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

e-Science and biological pathway semantics

PubMed Central

Luciano, Joanne S; Stevens, Robert D

2007-01-01

Background The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science. Results We demonstrate how BioPAX pathway data can be used to ask and answer some useful biological questions. We find that BioPAX comes close to meeting a broad range of e-Science needs, but certain semantic weaknesses mean that these goals are missed. We make a series of recommendations for re-modeling some aspects of BioPAX to better meet these needs. Conclusion Once these semantic weaknesses are addressed, it will be possible to integrate pathway information in a manner that would be useful in e-Science. PMID:17493286

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.

Entourage: Visualizing Relationships between Biological Pathways using Contextual Subsets

PubMed Central

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

2014-01-01

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

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

[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.

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.

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without

A Systems Toxicology Approach Reveals Biological Pathways Dysregulated by Prenatal Arsenic Exposure

PubMed Central

Laine, Jessica E.; Fry, Rebecca C.

2016-01-01

BACKGROUND Prenatal exposure to inorganic arsenic (iAs) is associated with dysregulated gene and protein expression in the fetus, both evident at birth. Potential epigenetic mechanisms that underlie these changes include but are not limited to the methylation of cytosines (CpG). OBJECTIVE The aim of the present study was to compile datasets from studies on prenatal arsenic exposure to identify whether key genes, proteins, or both and their associated biological pathways are perturbed. METHODS We compiled datasets from 12 studies that analyzed the relationship between prenatal iAs exposure and fetal changes to the epigenome (5-methyl cytosine), transcriptome (mRNA expression), and/or proteome (protein expression changes). FINDINGS Across the 12 studies, a set of 845 unique genes was identified and found to enrich for their role in biological pathways, including those signaled by peroxisome proliferator-activated receptor, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, and the glucocorticoid receptor. Tumor necrosis factor was identified as a putative cellular regulator underlying most (n = 277) of the identified iAs-associated genes or proteins. CONCLUSIONS Given their common identification across numerous human cohorts and their known toxicologic role in disease, the identified genes and pathways may underlie altered disease susceptibility associated with prenatal exposure to iAs. PMID:27325076

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.

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.

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

PubMed Central

Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

PubMed

Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

PubMed Central

King, Zachary A.; Dräger, Andreas; Ebrahim, Ali; Sonnenschein, Nikolaus; Lewis, Nathan E.; Palsson, Bernhard O.

2015-01-01

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools. PMID:26313928

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

Hippo Signaling: Key Emerging Pathway in Cellular and Whole-Body Metabolism.

PubMed

Ardestani, Amin; Lupse, Blaz; Maedler, Kathrin

2018-05-05

The evolutionarily conserved Hippo pathway is a key regulator of organ size and tissue homeostasis. Its dysregulation is linked to multiple pathological disorders. In addition to regulating development and growth, recent studies show that Hippo pathway components such as MST1/2 and LATS1/2 kinases, as well as YAP/TAZ transcriptional coactivators, are regulated by metabolic pathways and that the Hippo pathway controls metabolic processes at the cellular and organismal levels in physiological and metabolic disease states such as obesity, type 2 diabetes (T2D), nonalcoholic fatty liver disease (NAFLD), cardiovascular disorders, and cancer. In this review we summarize the connection between key Hippo components and metabolism, and how this interplay regulates cellular metabolism and metabolic pathways. The emerging function of Hippo in the regulation of metabolic homeostasis under physiological and pathological conditions is highlighted. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-09-01

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

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.

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

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

King, Zachary A.; Drager, Andreas; Ebrahim, Ali

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

DOE PAGES

King, Zachary A.; Drager, Andreas; Ebrahim, Ali; ...

2015-08-27

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less

Identification of the Key Genes and Pathways in Esophageal Carcinoma.

PubMed

Su, Peng; Wen, Shiwang; Zhang, Yuefeng; Li, Yong; Xu, Yanzhao; Zhu, Yonggang; Lv, Huilai; Zhang, Fan; Wang, Mingbo; Tian, Ziqiang

2016-01-01

Objective . Esophageal carcinoma (EC) is a frequently common malignancy of gastrointestinal cancer in the world. This study aims to screen key genes and pathways in EC and elucidate the mechanism of it. Methods . 5 microarray datasets of EC were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened by bioinformatics analysis. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network construction were performed to obtain the biological roles of DEGs in EC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression level of DEGs in EC. Results . A total of 1955 genes were filtered as DEGs in EC. The upregulated genes were significantly enriched in cell cycle and the downregulated genes significantly enriched in Endocytosis. PPI network displayed CDK4 and CCT3 were hub proteins in the network. The expression level of 8 dysregulated DEGs including CDK4, CCT3, THSD4, SIM2, MYBL2, CENPF, CDCA3, and CDKN3 was validated in EC compared to adjacent nontumor tissues and the results were matched with the microarray analysis. Conclusion . The significantly DEGs including CDK4, CCT3, THSD4, and SIM2 may play key roles in tumorigenesis and development of EC involved in cell cycle and Endocytosis.

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

PubMed Central

He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

2017-01-01

The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

PubMed

Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

2017-06-01

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched

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.

Ventral aspect of the visual form pathway is not critical for the perception of biological motion

PubMed Central

Gilaie-Dotan, Sharon; Saygin, Ayse Pinar; Lorenzi, Lauren J.; Rees, Geraint; Behrmann, Marlene

2015-01-01

Identifying the movements of those around us is fundamental for many daily activities, such as recognizing actions, detecting predators, and interacting with others socially. A key question concerns the neurobiological substrates underlying biological motion perception. Although the ventral “form” visual cortex is standardly activated by biologically moving stimuli, whether these activations are functionally critical for biological motion perception or are epiphenomenal remains unknown. To address this question, we examined whether focal damage to regions of the ventral visual cortex, resulting in significant deficits in form perception, adversely affects biological motion perception. Six patients with damage to the ventral cortex were tested with sensitive point-light display paradigms. All patients were able to recognize unmasked point-light displays and their perceptual thresholds were not significantly different from those of three different control groups, one of which comprised brain-damaged patients with spared ventral cortex (n > 50). Importantly, these six patients performed significantly better than patients with damage to regions critical for biological motion perception. To assess the necessary contribution of different regions in the ventral pathway to biological motion perception, we complement the behavioral findings with a fine-grained comparison between the lesion location and extent, and the cortical regions standardly implicated in biological motion processing. This analysis revealed that the ventral aspects of the form pathway (e.g., fusiform regions, ventral extrastriate body area) are not critical for biological motion perception. We hypothesize that the role of these ventral regions is to provide enhanced multiview/posture representations of the moving person rather than to represent biological motion perception per se. PMID:25583504

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

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.

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a

A zebrafish model of PINK1 deficiency reveals key pathway dysfunction including HIF signaling.

PubMed

Priyadarshini, M; Tuimala, J; Chen, Y C; Panula, P

2013-06-01

The PTEN induced putative kinase 1 (PINK1) gene is mutated in patients with hereditary early onset Parkinson's disease (PD). The targets of PINK1 and the mechanisms in PD are still not fully understood. Here, we carried out a high-throughput and unbiased microarray study to identify novel functions and pathways for PINK1. In larval zebrafish, the function of pink1 was inhibited using splice-site morpholino oligonucleotides and the samples were hybridized on a two-color gene expression array. We found 177 significantly altered genes in pink1 morphants compared with the uninjected wildtype controls (log fold change values from -1.6 to +0.9). The five most prominent pathways based on critical biological processes and key toxicological responses were hypoxia-inducible factor (HIF) signaling, TGF-β signaling, mitochondrial dysfunction, RAR activation, and biogenesis of mitochondria. Furthermore, we verified that potentially important genes such as hif1α, catalase, SOD3, and atp1a2a were downregulated in pink1 morphants, whereas genes such as fech, pax2a, and notch1a were upregulated. Some of these genes have been found to play important roles in HIF signaling pathways. The pink1 morphants were found to have heart dysfunction, increased erythropoiesis, increased expression of vascular endothelial growth factors, and increased ROS. Our findings suggest that a lack of pink1 in zebrafish alters many vital and critical pathways in addition to the HIF signaling pathway. Copyright © 2013 Elsevier Inc. All rights reserved.

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

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.

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

PubMed

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

2017-01-01

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

The oxalate-carbonate pathway: at the interface between biology and geology

NASA Astrophysics Data System (ADS)

Junier, P.; Cailleau, G.; Martin, G.; Guggiari, M.; Bravo, D.; Clerc, M.; Aragno, M.; Job, D.; Verrecchia, E.

2012-04-01

The formation of calcite in otherwise carbonate-free acidic soils through the biological degradation of oxalate is a mechanism termed oxalate-carbonate pathway. This pathway lies at the interface between biological and geological systems and constitutes an important, although underestimated, soil mineral carbon sink. In this case, atmospheric CO2 is fixed by the photosynthetic activity of oxalogenic plants, which is partly destined to the production of oxalate used for the chelation of metals, and particularly, calcium. Fungi are also able to produce oxalate to cope with elevated concentrations of metals. In spite of its abundance as a substrate, oxalate is a very stable organic anion that can be metabolized only by a group of bacteria that use it as carbon and energy sources. These bacteria close the biological cycle by degrading calcium oxalate, releasing Ca2+ and inducing a change in local soil pH. If parameters are favourable, the geological part of the pathway begins, because this change in pH will indirectly lead to the precipitation of secondary calcium carbonate (calcite) in unexpected geological conditions. Due to the initial acidic soil conditions, and the absence of geological carbonate in the basement, it is unexpected to find C in the form of calcite. The activity of the oxalate-carbonate pathway has now been demonstrated in several places around the world, suggesting that its importance can be even greater than expected. In addition, new roles for each of the biological players of the pathway have been revealed recently forcing us to reconsider a global biogeochemical model for oxalate cycling.

Biological Relevance of Key Events (KE) in utero in The Androgen Adverse Outcome Pathway Network (AOPn) to Adverse Effects in F1 Male Rats

EPA Science Inventory

We are conducting studies to evaluate the biological relevance of changes in KEs and molecular initiating events (MIE) in AOPs to determine if these can accurately predict of the dose levels of chemicals that disrupt the androgen signaling pathway in utero. Herein, we focus on ch...

Finding off-targets, biological pathways, and target diseases for chymase inhibitors via structure-based systems biology approach.

PubMed

Arooj, Mahreen; Sakkiah, Sugunadevi; Cao, Guang Ping; Kim, Songmi; Arulalapperumal, Venkatesh; Lee, Keun Woo

2015-07-01

Off-target binding connotes the binding of a small molecule of therapeutic significance to a protein target in addition to the primary target for which it was proposed. Progressively such off-targeting is emerging to be regular practice to reveal side effects. Chymase is an enzyme of hydrolase class that catalyzes hydrolysis of peptide bonds. A link between heart failure and chymase is ascribed, and a chymase inhibitor is in clinical phase II for treatment of heart failure. However, the underlying mechanisms of the off-target effects of human chymase inhibitors are still unclear. Here, we develop a robust computational strategy that is applicable to any enzyme system and that allows the prediction of drug effects on biological processes. Putative off-targets for chymase inhibitors were identified through various structural and functional similarity analyses along with molecular docking studies. Finally, literature survey was performed to incorporate these off-targets into biological pathways and to establish links between pathways and particular adverse effects. Off-targets of chymase inhibitors are linked to various biological pathways such as classical and lectin pathways of complement system, intrinsic and extrinsic pathways of coagulation cascade, and fibrinolytic system. Tissue kallikreins, granzyme M, neutrophil elastase, and mesotrypsin are also identified as off-targets. These off-targets and their associated pathways are elucidated for the effects of inflammation, cancer, hemorrhage, thrombosis, and central nervous system diseases (Alzheimer's disease). Prospectively, our approach is helpful not only to better understand the mechanisms of chymase inhibitors but also for drug repurposing exercises to find novel uses for these inhibitors. © 2014 Wiley Periodicals, Inc.

PyPathway: Python Package for Biological Network Analysis and Visualization.

PubMed

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

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

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

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.

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.

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

PubMed Central

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

2010-01-01

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

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.

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.

PathText: a text mining integrator for biological pathway visualizations

PubMed Central

Kemper, Brian; Matsuzaki, Takuya; Matsuoka, Yukiko; Tsuruoka, Yoshimasa; Kitano, Hiroaki; Ananiadou, Sophia; Tsujii, Jun'ichi

2010-01-01

Motivation: Metabolic and signaling pathways are an increasingly important part of organizing knowledge in systems biology. They serve to integrate collective interpretations of facts scattered throughout literature. Biologists construct a pathway by reading a large number of articles and interpreting them as a consistent network, but most of the models constructed currently lack direct links to those articles. Biologists who want to check the original articles have to spend substantial amounts of time to collect relevant articles and identify the sections relevant to the pathway. Furthermore, with the scientific literature expanding by several thousand papers per week, keeping a model relevant requires a continuous curation effort. In this article, we present a system designed to integrate a pathway visualizer, text mining systems and annotation tools into a seamless environment. This will enable biologists to freely move between parts of a pathway and relevant sections of articles, as well as identify relevant papers from large text bases. The system, PathText, is developed by Systems Biology Institute, Okinawa Institute of Science and Technology, National Centre for Text Mining (University of Manchester) and the University of Tokyo, and is being used by groups of biologists from these locations. Contact: brian@monrovian.com. PMID:20529930

THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK ...

EPA Pesticide Factsheets

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 Molecular Initiating Event (MIE), through intermediate KEs, ending in an Adverse Outcome (AO) which may be used as a basis for decision making. A KE is a measurable biological change, and is linked with other KEs via Key Event Relationships (KERs). A given KE may be involved in several AOPs, leading to a plausible network of biological changes that are involved in an organism’s response to an external stressor. When describing an AOP, five guiding principles have been proposed [1]: 1) an AOP is not specific to a single external stressor, 2) AOPs are modular, with KEs and KERs that can be used in several AOPs, 3) a single AOP is the unit of development, 4) most biological responses will be the result of networks of AOPs, and 5) AOPs will be modified as more biological knowledge becomes available. The collaborative development of AOPs is recommended to be performed using the AOP-Wiki (https://aopwiki.org), which is an effort between the European Commission – DG Joint Research Centre (JRC) and U.S. Environmental Protection Agency (EPA). The Wiki is one part of a larger OECD-sponsored AOP Knowledgebase effort, which is a repository for all AOPs developed as part of the Organization for Economic

A Web Tool for Generating High Quality Machine-readable Biological Pathways.

PubMed

Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Grant, Jason; Wu, Anthony; Wishart, David S

2017-02-08

PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to

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

EPA Pesticide Factsheets

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

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

PubMed

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

Key Pathways and Regulators of Vitamin K Function and Intermediary Metabolism.

PubMed

Shearer, Martin J; Okano, Toshio

2018-06-01

Vitamin K (VK) is an essential cofactor for the post-translational conversion of peptide-bound glutamate to γ-carboxyglutamate. The resultant vitamin K-dependent proteins are known or postulated to possess a variety of biological functions, chiefly in the maintenance of hemostasis. The vitamin K cycle is a cellular pathway that drives γ-carboxylation and recycling of VK via γ-carboxyglutamyl carboxylase (GGCX) and vitamin K epoxide reductase (VKOR), respectively. In this review, we show how novel molecular biological approaches are providing new insights into the pathophysiological mechanisms caused by rare mutations of both GGCX and VKOR. We also discuss how other protein regulators influence the intermediary metabolism of VK, first through intestinal absorption and second through a pathway that converts some dietary phylloquinone to menadione, which is prenylated to menaquinone-4 (MK-4) in target tissues by UBIAD1. The contribution of MK-4 synthesis to VK functions is yet to be revealed. Expected final online publication date for the Annual Review of Nutrition Volume 38 is August 21, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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.

Identifying biological pathways that underlie primordial short stature using network analysis.

PubMed

Hanson, Dan; Stevens, Adam; Murray, Philip G; Black, Graeme C M; Clayton, Peter E

2014-06-01

Mutations in CUL7, OBSL1 and CCDC8, leading to disordered ubiquitination, cause one of the commonest primordial growth disorders, 3-M syndrome. This condition is associated with i) abnormal p53 function, ii) GH and/or IGF1 resistance, which may relate to failure to recycle signalling molecules, and iii) cellular IGF2 deficiency. However the exact molecular mechanisms that may link these abnormalities generating growth restriction remain undefined. In this study, we have used immunoprecipitation/mass spectrometry and transcriptomic studies to generate a 3-M 'interactome', to define key cellular pathways and biological functions associated with growth failure seen in 3-M. We identified 189 proteins which interacted with CUL7, OBSL1 and CCDC8, from which a network including 176 of these proteins was generated. To strengthen the association to 3-M syndrome, these proteins were compared with an inferred network generated from the genes that were differentially expressed in 3-M fibroblasts compared with controls. This resulted in a final 3-M network of 131 proteins, with the most significant biological pathway within the network being mRNA splicing/processing. We have shown using an exogenous insulin receptor (INSR) minigene system that alternative splicing of exon 11 is significantly changed in HEK293 cells with altered expression of CUL7, OBSL1 and CCDC8 and in 3-M fibroblasts. The net result is a reduction in the expression of the mitogenic INSR isoform in 3-M syndrome. From these preliminary data, we hypothesise that disordered ubiquitination could result in aberrant mRNA splicing in 3-M; however, further investigation is required to determine whether this contributes to growth failure. © 2014 The authors.

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

PubMed Central

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

2011-01-01

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

Mapping the patent landscape of synthetic biology for fine chemical production pathways.

PubMed

Carbonell, Pablo; Gök, Abdullah; Shapira, Philip; Faulon, Jean-Loup

2016-09-01

A goal of synthetic biology bio-foundries is to innovate through an iterative design/build/test/learn pipeline. In assessing the value of new chemical production routes, the intellectual property (IP) novelty of the pathway is important. Exploratory studies can be carried using knowledge of the patent/IP landscape for synthetic biology and metabolic engineering. In this paper, we perform an assessment of pathways as potential targets for chemical production across the full catalogue of reachable chemicals in the extended metabolic space of chassis organisms, as computed by the retrosynthesis-based algorithm RetroPath. Our database for reactions processed by sequences in heterologous pathways was screened against the PatSeq database, a comprehensive collection of more than 150M sequences present in patent grants and applications. We also examine related patent families using Derwent Innovations. This large-scale computational study provides useful insights into the IP landscape of synthetic biology for fine and specialty chemicals production. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Whole genome association study identifies regions of the bovine genome and biological pathways involved in carcass trait performance in Holstein-Friesian cattle.

PubMed

Doran, Anthony G; Berry, Donagh P; Creevey, Christopher J

2014-10-01

such as glucagon and leptin. Several biological pathways, including PPAR signaling, were shown to be involved in various aspects of bovine carcass performance. These core genes and biological processes may form the foundation for further investigation to identify causative mutations involved in each trait. Results reported here support previous findings suggesting conservation of key biological processes involved in growth and metabolism.

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

Functional group diversity is key to Southern Ocean benthic carbon pathways

PubMed Central

Sands, Chester J.

2017-01-01

High latitude benthos are globally important in terms of accumulation and storage of ocean carbon, and the feedback this is likely to have on regional warming. Understanding this ecosystem service is important but difficult because of complex taxonomic diversity, history and geography of benthic biomass. Using South Georgia as a model location (where the history and geography of benthic biology is relatively well studied) we investigated whether the composition of functional groups were critical to benthic accumulation, immobilization and burial pathway to sequestration–and also aid their study through simplification of identification. We reclassified [1], [2]) morphotype and carbon mass data to 13 functional groups, for each sample of 32 sites around the South Georgia continental shelf. We investigated the influence on carbon accumulation, immobilization and sequestration estimate by multiple factors including the compositions of functional groups. Functional groups showed high diversity within and between sites, and within and between habitat types. Carbon storage was not linked to a functional group in particular but accumulation and immobilization increased with the number of functional groups present and the presence of hard substrata. Functional groups were also important to carbon burial rate, which increased with the presence of mixed (hard and soft substrata). Functional groups showed high surrogacy for taxonomic composition and were useful for examining contrasting habitat categorization. Functional groups not only aid marine carbon storage investigation by reducing time and the need for team size and speciality, but also important to benthic carbon pathways per se. There is a distinct geography to seabed carbon storage; seabed boulder-fields are hotspots of carbon accumulation and immobilization, whilst the interface between such boulder-fields and sediments are key places for burial and sequestration. PMID:28654664

Key aspects of the biology of snail-killing Sciomyzidae flies.

