons we learned from high-throughput and top-down systems biology analyses about glioma stem cells.

PubMed

Mock, Andreas; Chiblak, Sara; Herold-Mende, Christel

2014-01-01

A growing body of evidence suggests that glioma stem cells (GSCs) account for tumor initiation, therapy resistance, and the subsequent regrowth of gliomas. Thus, continuous efforts have been undertaken to further characterize this subpopulation of less differentiated tumor cells. Although we are able to enrich GSCs, we still lack a comprehensive understanding of GSC phenotypes and behavior. The advent of high-throughput technologies raised hope that incorporation of these newly developed platforms would help to tackle such questions. Since then a couple of comparative genome-, transcriptome- and proteome-wide studies on GSCs have been conducted giving new insights in GSC biology. However, lessons had to be learned in designing high-throughput experiments and some of the resulting conclusions fell short of expectations because they were performed on only a few GSC lines or at one molecular level instead of an integrative poly-omics approach. Despite these shortcomings, our knowledge of GSC biology has markedly expanded due to a number of survival-associated biomarkers as well as glioma-relevant signaling pathways and therapeutic targets being identified. In this article we review recent findings obtained by comparative high-throughput analyses of GSCs. We further summarize fundamental concepts of systems biology as well as its applications for glioma stem cell research.

Biological Targets and Mechanisms of Action of Natural Products from Marine Cyanobacteria

PubMed Central

Salvador-Reyes, Lilibeth A.

2015-01-01

Marine cyanobacteria are an ancient group of organisms and prolific producers of bioactive secondary metabolites. These compounds are presumably optimized by evolution over billions of years to exert high affinity for their intended biological target in the ecologically relevant organism but likely also possess activity in different biological contexts such as human cells. Screening of marine cyanobacterial extracts for bioactive natural products has largely focused on cancer cell viability; however, diversification of the screening platform led to the characterization of many new bioactive compounds. Targets of compounds have oftentimes been elusive if the compounds were discovered through phenotypic assays. Over the past few years, technology has advanced to determine mechanism of action (MOA) and targets through reverse chemical genetic and proteomic approaches, which has been applied to certain cyanobacterial compounds and will be discussed in this review. Some cyanobacterial molecules are the most-potent-in-class inhibitors and therefore may become valuable tools for chemical biology to probe protein function but also be templates for novel drugs, assuming in vitro potency translates into cellular and in vivo activity. Our review will focus on compounds for which the direct targets have been deciphered or which were found to target a novel pathway, and link them to disease states where target modulation may be beneficial. PMID:25571978

PathNER: a tool for systematic identification of biological pathway mentions in the literature

PubMed Central

2013-01-01

Background Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature. Results We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase. Conclusions In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/. PMID:24555844

Antioxidant Systems are Regulated by Nitric Oxide-Mediated Post-translational Modifications (NO-PTMs)

PubMed Central

Begara-Morales, Juan C.; Sánchez-Calvo, Beatriz; Chaki, Mounira; Valderrama, Raquel; Mata-Pérez, Capilla; Padilla, María N.; Corpas, Francisco J.; Barroso, Juan B.

2016-01-01

Nitric oxide (NO) is a biological messenger that orchestrates a plethora of plant functions, mainly through post-translational modifications (PTMs) such as S-nitrosylation or tyrosine nitration. In plants, hundreds of proteins have been identified as potential targets of these NO-PTMs under physiological and stress conditions indicating the relevance of NO in plant-signaling mechanisms. Among these NO protein targets, there are different antioxidant enzymes involved in the control of reactive oxygen species (ROS), such as H2O2, which is also a signal molecule. This highlights the close relationship between ROS/NO signaling pathways. The major plant antioxidant enzymes, including catalase, superoxide dismutases (SODs) peroxiredoxins (Prx) and all the enzymatic components of the ascorbate-glutathione (Asa-GSH) cycle, have been shown to be modulated to different degrees by NO-PTMs. This mini-review will update the recent knowledge concerning the interaction of NO with these antioxidant enzymes, with a special focus on the components of the Asa-GSH cycle and their physiological relevance. PMID:26909095

Biosynthesis and regulation of coronatine, a non-host-specific phytotoxin produced by Pseudomonas syringae.

PubMed

Bender, C L; Palmer, D A; Peñaloza-Vázquez, A; Rangaswamy, V; Ullrich, M

1998-01-01

Many P. syringae pathovars are known to produce low-molecular-weight, diffusible toxins in infected host plants. These phytotoxins reproduce some of the symptoms of the relevant bacterial disease and are effective at very low concentrations. Phytotoxins generally enhance the virulence of the P. syringae pathovar which produces them, but are not required for pathogenesis. Genes encoding phytotoxin production have been identified and cloned from several P. syringae pathovars. With the exception of coronatine, toxin biosynthetic gene clusters are generally chromosomally encoded. In several pathovars, the toxin biosynthetic gene cluster also contains a resistance gene which functions to protect the producing strain from the biocidal effects of the toxin. In the case of phaseolotoxin, a resistance gene (argK) has been utilized to engineer phaseolotoxin-resistant tobacco plants. Although P. syringae phytotoxins can induce very similar effects in plants (chlorosis and necrosis), their biosynthesis and mode of action can be quite different. Knowledge of the biosynthetic pathways to these toxins and the cloning of the structural genes for their biosynthesis has relevance to the development of new bioactive compounds with altered specificity. For example, polyketides constitute a huge family of structurally diverse natural products including antibiotics, chemotherapeutic compounds, and antiparasitics. Most of the research on polyketide synthesis in bacteria has focused on compounds synthesized by Streptomyces or other actinomycetes. It is also important to note that it is now possible to utilize a genetic rather than synthetic approach to biosynthesize novel polyketides with altered biological properties (Hutchinson and Fujii, 1995; Kao et al., 1994; Donadio et al., 1993; Katz and Donadio, 1993). Most of the reprogramming or engineering of novel polyketides has been done using actinomycete PKSs, but much of this technology could also be applied to polyketides synthesized by Pseudomonas when sufficient sequence information is available. It is important to note that Pseudomonas produces a variety of antimicrobial compounds from the polyketide pathway, including mupirocin (pseudomonic acid) (Feline et al., 1977), pyoluteorin (Cuppels et al., 1986), and 2-4 diacetylphloroglucinol (Phl) (Bangera and Thomashow, 1996). Pseudomonic acid is valued for its pharmaceutical properties as an antibiotic (Aldridge, 1992), whereas pyoluteorin and Phl have antifungal properties (Howell and Stipanovic, 1980; Keel et al., 1992). A thorough understanding of the biosynthetic pathway to polyketide phytotoxins such as coronatine may ultimately lead to the development of novel compounds with altered biological properties. Thus, specific genes in the biosynthetic pathways of P. syringae phytotoxins could be deployed in other systems to develop new compounds with a wide range of activities.