PubMed

Murphy, William L; Knutson, Lloyd V; Chapman, Eric G; Mc Donnell, Rory J; Williams, Christopher D; Foote, Benjamin A; Vala, Jean-Claude

2012-01-01

The biology of snail-killing flies (Diptera: Sciomyzidae) has been studied intensively over the past half-century, especially over the past decade. Today, sciomyzids are biologically the best-known group of higher Diptera. The overarching research objectives are evaluation of sciomyzids as biocontrols of disease-carrying or agriculturally important snails and slugs and as a paradigm group for the study of the evolution of diverse feeding and associated behaviors in flies. We present reviews and analyses of some key features of particular scientific and societal interest, including behavioral and phenological groups; laboratory experimental studies on behavior and development; population biology, bioindicators, ecosystem service provision, and conservation; phylogenetics, molecular studies, and evolutionary biology; and biocontrol. Copyright © 2012 by Annual Reviews. All rights reserved.

Identifying key genes, pathways and screening therapeutic agents for manganese-induced Alzheimer disease using bioinformatics analysis.

PubMed

Ling, JunJun; Yang, Shengyou; Huang, Yi; Wei, Dongfeng; Cheng, Weidong

2018-06-01

Alzheimer disease (AD) is a progressive neurodegenerative disease, the etiology of which remains largely unknown. Accumulating evidence indicates that elevated manganese (Mn) in brain exerts toxic effects on neurons and contributes to AD development. Thus, we aimed to explore the gene and pathway variations through analysis of high through-put data in this process.To screen the differentially expressed genes (DEGs) that may play critical roles in Mn-induced AD, public microarray data regarding Mn-treated neurocytes versus controls (GSE70845), and AD versus controls (GSE48350), were downloaded and the DEGs were screened out, respectively. The intersection of the DEGs of each datasets was obtained by using Venn analysis. Then, gene ontology (GO) function analysis and KEGG pathway analysis were carried out. For screening hub genes, protein-protein interaction network was constructed. At last, DEGs were analyzed in Connectivity Map (CMAP) for identification of small molecules that overcome Mn-induced neurotoxicity or AD development.The intersection of the DEGs obtained 140 upregulated and 267 downregulated genes. The top 5 items of biological processes of GO analysis were taxis, chemotaxis, cell-cell signaling, regulation of cellular physiological process, and response to wounding. The top 5 items of KEGG pathway analysis were cytokine-cytokine receptor interaction, apoptosis, oxidative phosphorylation, Toll-like receptor signaling pathway, and insulin signaling pathway. Afterwards, several hub genes such as INSR, VEGFA, PRKACB, DLG4, and BCL2 that might play key roles in Mn-induced AD were further screened out. Interestingly, tyrphostin AG-825, an inhibitor of tyrosine phosphorylation, was predicted to be a potential agent for overcoming Mn-induced neurotoxicity or AD development.The present study provided a novel insight into the molecular mechanisms of Mn-induced neurotoxicity or AD development and screened out several small molecular candidates that might be

[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.

The merged basins of signal transduction pathways in spatiotemporal cell biology.

PubMed

Hou, Yingchun; Hou, Yang; He, Siyu; Ma, Caixia; Sun, Mengyao; He, Huimin; Gao, Ning

2014-03-01

Numerous evidences have indicated that a signal system is composed by signal pathways, each pathway is composed by sub-pathways, and the sub-pathway is composed by the original signal terminals initiated with a protein/gene. We infer the terminal signals merged signal transduction system as "signal basin". In this article, we discussed the composition and regulation of signal basins, and the relationship between the signal basin control and triple W of spatiotemporal cell biology. Finally, we evaluated the importance of the systemic regulation to gene expression by signal basins under triple W. We hope our discussion will be the beginning to cause the attention for this area from the scientists of life science. © 2013 Wiley Periodicals, Inc.

Identification of Key Pathways and Genes in the Dynamic Progression of HCC Based on WGCNA.

PubMed

Yin, Li; Cai, Zhihui; Zhu, Baoan; Xu, Cunshuan

2018-02-14

Hepatocellular carcinoma (HCC) is a devastating disease worldwide. Though many efforts have been made to elucidate the process of HCC, its molecular mechanisms of development remain elusive due to its complexity. To explore the stepwise carcinogenic process from pre-neoplastic lesions to the end stage of HCC, we employed weighted gene co-expression network analysis (WGCNA) which has been proved to be an effective method in many diseases to detect co-expressed modules and hub genes using eight pathological stages including normal, cirrhosis without HCC, cirrhosis, low-grade dysplastic, high-grade dysplastic, very early and early, advanced HCC and very advanced HCC. Among the eight consecutive pathological stages, five representative modules are selected to perform canonical pathway enrichment and upstream regulator analysis by using ingenuity pathway analysis (IPA) software. We found that cell cycle related biological processes were activated at four neoplastic stages, and the degree of activation of the cell cycle corresponded to the deterioration degree of HCC. The orange and yellow modules enriched in energy metabolism, especially oxidative metabolism, and the expression value of the genes decreased only at four neoplastic stages. The brown module, enriched in protein ubiquitination and ephrin receptor signaling pathways, correlated mainly with the very early stage of HCC. The darkred module, enriched in hepatic fibrosis/hepatic stellate cell activation, correlated with the cirrhotic stage only. The high degree hub genes were identified based on the protein-protein interaction (PPI) network and were verified by Kaplan-Meier survival analysis. The novel five high degree hub genes signature that was identified in our study may shed light on future prognostic and therapeutic approaches. Our study brings a new perspective to the understanding of the key pathways and genes in the dynamic changes of HCC progression. These findings shed light on further investigations.

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

PubMed

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

2013-01-01

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

Nitric oxide and nitrous oxide turnover in natural and engineered microbial communities: biological pathways, chemical reactions, and novel technologies

PubMed Central

Schreiber, Frank; Wunderlin, Pascal; Udert, Kai M.; Wells, George F.

2012-01-01

Nitrous oxide (N2O) is an environmentally important atmospheric trace gas because it is an effective greenhouse gas and it leads to ozone depletion through photo-chemical nitric oxide (NO) production in the stratosphere. Mitigating its steady increase in atmospheric concentration requires an understanding of the mechanisms that lead to its formation in natural and engineered microbial communities. N2O is formed biologically from the oxidation of hydroxylamine (NH2OH) or the reduction of nitrite (NO−2) to NO and further to N2O. Our review of the biological pathways for N2O production shows that apparently all organisms and pathways known to be involved in the catabolic branch of microbial N-cycle have the potential to catalyze the reduction of NO−2 to NO and the further reduction of NO to N2O, while N2O formation from NH2OH is only performed by ammonia oxidizing bacteria (AOB). In addition to biological pathways, we review important chemical reactions that can lead to NO and N2O formation due to the reactivity of NO−2, NH2OH, and nitroxyl (HNO). Moreover, biological N2O formation is highly dynamic in response to N-imbalance imposed on a system. Thus, understanding NO formation and capturing the dynamics of NO and N2O build-up are key to understand mechanisms of N2O release. Here, we discuss novel technologies that allow experiments on NO and N2O formation at high temporal resolution, namely NO and N2O microelectrodes and the dynamic analysis of the isotopic signature of N2O with quantum cascade laser absorption spectroscopy (QCLAS). In addition, we introduce other techniques that use the isotopic composition of N2O to distinguish production pathways and findings that were made with emerging molecular techniques in complex environments. Finally, we discuss how a combination of the presented tools might help to address important open questions on pathways and controls of nitrogen flow through complex microbial communities that eventually lead to N2O build

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...

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

Systems biology, adverse outcome pathways, and ecotoxicology in the 21st century

EPA Science Inventory

While many definitions of systems biology exist, the majority of these contain most (if not all) of the following elements: global measurements of biological molecules to the extent technically feasible, dynamic measurements of key biological molecules to establish quantitative r...

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.

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.

Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture.

PubMed

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks ( Eedn ) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture

PubMed Central

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks (Eedn) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

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

HIF Oxygen Sensing Pathways in Lung Biology.

PubMed

Urrutia, Andrés A; Aragonés, Julián

2018-06-06

Cellular responses to oxygen fluctuations are largely mediated by hypoxia-inducible factors (HIFs). Upon inhalation, the first organ inspired oxygen comes into contact with is the lungs, but the understanding of the pulmonary HIF oxygen-sensing pathway is still limited. In this review we will focus on the role of HIF1α and HIF2α isoforms in lung responses to oxygen insufficiency. In particular, we will discuss novel findings regarding their role in the biology of smooth muscle cells and endothelial cells in the context of hypoxia-induced pulmonary vasoconstriction. Moreover, we will also discuss recent studies into HIF-dependent responses in the airway epithelium, which have been even less studied than the HIF-dependent vascular responses in the lungs. In summary, we will review the biological functions executed by HIF1 or HIF2 in the pulmonary vessels and epithelium to control lung responses to oxygen fluctuations as well as their pathological consequences in the hypoxic lung.

Screening for Key Pathways Associated with the Development of Osteoporosis by Bioinformatics Analysis

PubMed Central

Liu, Yanqing; Wang, Yueqiu; Zhang, Yanxia; Liu, Zhiyong; Xiang, Hongfei; Peng, Xianbo

2017-01-01

Objectives. We aimed to find the key pathways associated with the development of osteoporosis. Methods. We downloaded expression profile data of GSE35959 and analyzed the differentially expressed genes (DEGs) in 3 comparison groups (old_op versus middle, old_op versus old, and old_op versus senescent). KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses were carried out. Besides, Venn diagram analysis and gene functional interaction (FI) network analysis were performed. Results. Totally 520 DEGs, 966 DEGs, and 709 DEGs were obtained in old_op versus middle, old_op versus old, and old_op versus senescent groups, respectively. Lysosome pathway was the significantly enriched pathways enriched by intersection genes. The pathways enriched by subnetwork modules suggested that mitotic metaphase and anaphase and signaling by Rho GTPases in module 1 had more proteins from module. Conclusions. Lysosome pathway, mitotic metaphase and anaphase, and signaling by Rho GTPases may be involved in the development of osteoporosis. Furthermore, Rho GTPases may regulate the balance of bone resorption and bone formation via controlling osteoclast and osteoblast. These 3 pathways may be regarded as the treatment targets for osteoporosis. PMID:28466021

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

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.

Biological pathways involved in the development of inflammatory bowel disease.

PubMed

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

2014-10-01

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

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

Plant synthetic biology.

PubMed

Liu, Wusheng; Stewart, C Neal

2015-05-01

Plant synthetic biology is an emerging field that combines engineering principles with plant biology toward the design and production of new devices. This emerging field should play an important role in future agriculture for traditional crop improvement, but also in enabling novel bioproduction in plants. In this review we discuss the design cycles of synthetic biology as well as key engineering principles, genetic parts, and computational tools that can be utilized in plant synthetic biology. Some pioneering examples are offered as a demonstration of how synthetic biology can be used to modify plants for specific purposes. These include synthetic sensors, synthetic metabolic pathways, and synthetic genomes. We also speculate about the future of synthetic biology of plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

InFlo: a novel systems biology framework identifies cAMP-CREB1 axis as a key modulator of platinum resistance in ovarian cancer.

PubMed

Dimitrova, N; Nagaraj, A B; Razi, A; Singh, S; Kamalakaran, S; Banerjee, N; Joseph, P; Mankovich, A; Mittal, P; DiFeo, A; Varadan, V

2017-04-27

Characterizing the complex interplay of cellular processes in cancer would enable the discovery of key mechanisms underlying its development and progression. Published approaches to decipher driver mechanisms do not explicitly model tissue-specific changes in pathway networks and the regulatory disruptions related to genomic aberrations in cancers. We therefore developed InFlo, a novel systems biology approach for characterizing complex biological processes using a unique multidimensional framework integrating transcriptomic, genomic and/or epigenomic profiles for any given cancer sample. We show that InFlo robustly characterizes tissue-specific differences in activities of signalling networks on a genome scale using unique probabilistic models of molecular interactions on a per-sample basis. Using large-scale multi-omics cancer datasets, we show that InFlo exhibits higher sensitivity and specificity in detecting pathway networks associated with specific disease states when compared to published pathway network modelling approaches. Furthermore, InFlo's ability to infer the activity of unmeasured signalling network components was also validated using orthogonal gene expression signatures. We then evaluated multi-omics profiles of primary high-grade serous ovarian cancer tumours (N=357) to delineate mechanisms underlying resistance to frontline platinum-based chemotherapy. InFlo was the only algorithm to identify hyperactivation of the cAMP-CREB1 axis as a key mechanism associated with resistance to platinum-based therapy, a finding that we subsequently experimentally validated. We confirmed that inhibition of CREB1 phosphorylation potently sensitized resistant cells to platinum therapy and was effective in killing ovarian cancer stem cells that contribute to both platinum-resistance and tumour recurrence. Thus, we propose InFlo to be a scalable and widely applicable and robust integrative network modelling framework for the discovery of evidence-based biomarkers

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.

Detecting Disease Specific Pathway Substructures through an Integrated Systems Biology Approach

PubMed Central

Alaimo, Salvatore; Marceca, Gioacchino Paolo; Ferro, Alfredo; Pulvirenti, Alfredo

2017-01-01

In the era of network medicine, pathway analysis methods play a central role in the prediction of phenotype from high throughput experiments. In this paper, we present a network-based systems biology approach capable of extracting disease-perturbed subpathways within pathway networks in connection with expression data taken from The Cancer Genome Atlas (TCGA). Our system extends pathways with missing regulatory elements, such as microRNAs, and their interactions with genes. The framework enables the extraction, visualization, and analysis of statistically significant disease-specific subpathways through an easy to use web interface. Our analysis shows that the methodology is able to fill the gap in current techniques, allowing a more comprehensive analysis of the phenomena underlying disease states. PMID:29657291

Adverse Outcome Pathways – Organizing Toxicological ...

EPA Pesticide Factsheets

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High throughput screening (HTS) commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a natural framework for connecting high throughput toxicity testing (HTT) results to potential impacts on humans and wildlife populations. An AOP consists of two main components that describe the biological mechanisms driving toxicity. Key events represent biological processes essential for causing the adverse outcome that are also measurable experimentally. Key event relationships capture the biological processes connecting the key events. Evidence documented for each KER based on measurements of the KEs can provide the confidence needed for extrapolating HTT from early key events to overt toxicity represented by later key events based on the AOP. The IPCS mode of action (MOA) framework incorporates information required for making a chemical-specific toxicity determination. Given the close relationship between the AOP and MOA frameworks, it is possible to assemble an MOA by incorporating HTT results, chemical properties including absorption, distribution, metabolism, and excretion (ADME), and an AOP describing the biological basis of toxicity thereby streamlining the process. While current applications focus on the assessment of risk for environmental chemicals,

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

Esfahani, Mohammad Shahrokh; Dougherty, Edward R

2015-01-01

Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.

Development of an adverse outcome pathway for acetylcholinesterase inhibition leading to acute mortality

EPA Science Inventory

Adverse outcome pathways (AOPs) are designed to describe linkages of key events (KEs) within a biological pathway that result in an adverse outcome associated with chemical perturbation of a well-defined molecular initiating event (MIE). Risk assessors have traditionally relied ...

Experimental Approaches to Systematic Discovery and Development of Reproductive Adverse Outcome Pathways in Fish

EPA Science Inventory

Adverse outcome pathways (AOPs) are conceptual frameworks that portray causal and predictive linkages between key events at multiple scales of biological organization that connect molecular initiating events and early cellular perturbations (e.g., initiation of toxicity pathways)...

Integrating publicly-available data to generate computationally-predicted adverse outcome pathways for hepatic steatosis

EPA Science Inventory

The adverse outcome pathway (AOP) framework provides a way of organizing knowledge related to the key biological events that result in a particular health outcome. For the majority of environmental chemicals, the availability of curated pathways characterizing potential toxicity ...

Studying Biology to Understand Risk: Dosimetry Models and Quantitative Adverse Outcome Pathways

EPA Science Inventory

Confidence in the quantitative prediction of risk is increased when the prediction is based to as great an extent as possible on the relevant biological factors that constitute the pathway from exposure to adverse outcome. With the first examples now over 40 years old, physiologi...

The ORCA2 transcription factor plays a key role in regulation of the terpenoid indole alkaloid pathway

PubMed Central

2013-01-01

Background The terpenoid indole alkaloid (TIA) pathway leads to the production of pharmaceutically important drugs, such as the anticancer compounds vinblastine and vincristine. Unfortunately, these drugs are produced in trace amounts, causing them to be very costly. To increase production of these drugs, an improved understanding of the TIA regulatory pathway is needed. Towards this end, transgenic Catharanthus roseus hairy roots that overexpress the ORCA2 TIA transcriptional activator were generated and characterized. Results Transcriptional profiling experiments revealed that overexpression of ORCA2 results in altered expression of key genes from the indole and terpenoid pathways, which produce precursors for the TIA pathway, and from the TIA pathway itself. In addition, metabolite-profiling experiments revealed that overexpression of ORCA2 significantly affects the levels of several TIA metabolites. ORCA2 overexpression also causes significant increases in transcript levels of several TIA regulators, including TIA transcriptional repressors. Conclusions Results presented here indicate that ORCA2 plays a critical role in regulation of TIA metabolism. ORCA2 regulates expression of key genes from both feeder pathways, as well as the genes (STR and SGD) encoding the enzymes that catalyze the first two steps in TIA biosynthesis. ORCA2 may play an especially important role in regulation of the downstream branches of the TIA pathway, as it regulates four out of five genes characterized from this part of the pathway. Regulation of TIA transcriptional repressors by ORCA2 may provide a mechanism whereby increases in TIA metabolite levels in response to external stimuli are transient and limited in magnitude. PMID:24099172

Synthesis and biological applications of phosphinates and derivatives.

PubMed

Virieux, David; Volle, Jean-Noël; Bakalara, Norbert; Pirat, Jean-Luc

2015-01-01

This review first outlines general considerations on phosphinic acids and derivatives as bioisosteric groups. The next sections present key aspects of phosphinic acid-based molecules and include a brief description of the biological pathways involved for their activities. The synthetic aspects and the biological activities of such compounds reported in the literature between 2008 and 2013 are also described.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

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.

Synergy and Interactions Among Biological Pathways Leading to Preterm Premature Rupture of Membranes

PubMed Central

Lannon, Sophia M. R.; Vanderhoeven, Jeroen P.; Eschenbach, David A.; Gravett, Michael G.; Waldorf, Kristina M. Adams

2014-01-01

Preterm premature rupture of membranes (PPROM) occurs in 1% to 2% of births. Impact of PPROM is greatest in low- and middle-income countries where prematurity-related deaths are most common. Recent investigations identify cytokine and matrix metalloproteinase activation, oxidative stress, and apoptosis as primary pathways to PPROM. These biological processes are initiated by heterogeneous etiologies including infection/inflammation, placental bleeding, uterine overdistention, and genetic polymorphisms. We hypothesize that pathways to PPROM overlap and act synergistically to weaken membranes. We focus our discussion on membrane composition and strength, pathways linking risk factors to membrane weakening, and future research directions to reduce the global burden of PPROM. PMID:24840939

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

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.

Systems biology of the modified branched Entner-Doudoroff pathway in Sulfolobus solfataricus

PubMed Central

Figueiredo, Ana Sofia; Esser, Dominik; Haferkamp, Patrick; Wieloch, Patricia; Schomburg, Dietmar; Siebers, Bettina; Schaber, Jörg

2017-01-01

Sulfolobus solfataricus is a thermoacidophilic Archaeon that thrives in terrestrial hot springs (solfatares) with optimal growth at 80°C and pH 2–4. It catabolizes specific carbon sources, such as D-glucose, to pyruvate via the modified Entner-Doudoroff (ED) pathway. This pathway has two parallel branches, the semi-phosphorylative and the non-phosphorylative. However, the strategy of S.solfataricus to endure in such an extreme environment in terms of robustness and adaptation is not yet completely understood. Here, we present the first dynamic mathematical model of the ED pathway parameterized with quantitative experimental data. These data consist of enzyme activities of the branched pathway at 70°C and 80°C and of metabolomics data at the same temperatures for the wild type and for a metabolic engineered knockout of the semi-phosphorylative branch. We use the validated model to address two questions: 1. Is this system more robust to perturbations at its optimal growth temperature? 2. Is the ED robust to deletion and perturbations? We employed a systems biology approach to answer these questions and to gain further knowledge on the emergent properties of this biological system. Specifically, we applied deterministic and stochastic approaches to study the sensitivity and robustness of the system, respectively. The mathematical model we present here, shows that: 1. Steady state metabolite concentrations of the ED pathway are consistently more robust to stochastic internal perturbations at 80°C than at 70°C; 2. These metabolite concentrations are highly robust when faced with the knockout of either branch. Connected with this observation, these two branches show different properties at the level of metabolite production and flux control. These new results reveal how enzyme kinetics and metabolomics synergizes with mathematical modelling to unveil new systemic properties of the ED pathway in S.solfataricus in terms of its adaptation and robustness. PMID

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

CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets

PubMed Central

Li, Yang; Liu, Jun S.; Mootha, Vamsi K.

2017-01-01

In recent years, there has been a huge rise in the number of publicly available transcriptional profiling datasets. These massive compendia comprise billions of measurements and provide a special opportunity to predict the function of unstudied genes based on co-expression to well-studied pathways. Such analyses can be very challenging, however, since biological pathways are modular and may exhibit co-expression only in specific contexts. To overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression. CLIC accepts as input a pathway consisting of two or more genes. It then uses a Bayesian partition model to simultaneously partition the input gene set into coherent co-expressed modules (CEMs), while assigning the posterior probability for each dataset in support of each CEM. CLIC then expands each CEM by scanning the transcriptome for additional co-expressed genes, quantified by an integrated log-likelihood ratio (LLR) score weighted for each dataset. As a byproduct, CLIC automatically learns the conditions (datasets) within which a CEM is operative. We implemented CLIC using a compendium of 1774 mouse microarray datasets (28628 microarrays) or 1887 human microarray datasets (45158 microarrays). CLIC analysis reveals that of 910 canonical biological pathways, 30% consist of strongly co-expressed gene modules for which new members are predicted. For example, CLIC predicts a functional connection between protein C7orf55 (FMC1) and the mitochondrial ATP synthase complex that we have experimentally validated. CLIC is freely available at www.gene-clic.org. We anticipate that CLIC will be valuable both for revealing new components of biological pathways as well as the conditions in which they are active. PMID:28719601

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

PubMed

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

2016-12-23

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

Obesity and psychiatric disorders: commonalities in dysregulated biological pathways and their implications for treatment.

PubMed

Lopresti, Adrian L; Drummond, Peter D

2013-08-01

Rates of obesity are higher than normal across a range of psychiatric disorders, including major depressive disorder, bipolar disorder, schizophrenia and anxiety disorders. While the problem of obesity is generally acknowledged in mental health research and treatment, an understanding of their bi-directional relationship is still developing. In this review the association between obesity and psychiatric disorders is summarised, with a specific emphasis on similarities in their disturbed biological pathways; namely neurotransmitter imbalances, hypothalamus-pituitary-adrenal axis disturbances, dysregulated inflammatory pathways, increased oxidative and nitrosative stress, mitochondrial disturbances, and neuroprogression. The applicability and effectiveness of weight-loss interventions in psychiatric populations are reviewed along with their potential efficacy in ameliorating disturbed biological pathways, particularly those mediating inflammation and oxidative stress. It is proposed that weight loss may not only be an effective intervention to enhance physical health but may also improve mental health outcomes and slow the rate of neuroprogressive disturbances in psychiatric disorders. Areas of future research to help expand our understanding of the relationship between obesity and psychiatric disorders are also outlined. Copyright © 2013 Elsevier Inc. All rights reserved.

Dopamine is a key regulator in the signalling pathway underlying predator-induced defences in Daphnia

PubMed Central

Weiss, Linda C.; Leese, Florian; Laforsch, Christian; Tollrian, Ralph

2015-01-01

The waterflea Daphnia is a model to investigate the genetic basis of phenotypic plasticity resulting from one differentially expressed genome. Daphnia develops adaptive phenotypes (e.g. morphological defences) thwarting predators, based on chemical predator cue perception. To understand the genomic basis of phenotypic plasticity, the description of the precedent cellular and neuronal mechanisms is fundamental. However, key regulators remain unknown. All neuronal and endocrine stimulants were able to modulate but not induce defences, indicating a pathway of interlinked steps. A candidate able to link neuronal with endocrine responses is the multi-functional amine dopamine. We here tested its involvement in trait formation in Daphnia pulex and Daphnia longicephala using an induction assay composed of predator cues combined with dopaminergic and cholinergic stimulants. The mere application of both stimulants was sufficient to induce morphological defences. We determined dopamine localization in cells found in close association with the defensive trait. These cells serve as centres controlling divergent morphologies. As a mitogen and sclerotization agent, we anticipate that dopamine is involved in proliferation and structural formation of morphological defences. Furthermore, dopamine pathways appear to be interconnected with endocrine pathways, and control juvenile hormone and ecdysone levels. In conclusion, dopamine is suggested as a key regulator of phenotypic plasticity. PMID:26423840

A data mining paradigm for identifying key factors in biological processes using gene expression data.

PubMed

Li, Jin; Zheng, Le; Uchiyama, Akihiko; Bin, Lianghua; Mauro, Theodora M; Elias, Peter M; Pawelczyk, Tadeusz; Sakowicz-Burkiewicz, Monika; Trzeciak, Magdalena; Leung, Donald Y M; Morasso, Maria I; Yu, Peng

2018-06-13

A large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology

EPA Science Inventory

A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose–response, and time-course p...

Estimating Toxicity-Related Biological Pathway Altering Doses for High-Throughput Chemical Risk Assessment

EPA Science Inventory

We describe a framework for estimating the human dose at which a chemical significantly alters a biological pathway in vivo, making use of in vitro assay data and an in vitro derived pharmacokinetic model, coupled with estimates of population variability and uncertainty. The q...

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

Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways.

PubMed

Deng, Wenping; Zhang, Kui; Busov, Victor; Wei, Hairong

2017-01-01

Present knowledge indicates a multilayered hierarchical gene regulatory network (ML-hGRN) often operates above a biological pathway. Although the ML-hGRN is very important for understanding how a pathway is regulated, there is almost no computational algorithm for directly constructing ML-hGRNs. A backward elimination random forest (BWERF) algorithm was developed for constructing the ML-hGRN operating above a biological pathway. For each pathway gene, the BWERF used a random forest model to calculate the importance values of all transcription factors (TFs) to this pathway gene recursively with a portion (e.g. 1/10) of least important TFs being excluded in each round of modeling, during which, the importance values of all TFs to the pathway gene were updated and ranked until only one TF was remained in the list. The above procedure, termed BWERF. After that, the importance values of a TF to all pathway genes were aggregated and fitted to a Gaussian mixture model to determine the TF retention for the regulatory layer immediately above the pathway layer. The acquired TFs at the secondary layer were then set to be the new bottom layer to infer the next upper layer, and this process was repeated until a ML-hGRN with the expected layers was obtained. BWERF improved the accuracy for constructing ML-hGRNs because it used backward elimination to exclude the noise genes, and aggregated the individual importance values for determining the TFs retention. We validated the BWERF by using it for constructing ML-hGRNs operating above mouse pluripotency maintenance pathway and Arabidopsis lignocellulosic pathway. Compared to GENIE3, BWERF showed an improvement in recognizing authentic TFs regulating a pathway. Compared to the bottom-up Gaussian graphical model algorithm we developed for constructing ML-hGRNs, the BWERF can construct ML-hGRNs with significantly reduced edges that enable biologists to choose the implicit edges for experimental validation.

Inference of Evolutionary Forces Acting on Human Biological Pathways

PubMed Central

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

2015-01-01

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

Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components

PubMed Central

Wang, Min; Kornblau, Steven M; Coombes, Kevin R

2018-01-01

Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of significant principal components (PCs). Second, because each PC is a linear combination of genes, it rarely has a biological interpretation. Existing methods to determine the number of PCs are either subjective or computationally extensive. We review several methods and describe a new R package, PCDimension, that implements additional methods, the most important being an algorithm that extends and automates a graphical Bayesian method. Using simulations, we compared the methods. Our newly automated procedure is competitive with the best methods when considering both accuracy and speed and is the most accurate when the number of objects is small compared with the number of attributes. We applied the method to a proteomics data set from patients with acute myeloid leukemia. Proteins in the apoptosis pathway could be explained using 6 PCs. By clustering the proteins in PC space, we were able to replace the PCs by 6 “biological components,” 3 of which could be immediately interpreted from the current literature. We expect this approach combining PCA with clustering to be widely applicable. PMID:29881252

Proteomics for Adverse Outcome Pathway Discovery using Human Kidney Cells?

EPA Science Inventory

An Adverse Outcome Pathway (AOP) is a conceptual framework that applies molecular-based data for use in risk assessment and regulatory decision support. AOP development is based on effects data of chemicals on biological processes (i.e., molecular initiating events, key intermedi...

Hepatic Inflammation and Fibrosis: Functional Links and Key Pathways

PubMed Central

Seki, Ekihiro; Schwabe, Robert F.

2014-01-01

Inflammation is one of the most characteristic features of chronic liver disease of viral, alcoholic, fatty and autoimmune origin. Inflammation is typically present in all disease stages, and associated with the development of fibrosis, cirrhosis and hepatocellular carcinoma. In the past decade, numerous studies have contributed to improved understanding of the links between hepatic inflammation and fibrosis. Here, we review mechanisms that link inflammation with the development of liver fibrosis, focusing on the role of inflammatory mediators in hepatic stellate cell (HSC) activation and HSC survival during fibrogenesis and fibrosis regression. We will summarize the contributions of different inflammatory cells, including hepatic macrophages, T- and B-lymphocytes, NK cells and platelets, as well as key effectors such as cytokines, chemokines, and damage-associated molecular patterns. Furthermore, we will discuss the relevance of inflammatory signaling pathways for clinical liver disease and for the development of anti-fibrogenic strategies. PMID:25066777

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

Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps

PubMed Central

Silver, Matt; Montana, Giovanni

2012-01-01

Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways. We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our “pathways group lasso with adaptive weights” (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets. In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small. PMID:22499682

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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.

Branches of the NF-κB signaling pathway regulate proliferation of oval cells in rat liver regeneration.

PubMed

Zhao, W M; Qin, Y L; Niu, Z P; Chang, C F; Yang, J; Li, M H; Zhou, Y; Xu, C S

2016-03-24

The NF-kB (nuclear factor kB) pathway is involved in the proliferation of many cell types. To explore the mechanism of the NF-kB signaling pathway underlying the oval cell proliferation during rat liver regeneration, the Rat Genome 230 2.0 Array was used to detect expression changes of NF-kB signaling pathway-related genes in oval cells. The results revealed that the expression levels of many genes in the NF-kB pathway were significantly changed. This included 48 known genes and 16 homologous genes, as well as 370 genes and 85 homologous genes related to cell proliferation. To further understand the biological significance of these changes, an expression profile function was used to analyze the potential biological processes. The results showed that the NF-kB pathway promoted oval cell proliferation mainly through three signaling branches; the tumor necrosis factor alpha branch (TNF-a pathway), the growth factor branch, and the chemokine branch. An integrated statistics method was used to define the key genes in the NF-kB pathway. Seven genes were identified to play vital roles in the NF-kB pathway. To confirm these results, the protein content, including two key genes (TNF and FGF11) and two non-key genes (CCL2 and TNFRSF12A), were analyzed using two-dimensional gel electrophoresis and MALDI-TOF/TOF mass spectrometry. The results were generally consistent with those of the array data. To conclude, three branches and seven key genes were involved in the NF-kB signaling pathway that regulates oval cell proliferation during rat liver regeneration.

Co-production of hydrogen and ethanol from glucose by modification of glycolytic pathways in Escherichia coli - from Embden-Meyerhof-Parnas pathway to pentose phosphate pathway.

PubMed

Seol, Eunhee; Sekar, Balaji Sundara; Raj, Subramanian Mohan; Park, Sunghoon

2016-02-01

Hydrogen (H2) production from glucose by dark fermentation suffers from the low yield. As a solution to this problem, co-production of H2 and ethanol, both of which are good biofuels, has been suggested. To this end, using Escherichia coli, activation of pentose phosphate (PP) pathway, which can generate more NADPH than the Embden-Meyhof-Parnas (EMP) pathway, was attempted. Overexpression of two key enzymes in the branch nodes of the glycolytic pathway, Zwf and Gnd, significantly improved the co-production of H2 and ethanol with concomitant reduction of pyruvate secretion. Gene expression analysis and metabolic flux analysis (MFA) showed that, upon overexpression of Zwf and Gnd, glucose assimilation through the PP pathway, compared with that of the EMP or Entner-Doudoroff (ED) pathway, was greatly enhanced. The maximum co-production yields were 1.32 mol H2 mol(-1) glucose and 1.38 mol ethanol mol(-1) glucose, respectively. It is noteworthy that the glycolysis and the amount of NAD(P)H formed under anaerobic conditions could be altered by modifying (the activity of) several key enzymes. Our strategy could be applied for the development of industrial strains for biological production of reduced chemicals and biofuels which suffers from lack of reduced co-factors. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Non-nitrification pathway for NH4+ -N removal in pilot-scale drinking water biological processes].

PubMed

Yu, Xin; Ye, Lin; Li, Xu-dong; Zhang, Xiao-jian; Shi, Xu; Liu, Bo; Li, Rui-hua

2008-04-01

The non-nitrification pathway for NH4+ -N removal in pilot-scale drinking water biological treatment processes and its possible mechanism were investigated through calculating N and DO stoichiometric balance. With more than 2 mg/L NH4+ -N in the influent, for the fluidized bed bioreactor (FBBR), the total of NH4+ -N, NO2(-) -N, NO3(-) -N in the influent was 0.91 mg/L higher than that in the effluent, and for the biofilter, its DO consumption was 2.90 mg/L less than the stoichiometric amount. The results suggested that nitrogen loss occurred in both reactors and a part of NH4+ -N was removed through non-nitrification pathway. Because the utilization of phosphorus and organic matters was independent of nitrogen loss, the assimilation and denitrification could be excluded from the possible mechanisms. Because the very low C/N in the influent and the accumulation of NO2(-) -N in the reactors were similar with the wastewater biological processes, the "autotrophic removal of nitrogen" was regarded as the most probable non-nitrification pathway. In this mechanism, the couple of short-cut nitrification and ANAMMOX (or OLAND) leading to the transformation of NH4+ -N and NO2(-) -N into gaseous N2 was responsible for the nitrogen loss in drinking water biological processes.

Stress and DNA repair biology of the Fanconi anemia pathway

PubMed Central

Longerich, Simonne; Li, Jian; Xiong, Yong; Sung, Patrick

2014-01-01

Fanconi anemia (FA) represents a paradigm of rare genetic diseases, where the quest for cause and cure has led to seminal discoveries in cancer biology. Although a total of 16 FA genes have been identified thus far, the biochemical function of many of the FA proteins remains to be elucidated. FA is rare, yet the fact that 5 FA genes are in fact familial breast cancer genes and FA gene mutations are found frequently in sporadic cancers suggest wider applicability in hematopoiesis and oncology. Establishing the interaction network involving the FA proteins and their associated partners has revealed an intersection of FA with several DNA repair pathways, including homologous recombination, DNA mismatch repair, nucleotide excision repair, and translesion DNA synthesis. Importantly, recent studies have shown a major involvement of the FA pathway in the tolerance of reactive aldehydes. Moreover, despite improved outcomes in stem cell transplantation in the treatment of FA, many challenges remain in patient care. PMID:25237197

Significant Deregulated Pathways in Diabetes Type II Complications Identified through Expression Based Network Biology

NASA Astrophysics Data System (ADS)

Ukil, Sanchaita; Sinha, Meenakshee; Varshney, Lavneesh; Agrawal, Shipra

Type 2 Diabetes is a complex multifactorial disease, which alters several signaling cascades giving rise to serious complications. It is one of the major risk factors for cardiovascular diseases. The present research work describes an integrated functional network biology approach to identify pathways that get transcriptionally altered and lead to complex complications thereby amplifying the phenotypic effect of the impaired disease state. We have identified two sub-network modules, which could be activated under abnormal circumstances in diabetes. Present work describes key proteins such as P85A and SRC serving as important nodes to mediate alternate signaling routes during diseased condition. P85A has been shown to be an important link between stress responsive MAPK and CVD markers involved in fibrosis. MAPK8 has been shown to interact with P85A and further activate CTGF through VEGF signaling. We have traced a novel and unique route correlating inflammation and fibrosis by considering P85A as a key mediator of signals. The next sub-network module shows SRC as a junction for various signaling processes, which results in interaction between NF-kB and beta catenin to cause cell death. The powerful interaction between these important genes in response to transcriptionally altered lipid metabolism and impaired inflammatory response via SRC causes apoptosis of cells. The crosstalk between inflammation, lipid homeostasis and stress, and their serious effects downstream have been explained in the present analyses.

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

Detecting gene subnetworks under selection in biological pathways.

PubMed

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

2017-09-19

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

The Pathway Coexpression Network: Revealing pathway relationships

PubMed Central

Tanzi, Rudolph E.

2018-01-01

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of

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

Combining chemoinformatics with bioinformatics: in silico prediction of bacterial flavor-forming pathways by a chemical systems biology approach "reverse pathway engineering".

PubMed

Liu, Mengjin; Bienfait, Bruno; Sacher, Oliver; Gasteiger, Johann; Siezen, Roland J; Nauta, Arjen; Geurts, Jan M W

2014-01-01

The incompleteness of genome-scale metabolic models is a major bottleneck for systems biology approaches, which are based on large numbers of metabolites as identified and quantified by metabolomics. Many of the revealed secondary metabolites and/or their derivatives, such as flavor compounds, are non-essential in metabolism, and many of their synthesis pathways are unknown. In this study, we describe a novel approach, Reverse Pathway Engineering (RPE), which combines chemoinformatics and bioinformatics analyses, to predict the "missing links" between compounds of interest and their possible metabolic precursors by providing plausible chemical and/or enzymatic reactions. We demonstrate the added-value of the approach by using flavor-forming pathways in lactic acid bacteria (LAB) as an example. Established metabolic routes leading to the formation of flavor compounds from leucine were successfully replicated. Novel reactions involved in flavor formation, i.e. the conversion of alpha-hydroxy-isocaproate to 3-methylbutanoic acid and the synthesis of dimethyl sulfide, as well as the involved enzymes were successfully predicted. These new insights into the flavor-formation mechanisms in LAB can have a significant impact on improving the control of aroma formation in fermented food products. Since the input reaction databases and compounds are highly flexible, the RPE approach can be easily extended to a broad spectrum of applications, amongst others health/disease biomarker discovery as well as synthetic biology.

Angiosperms Are Unique among Land Plant Lineages in the Occurrence of Key Genes in the RNA-Directed DNA Methylation (RdDM) Pathway.