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

Molecular and biological pathways of skeletal muscle dysfunction in chronic obstructive pulmonary disease

PubMed Central

Gea, Joaquim

2016-01-01

Chronic obstructive pulmonary disease (COPD) will be a major leading cause of death worldwide in the near future. Weakness and atrophy of the quadriceps are associated with a significantly poorer prognosis and increased mortality in COPD. Despite that skeletal muscle dysfunction may affect both respiratory and limb muscle groups in COPD, the latter are frequently more severely affected. Therefore, muscle dysfunction in COPD is a common systemic manifestation that should be evaluated on routine basis in clinical settings. In the present review, several aspects of COPD muscle dysfunction are being reviewed, with special emphasis on the underlying biological mechanisms. Figures on the prevalence of COPD muscle dysfunction and the most relevant etiologic contributors are also provided. Despite that ongoing research will shed light into the contribution of additional mechanisms to COPD muscle dysfunction, current knowledge points toward the involvement of a wide spectrum of cellular and molecular events that are differentially expressed in respiratory and limb muscles. Such mechanisms are thoroughly described in the article. The contribution of epigenetic events on COPD muscle dysfunction is also reviewed. We conclude that in view of the latest discoveries, from now, on new avenues of research should be designed to specifically target cellular mechanisms and pathways that impair muscle mass and function in COPD using pharmacological strategies and/or exercise training modalities. PMID:27056059

Deconstructing Memory in Drosophila

PubMed Central

Margulies, Carla; Tully, Tim; Dubnau, Josh

2011-01-01

Unlike most organ systems, which have evolved to maintain homeostasis, the brain has been selected to sense and adapt to environmental stimuli by constantly altering interactions in a gene network that functions within a larger neural network. This unique feature of the central nervous system provides a remarkable plasticity of behavior, but also makes experimental investigations challenging. Each experimental intervention ramifies through both gene and neural networks, resulting in unpredicted and sometimes confusing phenotypic adaptations. Experimental dissection of mechanisms underlying behavioral plasticity ultimately must accomplish an integration across many levels of biological organization, including genetic pathways acting within individual neurons, neural network interactions which feed back to gene function, and phenotypic observations at the behavioral level. This dissection will be more easily accomplished for model systems such as Drosophila, which, compared with mammals, have relatively simple and manipulable nervous systems and genomes. The evolutionary conservation of behavioral phenotype and the underlying gene function ensures that much of what we learn in such model systems will be relevant to human cognition. In this essay, we have not attempted to review the entire Drosophila memory field. Instead, we have tried to discuss particular findings that provide some level of intellectual synthesis across three levels of biological organization: behavior, neural circuitry and biochemical pathways. We have attempted to use this integrative approach to evaluate distinct mechanistic hypotheses, and to propose critical experiments that will advance this field. PMID:16139203

Depressive symptoms in patients with obstructive sleep apnea: biological mechanistic pathways.

PubMed

Chirinos, Diana A; Gurubhagavatula, Indira; Broderick, Preston; Chirinos, Julio A; Teff, Karen; Wadden, Thomas; Maislin, Greg; Saif, Hassam; Chittams, Jesse; Cassidy, Caitlin; Hanlon, Alexandra L; Pack, Allan I

2017-12-01

This study examined the association between depressive symptoms, as well as depressive symptom dimensions, and three candidate biological pathways linking them to Obstructive sleep apnea (OSA): (1) inflammation; (2) circulating leptin; and (3) intermittent hypoxemia. Participants included 181 obese adults with moderate-to-severe OSA enrolled in the Cardiovascular Consequences of Sleep Apnea (COSA) trial. Depressive symptoms were measured using the Beck Depression Inventory-II (BDI-II). We assessed inflammation using C-reactive protein levels (CRP), circulating leptin by radioimmunoassay using a double antibody/PEG assay, and intermittent hypoxemia by the percentage of sleep time each patient had below 90% oxyhemoglobin saturation. We found no significant associations between BDI-II total or cognitive scores and CRP, leptin, or percentage of sleep time below 90% oxyhemoglobin saturation after controlling for relevant confounding factors. Somatic symptoms, however, were positively associated with percentage of sleep time below 90% saturation (β = 0.202, P = 0.032), but not with CRP or circulating leptin in adjusted models. Another significant predictor of depressive symptoms included sleep efficiency (β BDI Total  = -0.230, P = 0.003; β cognitive  = -0.173, P = 0.030 (β somatic  = -0.255, P = 0.001). In patients with moderate-to-severe OSA, intermittent hypoxia may play a role in somatic rather than cognitive or total depressive symptoms.

PUTATIVE ADVERSE OUTCOME PATHWAY FOR INHIBITON ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) provides a framework for organizing knowledge to define links between a molecular initiating event (MIE) and an adverse outcome (AO) occurring at a higher level of biological organization, such as the individual or population. The AOP framework proceeds from a general (e.g., not chemical specific) molecular mode of action, designated as a MIE, through stepwise changes in biological status, defined as key events (KEs), to a final AO that can be used in risk assessment. Because aromatase-inhibiting pharmaceuticals are widely used to treat breast cancer patients, we explored the unintended consequences that might occur in fish exposed to these chemicals through wastewater discharge into the aquatic environment. Unlike mammals, fish have two isoforms of aromatase, one that predominates in the ovary (cyp19a1a) and a second (cyp19a1b) that prevails in the brain. Aromatase activity in fish brain can be 100 to 1000 times that in mammals and is associated with reproduction. We have developed a putative AOP for inhibition of brain aromatase in fish leading to reproductive dysfunction based on review of relevant literature and reproductive experiments with the marine fish cunner (Tautogolabrus adspersus) exposed to aromatase-inhibiting pharmaceuticals in the laboratory. The first KE in this AOP is a decrease in brain aromatase activity due to exposure to an aromatase inhibitor. KEs then progress through subsequent steps including decreas

The evolution of human adiposity and obesity: where did it all go wrong?

PubMed Central

Wells, Jonathan C. K.

2012-01-01

Because obesity is associated with diverse chronic diseases, little attention has been directed to the multiple beneficial functions of adipose tissue. Adipose tissue not only provides energy for growth, reproduction and immune function, but also secretes and receives diverse signaling molecules that coordinate energy allocation between these functions in response to ecological conditions. Importantly, many relevant ecological cues act on growth and physique, with adiposity responding as a counterbalancing risk management strategy. The large number of individual alleles associated with adipose tissue illustrates its integration with diverse metabolic pathways. However, phenotypic variation in age, sex, ethnicity and social status is further associated with different strategies for storing and using energy. Adiposity therefore represents a key means of phenotypic flexibility within and across generations, enabling a coherent life-history strategy in the face of ecological stochasticity. The sensitivity of numerous metabolic pathways to ecological cues makes our species vulnerable to manipulative globalized economic forces. The aim of this article is to understand how human adipose tissue biology interacts with modern environmental pressures to generate excess weight gain and obesity. The disease component of obesity might lie not in adipose tissue itself, but in its perturbation by our modern industrialized niche. Efforts to combat obesity could be more effective if they prioritized ‘external’ environmental change rather than attempting to manipulate ‘internal’ biology through pharmaceutical or behavioral means. PMID:22915021

The evolution of human adiposity and obesity: where did it all go wrong?

PubMed

Wells, Jonathan C K

2012-09-01

Because obesity is associated with diverse chronic diseases, little attention has been directed to the multiple beneficial functions of adipose tissue. Adipose tissue not only provides energy for growth, reproduction and immune function, but also secretes and receives diverse signaling molecules that coordinate energy allocation between these functions in response to ecological conditions. Importantly, many relevant ecological cues act on growth and physique, with adiposity responding as a counterbalancing risk management strategy. The large number of individual alleles associated with adipose tissue illustrates its integration with diverse metabolic pathways. However, phenotypic variation in age, sex, ethnicity and social status is further associated with different strategies for storing and using energy. Adiposity therefore represents a key means of phenotypic flexibility within and across generations, enabling a coherent life-history strategy in the face of ecological stochasticity. The sensitivity of numerous metabolic pathways to ecological cues makes our species vulnerable to manipulative globalized economic forces. The aim of this article is to understand how human adipose tissue biology interacts with modern environmental pressures to generate excess weight gain and obesity. The disease component of obesity might lie not in adipose tissue itself, but in its perturbation by our modern industrialized niche. Efforts to combat obesity could be more effective if they prioritized 'external' environmental change rather than attempting to manipulate 'internal' biology through pharmaceutical or behavioral means.

Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis.

PubMed

Uimari, Outi; Rahmioglu, Nilufer; Nyholt, Dale R; Vincent, Katy; Missmer, Stacey A; Becker, Christian; Morris, Andrew P; Montgomery, Grant W; Zondervan, Krina T