PubMed

Ma, Lu; Hatlen, Andrea; Kelly, Laura J; Becher, Hannes; Wang, Wencai; Kovarik, Ales; Leitch, Ilia J; Leitch, Andrew R

2015-09-02

The RNA-directed DNA methylation (RdDM) pathway can be divided into three phases: 1) small interfering RNA biogenesis, 2) de novo methylation, and 3) chromatin modification. To determine the degree of conservation of this pathway we searched for key genes among land plants. We used OrthoMCL and the OrthoMCL Viridiplantae database to analyze proteomes of species in bryophytes, lycophytes, monilophytes, gymnosperms, and angiosperms. We also analyzed small RNA size categories and, in two gymnosperms, cytosine methylation in ribosomal DNA. Six proteins were restricted to angiosperms, these being NRPD4/NRPE4, RDM1, DMS3 (defective in meristem silencing 3), SHH1 (SAWADEE homeodomain homolog 1), KTF1, and SUVR2, although we failed to find the latter three proteins in Fritillaria persica, a species with a giant genome. Small RNAs of 24 nt in length were abundant only in angiosperms. Phylogenetic analyses of Dicer-like (DCL) proteins showed that DCL2 was restricted to seed plants, although it was absent in Gnetum gnemon and Welwitschia mirabilis. The data suggest that phases (1) and (2) of the RdDM pathway, described for model angiosperms, evolved with angiosperms. The absence of some features of RdDM in F. persica may be associated with its large genome. Phase (3) is probably the most conserved part of the pathway across land plants. DCL2, involved in virus defense and interaction with the canonical RdDM pathway to facilitate methylation of CHH, is absent outside seed plants. Its absence in G. gnemon, and W. mirabilis coupled with distinctive patterns of CHH methylation, suggest a secondary loss of DCL2 following the divergence of Gnetales. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Keys and the crisis in taxonomy: extinction or reinvention?

PubMed

Walter, David Evans; Winterton, Shaun

2007-01-01

Dichotomous keys that follow a single pathway of character state choices to an end point have been the primary tools for the identification of unknown organisms for more than two centuries. However, a revolution in computer diagnostics is now under way that may result in the replacement of traditional keys by matrix-based computer interactive keys that have many paths to a correct identification and make extensive use of hypertext to link to images, glossaries, and other support material. Progress is also being made on replacing keys entirely by optical matching of specimens to digital databases and DNA sequences. These new tools may go some way toward alleviating the taxonomic impediment to biodiversity studies and other ecological and evolutionary research, especially with better coordination between those who produce keys and those who use them and by integrating interactive keys into larger biological Web sites.

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.

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

Microbial production of natural and non-natural flavonoids: Pathway engineering, directed evolution and systems/synthetic biology.

PubMed

Pandey, Ramesh Prasad; Parajuli, Prakash; Koffas, Mattheos A G; Sohng, Jae Kyung

2016-01-01

In this review, we address recent advances made in pathway engineering, directed evolution, and systems/synthetic biology approaches employed in the production and modification of flavonoids from microbial cells. The review is divided into two major parts. In the first, various metabolic engineering and system/synthetic biology approaches used for production of flavonoids and derivatives are discussed broadly. All the manipulations/engineering accomplished on the microorganisms since 2000 are described in detail along with the biosynthetic pathway enzymes, their sources, structures of the compounds, and yield of each product. In the second part of the review, post-modifications of flavonoids by four major reactions, namely glycosylations, methylations, hydroxylations and prenylations using recombinant strains are described. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways.

PubMed

Chen, Lei; Zhang, Yu-Hang; Lu, Guohui; Huang, Tao; Cai, Yu-Dong

2017-02-01

Cancer is a disease that involves abnormal cell growth and can invade or metastasize to other tissues. It is known that several factors are related to its initiation, proliferation, and invasiveness. Recently, it has been reported that long non-coding RNAs (lncRNAs) can participate in specific functional pathways and further regulate the biological function of cancer cells. Studies on lncRNAs are therefore helpful for uncovering the underlying mechanisms of cancer biological processes. We investigated cancer-related lncRNAs using gene ontology (GO) terms and KEGG pathway enrichment scores of neighboring genes that are co-expressed with the lncRNAs by extracting important GO terms and KEGG pathways that can help us identify cancer-related lncRNAs. The enrichment theory of GO terms and KEGG pathways was adopted to encode each lncRNA. Then, feature selection methods were employed to analyze these features and obtain the key GO terms and KEGG pathways. The analysis indicated that the extracted GO terms and KEGG pathways are closely related to several cancer associated processes, such as hormone associated pathways, energy associated pathways, and ribosome associated pathways. And they can accurately predict cancer-related lncRNAs. This study provided novel insight of how lncRNAs may affect tumorigenesis and which pathways may play important roles during it. These results could help understanding the biological mechanisms of lncRNAs and treating cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing autism spectrum disorders by key biochemical pathways.

PubMed

Subramanian, Megha; Timmerman, Christina K; Schwartz, Joshua L; Pham, Daniel L; Meffert, Mollie K

2015-01-01

The genetic and phenotypic heterogeneity of autism spectrum disorders (ASD) presents a substantial challenge for diagnosis, classification, research, and treatment. Investigations into the underlying molecular etiology of ASD have often yielded mixed and at times opposing findings. Defining the molecular and biochemical underpinnings of heterogeneity in ASD is crucial to our understanding of the pathophysiological development of the disorder, and has the potential to assist in diagnosis and the rational design of clinical trials. In this review, we propose that genetically diverse forms of ASD may be usefully parsed into entities resulting from converse patterns of growth regulation at the molecular level, which lead to the correlates of general synaptic and neural overgrowth or undergrowth. Abnormal brain growth during development is a characteristic feature that has been observed both in children with autism and in mouse models of autism. We review evidence from syndromic and non-syndromic ASD to suggest that entities currently classified as autism may fundamentally differ by underlying pro- or anti-growth abnormalities in key biochemical pathways, giving rise to either excessive or reduced synaptic connectivity in affected brain regions. We posit that this classification strategy has the potential not only to aid research efforts, but also to ultimately facilitate early diagnosis and direct appropriate therapeutic interventions.

Characterizing autism spectrum disorders by key biochemical pathways

PubMed Central

Subramanian, Megha; Timmerman, Christina K.; Schwartz, Joshua L.; Pham, Daniel L.; Meffert, Mollie K.

2015-01-01

The genetic and phenotypic heterogeneity of autism spectrum disorders (ASD) presents a substantial challenge for diagnosis, classification, research, and treatment. Investigations into the underlying molecular etiology of ASD have often yielded mixed and at times opposing findings. Defining the molecular and biochemical underpinnings of heterogeneity in ASD is crucial to our understanding of the pathophysiological development of the disorder, and has the potential to assist in diagnosis and the rational design of clinical trials. In this review, we propose that genetically diverse forms of ASD may be usefully parsed into entities resulting from converse patterns of growth regulation at the molecular level, which lead to the correlates of general synaptic and neural overgrowth or undergrowth. Abnormal brain growth during development is a characteristic feature that has been observed both in children with autism and in mouse models of autism. We review evidence from syndromic and non-syndromic ASD to suggest that entities currently classified as autism may fundamentally differ by underlying pro- or anti-growth abnormalities in key biochemical pathways, giving rise to either excessive or reduced synaptic connectivity in affected brain regions. We posit that this classification strategy has the potential not only to aid research efforts, but also to ultimately facilitate early diagnosis and direct appropriate therapeutic interventions. PMID:26483618

Pericytes of the neurovascular unit: Key functions and signaling pathways

PubMed Central

Sweeney, Melanie D.; Ayyadurai, Shiva; Zlokovic, Berislav V.

2017-01-01

Pericytes are vascular mural cells embedded in the basement membrane of blood microvessels. They extend their processes along capillaries, pre-capillary arterioles, and post-capillary venules. The central nervous system (CNS) pericytes are uniquely positioned within the neurovascular unit between endothelial cells, astrocytes, and neurons. They integrate, coordinate, and process signals from their neighboring cells to generate diverse functional responses that are critical for CNS functions in health and disease including regulation of the blood-brain barrier permeability, angiogenesis, clearance of toxic metabolites, capillary hemodynamic responses, neuroinflammation, and stem cell activity. Here, we examine the key signaling pathways between pericytes and their neighboring endothelial cells, astrocytes, and neurons that control neurovascular functions. We also review the role of pericytes in different CNS disorders including rare monogenic diseases and complex neurological disorders such as Alzheimer's disease and brain tumors. Finally, we discuss directions for future studies. PMID:27227366

Microbial regulation of terrestrial nitrous oxide formation: understanding the biological pathways for prediction of emission rates.

PubMed

Hu, Hang-Wei; Chen, Deli; He, Ji-Zheng

2015-09-01

The continuous increase of the greenhouse gas nitrous oxide (N2O) in the atmosphere due to increasing anthropogenic nitrogen input in agriculture has become a global concern. In recent years, identification of the microbial assemblages responsible for soil N2O production has substantially advanced with the development of molecular technologies and the discoveries of novel functional guilds and new types of metabolism. However, few practical tools are available to effectively reduce in situ soil N2O flux. Combating the negative impacts of increasing N2O fluxes poses considerable challenges and will be ineffective without successfully incorporating microbially regulated N2O processes into ecosystem modeling and mitigation strategies. Here, we synthesize the latest knowledge of (i) the key microbial pathways regulating N2O production and consumption processes in terrestrial ecosystems and the critical environmental factors influencing their occurrence, and (ii) the relative contributions of major biological pathways to soil N2O emissions by analyzing available natural isotopic signatures of N2O and by using stable isotope enrichment and inhibition techniques. We argue that it is urgently necessary to incorporate microbial traits into biogeochemical ecosystem modeling in order to increase the estimation reliability of N2O emissions. We further propose a molecular methodology oriented framework from gene to ecosystem scales for more robust prediction and mitigation of future N2O emissions. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identification of key nitrous oxide production pathways in aerobic partial nitrifying granules.

PubMed

Ishii, Satoshi; Song, Yanjun; Rathnayake, Lashitha; Tumendelger, Azzaya; Satoh, Hisashi; Toyoda, Sakae; Yoshida, Naohiro; Okabe, Satoshi

2014-10-01

The identification of the key nitrous oxide (N2O) production pathways is important to establish a strategy to mitigate N2O emission. In this study, we combined real-time gas-monitoring analysis, (15)N stable isotope analysis, denitrification functional gene transcriptome analysis and microscale N2O concentration measurements to identify the main N2O producers in a partial nitrification (PN) aerobic granule reactor, which was fed with ammonium and acetate. Our results suggest that heterotrophic denitrification was the main contributor to N2O production in our PN aerobic granule reactor. The heterotrophic denitrifiers were probably related to Rhodocyclales bacteria, although different types of bacteria were active in the initial and latter stages of the PN reaction cycles, most likely in response to the presence of acetate. Hydroxylamine oxidation and nitrifier denitrification occurred, but their contribution to N2O emission was relatively small (20-30%) compared with heterotrophic denitrification. Our approach can be useful to quantitatively examine the relative contributions of the three pathways (hydroxylamine oxidation, nitrifier denitrification and heterotrophic denitrification) to N2O emission in mixed microbial populations. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Exploring the key genes and pathways in enchondromas using a gene expression microarray.

PubMed

Shi, Zhongju; Zhou, Hengxing; Pan, Bin; Lu, Lu; Kang, Yi; Liu, Lu; Wei, Zhijian; Feng, Shiqing

2017-07-04

Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

Cell-free synthetic biology for environmental sensing and remediation.

PubMed

Karig, David K

2017-06-01

The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation. Copyright © 2017 The Author. Published by 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.

Biological pathways and genetic mechanisms involved in social functioning.

PubMed

Ordoñana, Juan R; Bartels, Meike; Boomsma, Dorret I; Cella, David; Mosing, Miriam; Oliveira, Joao R; Patrick, Donald L; Veenhoven, Ruut; Wagner, Gert G; Sprangers, Mirjam A G

2013-08-01

To describe the major findings in the literature regarding associations between biological and genetic factors and social functioning, paying special attention to: (1) heritability studies on social functioning and related concepts; (2) hypothesized biological pathways and genetic variants that could be involved in social functioning, and (3) the implications of these results for quality-of-life research. A search of Web of Science and PubMed databases was conducted using combinations of the following keywords: genetics, twins, heritability, social functioning, social adjustment, social interaction, and social dysfunction. Variability in the definitions and measures of social functioning was extensive. Moderate to high heritability was reported for social functioning and related concepts, including prosocial behavior, loneliness, and extraversion. Disorders characterized by impairments in social functioning also show substantial heritability. Genetic variants hypothesized to be involved in social functioning are related to the network of brain structures and processes that are known to affect social cognition and behavior. Better knowledge and understanding about the impact of genetic factors on social functioning is needed to help us to attain a more comprehensive view of health-related quality-of-life (HRQOL) and will ultimately enhance our ability to identify those patients who are vulnerable to poor social functioning.

Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language.

PubMed

Elmarakeby, Haitham; Arefiyan, Mostafa; Myers, Elijah; Li, Song; Grene, Ruth; Heath, Lenwood S

2017-12-01

The Beacon Editor is a cross-platform desktop application for the creation and modification of signal transduction pathways using the Systems Biology Graphical Notation Activity Flow (SBGN-AF) language. Prompted by biologists' requests for enhancements, the Beacon Editor includes numerous powerful features for the benefit of creation and presentation.

Regulation of Tissue Growth by the Mammalian Hippo Signaling Pathway

PubMed Central

Watt, Kevin I.; Harvey, Kieran F.; Gregorevic, Paul

2017-01-01

The integrative control of diverse biological processes such as proliferation, differentiation, apoptosis and metabolism is essential to maintain cellular and tissue homeostasis. Disruption of these underlie the development of many disease states including cancer and diabetes, as well as many of the complications that arise as a consequence of aging. These biological outputs are governed by many cellular signaling networks that function independently, and in concert, to convert changes in hormonal, mechanical and metabolic stimuli into alterations in gene expression. First identified in Drosophila melanogaster as a powerful mediator of cell division and apoptosis, the Hippo signaling pathway is a highly conserved regulator of mammalian organ size and functional capacity in both healthy and diseased tissues. Recent studies have implicated the pathway as an effector of diverse physiological cues demonstrating an essential role for the Hippo pathway as an integrative component of cellular homeostasis. In this review, we will: (a) outline the critical signaling elements that constitute the mammalian Hippo pathway, and how they function to regulate Hippo pathway-dependent gene expression and tissue growth, (b) discuss evidence that shows this pathway functions as an effector of diverse physiological stimuli and (c) highlight key questions in this developing field. PMID:29225579

Total solids content: a key parameter of metabolic pathways in dry anaerobic digestion

PubMed Central

2013-01-01

Background In solid-state anaerobic digestion (AD) bioprocesses, hydrolytic and acidogenic microbial metabolisms have not yet been clarified. Since these stages are particularly important for the establishment of the biological reaction, better knowledge could optimize the process performances by process parameters adjustment. Results This study demonstrated the effect of total solids (TS) content on microbial fermentation of wheat straw with six different TS contents ranging from wet to dry conditions (10 to 33% TS). Three groups of metabolic behaviors were distinguished based on wheat straw conversion rates with 2,200, 1,600, and 1,400 mmol.kgVS-1 of fermentative products under wet (10 and 14% TS), dry (19 to 28% TS), and highly dry (28 to 33% TS) conditions, respectively. Furthermore, both wet and dry fermentations showed acetic and butyric acid metabolisms, whereas a mainly butyric acid metabolism occurred in highly dry fermentation. Conclusion Substrate conversion was reduced with no changes of the metabolic pathways until a clear limit at 28% TS content, which corresponded to the threshold value of free water content of wheat straw. This study suggested that metabolic pathways present a limit of TS content for high-solid AD. PMID:24261971

Molecular Pathways: Hippo Signaling, a Critical Tumor Suppressor.

PubMed

Sebio, Ana; Lenz, Heinz-Josef

2015-11-15

The Salvador-Warts-Hippo pathway controls cell fate and tissue growth. The main function of the Hippo pathway is to prevent YAP and TAZ translocation to the nucleus where they induce the transcription of genes involved in cell proliferation, survival, and stem cell maintenance. Hippo signaling is, thus, a complex tumor suppressor, and its deregulation is a key feature in many cancers. Recent mounting evidence suggests that the overexpression of Hippo components can be useful prognostic biomarkers. Moreover, Hippo signaling appears to be intimately linked to some of the most important signaling pathways involved in cancer development and progression. A better understanding of the Hippo pathway is thus essential to untangle tumor biology and to develop novel anticancer therapies. Here, we comment on the progress made in understanding Hippo signaling and its connections, and also on how new drugs modulating this pathway, such as Verteporfin and C19, are highly promising cancer therapeutics. ©2015 American Association for Cancer Research.

Prediction of enzymatic pathways by integrative pathway mapping

PubMed Central

Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

2018-01-01

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

Ecdysone receptor agonism leading to lethal molting disruption in arthropods: Review and adverse outcome pathway development

EPA Science Inventory

Molting is a key biological process in growth, development, reproduction and survival in arthropods. Complex neuroendocrine pathways are involved in the regulation of molting and may potentially become targets of environmental endocrine disrupting compounds (EDCs). For example, s...

Alternative ground states enable pathway switching in biological electron transfer

DOE PAGES

Abriata, Luciano A.; Alvarez-Paggi, Damian; Ledesma, Gabirela N.; ...

2012-10-10

Electron transfer is the simplest chemical reaction and constitutes the basis of a large variety of biological processes, such as photosynthesis and cellular respiration. Nature has evolved specific proteins and cofactors for these functions. The mechanisms optimizing biological electron transfer have been matter of intense debate, such as the role of the protein milieu between donor and acceptor sites. Here we propose a mechanism regulating long-range electron transfer in proteins. Specifically, we report a spectroscopic, electrochemical, and theoretical study on WT and single-mutant CuA redox centers from Thermus thermophilus, which shows that thermal fluctuations may populate two alternative ground-state electronicmore » wave functions optimized for electron entry and exit, respectively, through two different and nearly perpendicular pathways. In conclusion, these findings suggest a unique role for alternative or “invisible” electronic ground states in directional electron transfer. Moreover, it is shown that this energy gap and, therefore, the equilibrium between ground states can be fine-tuned by minor perturbations, suggesting alternative ways through which protein–protein interactions and membrane potential may optimize and regulate electron–proton energy transduction.« less

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.

New era of biologic therapeutics in atopic dermatitis.

PubMed

Guttman-Yassky, Emma; Dhingra, Nikhil; Leung, Donald Y M

2013-04-01

Atopic dermatitis (AD) is a common inflammatory skin disease regulated by genetic and environmental factors. Both skin barrier defects and aberrant immune responses are believed to drive cutaneous inflammation in AD. Existing therapies rely largely on allergen avoidance, emollients and topical and systemic immune-suppressants, some with significant toxicity and transient efficacy; no specific targeted therapies are in clinical use today. As our specific understanding of the immune and molecular pathways that cause different subsets of AD increases, a variety of experimental agents, particularly biologic agents that target pathogenic molecules bring the promise of safe and effective therapeutics for long-term use. This paper discusses the molecular pathways characterizing AD, the contributions of barrier and immune abnormalities to its pathogenesis, and development of new treatments that target key molecules in these pathways. In this review, we will discuss a variety of biologic therapies that are in development or in clinical trials for AD, perhaps revolutionizing treatment of this disease. Biologic agents in moderate to severe AD offer promise for controlling a disease that currently lacks good and safe therapeutics posing a large unmet need. Unfortunately, existing treatments for AD aim to decrease cutaneous inflammation, but are not specific for the pathways driving this disease. An increasing understanding of the immune mechanisms underlying AD brings the promise of narrow targeted therapies as has occurred for psoriasis, another inflammatory skin disease, for which specific biologic agents have been demonstrated to both control the disease and prevent occurrence of new skin lesions. Although no biologic is yet approved for AD, these are exciting times for active therapeutic development in AD that might lead to revolutionary therapeutics for this disease.

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

Key apoptotic pathways for heat-induced programmed germ cell death in the testis.

PubMed

Hikim, Amiya P Sinha; Lue, Yanhe; Yamamoto, Cindy M; Vera, Yanira; Rodriguez, Susana; Yen, Pauline H; Soeng, Kevin; Wang, Christina; Swerdloff, Ronald S

2003-07-01

Short-term exposure (43 C for 15 min) of the rat testis to mild heat results within 6 h in stage- and cell-specific activation of germ cell apoptosis. Initiation of apoptosis was preceded by a redistribution of Bax from a cytoplasmic to paranuclear localization in heat-susceptible germ cells. Here we show that the relocation of Bax is accompanied by cytosolic translocation of cytochrome c and is associated with activation of the initiator caspase 9 and the executioner caspases 3, 6, and 7 and cleavage of poly(ADP) ribose polymerase. Furthermore, early in apoptosis, a significant amount of Bax also accumulates in endoplasmic reticulum, as assessed by Western blot analyses of fractionated testicular lysates. In additional studies using the FasL-defective gld mice, we have shown that heat-induced germ cell apoptosis is not blocked, thus providing evidence that the Fas signaling system may be dispensable for heat-induced germ cell apoptosis in the testis. Taken together, these results demonstrate that the mitochondria- and possibly also endoplasmic reticulum-dependent pathways are the key apoptotic pathways for heat-induced germ cell death in the testis.

Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities.

PubMed

DePaoli, Henrique C; Borland, Anne M; Tuskan, Gerald A; Cushman, John C; Yang, Xiaohan

2014-07-01

To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Regulatory mechanism of protein metabolic pathway during the differentiation process of chicken male germ cell.

PubMed

Li, Dong; Zuo, Qisheng; Lian, Chao; Zhang, Lei; Shi, Qingqing; Zhang, Zhentao; Wang, Yingjie; Ahmed, Mahmoud F; Tang, Beibei; Xiao, Tianrong; Zhang, Yani; Li, Bichun

2015-08-01

We explored the regulatory mechanism of protein metabolism during the differentiation process of chicken male germ cells and provide a basis for improving the induction system of embryonic stem cell differentiation to male germ cells in vitro. We sequenced the transcriptome of embryonic stem cells, primordial germ cells, and spermatogonial stem cells with RNA sequencing (RNA-Seq), bioinformatics analysis methods, and detection of the key genes by quantitative reverse transcription PCR (qRT-PCR). Finally, we found 16 amino acid metabolic pathways enriched in the biological metabolism during the differentiation process of embryonic stem cells to primordial germ cells and 15 amino acid metabolic pathways enriched in the differentiation stage of primordial germ cells to spermatogonial stem cells. We found three pathways, arginine-proline metabolic pathway, tyrosine metabolic pathway, and tryptophan metabolic pathway, significantly enriched in the whole differentiation process of embryonic stem cells to spermatogonial stem cells. Moreover, for these three pathways, we screened key genes such as NOS2, ADC, FAH, and IDO. qRT-PCR results showed that the expression trend of these genes were the same to RNA-Seq. Our findings showed that the three pathways and these key genes play an important role in the differentiation process of embryonic stem cells to male germ cells. These results provide basic information for improving the induction system of embryonic stem cell differentiation to male germ cells in vitro.

Tracking of Short Distance Transport Pathways in Biological Tissues by Ultra-Small Nanoparticles

NASA Astrophysics Data System (ADS)

Segmehl, Jana S.; Lauria, Alessandro; Keplinger, Tobias; Berg, John K.; Burgert, Ingo

2018-03-01

In this work, ultra-small europium-doped HfO2 nanoparticles were infiltrated into native wood and used as trackers for studying penetrability and diffusion pathways in the hierarchical wood structure. The high electron density, laser induced luminescence, and crystallinity of these particles allowed for a complementary detection of the particles in the cellular tissue. Confocal Raman microscopy and high-resolution synchrotron scanning wide-angle X-ray scattering (WAXS) measurements were used to detect the infiltrated particles in the native wood cell walls. This approach allows for simultaneously obtaining chemical information of the probed biological tissue and the spatial distribution of the integrated particles. The in-depth information about particle distribution in the complex wood structure can be used for revealing transport pathways in plant tissues, but also for gaining better understanding of modification treatments of plant scaffolds aiming at novel functionalized materials.

Metal-induced Dysregulation of the NF-kB Pathway in a Detroit Michigan's Children Cohort

EPA Science Inventory

Heavy metal exposure can have adverse effects on childhood development, and early life exposures have been shown to modify key biological pathways. We set out to evaluate the genome-wide effects of metals exposure in the Mechanistic Indicators of Childhood Asthma (MICA) study, wh...

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

PubMed Central

Marballi, Ketan K.; Gallitano, Amelia L.

2018-01-01

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

Genome-wide association study and biological pathway analysis of the Eimeria maxima response in broilers.

PubMed

Hamzić, Edin; Buitenhuis, Bart; Hérault, Frédéric; Hawken, Rachel; Abrahamsen, Mitchel S; Servin, Bertrand; Elsen, Jean-Michel; Pinard-van der Laan, Marie-Hélène; Bed'Hom, Bertrand

2015-11-25

Coccidiosis is the most common and costly disease in the poultry industry and is caused by protozoans of the Eimeria genus. The current control of coccidiosis, based on the use of anticoccidial drugs and vaccination, faces serious obstacles such as drug resistance and the high costs for the development of efficient vaccines, respectively. Therefore, the current control programs must be expanded with complementary approaches such as the use of genetics to improve the host response to Eimeria infections. Recently, we have performed a large-scale challenge study on Cobb500 broilers using E. maxima for which we investigated variability among animals in response to the challenge. As a follow-up to this challenge study, we performed a genome-wide association study (GWAS) to identify genomic regions underlying variability of the measured traits in the response to Eimeria maxima in broilers. Furthermore, we conducted a post-GWAS functional analysis to increase our biological understanding of the underlying response to Eimeria maxima challenge. In total, we identified 22 single nucleotide polymorphisms (SNPs) with q value <0.1 distributed across five chromosomes. The highly significant SNPs were associated with body weight gain (three SNPs on GGA5, one SNP on GGA1 and one SNP on GGA3), plasma coloration measured as optical density at wavelengths in the range 465-510 nm (10 SNPs and all on GGA10) and the percentage of β2-globulin in blood plasma (15 SNPs on GGA1 and one SNP on GGA2). Biological pathways related to metabolic processes, cell proliferation, and primary innate immune processes were among the most frequent significantly enriched biological pathways. Furthermore, the network-based analysis produced two networks of high confidence, with one centered on large tumor suppressor kinase 1 (LATS1) and 2 (LATS2) and the second involving the myosin heavy chain 6 (MYH6). We identified several strong candidate genes and genomic regions associated with traits measured in

Identification of Key Transcription Factors Associated with Lung Squamous Cell Carcinoma

PubMed Central

Zhang, Feng; Chen, Xia; Wei, Ke; Liu, Daoming; Xu, Xiaodong; Zhang, Xing; Shi, Hong

2017-01-01

Background Lung squamous cell carcinoma (lung SCC) is a common type of lung cancer, but its mechanism of pathogenesis is unclear. The aim of this study was to identify key transcription factors in lung SCC and elucidate its mechanism. Material/Methods Six published microarray datasets of lung SCC were downloaded from Gene Expression Omnibus (GEO) for integrated bioinformatics analysis. Significance analysis of microarrays was used to identify differentially expressed genes (DEGs) between lung SCC and normal controls. The biological functions and signaling pathways of DEGs were mapped in the Gene Otology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, respectively. A transcription factor gene regulatory network was used to obtain insights into the functions of DEGs. Results A total of 1,011 genes, including 539 upregulated genes and 462 downregulated genes, were filtered as DEGs between lung SCC and normal controls. DEGs were significantly enriched in cell cycle, DNA replication, p53 signaling pathway, pathways in cancer, adherens junction, and cell adhesion molecules signaling pathways. There were 57 transcription factors identified, which were used to construct a regulatory network. The network consisted of 736 interactions between 49 transcription factors and 486 DEGs. NFIC, BRCA1, and NFATC2 were the top 3 transcription factors that had the highest connectivity with DEGs and that regulated 83, 82, and 75 DEGs in the network, respectively. Conclusions NFIC, BRCA1, and NFATC2 might be the key transcription factors in the development of lung SCC by regulating the genes involved in cell cycle and DNA replication pathways. PMID:28081052

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens

PubMed Central

Zeng, Y.; Yin, T.; Brügemann, K.

2018-01-01

Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle. PMID:29608619

Pathways to Aging: The Mitochondrion at the Intersection of Biological and Psychosocial Sciences

PubMed Central

Picard, Martin

2011-01-01

Compelling evidence suggests that both biological and psychosocial factors impact the process of aging. However, our understanding of the dynamic interplay among biological and psychosocial factors across the life course is still fragmentary. For example, it needs to be established how the interaction of individual factors (e.g., genetic and epigenetic endowment and personality), behavioral factors (e.g., physical activity, diet, and stress management), and psychosocial experiences (e.g., social support, well-being, socioeconomic status, and marriage) in perinatal, childhood, and adulthood influence health across the aging continuum. This paper aims to outline potential intersection points serving as an interface between biological and psychosocial factors, with an emphasis on the mitochondrion. Mitochondria are cellular organelles which play a critical role in cellular senescence. Both chronic exposure to psychosocial stress and genetic-based mitochondrial dysfunction have strikingly similar biological consequences; both predispose individuals to adverse age-related health disorders and early mortality. Exploring the interactive nature of the factors resulting in pathways to normal healthy aging, as well as those leading to morbidity and early mortality, will continue to enhance our ability to translate research into effective practices that can be implemented throughout the life course to optimise the aging process. PMID:21961065

Pathways to aging: the mitochondrion at the intersection of biological and psychosocial sciences.

PubMed

Picard, Martin

2011-01-01

Compelling evidence suggests that both biological and psychosocial factors impact the process of aging. However, our understanding of the dynamic interplay among biological and psychosocial factors across the life course is still fragmentary. For example, it needs to be established how the interaction of individual factors (e.g., genetic and epigenetic endowment and personality), behavioral factors (e.g., physical activity, diet, and stress management), and psychosocial experiences (e.g., social support, well-being, socioeconomic status, and marriage) in perinatal, childhood, and adulthood influence health across the aging continuum. This paper aims to outline potential intersection points serving as an interface between biological and psychosocial factors, with an emphasis on the mitochondrion. Mitochondria are cellular organelles which play a critical role in cellular senescence. Both chronic exposure to psychosocial stress and genetic-based mitochondrial dysfunction have strikingly similar biological consequences; both predispose individuals to adverse age-related health disorders and early mortality. Exploring the interactive nature of the factors resulting in pathways to normal healthy aging, as well as those leading to morbidity and early mortality, will continue to enhance our ability to translate research into effective practices that can be implemented throughout the life course to optimise the aging process.

Toxicogenomics and cancer risk assessment: a framework for key event analysis and dose-response assessment for nongenotoxic carcinogens.

PubMed

Bercu, Joel P; Jolly, Robert A; Flagella, Kelly M; Baker, Thomas K; Romero, Pedro; Stevens, James L

2010-12-01

In order to determine a threshold for nongenotoxic carcinogens, the traditional risk assessment approach has been to identify a mode of action (MOA) with a nonlinear dose-response. The dose-response for one or more key event(s) linked to the MOA for carcinogenicity allows a point of departure (POD) to be selected from the most sensitive effect dose or no-effect dose. However, this can be challenging because multiple MOAs and key events may exist for carcinogenicity and oftentimes extensive research is required to elucidate the MOA. In the present study, a microarray analysis was conducted to determine if a POD could be identified following short-term oral rat exposure with two nongenotoxic rodent carcinogens, fenofibrate and methapyrilene, using a benchmark dose analysis of genes aggregated in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) biological processes, which likely encompass key event(s) for carcinogenicity. The gene expression response for fenofibrate given to rats for 2days was consistent with its MOA and known key events linked to PPARα activation. The temporal response from daily dosing with methapyrilene demonstrated biological complexity with waves of pathways/biological processes occurring over 1, 3, and 7days; nonetheless, the benchmark dose values were consistent over time. When comparing the dose-response of toxicogenomic data to tumorigenesis or precursor events, the toxicogenomics POD was slightly below any effect level. Our results suggest that toxicogenomic analysis using short-term studies can be used to identify a threshold for nongenotoxic carcinogens based on evaluation of potential key event(s) which then can be used within a risk assessment framework. Copyright © 2010 Elsevier Inc. All rights reserved.

Computational genomic identification and functional reconstitution of plant natural product biosynthetic pathways

PubMed Central

2016-01-01

Covering: 2003 to 2016 The last decade has seen the first major discoveries regarding the genomic basis of plant natural product biosynthetic pathways. Four key computationally driven strategies have been developed to identify such pathways, which make use of physical clustering, co-expression, evolutionary co-occurrence and epigenomic co-regulation of the genes involved in producing a plant natural product. Here, we discuss how these approaches can be used for the discovery of plant biosynthetic pathways encoded by both chromosomally clustered and non-clustered genes. Additionally, we will discuss opportunities to prioritize plant gene clusters for experimental characterization, and end with a forward-looking perspective on how synthetic biology technologies will allow effective functional reconstitution of candidate pathways using a variety of genetic systems. PMID:27321668

PATHWAYS - ELECTRON TUNNELING PATHWAYS IN PROTEINS

NASA Technical Reports Server (NTRS)

Beratan, D. N.

1994-01-01

The key to understanding the mechanisms of many important biological processes such as photosynthesis and respiration is a better understanding of the electron transfer processes which take place between metal atoms (and other groups) fixed within large protein molecules. Research is currently focused on the rate of electron transfer and the factors that influence it, such as protein composition and the distance between metal atoms. Current models explain the swift transfer of electrons over considerable distances by postulating bridge-mediated tunneling, or physical tunneling pathways, made up of interacting bonds in the medium around and between donor and acceptor sites. The program PATHWAYS is designed to predict the route along which electrons travel in the transfer processes. The basic strategy of PATHWAYS is to begin by recording each possible path element on a connectivity list, including in each entry which two atoms are connected and what contribution the connection would make to the overall rate if it were included in a pathway. The list begins with the bonded molecular structure (including the backbone sequence and side chain connectivity), and then adds probable hydrogen bond links and through-space contacts. Once this list is completed, the program runs a tree search from the donor to the acceptor site to find the dominant pathways. The speed and efficiency of the computer search offers an improvement over manual techniques. PATHWAYS is written in FORTRAN 77 for execution on DEC VAX series computers running VMS. The program inputs data from four data sets and one structure file. The software was written to input BIOGRAF (old format) structure files based on x-ray crystal structures and outputs ASCII files listing the best pathways and BIOGRAF vector files containing the paths. Relatively minor changes could be made in the input format statements for compatibility with other graphics software. The executable and source code are included with the

[Progress in synthetic biology of pinocembrin].

PubMed

Guo, Lei; Kong, Jianqiang

2015-04-01

Pinocembrin, belonging to flavanons, was isolated from various plants. Pinocembrin has a variety of pharmacological activities, such as neuroprotective effect, antimicrobial activity, and antioxidant efficacy. Pinocembrin was approved as class I drugs to its phase II clinical trial by CFDA in 2009, mainly used for the treatment of ischemic stroke. As a promising compound, the manufacturing technologies of pinocembrin, including chemical synthesis, extraction from plant and synthetic biology, have attracted many attentions. Compared with the first two technologies, synthetic biology has many advantages, such as environment-friendly and low-cost. Construction of biosynthetic pathway in microorganism offers promising results for large scale pinocembrin production by fermentation after taking lots of effective strategies. This article reviews some of recent strategies in microorganisms to improve the yield, with focus on the selection of appropriate the key enzyme sources, the supply of precursors and cofactors by microorganisms, the choice of substance and the level of the key enzyme expression.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways.

PubMed

Wang, Q; Shi, C-J; Lv, S-H

2017-03-30

Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC) based on the functional dependency among pathways. Protein-protein interaction (PPI) information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA) method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN), where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

Emergent biological properties of arrestin pathway-selective biased agonism.

PubMed

Appleton, Kathryn M; Luttrell, Louis M

2013-06-01

Our growing appreciation of the pluridimensionality of G protein-coupled receptor (GPCR) signaling, combined with the phenomenon of orthosteric ligand "bias", has created the possibility of drugs that selectively modulate different aspects of GPCR function for therapeutic benefit. When viewed from the short-term perspective, e.g. changes in receptor conformation, effector coupling or second messenger generation, biased ligands appear to activate a subset of the response profile produced by a conventional agonist. Yet when examined in vivo, the limited data available suggest that biased ligand effects can diverge from their conventional counterparts in ways that cannot be predicted from their in vitro efficacy profile. What is currently missing, at least with respect to G protein and arrestin pathway-selective ligands, is a rational framework for relating the in vitro efficacy of a "biased" agonist to its in vivo actions that will enable drug screening programs to identify ligands with the desired biological effects.

Plant synthetic biology for molecular engineering of signalling and development.

PubMed

Nemhauser, Jennifer L; Torii, Keiko U

2016-03-02

Molecular genetic studies of model plants in the past few decades have identified many key genes and pathways controlling development, metabolism and environmental responses. Recent technological and informatics advances have led to unprecedented volumes of data that may uncover underlying principles of plants as biological systems. The newly emerged discipline of synthetic biology and related molecular engineering approaches is built on this strong foundation. Today, plant regulatory pathways can be reconstituted in heterologous organisms to identify and manipulate parameters influencing signalling outputs. Moreover, regulatory circuits that include receptors, ligands, signal transduction components, epigenetic machinery and molecular motors can be engineered and introduced into plants to create novel traits in a predictive manner. Here, we provide a brief history of plant synthetic biology and significant recent examples of this approach, focusing on how knowledge generated by the reference plant Arabidopsis thaliana has contributed to the rapid rise of this new discipline, and discuss potential future directions.

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

A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

PubMed

Chang, Tzu-Hao; Wu, Shih-Lin; Wang, Wei-Jen; Horng, Jorng-Tzong; Chang, Cheng-Wei

2014-01-01

Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.

Dissection of Biological Property of Chinese Acupuncture Point Zusanli Based on Long-Term Treatment via Modulating Multiple Metabolic Pathways.

PubMed

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

2013-01-01

Acupuncture has a history of over 3000 years and is a traditional Chinese medical therapy that uses hair-thin metal needles to puncture the skin at specific points on the body to promote wellbeing, while its molecular mechanism and ideal biological pathways are still not clear. High-throughput metabolomics is the global assessment of endogenous metabolites within a biologic system and can potentially provide a more accurate snap shot of the actual physiological state. We hypothesize that acupuncture-treated human would produce unique characterization of metabolic phenotypes. In this study, UPLC/ESI-HDMS coupled with pattern recognition methods and system analysis were carried out to investigate the mechanism and metabolite biomarkers for acupuncture treatment at "Zusanli" acupoint (ST-36) as a case study. The top 5 canonical pathways including alpha-linolenic acid metabolism, d-glutamine and d-glutamate metabolism, citrate cycle, alanine, aspartate, and glutamate metabolism, and vitamin B6 metabolism pathways were acutely perturbed, and 53 differential metabolites were identified by chemical profiling and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Urine metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture.

Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.

PubMed

Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E N; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

2016-01-01

Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map. © 2015 The International Union of Biochemistry and Molecular Biology.

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways

PubMed Central

Han, Junwei; Li, Chunquan; Yang, Haixiu; Xu, Yanjun; Zhang, Chunlong; Ma, Jiquan; Shi, Xinrui; Liu, Wei; Shang, Desi; Yao, Qianlan; Zhang, Yunpeng; Su, Fei; Feng, Li; Li, Xia

2015-01-01

Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI). PMID:25551156

Introductory Biology Students' Use of Enhanced Answer Keys and Reflection Questions to Engage in Metacognition and Enhance Understanding.