2017-04-01

Do genome-wide association study (GWAS) data for endometriosis provide insight into novel biological pathways associated with its pathogenesis? GWAS analysis uncovered multiple pathways that are statistically enriched for genetic association signals, analysis of Stage A disease highlighted a novel variant in MAP3K4, while top pathways significantly associated with all endometriosis and Stage A disease included several mitogen-activated protein kinase (MAPK)-related pathways. Endometriosis is a complex disease with an estimated heritability of 50%. To date, GWAS revealed 10 genomic regions associated with endometriosis, explaining <4% of heritability, while half of the heritability is estimated to be due to common risk variants. Pathway analyses combine the evidence of single variants into gene-based measures, leveraging the aggregate effect of variants in genes and uncovering biological pathways involved in disease pathogenesis. Pathway analysis was conducted utilizing the International Endogene Consortium GWAS data, comprising 3194 surgically confirmed endometriosis cases and 7060 controls of European ancestry with genotype data imputed up to 1000 Genomes Phase three reference panel. GWAS was performed for all endometriosis cases and for Stage A (revised American Fertility Society (rAFS) I/II, n = 1686) and B (rAFS III/IV, n = 1364) cases separately. The identified significant pathways were compared with pathways previously investigated in the literature through candidate association studies. The most comprehensive biological pathway databases, MSigDB (including BioCarta, KEGG, PID, SA, SIG, ST and GO) and PANTHER were utilized to test for enrichment of genetic variants associated with endometriosis. Statistical enrichment analysis was performed using the MAGENTA (Meta-Analysis Gene-set Enrichment of variaNT Associations) software. The first genome-wide association analysis for Stage A endometriosis revealed a novel locus, rs144240142 (P = 6.45 × 10-8, OR = 1.71, 95% CI = 1.23-2.37), an intronic single-nucleotide polymorphism (SNP) within MAP3K4. This SNP was not associated with Stage B disease (P = 0.086). MAP3K4 was also shown to be differentially expressed in eutopic endometrium between Stage A endometriosis cases and controls (P = 3.8 × 10-4), but not with Stage B disease (P = 0.26). A total of 14 pathways enriched with genetic endometriosis associations were identified (false discovery rate (FDR)-P < 0.05). The pathways associated with any endometriosis were Grb2-Sos provides linkage to MAPK signaling for integrins pathway (P = 2.8 × 10-5, FDR-P = 3.0 × 10-3), Wnt signaling (P = 0.026, FDR-P = 0.026) and p130Cas linkage to MAPK signaling for integrins pathway (P = 6.0 × 10-4, FDR-P = 0.029); with Stage A endometriosis: extracellular signal-regulated kinase (ERK)1 ERK2 MAPK (P = 5.0 × 10-4, FDR-P = 5.0 × 10-4) and with Stage B endometriosis: two overlapping pathways that related to extracellular matrix biology-Core matrisome (P = 1.4 × 10-3, FDR-P = 0.013) and ECM glycoproteins (P = 1.8 × 10-3, FDR-P = 7.1 × 10-3). Genes arising from endometriosis candidate gene studies performed to date were enriched for Interleukin signaling pathway (P = 2.3 × 10-12), Apoptosis signaling pathway (P = 9.7 × 10-9) and Gonadotropin releasing hormone receptor pathway (P = 1.2 × 10-6); however, these pathways did not feature in the results based on GWAS data. Not applicable. The analysis is restricted to (i) variants in/near genes that can be assigned to pathways, excluding intergenic variants; (ii) the gene-based pathway definition as registered in the databases; (iii) women of European ancestry. The top ranked pathways associated with overall and Stage A endometriosis in particular involve integrin-mediated MAPK activation and intracellular ERK/MAPK acting downstream in the MAPK cascade, both acting in the control of cell division, gene expression, cell movement and survival. Other top enriched pathways in Stage B disease include ECM glycoprotein pathways important for extracellular structure and biochemical support. The results highlight the need for increased efforts to understand the functional role of these pathways in endometriosis pathogenesis, including the investigation of the biological effects of the genetic variants on downstream molecular processes in tissue relevant to endometriosis. Additionally, our results offer further support for the hypothesis of at least partially distinct causal pathophysiology for minimal/mild (rAFS I/II) vs. moderate/severe (rAFS III/IV) endometriosis. The genome-wide association data and Wellcome Trust Case Control Consortium (WTCCC) were generated through funding from the Wellcome Trust (WT084766/Z/08/Z, 076113 and 085475) and the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485 and 552498). N.R. was funded by a grant from the Medical Research Council UK (MR/K011480/1). A.P.M. is a Wellcome Trust Senior Fellow in Basic Biomedical Science (grant WT098017). All authors declare there are no conflicts of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

PubMed

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

From integrative genomics to systems genetics in the rat to link genotypes to phenotypes

PubMed Central

Moreno-Moral, Aida

2016-01-01

ABSTRACT Complementary to traditional gene mapping approaches used to identify the hereditary components of complex diseases, integrative genomics and systems genetics have emerged as powerful strategies to decipher the key genetic drivers of molecular pathways that underlie disease. Broadly speaking, integrative genomics aims to link cellular-level traits (such as mRNA expression) to the genome to identify their genetic determinants. With the characterization of several cellular-level traits within the same system, the integrative genomics approach evolved into a more comprehensive study design, called systems genetics, which aims to unravel the complex biological networks and pathways involved in disease, and in turn map their genetic control points. The first fully integrated systems genetics study was carried out in rats, and the results, which revealed conserved trans-acting genetic regulation of a pro-inflammatory network relevant to type 1 diabetes, were translated to humans. Many studies using different organisms subsequently stemmed from this example. The aim of this Review is to describe the most recent advances in the fields of integrative genomics and systems genetics applied in the rat, with a focus on studies of complex diseases ranging from inflammatory to cardiometabolic disorders. We aim to provide the genetics community with a comprehensive insight into how the systems genetics approach came to life, starting from the first integrative genomics strategies [such as expression quantitative trait loci (eQTLs) mapping] and concluding with the most sophisticated gene network-based analyses in multiple systems and disease states. Although not limited to studies that have been directly translated to humans, we will focus particularly on the successful investigations in the rat that have led to primary discoveries of genes and pathways relevant to human disease. PMID:27736746

Gene co-expression networks shed light into diseases of brain iron accumulation

PubMed Central

Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M.; Botía, Juan A.; Collingwood, Joanna F.; Hardy, John; Milward, Elizabeth A.; Ryten, Mina; Houlden, Henry

2016-01-01

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. PMID:26707700

From integrative genomics to systems genetics in the rat to link genotypes to phenotypes.

PubMed

Moreno-Moral, Aida; Petretto, Enrico

2016-10-01

Complementary to traditional gene mapping approaches used to identify the hereditary components of complex diseases, integrative genomics and systems genetics have emerged as powerful strategies to decipher the key genetic drivers of molecular pathways that underlie disease. Broadly speaking, integrative genomics aims to link cellular-level traits (such as mRNA expression) to the genome to identify their genetic determinants. With the characterization of several cellular-level traits within the same system, the integrative genomics approach evolved into a more comprehensive study design, called systems genetics, which aims to unravel the complex biological networks and pathways involved in disease, and in turn map their genetic control points. The first fully integrated systems genetics study was carried out in rats, and the results, which revealed conserved trans-acting genetic regulation of a pro-inflammatory network relevant to type 1 diabetes, were translated to humans. Many studies using different organisms subsequently stemmed from this example. The aim of this Review is to describe the most recent advances in the fields of integrative genomics and systems genetics applied in the rat, with a focus on studies of complex diseases ranging from inflammatory to cardiometabolic disorders. We aim to provide the genetics community with a comprehensive insight into how the systems genetics approach came to life, starting from the first integrative genomics strategies [such as expression quantitative trait loci (eQTLs) mapping] and concluding with the most sophisticated gene network-based analyses in multiple systems and disease states. Although not limited to studies that have been directly translated to humans, we will focus particularly on the successful investigations in the rat that have led to primary discoveries of genes and pathways relevant to human disease. © 2016. Published by The Company of Biologists Ltd.