PubMed

Sabel, Jaime L; Dauer, Joseph T; Forbes, Cory T

2017-01-01

Providing feedback to students as they learn to integrate individual concepts into complex systems is an important way to help them to develop robust understanding, but it is challenging in large, undergraduate classes for instructors to provide feedback that is frequent and directed enough to help individual students. Various scaffolds can be used to help students engage in self-regulated learning and generate internal feedback to improve their learning. This study examined the use of enhanced answer keys with added reflection questions and instruction as scaffolds for engaging undergraduate students in self-regulated learning within an introductory biology course. Study findings show that both the enhanced answer keys and reflection questions helped students to engage in metacognition and develop greater understanding of biological concepts. Further, students who received additional instruction on the use of the scaffolds changed how they used them and, by the end of the semester, were using the scaffolds in significantly different ways and showed significantly higher learning gains than students who did not receive the instruction. These findings provide evidence for the benefit of designing scaffolds within biology courses that will support students in engaging in metacognition and enhancing their understanding of biological concepts. © 2017 J. L. Sabel et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Introductory Biology Students’ Use of Enhanced Answer Keys and Reflection Questions to Engage in Metacognition and Enhance Understanding

PubMed Central

Sabel, Jaime L.; Dauer, Joseph T.; Forbes, Cory T.

2017-01-01

Providing feedback to students as they learn to integrate individual concepts into complex systems is an important way to help them to develop robust understanding, but it is challenging in large, undergraduate classes for instructors to provide feedback that is frequent and directed enough to help individual students. Various scaffolds can be used to help students engage in self-regulated learning and generate internal feedback to improve their learning. This study examined the use of enhanced answer keys with added reflection questions and instruction as scaffolds for engaging undergraduate students in self-regulated learning within an introductory biology course. Study findings show that both the enhanced answer keys and reflection questions helped students to engage in metacognition and develop greater understanding of biological concepts. Further, students who received additional instruction on the use of the scaffolds changed how they used them and, by the end of the semester, were using the scaffolds in significantly different ways and showed significantly higher learning gains than students who did not receive the instruction. These findings provide evidence for the benefit of designing scaffolds within biology courses that will support students in engaging in metacognition and enhancing their understanding of biological concepts. PMID:28645893

Iso-seco-tanapartholides: Isolation, Synthesis and Biological Evaluation

PubMed Central

Makiyi, Edward F; Frade, Raquel F M; Lebl, Tomas; Jaffray, Ellis G; Cobb, Susan E; Harvey, Alan L; Slawin, Alexandra M Z; Hay, Ronald T; Westwood, Nicholas J

2009-01-01

The isolation, identification and total synthesis of two plant-derived inhibitors of the NF-κB signaling pathway from the iso-seco-tanapartholide family of natural products is described. A key step in the efficient reaction sequence is a late-stage oxidative cleavage reaction that was carried out in the absence of protecting groups to give the natural products directly. A detailed comparison of the synthetic material with samples of the natural products proved informative. Biological studies on synthetic material confirmed that these compounds act late in the NF-κB signaling pathway. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2009) PMID:23606807

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

PubMed Central

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

2010-01-01

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

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Can Erythrocytes Transmit Oxidative Stress Beyond the Lungs? An Adverse Outcome Pathway for the Cardiovascular Effects of Air Pollution.

EPA Science Inventory

Adverse outcome pathways (AOPs) are systems biology roadmaps with potential utility in xenobiotic exposure risk assessment. AOPs connect molecular initiating events (MIEs) to population-level adverse outcomes (AOs) via cellular, organ, and organism key events (KE) and KE relatio...

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Application of Adverse Outcome Pathways to U.S. EPA’s Endocrine Disruptor Screening Program

PubMed Central

Noyes, Pamela D.; Casey, Warren M.; Dix, David J.

2017-01-01

Background: The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) screens and tests environmental chemicals for potential effects in estrogen, androgen, and thyroid hormone pathways, and it is one of the only regulatory programs designed around chemical mode of action. Objectives: This review describes the EDSP’s use of adverse outcome pathway (AOP) and toxicity pathway frameworks to organize and integrate diverse biological data for evaluating the endocrine activity of chemicals. Using these frameworks helps to establish biologically plausible links between endocrine mechanisms and apical responses when those end points are not measured in the same assay. Results: Pathway frameworks can facilitate a weight of evidence determination of a chemical’s potential endocrine activity, identify data gaps, aid study design, direct assay development, and guide testing strategies. Pathway frameworks also can be used to evaluate the performance of computational approaches as alternatives for low-throughput and animal-based assays and predict downstream key events. In cases where computational methods can be validated based on performance, they may be considered as alternatives to specific assays or end points. Conclusions: A variety of biological systems affect apical end points used in regulatory risk assessments, and without mechanistic data, an endocrine mode of action cannot be determined. Because the EDSP was designed to consider mode of action, toxicity pathway and AOP concepts are a natural fit. Pathway frameworks have diverse applications to endocrine screening and testing. An estrogen pathway example is presented, and similar approaches are being used to evaluate alternative methods and develop predictive models for androgen and thyroid pathways. https://doi.org/10.1289/EHP1304 PMID:28934726

IntegromeDB: an integrated system and biological search engine

PubMed Central

2012-01-01

Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback. PMID:22260095

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

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

PubMed Central

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

2016-01-01

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

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.

Key genes and pathways in measles and their interaction with environmental chemicals

PubMed Central

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-01-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles. PMID:29805511

Key genes and pathways in measles and their interaction with environmental chemicals.

PubMed

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-06-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles.

Refining Pathways: A Model Comparison Approach

PubMed Central

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

2016-01-01

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

An “ADME Module” in the Adverse Outcome Pathway ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework has generated intense interest for its utility to organize knowledge on the toxicity mechanisms, starting from a molecular initiating event (MIE) to an adverse outcome across various levels of biological organization. While the AOP framework is designed to be chemical agnostic, it is widely recognized that considering chemicals’ absorption, distribution, metabolism, and excretion (ADME) behaviors is critical in applying the AOP framework in chemical-specific risk assessment. Currently, information being generated as part of the Organisation for Economic Co-operation and Development (OECD) AOP Development Programme is being consolidated into an AOP Knowledgebase (http://aopwiki.org). To enhance the use of this Knowledgebase in risk assessment, an ADME Module has been developed to contain the ADME information needed to connect MIEs and other key events in an AOP for specific chemicals. The conceptual structure of this module characterizes the potential of a chemical to reach the target MIE based on either its structure-based features or relative rates of ADME. The key features of this module include (1) a framework for connecting biology-based AOP to biochemical-based ADME and chemical/human activity-based exposure pathways; (2) links to qualitative tools (e.g., structure-based cheminformatic model) that screen for chemicals that could potentially reach the target MIE; (3) links to quantitative tools (e.g., dose-r

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-09-01

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

Acetogenesis and the Wood-Ljungdahl Pathway of CO2 Fixation

PubMed Central

Ragsdale, Stephen W.; Pierce, Elizabeth

2008-01-01

I. Summary Conceptually, the simplest way to synthesize an organic molecule is to construct it one carbon at a time. The Wood-Ljungdahl pathway of CO2 fixation involves this type of stepwise process. The biochemical events that underlie the condensation of two one-carbon units to form the two-carbon compound, acetate, have intrigued chemists, biochemists, and microbiologists for many decades. We begin this review with a description of the biology of acetogenesis. Then, we provide a short history of the important discoveries that have led to the identification of the key components and steps of this usual mechanism of CO and CO2 fixation. In this historical perspective, we have included reflections that hopefully will sketch the landscape of the controversies, hypotheses, and opinions that led to the key experiments and discoveries. We then describe the properties of the genes and enzymes involved in the pathway and conclude with a section describing some major questions that remain unanswered. PMID:18801467

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.

Systems biology for organotypic cell cultures.

PubMed

Grego, Sonia; Dougherty, Edward R; Alexander, Francis J; Auerbach, Scott S; Berridge, Brian R; Bittner, Michael L; Casey, Warren; Cooley, Philip C; Dash, Ajit; Ferguson, Stephen S; Fennell, Timothy R; Hawkins, Brian T; Hickey, Anthony J; Kleensang, Andre; Liebman, Michael N J; Martin, Florian; Maull, Elizabeth A; Paragas, Jason; Qiao, Guilin Gary; Ramaiahgari, Sreenivasa; Sumner, Susan J; Yoon, Miyoung

2017-01-01

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

Framing Ethnic Variations in Alcohol Outcomes from Biological Pathways to Neighborhood Context

PubMed Central

Chartier, Karen G.; Scott, Denise M.; Wall, Tamara L.; Covault, Jonathan; Karriker-Jaffe, Katherine J.; Mills, Britain A.; Luczak, Susan E.; Caetano, Raul; Arroyo, Judith A.

2013-01-01

Health disparities research seeks to eliminate disproportionate negative health outcomes experienced in some racial/ethnic minority groups. This brief review presents findings on factors associated with drinking and alcohol-related problems in racial/ethnic groups. Those discussed are: 1) biological pathways to alcohol problems, 2) gene by stress interactions, 3) neighborhood disadvantage, stress, and access to alcohol, and 4) drinking cultures and contexts. These factors and their interrelationships are complex, requiring a multi-level perspective. The use of interdisciplinary teams and an epigenetic focus are suggested to move the research forward. The application of multi-level research to policy, prevention, and intervention programs may help prioritize combinations of the most promising intervention targets. PMID:24483624

Biology of Healthy Aging and Longevity.

PubMed

Carmona, Juan José; Michan, Shaday

2016-01-01

As human life expectancy is prolonged, age-related diseases are thriving. Aging is a complex multifactorial process of molecular and cellular decline that affects tissue function over time, rendering organisms frail and susceptible to disease and death. Over the last decades, a growing body of scientific literature across different biological models, ranging from yeast, worms, flies, and mice to primates, humans and other long-lived animals, has contributed greatly towards identifying conserved biological mechanisms that ward off structural and functional deterioration within living systems. Collectively, these data offer powerful insights into healthy aging and longevity. For example, molecular integrity of the genome, telomere length, epigenetic landscape stability, and protein homeostasis are all features linked to "youthful" states. These molecular hallmarks underlie cellular functions associated with aging like mitochondrial fitness, nutrient sensing, efficient intercellular communication, stem cell renewal, and regenerative capacity in tissues. At present, calorie restriction remains the most robust strategy for extending health and lifespan in most biological models tested. Thus, pathways that mediate the beneficial effects of calorie restriction by integrating metabolic signals to aging processes have received major attention, such as insulin/insulin growth factor-1, sirtuins, mammalian target of rapamycin, and 5' adenosine monophosphate-activated protein kinase. Consequently, small-molecule targets of these pathways have emerged in the impetuous search for calorie restriction mimetics, of which resveratrol, metformin, and rapamycin are the most extensively studied. A comprehensive understanding of the molecular and cellular mechanisms that underlie age-related deterioration and repair, and how these pathways interconnect, remains a major challenge for uncovering interventions to slow human aging while extending molecular and physiological youthfulness

Cutaneous wound healing: recruiting developmental pathways for regeneration.

PubMed

Bielefeld, Kirsten A; Amini-Nik, Saeid; Alman, Benjamin A

2013-06-01

Following a skin injury, the damaged tissue is repaired through the coordinated biological actions that constitute the cutaneous healing response. In mammals, repaired skin is not identical to intact uninjured skin, however, and this disparity may be caused by differences in the mechanisms that regulate postnatal cutaneous wound repair compared to embryonic skin development. Improving our understanding of the molecular pathways that are involved in these processes is essential to generate new therapies for wound healing complications. Here we focus on the roles of several key developmental signaling pathways (Wnt/β-catenin, TGF-β, Hedgehog, Notch) in mammalian cutaneous wound repair, and compare this to their function in skin development. We discuss the varying responses to cutaneous injury across the taxa, ranging from complete regeneration to scar tissue formation. Finally, we outline how research into the role of developmental pathways during skin repair has contributed to current wound therapies, and holds potential for the development of more effective treatments.

An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

PubMed

Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

2008-10-01

This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

Cellular Metabolic and Autophagic Pathways: Traffic Control by Redox Signaling

PubMed Central

Dodson, Matthew; Darley-Usmar, Victor; Zhang, Jianhua

2013-01-01

It has been established that the key metabolic pathways of glycolysis and oxidative phosphorylation are intimately related to redox biology through control of cell signaling. Under physiological conditions glucose metabolism is linked to control of the NADH/NAD redox couple, as well as providing the major reductant, NADPH, for thiol-dependent antioxidant defenses. Retrograde signaling from the mitochondrion to the nucleus or cytosol controls cell growth and differentiation. Under pathological conditions mitochondria are targets for reactive oxygen and nitrogen species and are critical in controlling apoptotic cell death. At the interface of these metabolic pathways, the autophagy-lysosomal pathway functions to maintain mitochondrial quality, and generally serves an important cytoprotective function. In this review we will discuss the autophagic response to reactive oxygen and nitrogen species that are generated from perturbations of cellular glucose metabolism and bioenergetic function. PMID:23702245

Free Energy Landscape - Settlements of Key Residues.

NASA Astrophysics Data System (ADS)

Aroutiounian, Svetlana

2007-03-01

FEL perspective in studies of protein folding transitions reflects notion that since there are ˜10^N conformations to scan in search of lowest free energy state, random search is beyond biological timescale. Protein folding must follow certain fel pathways and folding kinetics of evolutionary selected proteins dominates kinetic traps. Good model for functional robustness of natural proteins - coarse-grained model protein is not very accurate but affords bringing simulations closer to biological realm; Go-like potential secures the fel funnel shape; biochemical contacts signify the funnel bottleneck. Boltzmann-weighted ensemble of protein conformations and histogram method are used to obtain from MC sampling of protein conformational space the approximate probability distribution. The fel is F(rmsd) = -1/βLn[Hist(rmsd)], β=kBT and rmsd is root-mean-square-deviation from native conformation. The sperm whale myoglobin has rich dynamic behavior, is small and large - on computational scale, has a symmetry in architecture and unusual sextet of residue pairs. Main idea: there is a mathematical relation between protein fel and a key residues set providing stability to folding transition. Is the set evolutionary conserved also for functional reasons? Hypothesis: primary sequence determines the key residues positions conserved as stabilizers and the fel is the battlefield for the folding stability. Preliminary results: primary sequence - not the architecture, is the rule settler, indeed.

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

Branches of NF-κb signaling pathway regulate hepatocyte proliferation in rat liver regeneration.

PubMed

Chang, C F; Zhao, W M; Mei, J X; Zhou, Y; Pan, C Y; Xu, T T; Xu, C S

2015-07-13

Previous studies have demonstrated that the nuclear factor κB (NF-κB) pathway is involved in promoting cell proliferation. To further explore the regulatory branches and their sequence in the NF-κB pathway in the promotion of hepatocyte proliferation at the transcriptional level during rat liver regeneration, Rat Genome 230 2.0 array was used to detect the expression changes of the isolated hepatocytes. We found that many genes involved in the NF-κB pathway (including 73 known genes and 19 homologous genes) and cell proliferation (including 484 genes and 104 homologous genes) were associated with liver regeneration. Expression profile function (Ep) was used to analyze the biological processes. It was revealed that the NF-κB pathway promoted hepatocyte proliferation through three branches. Several methods of integrated statistics were applied to extract and screen key genes in liver regeneration, and it indicated that eight genes may play a vital role in rat liver regeneration. To confirm the above predicted results, Ccnd1, Jun and Myc were analyzed using qRT-PCR, and the results were generally consistent with that of microarray data. It is concluded that 3 branches and 8 key genes involved in the NF-κB pathway regulate hepatocyte proliferation during rat liver regeneration.

No longer "if," but "when": the coming abbreviated approval pathway for follow-on biologics.

PubMed

Kelly, Jeremiah J; David, Michael

2009-01-01

Abbreviated approval of follow-on biologics involves answering complex scientific, legal, and policy questions. The Food and Drug Administration (FDA or the Agency) asserts that it lacks the statutory authority to approve follow-on versions of biologics licensed under Section 351 of the Public Health Service Act (PHSA). Despite persuasive arguments to the contrary the one hundred and tenth Congress entertained four legislative proposals to give FDA this authority, each markedly different. It is no longer a question of "if," but "when" FDA will receive authority to review and license abbreviated applications for follow-on biologics. Any legislation in the one hundred and eleventh Congress must determine: (1) if FDA should be granted authority to develop an abbreviated pathway through rulemaking or guidance; (2) if human clinical trials should be mandatory or discretionary; (3) the feasibility of interchangeability determinations in light of patient safety concerns; (4) the duration of marketing exclusivity for associated products; (5) which products are eligible for follow-on approval; and (6) the degree to which uniformity is achievable between the FD&C Act and the PHSA. This paper recommends the one hundred and eleventh Congress strike a balance between patient safety, incentives for product innovation, price competition, and the need for a flexible, transparent process that capitalizes on FDA's growing expertise with follow-on biologics approvals under Section 505(b)(2) of the FD&C Act.

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

The SUMO Pathway in Mitosis.

PubMed

Mukhopadhyay, Debaditya; Dasso, Mary

2017-01-01

Mitosis is the stage of the cell cycle during which replicated chromosomes must be precisely divided to allow the formation of two daughter cells possessing equal genetic material. Much of the careful spatial and temporal organization of mitosis is maintained through post-translational modifications, such as phosphorylation and ubiquitination, of key cellular proteins. Here, we will review evidence that sumoylation, conjugation to the SUMO family of small ubiquitin-like modifiers, also serves essential regulatory roles during mitosis. We will discuss the basic biology of sumoylation, how the SUMO pathway has been implicated in particular mitotic functions, including chromosome condensation, centromere/kinetochore organization and cytokinesis, and what cellular proteins may be the targets underlying these phenomena.

A mouse model of alcoholic liver fibrosis-associated acute kidney injury identifies key molecular pathways

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

Furuya, Shinji; Chappell, Grace A.; Iwata, Yasuhir

Clinical data strongly indicate that acute kidney injury (AKI) is a critical complication in alcoholic hepatitis, an acute-on-chronic form of liver failure in patients with advanced alcoholic fibrosis. Development of targeted therapies for AKI in this setting is hampered by the lack of an animal model. To enable research into molecular drivers and novel therapies for fibrosis- and alcohol-associated AKI, we aimed to combine carbon tetrachloride (CCl{sub 4})-induced fibrosis with chronic intra-gastric alcohol feeding. Male C57BL/6J mice were administered a low dose of CCl{sub 4} (0.2 ml/kg 2 × week/6 weeks) followed by alcohol intragastrically (up to 25 g/kg/day formore » 3 weeks) and with continued CCl{sub 4}. We observed that combined treatment with CCl{sub 4} and alcohol resulted in severe liver injury, more pronounced than using each treatment alone. Importantly, severe kidney injury was evident only in the combined treatment group. This mouse model reproduced distinct pathological features consistent with AKI in human alcoholic hepatitis. Transcriptomic analysis of kidneys revealed profound effects in the combined treatment group, with enrichment for damage-associated pathways, such as apoptosis, inflammation, immune-response and hypoxia. Interestingly, Havcr1 and Lcn2, biomarkers of AKI, were markedly up-regulated. Overall, this study established a novel mouse model of fibrosis- and alcohol-associated AKI and identified key mechanistic pathways. - Highlights: • Acute kidney injury (AKI) is a critical complication in alcoholic hepatitis • We developed a novel mouse model of fibrosis- and alcohol-associated AKI • This model reproduces key molecular and pathological features of human AKI • This animal model can help identify new targeted therapies for alcoholic hepatitis.« less

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

PubMed Central

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

PubMed

Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-11-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

Framing ethnic variations in alcohol outcomes from biological pathways to neighborhood context.