Gene co-expression networks shed light into diseases of brain iron accumulation.

PubMed

Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M; Botía, Juan A; Collingwood, Joanna F; Hardy, John; Milward, Elizabeth A; Ryten, Mina; Houlden, Henry

2016-03-01

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Toxicogenomic effects common to triazole antifungals and conserved between rats and humans.

PubMed

Goetz, Amber K; Dix, David J

2009-07-01

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 timepoints and various study designs, gene expression profiling was conducted on rat livers from three separate studies with triazole treatment groups ranging from 6 h after a single oral gavage exposure, to prenatal to adult exposures via feed. To explore conservation of responses across species, gene expression from the rat liver studies were compared to in vitro data from rat and human primary hepatocytes exposed to the triazoles. Toxicogenomic data on triazoles from 33 different treatment groups and 135 samples (microarrays) identified thousands of probe sets and dozens of pathways differentially expressed across time, dose, and species--many of these were common to all three triazoles, or conserved between rodents and humans. Common and conserved pathways included androgen and estrogen metabolism, xenobiotic metabolism signaling through CAR and PXR, and CYP mediated metabolism. Differentially expressed genes included the Phase I xenobiotic, fatty acid, sterol and steroid metabolism genes Cyp2b2 and CYP2B6, Cyp3a1 and CYP3A4, and Cyp4a22 and CYP4A11; Phase II conjugation enzyme genes Ugt1a1 and UGT1A1; and Phase III ABC transporter genes Abcb1 and ABCB1. Gene expression changes caused by all three triazoles in liver and hepatocytes were concentrated in biological pathways regulating lipid, sterol and steroid homeostasis, identifying a potential common mode of action conserved between rodents and humans. Modulation of hepatic sterol and steroid metabolism is a plausible mode of action for changes in serum testosterone and adverse reproductive outcomes observed in rat studies, and may be relevant to human risk assessment.

Design and analysis of metabolic pathways supporting formatotrophic growth for electricity-dependent cultivation of microbes.

PubMed

Bar-Even, Arren; Noor, Elad; Flamholz, Avi; Milo, Ron

2013-01-01

Electrosynthesis is a promising approach that enables the biological production of commodities, like fuels and fine chemicals, using renewably produced electricity. Several techniques have been proposed to mediate the transfer of electrons from the cathode to living cells. Of these, the electroproduction of formate as a mediator seems especially promising: formate is readily soluble, of low toxicity and can be produced at relatively high efficiency and at reasonable current density. While organisms that are capable of formatotrophic growth, i.e. growth on formate, exist naturally, they are generally less suitable for bulk cultivation and industrial needs. Hence, it may be helpful to engineer a model organism of industrial relevance, such as E. coli, for growth on formate. There are numerous metabolic pathways that can potentially support formatotrophic growth. Here we analyze these diverse pathways according to various criteria including biomass yield, thermodynamic favorability, chemical motive force, kinetics and the practical challenges posed by their expression. We find that the reductive glycine pathway, composed of the tetrahydrofolate system, the glycine cleavage system, serine hydroxymethyltransferase and serine deaminase, is a promising candidate to support electrosynthesis in E. coli. The approach presented here exemplifies how combining different computational approaches into a systematic analysis methodology provides assistance in redesigning metabolism. This article is part of a Special Issue entitled: Metals in Bioenergetics and Biomimetics Systems. Copyright © 2012 Elsevier B.V. All rights reserved.

Identification of pathways directly regulated by SHORT VEGETATIVE PHASE during vegetative and reproductive development in Arabidopsis

PubMed Central

2013-01-01

Background MADS-domain transcription factors play important roles during plant development. The Arabidopsis MADS-box gene SHORT VEGETATIVE PHASE (SVP) is a key regulator of two developmental phases. It functions as a repressor of the floral transition during the vegetative phase and later it contributes to the specification of floral meristems. How these distinct activities are conferred by a single transcription factor is unclear, but interactions with other MADS domain proteins which specify binding to different genomic regions is likely one mechanism. Results To compare the genome-wide DNA binding profile of SVP during vegetative and reproductive development we performed ChIP-seq analyses. These ChIP-seq data were combined with tiling array expression analysis, induction experiments and qRT-PCR to identify biologically relevant binding sites. In addition, we compared genome-wide target genes of SVP with those published for the MADS domain transcription factors FLC and AP1, which interact with SVP during the vegetative and reproductive phases, respectively. Conclusions Our analyses resulted in the identification of pathways that are regulated by SVP including those controlling meristem development during vegetative growth and flower development whereas floral transition pathways and hormonal signaling were regulated predominantly during the vegetative phase. Thus, SVP regulates many developmental pathways, some of which are common to both of its developmental roles whereas others are specific to only one of them. PMID:23759218

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

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

Costa, Pedro M.; Fadeel, Bengt, E-mail: Bengt.Fade

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems shouldmore » be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.« less

Understanding the sorption and biotransformation of organic micropollutants in innovative biological wastewater treatment technologies.

PubMed

Alvarino, T; Suarez, S; Lema, J; Omil, F

2018-02-15

New technologies for wastewater treatment have been developed in the last years based on the combination of biological reactors operating under different redox conditions. Their efficiency in the removal of organic micropollutants (OMPs) has not been clearly assessed yet. This review paper is focussed on understanding the sorption and biotransformation of a selected group of 17 OMPs, including pharmaceuticals, hormones and personal care products, during biological wastewater treatment processes. Apart from considering the role of "classical" operational parameters, new factors such as biomass conformation and particle size, upward velocity applied or the addition of adsorbents have been considered. It has been found that the OMP removal by sorption not only depends on their physico-chemical characteristics and other parameters, such as the biomass conformation and particle size, or some operational conditions also relevant. Membrane biological reactors (MBR), have shown to enhance sorption and biotransformation of some OMPs. The same applies to technologies bases on direct addition of activated carbon in bioreactors. The OMP biotransformation degree and pathway is mainly driven by the redox potential and the primary substrate activity. The combination of different redox potentials in hybrid reactor systems can significantly enhance the overall OMP removal efficiency. Sorption and biotransformation can be synergistically promoted in biological reactors by the addition of activated carbon. The deeper knowledge of the main parameters influencing OMP removal provided by this review will allow optimizing the biological processes in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Basal-like Breast Cancers: From Pathology to Biology and Back Again.