PubMed

Chartier, Karen G; Scott, Denise M; Wall, Tamara L; Covault, Jonathan; Karriker-Jaffe, Katherine J; Mills, Britain A; Luczak, Susan E; Caetano, Raul; Arroyo, Judith A

2014-03-01

Health disparities research seeks to eliminate disproportionate negative health outcomes experienced in some racial/ethnic minority groups. This brief review presents findings on factors associated with drinking and alcohol-related problems in racial/ethnic groups. Those discussed are as follows: (i) biological pathways to alcohol problems, (ii) gene × stress interactions, (iii) neighborhood disadvantage, stress, and access to alcohol, and (iv) drinking cultures and contexts. These factors and their interrelationships are complex, requiring a multilevel perspective. The use of interdisciplinary teams and an epigenetic focus are suggested to move the research forward. The application of multilevel research to policy, prevention, and intervention programs may help prioritize combinations of the most promising intervention targets. Copyright © 2014 by the Research Society on Alcoholism.

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

PubMed

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

2012-09-07

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

Tools for visually exploring biological networks.

PubMed

Suderman, Matthew; Hallett, Michael

2007-10-15

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.

A shortcut to wide-ranging biological actions of dietary polyphenols: modulation of the nitrate-nitrite-nitric oxide pathway in the gut.

PubMed

Rocha, Bárbara S; Nunes, Carla; Pereira, Cassilda; Barbosa, Rui M; Laranjinha, João

2014-08-01

Dietary polyphenols are complex, natural compounds with recognized health benefits. Initially attractive to the biomedical area due to their in vitro antioxidant properties, the biological implications of polyphenols are now known to be far from their acute ability to scavenge free radicals but rather to modulate redox signaling pathways. Actually, it is now recognized that dietary polyphenols are extensively metabolized in vivo and that the chemical, biophysical and biological properties of their metabolites are, in most cases, quite different from the ones of the parent molecules. Hence, the study of the metabolic, absorptive and signaling pathways of both phenolics and derivatives has become a major issue. In this paper we propose a short-cut for the systemic effects of polyphenols in connection with nitric oxide (˙NO) biology. This free radical is a ubiquitous signaling molecule with pivotal functions in vivo. It is produced through an enzymatic pathway and also through the reduction of dietary nitrate and nitrite in the human stomach. At acidic gastric pH, dietary polyphenols, in the form they are conveyed in foods and at high concentration, not only promote nitrite reduction to ˙NO but also embark in a complex network of chemical reactions to produce higher nitrogen oxides with signaling functions, namely by inducing post-translational modifications. Modified endogenous molecules, such as nitrated proteins and lipids, acquire important physiological functions. Thus, local and systemic effects of ˙NO such as modulation of vascular tone, mucus production in the gut and protection against ischemia-reperfusion injury are, in this sense, triggered by dietary polyphenols. Evidence to support the signaling and biological effects of polyphenols by modulation of the nitrate-nitrite-NO pathway will be herein provided and discussed. General actions of polyphenols encompassing absorption and metabolism in the intestine/liver are short-cut via the production of

Host Glycan Sugar-Specific Pathways in Streptococcus pneumonia: Galactose as a Key Sugar in Colonisation and Infection

PubMed Central

Paixão, Laura; Oliveira, Joana; Veríssimo, André; Vinga, Susana; Lourenço, Eva C.; Ventura, M. Rita; Kjos, Morten; Veening, Jan-Willem; Fernandes, Vitor E.; Andrew, Peter W.; Yesilkaya, Hasan; Neves, Ana Rute

2015-01-01

The human pathogen Streptococcus pneumoniae is a strictly fermentative organism that relies on glycolytic metabolism to obtain energy. In the human nasopharynx S. pneumoniae encounters glycoconjugates composed of a variety of monosaccharides, which can potentially be used as nutrients once depolymerized by glycosidases. Therefore, it is reasonable to hypothesise that the pneumococcus would rely on these glycan-derived sugars to grow. Here, we identified the sugar-specific catabolic pathways used by S. pneumoniae during growth on mucin. Transcriptome analysis of cells grown on mucin showed specific upregulation of genes likely to be involved in deglycosylation, transport and catabolism of galactose, mannose and N acetylglucosamine. In contrast to growth on mannose and N-acetylglucosamine, S. pneumoniae grown on galactose re-route their metabolic pathway from homolactic fermentation to a truly mixed acid fermentation regime. By measuring intracellular metabolites, enzymatic activities and mutant analysis, we provide an accurate map of the biochemical pathways for galactose, mannose and N-acetylglucosamine catabolism in S. pneumoniae. Intranasal mouse infection models of pneumococcal colonisation and disease showed that only mutants in galactose catabolic genes were attenuated. Our data pinpoint galactose as a key nutrient for growth in the respiratory tract and highlights the importance of central carbon metabolism for pneumococcal pathogenesis. PMID:25826206

Follow-on biologics: data exclusivity and the balance between innovation and competition.

PubMed

Grabowski, Henry

2008-06-01

Legislation to create a regulatory pathway for follow-on biologics is currently being considered by the United States Congress. A critical issue in this respect is the period of data exclusivity for innovator companies before a follow-on competitor can rely in part on data obtained for an original biologic for an abbreviated approval. Given the nature of patents on biologics, the period of data exclusivity is anticipated to have a key role in determining how quickly follow-on competitors emerge, and consequently also on the time available for originator companies to recoup their investment. With this issue in mind, this article discusses factors influencing return on investment on biologic research and development. A break-even analysis for a representative portfolio of biologics provides support for a substantial data exclusivity period.

Responsive eLearning exercises to enhance student interaction with metabolic pathways.

PubMed

Roesler, William J; Dreaver-Charles, Kristine

2018-05-01

Successful learning of biochemistry requires students to engage with the material. In the past this often involved students writing out pathways by hand, and more recently directing students to online resources such as videos, songs, and animated slide presentations. However, even these latter resources do not really provide students an opportunity to engage with the material in an active fashion. As part of an online introductory metabolism course that was developed at our university, we created a series of twelve online interactive activities using Adobe Captivate 9. These activities targeted glycolysis, gluconeogenesis, the pentose phosphate pathway, glycogen metabolism, the citric acid cycle, and fatty acid oxidation. The interactive exercises consisted of two types. One involved dragging objects such as names of enzymes or allosteric modifiers to their correct drop locations such as a particular point in a metabolic pathway, a specific enzyme, and so forth. A second type involved clicking on objects, locations within a pathway, and so forth, in response to a particular question. In both types of exercises, students received feedback on their decisions in order to enhance learning. The student feedback received on these activities was very positive, and indicated that they found them to increase their confidence in the material and that they had learned the key principles of each pathway. © 2018 by The International Union of Biochemistry and Molecular Biology, 46(3):223-229, 2018. © 2018 The International Union of Biochemistry and Molecular Biology.

Crystallization Pathways in Biomineralization

NASA Astrophysics Data System (ADS)

Weiner, Steve; Addadi, Lia

2011-08-01

A crystallization pathway describes the movement of ions from their source to the final product. Cells are intimately involved in biological crystallization pathways. In many pathways the cells utilize a unique strategy: They temporarily concentrate ions in intracellular membrane-bound vesicles in the form of a highly disordered solid phase. This phase is then transported to the final mineralization site, where it is destabilized and crystallizes. We present four case studies, each of which demonstrates specific aspects of biological crystallization pathways: seawater uptake by foraminifera, calcite spicule formation by sea urchin larvae, goethite formation in the teeth of limpets, and guanine crystal formation in fish skin and spider cuticles. Three representative crystallization pathways are described, and aspects of the different stages of crystallization are discussed. An in-depth understanding of these complex processes can lead to new ideas for synthetic crystallization processes of interest to materials science.

Systems Biology for Organotypic Cell Cultures

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

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis J.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the

Protein-protein interaction analysis of Alzheimer`s disease and NAFLD based on systems biology methods unhide common ancestor pathways.

PubMed

Karbalaei, Reza; Allahyari, Marzieh; Rezaei-Tavirani, Mostafa; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

2018-01-01

Analysis reconstruction networks from two diseases, NAFLD and Alzheimer`s diseases and their relationship based on systems biology methods. NAFLD and Alzheimer`s diseases are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on relation and same spreading pathways of these two diseases. In addition, they have some similar risk factors, exclusively lifestyle such as feeding, exercises and so on. Therefore, systems biology approach can help to discover their relationship. DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. An R package used to define best centrality method. Finally, based on degree and Betweenness, hubs and bottleneck nodes were defined. Common genes between NAFLD and Alzheimer`s disease were 190 genes that used construct a network with STRING database. The resulting network contained 182 nodes and 2591 edges and comprises from four clusters. Enrichment of these clusters separately lead to carbohydrate metabolism, long chain fatty acid and regulation of JAK-STAT and IL-17 signaling pathways, respectively. Also seven genes selected as hub-bottleneck include: IL6, AKT1, TP53, TNF, JUN, VEGFA and PPARG. Enrichment of these proteins and their first neighbors in network by OMIM database lead to diabetes and obesity as ancestors of NAFLD and AD. Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.

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

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

Nanobodies and recombinant binders in cell biology.

PubMed

Helma, Jonas; Cardoso, M Cristina; Muyldermans, Serge; Leonhardt, Heinrich

2015-06-08

Antibodies are key reagents to investigate cellular processes. The development of recombinant antibodies and binders derived from natural protein scaffolds has expanded traditional applications, such as immunofluorescence, binding arrays, and immunoprecipitation. In addition, their small size and high stability in ectopic environments have enabled their use in all areas of cell research, including structural biology, advanced microscopy, and intracellular expression. Understanding these novel reagents as genetic modules that can be integrated into cellular pathways opens up a broad experimental spectrum to monitor and manipulate cellular processes. © 2015 Helma et al.

Nanobodies and recombinant binders in cell biology

PubMed Central

Helma, Jonas; Cardoso, M. Cristina; Muyldermans, Serge

2015-01-01

Antibodies are key reagents to investigate cellular processes. The development of recombinant antibodies and binders derived from natural protein scaffolds has expanded traditional applications, such as immunofluorescence, binding arrays, and immunoprecipitation. In addition, their small size and high stability in ectopic environments have enabled their use in all areas of cell research, including structural biology, advanced microscopy, and intracellular expression. Understanding these novel reagents as genetic modules that can be integrated into cellular pathways opens up a broad experimental spectrum to monitor and manipulate cellular processes. PMID:26056137

Expression profiling indicating low selenium-sensitive microRNA levels linked to cell cycle and cell stress response pathways in the CaCo-2 cell line.

PubMed

McCann, Mark J; Rotjanapun, Kunjana; Hesketh, John E; Roy, Nicole C

2017-05-01

Se is an essential micronutrient for human health, and fluctuations in Se levels and the potential cellular dysfunction associated with it may increase the risk for disease. Although Se has been shown to influence several biological pathways important in health, little is known about the effect of Se on the expression of microRNA (miRNA) molecules regulating these pathways. To explore the potential role of Se-sensitive miRNA in regulating pathways linked with colon cancer, we profiled the expression of 800 miRNA in the CaCo-2 human adenocarcinoma cell line in response to a low-Se (72 h at <40 nm) environment using nCounter direct quantification. These data were then examined using a range of in silico databases to identify experimentally validated miRNA-mRNA interactions and the biological pathways involved. We identified ten Se-sensitive miRNA (hsa-miR-93-5p, hsa-miR-106a-5p, hsa-miR-205-5p, hsa-miR-200c-3p, hsa-miR-99b-5p, hsa-miR-302d-3p, hsa-miR-373-3p, hsa-miR-483-3p, hsa-miR-512-5p and hsa-miR-4454), which regulate 3588 mRNA in key pathways such as the cell cycle, the cellular response to stress, and the canonical Wnt/β-catenin, p53 and ERK/MAPK signalling pathways. Our data show that the effects of low Se on biological pathways may, in part, be due to these ten Se-sensitive miRNA. Dysregulation of the cell cycle and of the stress response pathways due to low Se may influence key genes involved in carcinogenesis.

Neurophysiology and itch pathways.

PubMed

Schmelz, Martin

2015-01-01

As we all can easily differentiate the sensations of itch and pain, the most straightforward neurophysiologic concept would consist of two specific pathways that independently encode itch and pain. Indeed, a neuronal pathway for histamine-induced itch in the peripheral and central nervous system has been described in animals and humans, and recently several non-histaminergic pathways for itch have been discovered in rodents that support a dichotomous concept differentiated into a pain and an itch pathway, with both pathways being composed of different "flavors." Numerous markers and mediators have been found that are linked to itch processing pathways. Thus, the delineation of neuronal pathways for itch from pain pathways seemingly proves that all sensory aspects of itch are based on an itch-specific neuronal pathway. However, such a concept is incomplete as itch can also be induced by the activation of the pain pathway in particular when the stimulus is applied in a highly localized spatial pattern. These opposite views reflect the old dispute between specificity and pattern theories of itch. Rather than only being of theoretic interest, this conceptual problem has key implication for the strategy to treat chronic itch as key therapeutic targets would be either itch-specific pathways or unspecific nociceptive pathways.

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

Finding the key - cell biology and science education.

PubMed

Miller, Kenneth R

2010-12-01

No international research community, cell biology included, can exist without an educational community to renew and replenish it. Unfortunately, cell biology researchers frequently regard their work as independent of the process of education and see little reason to reach out to science teachers. For cell biology to continue to prosper, I argue that researchers must support education in at least three ways. First, we must view education and research as part of a single scientific community. Second, we should take advantage of new technologies to connect the research laboratory to the classroom. Finally, we must take the initiative in defending the integrity of science teaching, particularly when education is under attack for political or religious reasons. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Western Blot-based Investigation of the Yeast Secretory Pathway Designed for an Intermediate-Level Undergraduate Cell Biology Laboratory

ERIC Educational Resources Information Center

Hood-DeGrenier, Jennifer K.

2008-01-01

The movement of newly synthesized proteins through the endomembrane system of eukaryotic cells, often referred to generally as the secretory pathway, is a topic covered in most intermediate-level undergraduate cell biology courses. An article previously published in this journal described a laboratory exercise in which yeast mutants defective in…

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 ...

Phylogenetically informed logic relationships improve detection of biological network organization

PubMed Central

2011-01-01

Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

Implementing Guided Pathways: Early Insights from the AACC Pathways Colleges. Executive Summary

ERIC Educational Resources Information Center

Jenkins, Davis; Lahr, Hana; Fink, John

2017-01-01

This summary is a digest of key findings from "Implementing Guided Pathways: Early Insights From the AACC Pathways Colleges," a report based on Community College Research Center's (CCRC's) research on the 30 colleges involved in the American Association of Community Colleges' (AACC) Pathways Project. The research presented in this report…

Quantitative Biology of Exercise-Induced Signal Transduction Pathways.

PubMed

Liu, Timon Cheng-Yi; Liu, Gang; Hu, Shao-Juan; Zhu, Ling; Yang, Xiang-Bo; Zhang, Quan-Guang

2017-01-01

Exercise is essential in regulating energy metabolism. Exercise activates cellular, molecular, and biochemical pathways with regulatory roles in training response adaptation. Among them, endurance/strength training of an individual has been shown to activate its respective signal transduction pathways in skeletal muscle. This was further studied from the viewpoint of quantitative difference (QD). For the mean values, [Formula: see text], of two sets of data, their QD is defined as [Formula: see text] ([Formula: see text]). The function-specific homeostasis (FSH) of a function of a biosystem is a negative-feedback response of the biosystem to maintain the function-specific conditions inside the biosystem so that the function is perfectly performed. A function in/far from its FSH is called a normal/dysfunctional function. A cellular normal function can resist the activation of other signal transduction pathways so that there are normal function-specific signal transduction pathways which full activation maintains the normal function. An acute endurance/strength training may be dysfunctional, but its regular training may be normal. The normal endurance/strength training of an individual may resist the activation of other signal transduction pathways in skeletal muscle so that there may be normal endurance/strength training-specific signal transduction pathways (NEPs/NSPs) in skeletal muscle. The endurance/strength training may activate NSPs/NEPs, but the QD from the control is smaller than 0.80. The simultaneous activation of both NSPs and NEPs may enhance their respective activation, and the QD from the control is larger than 0.80. The low level laser irradiation pretreatment of rats may promote the activation of NSPs in endurance training skeletal muscle. There may be NEPs/NSPs in skeletal muscle trained by normal endurance/strength training.

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

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

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.

Multiple biological pathways link cognitive lifestyle to protection from dementia.

PubMed

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

2012-05-01

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

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

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...

A pathway-based network analysis of hypertension-related genes

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Development of a Systems Computational Model to Investigate Early Biological Events in Hepatic Activation of Constitutive Androstane Receptor (CAR) by Phenobarbital

EPA Science Inventory

Activation of the nuclear receptor CAR (constitutive active/androstane receptor) is implicated in the control several key biological events such as metabolic pathways. Here, we combined data from literature with information obtained from in vitro assays in the US EPA ToxCast dat...

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

Future biologic therapies in asthma.

PubMed

Quirce, Santiago; Bobolea, Irina; Domínguez-Ortega, Javier; Barranco, Pilar

2014-08-01

Despite the administration of appropriate treatment, a high number of patients with asthma remain uncontrolled. This suggests the need for alternative treatments that are effective, safe and selective for the established asthma phenotypes, especially in patients with uncontrolled severe asthma. The most promising options among the new asthma treatments in development are biological therapies, particularly those monoclonal antibodies directed at selective targets. It should be noted that the different drugs, and especially the new biologics, act on very specific pathogenic pathways. Therefore, determination of the individual profile of predominant pathophysiological alterations of each patient will be increasingly important for prescribing the most appropriate treatment in each case. The treatment of severe allergic asthma with anti-IgE monoclonal antibody (omalizumab) has been shown to be effective in a large number of patients, and new anti-IgE antibodies with improved pharmacodynamic properties are being investigated. Among developing therapies, biologics designed to block certain pro-inflammatory cytokines, such as IL-5 (mepolizumab) and IL-13 (lebrikizumab), have a greater chance of being used in the clinic. Perhaps blocking more than one cytokine pathway (such as IL-4 and IL-13 with dulipumab) might confer increased efficacy of treatment, along with acceptable safety. Stratification of asthma based on the predominant pathogenic mechanisms of each patient (phenoendotypes) is slowly, but probably irreversibly, emerging as a tailored medical approach to asthma, and is becoming a key factor in the development of drugs for this complex respiratory syndrome. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

Resilience of Key Biological Parameters of the Senegalese Flat Sardinella to Overfishing and Climate Change.

PubMed

Ba, Kamarel; Thiaw, Modou; Lazar, Najih; Sarr, Alassane; Brochier, Timothée; Ndiaye, Ismaïla; Faye, Alioune; Sadio, Oumar; Panfili, Jacques; Thiaw, Omar Thiom; Brehmer, Patrice

2016-01-01

The stock of the Senegalese flat sardinella, Sardinella maderensis, is highly exploited in Senegal, West Africa. Its growth and reproduction parameters are key biological indicators for improving fisheries management. This study reviewed these parameters using landing data from small-scale fisheries in Senegal and literature information dated back more than 25 years. Age was estimated using length-frequency data to calculate growth parameters and assess the growth performance index. With global climate change there has been an increase in the average sea surface temperature along the Senegalese coast but the length-weight parameters, sex ratio, size at first sexual maturity, period of reproduction and condition factor of S. maderensis have not changed significantly. The above parameters of S. maderensis have hardly changed, despite high exploitation and fluctuations in environmental conditions that affect the early development phases of small pelagic fish in West Africa. This lack of plasticity of the species regarding of the biological parameters studied should be considered when planning relevant fishery management plans.