PubMed

Gusterson, Barry; Eaves, Connie J

2018-06-05

Human breast cancers referred to as "basal-like" are of interest because they lack effective therapies and their biology is poorly understood. The term basal-like derives from studies demonstrating tumor gene expression profiles that include some transcripts characteristic of the basal cells of the normal adult human mammary gland and others associated with a subset of normal luminal cells. Elucidating the mechanisms responsible for the profiles of basal-like tumors is an active area of investigation. More refined molecular analysis of patients' samples and genetic strategies to produce breast cancers de novo from defined populations of normal mouse mammary cells have served as complementary approaches to identify relevant pathway alterations. However, both also have limitations. Here, we review some of the underlying reasons, including the unifying concept that some normal luminal cells have both luminal and basal features, as well as some emerging new avenues of investigation. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Using a systems biology approach to understand and study the mechanisms of metastasis.

PubMed

Ha, Ngoc-Han; Hunter, Kent W

2014-01-01

Metastasis remains the main cause for cancer-related deaths due to the lack of effective therapy. The clonal selection model has long been thought to be the primary mechanism of metastatic progression but many different mechanisms have been hypothesized for the progression from tumorigenesis to the successful dissemination and expansion of tumor cells at the secondary site. MicroRNAs, germline polymorphisms in combination with the tumor microenvironment are few of the different pathways to explain the metastatic cascade. Technological advances for high-throughput screening of cells such as expression profiling, next generation sequencing, as well as global network analyses have advanced the studies of these mechanisms. Combined with new insights into the various mechanisms of metastasis a systems biology approach has also been shown to be useful in identifying metastasis-specific gene signatures as well as predicting disease outcome. Furthermore, the results of these studies have been relevant for identifying biomarkers for metastatic disease. © 2013 Wiley Periodicals, Inc.

The potential for biologically catalyzed anaerobic methane oxidation on ancient Mars.

PubMed

Marlow, Jeffrey J; Larowe, Douglas E; Ehlmann, Bethany L; Amend, Jan P; Orphan, Victoria J

2014-04-01

This study examines the potential for the biologically mediated anaerobic oxidation of methane (AOM) coupled to sulfate reduction on ancient Mars. Seven distinct fluids representative of putative martian groundwater were used to calculate Gibbs energy values in the presence of dissolved methane under a range of atmospheric CO2 partial pressures. In all scenarios, AOM is exergonic, ranging from -31 to -135 kJ/mol CH4. A reaction transport model was constructed to examine how environmentally relevant parameters such as advection velocity, reactant concentrations, and biomass production rate affect the spatial and temporal dependences of AOM reaction rates. Two geologically supported models for ancient martian AOM are presented: a sulfate-rich groundwater with methane produced from serpentinization by-products, and acid-sulfate fluids with methane from basalt alteration. The simulations presented in this study indicate that AOM could have been a feasible metabolism on ancient Mars, and fossil or isotopic evidence of this metabolic pathway may persist beneath the surface and in surface exposures of eroded ancient terrains.

NGF and romantic love.

PubMed

Emanuele, Enzo

2011-06-01

Romantic love is the catalyst behind the spread of the human life. The neurobiology of love embraces the hypothesis that what we call "romantic attachment" or "romantic love" may be at least in part the expression of biological factors. A corollary of this hypothesis states that it is possible to learn much about the nature of human love by studying the molecules involved in the expression of social and affiliative behaviours. Under this theoretical framework, we have investigated the changes in plasma neurotrophin levels in subjects with early stage romantic love. A positive association between the intensity of early romantic feelings and serum levels of nerve growth factor (NGF) has been identified. These findings link love with biologically relevant pathways for neuron survival and illuminate the biochemical correlates of such a complex feeling that so deeply affects our own lives. The progresses in the neurobiology of love suggest that this kind of research may open a new window onto our understanding of the very nature of human romantic bonding.

Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques

NASA Astrophysics Data System (ADS)

Lespinats, Sylvain; Pinker-Domenig, Katja; Wengert, Georg; Houben, Ivo; Lobbes, Marc; Stadlbauer, Andreas; Meyer-Bäse, Anke

2016-05-01

Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques are insufficient to interpret and visualize these resulting experimental data. The emphasis of this paper lies in the application of novel approaches for the visualization, clustering and projection representation to unveil hidden data structures relevant for the accurate interpretation of biological experiments. These qualitative and quantitative methods are applied to the proteomic analysis of data sets derived from the GSCs. The achieved clustering and visualization results provide a more detailed insight into the protein-level fold changes and putative upstream regulators for the GSCs. However the extracted molecular information is insufficient in classifying GSCs and paving the pathway to an improved therapeutics of the heterogeneous glioma.

Pathway enrichment based on text mining and its validation on carotenoid and vitamin A metabolism.

PubMed

Waagmeester, Andra; Pezik, Piotr; Coort, Susan; Tourniaire, Franck; Evelo, Chris; Rebholz-Schuhmann, Dietrich

2009-10-01

Carotenoid metabolism is relevant to the prevention of various diseases. Although the main actors in this metabolic pathway are known, our understanding of the pathway is still incomplete. The information on the carotenoids is scattered in the large and growing body of scientific literature. We designed a text-mining work flow to enrich existing pathways. It has been validated on the vitamin A pathway, which is a well-studied part of the carotenoid metabolism. In this study we used the vitamin A metabolism pathway as it has been described by an expert team on carotenoid metabolism from the European network of excellence in Nutrigenomics (NuGO). This work flow uses an initial set of publications cited in a review paper (1,191 publications), enlarges this corpus with Medline abstracts (13,579 documents), and then extracts the key terminology from all relevant publications. Domain experts validated the intermediate and final results of our text-mining work flow. With our approach we were able to enrich the pathway representing vitamin A metabolism. We found 37 new and relevant terms from a total of 89,086 terms, which have been qualified for inclusion in the analyzed pathway. These 37 terms have been assessed manually and as a result 13 new terms were then added as entities to the pathway. Another 14 entities belonged to other pathways, which could form the link of these pathways with the vitamin A pathway. The remaining 10 terms were classified as biomarkers or nutrients. Automatic literature analysis improves the enrichment of pathways with entities already described in the scientific literature.

Comparing the transcriptomes of embryos from domesticated and wild Atlantic salmon (Salmo salar L.) stocks and examining factors that influence heritability of gene expression.

PubMed

Bicskei, Beatrix; Taggart, John B; Glover, Kevin A; Bron, James E

2016-03-17

Due to selective breeding, domesticated and wild Atlantic salmon are genetically diverged, which raises concerns about farmed escapees having the potential to alter the genetic composition of wild populations and thereby disrupting local adaptation. Documenting transcriptional differences between wild and domesticated stocks under controlled conditions is one way to explore the consequences of domestication and selection. We compared the transcriptomes of wild and domesticated Atlantic salmon embryos, by using a custom 44k oligonucleotide microarray to identify perturbed gene pathways between the two stocks, and to document the inheritance patterns of differentially-expressed genes by examining gene expression in their reciprocal hybrids. Data from 24 array interrogations were analysed: four reciprocal cross types (W♀ × W♂, D♀ × W♂; W♀ × D♂, D♀ × D♂) × six biological replicates. A common set of 31,491 features on the microarrays passed quality control, of which about 62 % were assigned a KEGG Orthology number. A total of 6037 distinct genes were identified for gene-set enrichment/pathway analysis. The most highly enriched functional groups that were perturbed between the two stocks were cellular signalling and immune system, ribosome and RNA transport, and focal adhesion and gap junction pathways, relating to cell communication and cell adhesion molecules. Most transcripts that were differentially expressed between the stocks were governed by additive gene interaction (33 to 42 %). Maternal dominance and over-dominance were also prevalent modes of inheritance, with no convincing evidence for a stock effect. Our data indicate that even at this relatively early developmental stage, transcriptional differences exist between the two stocks and affect pathways that are relevant to wild versus domesticated environments. Many of the identified differentially perturbed pathways are involved in organogenesis, which is expected to be an active process at the eyed egg stage. The dominant effects are more largely due to the maternal line than to the origin of the stock. This finding is particularly relevant in the context of potential introgression between farmed and wild fish, since female escapees tend to have a higher spawning success rate compared to males.

Water quality assessment using the AREc32 reporter gene assay indicative of the oxidative stress response pathway.

PubMed

Escher, Beate I; Dutt, Mriga; Maylin, Erin; Tang, Janet Y M; Toze, Simon; Wolf, C Roland; Lang, Matti

2012-11-01

The reporter gene assay AREc32 is based on the induction of the Nrf2 mediated oxidative stress response pathway in the human breast cancer cell line MCF7, where eight copies of the antioxidant response element (ARE) are linked to a reporter gene encoding for luciferase. The Nrf2-ARE pathway is responsive to many chemicals that cause oxidative stress, among them a large number of pesticides and skin irritants. We adopted and validated the AREc32 bioassay for water quality testing. tert-Butylhydroquinone served as the positive control, phenol as the negative control and other reactive chemicals were assessed for their specificity. An environmentally relevant reference chemical, benzo(a)pyrene was the most potent inducer of all tested chemicals. The concentration causing an induction ratio (IR) of 1.5 (EC(IR1.5)) was chosen as the effect benchmark value. The assay was applied to 21 water samples ranging from sewage to drinking water, including secondary treatment and various tertiary treatment options (ozonation, biologically activated carbon filtration, membrane filtration, reverse osmosis, advanced oxidation, chlorination, chloramination). The samples were enriched by solid phase extraction. In most samples the oxidative stress response was far more sensitive than cytotoxicity. The primary and secondary treated effluent exceeded the effect threshold IR 1.5 at a relative enrichment factor (REF) of 1, i.e., the native samples were active. All tertiary treated samples were less potent and their EC(IR1.5) lay between REF 1 and 10. The Nrf2 pathway was induced at a REF of approximately 10 for surface waters and drinking water, and above this enrichment cytotoxicity took over in most samples and quenched the induction. The blank (ultrapure water run through the sample enrichment process) was cytotoxic at an REF of 100, which is the limit of concentrations range that can be evaluated. Treatment typically decreased both the cytotoxicity and oxidative stress response apart from drinking water treatment where chlorination caused an increase in oxidative stress response, presumably due to the formation of disinfection by-products. This study demonstrates the relevance and applicability of the oxidative stress response pathway for water quality monitoring.

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

Adverse Outcome Pathway (AOP) Network Development for Fatty Liver

EPA Science Inventory

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 re...

Spatially organizing biochemistry: choosing a strategy to translate synthetic biology to the factory.

PubMed

Jakobson, Christopher M; Tullman-Ercek, Danielle; Mangan, Niall M

2018-05-29

Natural biochemical systems are ubiquitously organized both in space and time. Engineering the spatial organization of biochemistry has emerged as a key theme of synthetic biology, with numerous technologies promising improved biosynthetic pathway performance. One strategy, however, may produce disparate results for different biosynthetic pathways. We use a spatially resolved kinetic model to explore this fundamental design choice in systems and synthetic biology. We predict that two example biosynthetic pathways have distinct optimal organization strategies that vary based on pathway-dependent and cell-extrinsic factors. Moreover, we demonstrate that the optimal design varies as a function of kinetic and biophysical properties, as well as culture conditions. Our results suggest that organizing biosynthesis has the potential to substantially improve performance, but that choosing the appropriate strategy is key. The flexible design-space analysis we propose can be adapted to diverse biosynthetic pathways, and lays a foundation to rationally choose organization strategies for biosynthesis.

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

PubMed

Xiang, Bo; Yu, Minglan; Liang, Xuemei; Lei, Wei; Huang, Chaohua; Chen, Jing; He, Wenying; Zhang, Tao; Li, Tao; Liu, Kezhi

2017-12-10

To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Collision induced dissociation of protonated N-nitrosodimethylamine by ion trap mass spectrometry: Ultimate carcinogens in gas phase

NASA Astrophysics Data System (ADS)

Kulikova, Natalia; Baker, Michael; Gabryelski, Wojciech

2009-12-01

Collision induced dissociation of protonated N-nitrosodimethylamine (NDMA) and isotopically labeled N-nitrosodimethyl-d6-amine (NDMA-d6) was investigated by sequential ion trap mass spectrometry to establish mechanisms of gas phase reactions leading to intriguing products of this potent carcinogen. The fragmentation of (NDMA + H+) occurs via two dissociation pathways. In the alkylation pathway, homolytic cleavage of the N-O bond of N-dimethyl, N'-hydroxydiazenium ion generates N-dimethyldiazenium distonic ion which reacts further by a CH3 radical loss to form methanediazonium ion. Both methanediazonium ion and its precursor are involved in ion/molecule reactions. Methanediazonium ion showed to be capable of methylating water and methanol molecules in the gas phase of the ion trap and N-dimethyldiazenium distonic ion showed to abstract a hydrogen atom from a solvent molecule. In the denitrosation pathway, a tautomerization of N-dimethyl, N'-hydroxydiazenium ion to N-nitrosodimethylammonium intermediate ion results in radical cleavage of the N-N bond of the intermediate ion to form N-dimethylaminium radical cation which reacts further through [alpha]-cleavage to generate N-methylmethylenimmonium ion. Although the reactions of NDMA in the gas phase are different to those for enzymatic conversion of NDMA in biological systems, each activation method generates the same products. We will show that collision induced dissociation of N-nitrosodiethylamine (NDEA) and N-nitrosodipropylamine (NDPA) is also a feasible approach to gain information on formation, stability, and reactivity of alkylating agents originating from NDEA and NDPA. Investigating such biologically relevant, but highly reactive intermediates in the condensed phase is hampered by the short life-times of these transient species.

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

PubMed

Wang, Rui-Sheng; Loscalzo, Joseph

2018-05-20

Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunctional mechanistic pathways. Identifying such disease modules will provide insights into a systems-level understanding of molecular mechanisms of diseases. Owing to the incompleteness of our knowledge of disease proteins and limited information on the biological mediators of pathobiological processes, the key proteins (seed proteins) for many diseases appear scattered over the human protein-protein interactome and form a few small branches, rather than coherent network modules. In this paper, we develop a network-based algorithm, called the Seed Connector algorithm (SCA), to pinpoint disease modules by adding as few additional linking proteins (seed connectors) to the seed protein pool as possible. Such seed connectors are hidden disease module elements that are critical for interpreting the functional context of disease proteins. The SCA aims to connect seed disease proteins so that disease mechanisms and pathways can be decoded based on predicted coherent network modules. We validate the algorithm using a large corpus of 70 complex diseases and binding targets of over 200 drugs, and demonstrate the biological relevance of the seed connectors. Lastly, as a specific proof of concept, we apply the SCA to a set of seed proteins for coronary artery disease derived from a meta-analysis of large-scale genome-wide association studies and obtain a coronary artery disease module enriched with important disease-related signaling pathways and drug targets not previously recognized. Copyright © 2018 Elsevier Ltd. All rights reserved.

Petri net modelling of gene regulation of the Duchenne muscular dystrophy.

PubMed

Grunwald, Stefanie; Speer, Astrid; Ackermann, Jörg; Koch, Ina

2008-05-01

Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities. Free availability of the Petri net editor and animator Snoopy and the clustering tool PInA via http://www-dssz.informatik.tu-cottbus.de/~ wwwdssz/. The Petri net models used can be accessed via http://www.tfh-berlin.de/bi/duchenne/.

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

PubMed Central

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

2015-01-01

Reverse phase protein arrays (RPPA) are an established tool for measuring the expression and activation status of multiple proteins in parallel using only very small amounts of tissue. Several studies have demonstrated the value of this technique for signaling pathway analysis using proteins extracted from fresh frozen (FF) tissue in line with validated antibodies for this tissue type; however, formalin fixation and paraffin embedding (FFPE) is the standard method for tissue preservation in the clinical setting. Hence, we performed RPPA to measure profiles for a set of 300 protein markers using matched FF and FFPE tissue specimens to identify which markers performed similarly using the RPPA technique in fixed and unfixed tissues. Protein lysates were prepared from matched FF and FFPE tissue specimens of individual tumors taken from three different xenograft models of human cancer. Materials from both untreated mice and mice treated with either anti-HER3 or bispecific anti-IGF-1R/EGFR monoclonal antibodies were analyzed. Correlations between signals from FF and FFPE tissue samples were investigated. Overall, 60 markers were identified that produced comparable profiles between FF and FFPE tissues, demonstrating significant correlation between the two sample types. The top 25 markers also showed significance after correction for multiple testing. The panel of markers covered several clinically relevant tumor signaling pathways and both phosphorylated and nonphosphorylated proteins were represented. Biologically relevant changes in marker expression were noted when RPPA profiles from treated and untreated xenografts were compared. These data demonstrate that, using appropriately selected antibodies, RPPA analysis from FFPE tissue is well feasible and generates biologically meaningful information. The identified panel of markers that generate similar profiles in matched fixed and unfixed tissue samples may be clinically useful for pharmacodynamic studies of drug effect using FFPE tissues. PMID:26106084