Insights into the key roles of proteoglycans in breast cancer biology and translational medicine

PubMed Central

Theocharis, Achilleas D.; Skandalis, Spyros S.; Neill, Thomas; Multhaupt, Hinke A. B.; Hubo, Mario; Frey, Helena; Gopal, Sandeep; Gomes, Angélica; Afratis, Nikos; Lim, Hooi Ching; Couchman, John R.; Filmus, Jorge; Sanderson, Ralph D.; Schaefer, Liliana; Iozzo, Renato V.; Karamanos, Nikos K.

2015-01-01

Proteoglycans control numerous normal and pathological processes, among which are morphogenesis, tissue repair, inflammation, vascularization and cancer metastasis. During tumor development and growth, proteoglycan expression is markedly modified in the tumor microenvironment. Altered expression of proteoglycans on tumor and stromal cell membranes affects cancer cell signaling, growth and survival, cell adhesion, migration and angiogenesis. Despite the high complexity and heterogeneity of breast cancer, the rapid evolution in our knowledge that proteoglycans are among the key players in the breast tumor microenvironment suggests their potential as pharmacological targets in this type of cancer. It has been recently suggested that pharmacological treatment may target proteoglycan metabolism, their utilization as targets for immunotherapy or their direct use as therapeutic agents. The diversity inherent in the proteoglycans that will be presented herein provides the potential for multiple layers of regulation of breast tumor behavior. This review summarizes recent developments concerning the biology of selected proteoglycans in breast cancer, and presents potential targeted therapeutic approaches based on their novel key roles in breast cancer. PMID:25829250

Transcriptome Analysis of Three Sheep Intestinal Regions reveals Key Pathways and Hub Regulatory Genes of Large Intestinal Lipid Metabolism.

PubMed

Chao, Tianle; Wang, Guizhi; Ji, Zhibin; Liu, Zhaohua; Hou, Lei; Wang, Jin; Wang, Jianmin

2017-07-13

The large intestine, also known as the hindgut, is an important part of the animal digestive system. Recent studies on digestive system development in ruminants have focused on the rumen and the small intestine, but the molecular mechanisms underlying sheep large intestine metabolism remain poorly understood. To identify genes related to intestinal metabolism and to reveal molecular regulation mechanisms, we sequenced and compared the transcriptomes of mucosal epithelial tissues among the cecum, proximal colon and duodenum. A total of 4,221 transcripts from 3,254 genes were identified as differentially expressed transcripts. Between the large intestine and duodenum, differentially expressed transcripts were found to be significantly enriched in 6 metabolism-related pathways, among which PPAR signaling was identified as a key pathway. Three genes, CPT1A, LPL and PCK1, were identified as higher expression hub genes in the large intestine. Between the cecum and colon, differentially expressed transcripts were significantly enriched in 5 lipid metabolism related pathways, and CEPT1 and MBOAT1 were identified as hub genes. This study provides important information regarding the molecular mechanisms of intestinal metabolism in sheep and may provide a basis for further study.

A new synthetic biology approach allows transfer of an entire metabolic pathway from a medicinal plant to a biomass crop.

PubMed

Fuentes, Paulina; Zhou, Fei; Erban, Alexander; Karcher, Daniel; Kopka, Joachim; Bock, Ralph

2016-06-14

Artemisinin-based therapies are the only effective treatment for malaria, the most devastating disease in human history. To meet the growing demand for artemisinin and make it accessible to the poorest, an inexpensive and rapidly scalable production platform is urgently needed. Here we have developed a new synthetic biology approach, combinatorial supertransformation of transplastomic recipient lines (COSTREL), and applied it to introduce the complete pathway for artemisinic acid, the precursor of artemisinin, into the high-biomass crop tobacco. We first introduced the core pathway of artemisinic acid biosynthesis into the chloroplast genome. The transplastomic plants were then combinatorially supertransformed with cassettes for all additional enzymes known to affect flux through the artemisinin pathway. By screening large populations of COSTREL lines, we isolated plants that produce more than 120 milligram artemisinic acid per kilogram biomass. Our work provides an efficient strategy for engineering complex biochemical pathways into plants and optimizing the metabolic output.

A new synthetic biology approach allows transfer of an entire metabolic pathway from a medicinal plant to a biomass crop

PubMed Central

Fuentes, Paulina; Zhou, Fei; Erban, Alexander; Karcher, Daniel; Kopka, Joachim; Bock, Ralph

2016-01-01

Artemisinin-based therapies are the only effective treatment for malaria, the most devastating disease in human history. To meet the growing demand for artemisinin and make it accessible to the poorest, an inexpensive and rapidly scalable production platform is urgently needed. Here we have developed a new synthetic biology approach, combinatorial supertransformation of transplastomic recipient lines (COSTREL), and applied it to introduce the complete pathway for artemisinic acid, the precursor of artemisinin, into the high-biomass crop tobacco. We first introduced the core pathway of artemisinic acid biosynthesis into the chloroplast genome. The transplastomic plants were then combinatorially supertransformed with cassettes for all additional enzymes known to affect flux through the artemisinin pathway. By screening large populations of COSTREL lines, we isolated plants that produce more than 120 milligram artemisinic acid per kilogram biomass. Our work provides an efficient strategy for engineering complex biochemical pathways into plants and optimizing the metabolic output. DOI: http://dx.doi.org/10.7554/eLife.13664.001 PMID:27296645

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

PubMed

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Making Sense of the Yeast Sphingolipid Pathway.

PubMed

Megyeri, Márton; Riezman, Howard; Schuldiner, Maya; Futerman, Anthony H

2016-12-04

Sphingolipids (SL) and their metabolites play key roles both as structural components of membranes and as signaling molecules. Many of the key enzymes and regulators of SL metabolism were discovered using the yeast Saccharomyces cerevisiae, and based on the high degree of conservation, a number of mammalian homologs were identified. Although yeast continues to be an important tool for SL research, the complexity of SL structure and nomenclature often hampers the ability of new researchers to grasp the subtleties of yeast SL biology and discover new modulators of this intricate pathway. Moreover, the emergence of lipidomics by mass spectrometry has enabled the rapid identification of SL species in yeast and rendered the analysis of SL composition under various physiological and pathophysiological conditions readily amenable. However, the complex nomenclature of the identified species renders much of the data inaccessible to non-specialists. In this review, we focus on parsing both the classical SL nomenclature and the nomenclature normally used during mass spectrometry analysis, which should facilitate the understanding of yeast SL data and might shed light on biological processes in which SLs are involved. Finally, we discuss a number of putative roles of various yeast SL species. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing Master Keys to Brain Pathology, Cancer and Aging from the Structural Biology of Proteins Controlling Reactive Oxygen Species and DNA Repair

PubMed Central

Perry, J. Jefferson P.; Fan, Li; Tainer, John A.

2007-01-01

This review is focused on proteins with key roles in pathways controlling either reactive oxygen species or DNA damage responses, both of which are essential for preserving the nervous system. An imbalance of reactive oxygen species or inappropriate DNA damage response likely causes mutational or cytotoxic outcomes, which may lead to cancer and/or aging phenotypes. Moreover, individuals with hereditary disorders in proteins of these cellular pathways have significant neurological abnormalities. Mutations in a superoxide dismutase, which removes oxygen free radicals, may cause the neurodegenerative disease amyotrophic lateral sclerosis. Additionally, DNA repair disorders that affect the brain to varying extents include ataxia-telangiectasia-like disorder, Cockayne syndrome or Werner syndrome. Here, we highlight recent advances gained through structural biochemistry studies on enzymes linked to these disorders and other related enzymes acting within the same cellular pathways. We describe the current understanding of how these vital proteins coordinate chemical steps and integrate cellular signaling and response events. Significantly, these structural studies may provide a set of master keys to developing a unified understanding of the survival mechanisms utilized after insults by reactive oxygen species and genotoxic agents, and also provide a basis for developing an informed intervention in brain tumor and neurodegenerative disease progression. PMID:17174478

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

PubMed Central

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

2012-01-01

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

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

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

From Hans Selye’s Discovery of Biological Stress to the Identification of Corticotropin Releasing Factor signaling pathways: Implication in Stress-Related Functional Bowel Diseases

PubMed Central

Taché, Yvette; Brunnhuber, Stefan

2010-01-01

Selye’s pioneer the concept of biological stress in 1936 culminating to the identification of the corticotropin releasing factor (CRF) signaling pathways by Vale’s group in the last two decades. The characterization of the 41 amino-acid CRF and other peptide members of the mammalian CRF family, urocortin 1, urocortin 2 and urocortin 3, the cloning of CRF1 and CRF2 receptors, which display distinct affinity for CRF ligands, combined with the development of selective CRF receptor antagonists enable to unravel the importance of CRF1 receptor in the stress-related endocrine (activation of pituitary-adrenal axis), behavioral (anxiety/depression, altered feeding), autonomic (activation of sympathetic nervous system) and immune responses. The activation of CRF1 receptors is also part of key mechanisms through which various stressors impact the gut to stimulate colonic propulsive motor function and to induce hypersensitivity to colorectal distension as shown by the efficacy of the CRF1 receptor antagonists in blunting these stress-related components. The importance of CRF1 signaling pathways in the visceral response to stress in experimental animals provided new therapeutic approaches for treatment of functional bowel disorder such as irritable bowel syndrome, a multifactor functional disorder characterized by altered bowel habits and visceral pain for which stress has been implicated in the pathophysiology and is associated with anxiety-depression in subset of patients. PMID:19120089

Multi-Omics Reveals that Lead Exposure Disturbs Gut Microbiome Development, Key Metabolites, and Metabolic Pathways.

PubMed

Gao, Bei; Chi, Liang; Mahbub, Ridwan; Bian, Xiaoming; Tu, Pengcheng; Ru, Hongyu; Lu, Kun

2017-04-17

Lead exposure remains a global public health issue, and the recent Flint water crisis has renewed public concern about lead toxicity. The toxicity of lead has been well established in a variety of systems and organs. The gut microbiome has been shown to be highly involved in many critical physiological processes, including food digestion, immune system development, and metabolic homeostasis. However, despite the key role of the gut microbiome in human health, the functional impact of lead exposure on the gut microbiome has not been studied. The aim of this study is to define gut microbiome toxicity induced by lead exposure in C57BL/6 mice using multiomics approaches, including 16S rRNA sequencing, whole genome metagenomics sequencing, and gas chromatography-mass spectrometry (GC-MS) metabolomics. 16S rRNA sequencing revealed that lead exposure altered the gut microbiome trajectory and phylogenetic diversity. Metagenomics sequencing and metabolomics profiling showed that numerous metabolic pathways, including vitamin E, bile acids, nitrogen metabolism, energy metabolism, oxidative stress, and the defense/detoxification mechanism, were significantly disturbed by lead exposure. These perturbed molecules and pathways may have important implications for lead toxicity in the host. Taken together, these results demonstrated that lead exposure not only altered the gut microbiome community structures/diversity but also greatly affected metabolic functions, leading to gut microbiome toxicity.

Synthetic biology and metabolic engineering.

PubMed

Stephanopoulos, Gregory

2012-11-16

Metabolic engineering emerged 20 years ago as the discipline occupied with the directed modification of metabolic pathways for the microbial synthesis of various products. As such, it deals with the engineering (design, construction, and optimization) of native as well as non-natural routes of product synthesis, aided in this task by the availability of synthetic DNA, the core enabling technology of synthetic biology. The two fields, however, only partially overlap in their interest in pathway engineering. While fabrication of biobricks, synthetic cells, genetic circuits, and nonlinear cell dynamics, along with pathway engineering, have occupied researchers in the field of synthetic biology, the sum total of these areas does not constitute a coherent definition of synthetic biology with a distinct intellectual foundation and well-defined areas of application. This paper reviews the origins of the two fields and advances two distinct paradigms for each of them: that of unit operations for metabolic engineering and electronic circuits for synthetic biology. In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

The Akt signaling pathway

PubMed Central

Madhunapantula, SubbaRao V; Mosca, Paul J

2011-01-01

Studies using cultured melanoma cells and patient tumor biopsies have demonstrated deregulated PI3 kinase-Akt3 pathway activity in ∼70% of melanomas. Furthermore, targeting Akt3 and downstream PRAS40 has been shown to inhibit melanoma tumor development in mice. Although these preclinical studies and several other reports using small interfering RNAs and pharmacological agents targeting key members of this pathway have been shown to retard melanoma development, analysis of early Phase I and Phase II clinical trials using pharmacological agents to target this pathway demonstrate the need for (1) selection of patients whose tumors have PI3 kinase-Akt pathway deregulation, (2) further optimization of therapeutic agents for increased potency and reduced toxicity, (3) the identification of additional targets in the same pathway or in other signaling cascades that synergistically inhibit the growth and progression of melanoma, and (4) better methods for targeted delivery of pharmaceutical agents inhibiting this pathway. In this review we discuss key potential targets in PI3K-Akt3 signaling, the status of pharmacological agents targeting these proteins, drugs under clinical development, and strategies to improve the efficacy of therapeutic agents targeting this pathway. PMID:22157148

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.

Identification of key genes and pathways associated with neuropathic pain in uninjured dorsal root ganglion by using bioinformatic analysis.

PubMed

Chen, Chao-Jin; Liu, De-Zhao; Yao, Wei-Feng; Gu, Yu; Huang, Fei; Hei, Zi-Qing; Li, Xiang

2017-01-01

Neuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs) drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs) and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL) by using bioinformatic analysis. The microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein-protein interaction (PPI) network and module analysis. Real-time polymerase chain reaction (PCR) and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model. A total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were upregulated in both L4 and L5 DRGs. This study provides insight into the functional gene sets and pathways associated with neuropathic pain in L4 uninjured DRG after L5 SNL, which might promote our understanding of the molecular mechanisms underlying the development of neuropathic pain.

Key Enzymes of the Semiphosphorylative Entner-Doudoroff Pathway in the Haloarchaeon Haloferax volcanii: Characterization of Glucose Dehydrogenase, Gluconate Dehydratase, and 2-Keto-3-Deoxy-6-Phosphogluconate Aldolase.

PubMed

Sutter, Jan-Moritz; Tästensen, Julia-Beate; Johnsen, Ulrike; Soppa, Jörg; Schönheit, Peter

2016-08-15

The halophilic archaeon Haloferax volcanii has been proposed to degrade glucose via the semiphosphorylative Entner-Doudoroff (spED) pathway. So far, the key enzymes of this pathway, glucose dehydrogenase (GDH), gluconate dehydratase (GAD), and 2-keto-3-deoxy-6-phosphogluconate (KDPG) aldolase (KDPGA), have not been characterized, and their functional involvement in glucose degradation has not been demonstrated. Here we report that the genes HVO_1083 and HVO_0950 encode GDH and KDPGA, respectively. The recombinant enzymes show high specificity for glucose and KDPG and did not convert the corresponding C4 epimers galactose and 2-keto-3-deoxy-6-phosphogalactonate at significant rates. Growth studies of knockout mutants indicate the functional involvement of both GDH and KDPGA in glucose degradation. GAD was purified from H. volcanii, and the encoding gene, gad, was identified as HVO_1488. GAD catalyzed the specific dehydration of gluconate and did not utilize galactonate at significant rates. A knockout mutant of GAD lost the ability to grow on glucose, indicating the essential involvement of GAD in glucose degradation. However, following a prolonged incubation period, growth of the Δgad mutant on glucose was recovered. Evidence is presented that under these conditions, GAD was functionally replaced by xylonate dehydratase (XAD), which uses both xylonate and gluconate as substrates. Together, the characterization of key enzymes and analyses of the respective knockout mutants present conclusive evidence for the in vivo operation of the spED pathway for glucose degradation in H. volcanii The work presented here describes the identification and characterization of the key enzymes glucose dehydrogenase, gluconate dehydratase, and 2-keto-3-deoxy-6-phosphogluconate aldolase and their encoding genes of the proposed semiphosphorylative Entner-Doudoroff pathway in the haloarchaeon Haloferax volcanii The functional involvement of the three enzymes was proven by analyses of the

Methods and approaches in the topology-based analysis of biological pathways

PubMed Central

Mitrea, Cristina; Taghavi, Zeinab; Bokanizad, Behzad; Hanoudi, Samer; Tagett, Rebecca; Donato, Michele; Voichiţa, Călin; Drăghici, Sorin

2013-01-01

The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as “third generation,” have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity. PMID:24133454

Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

PubMed

Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

2012-12-01

Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

Depletion of key protein components of the RISC pathway impairs pre-ribosomal RNA processing.

PubMed

Liang, Xue-Hai; Crooke, Stanley T

2011-06-01

Little is known about whether components of the RNA-induced silencing complex (RISC) mediate the biogenesis of RNAs other than miRNA. Here, we show that depletion of key proteins of the RISC pathway by antisense oligonucleotides significantly impairs pre-rRNA processing in human cells. In cells depleted of Drosha or Dicer, different precursors to 5.8S rRNA strongly accumulated, without affecting normal endonucleolytic cleavages. Moderate yet distinct processing defects were also observed in Ago2-depleted cells. Physical links between pre-rRNA and these proteins were identified by co-immunoprecipitation analyses. Interestingly, simultaneous depletion of Dicer and Drosha led to a different processing defect, causing slower production of 28S rRNA and its precursor. Both Dicer and Ago2 were detected in the nuclear fraction, and reduction of Dicer altered the structure of the nucleolus, where pre-rRNA processing occurs. Together, these results suggest that Drosha and Dicer are implicated in rRNA biogenesis.

High-throughput sequencing reveals key genes and immune homeostatic pathways activated in myeloid dendritic cells by Porphyromonas gingivalis 381 and its fimbrial mutants.

PubMed

Arjunan, P; El-Awady, A; Dannebaum, R O; Kunde-Ramamoorthy, G; Cutler, C W

2016-02-01

The human microbiome consists of highly diverse microbial communities that colonize our skin and mucosal surfaces, aiding in maintenance of immune homeostasis. The keystone pathogen Porphyromonas gingivalis induces a dysbiosis and disrupts immune homeostasis through as yet unclear mechanisms. The fimbrial adhesins of P. gingivalis facilitate biofilm formation, invasion of and dissemination by blood dendritic cells; hence, fimbriae may be key factors in disruption of immune homeostasis. In this study we employed RNA-sequencing transcriptome profiling to identify differentially expressed genes (DEGs) in human monocyte-derived dendritic cells (MoDCs) in response to in vitro infection/exposure by Pg381 or its isogenic mutant strains that solely express minor-Mfa1 fimbriae (DPG3), major-FimA fimbriae (MFI) or are deficient in both fimbriae (MFB) relative to uninfected control. Our results yielded a total of 479 DEGs that were at least two-fold upregulated and downregulated in MoDCs significantly (P ≤ 0.05) by all four strains and certain DEGs that were strain-specific. Interestingly, the gene ontology biological and functional analysis shows that the upregulated genes in DPG3-induced MoDCs were more significant than other strains and associated with inflammation, immune response, anti-apoptosis, cell proliferation, and other homeostatic functions. Both transcriptome and quantitative polymerase chain reaction results show that DPG3, which solely expresses Mfa1, increased ZNF366, CD209, LOX1, IDO1, IL-10, CCL2, SOCS3, STAT3 and FOXO1 gene expression. In conclusion, we have identified key DC-mediated immune homeostatic pathways that could contribute to dysbiosis in periodontal infection with P. gingivalis. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The stat3/socs3a pathway is a key regulator of hair cell regeneration in zebrafish. [corrected].

PubMed

Liang, Jin; Wang, Dongmei; Renaud, Gabriel; Wolfsberg, Tyra G; Wilson, Alexander F; Burgess, Shawn M

2012-08-01

All nonmammalian vertebrates studied can regenerate inner ear mechanosensory receptors (i.e., hair cells) (Corwin and Cotanche, 1988; Lombarte et al., 1993; Baird et al., 1996), but mammals possess only a very limited capacity for regeneration after birth (Roberson and Rubel, 1994). As a result, mammals experience permanent deficiencies in hearing and balance once their inner ear hair cells are lost. The mechanisms of hair cell regeneration are poorly understood. Because the inner ear sensory epithelium is highly conserved in all vertebrates (Fritzsch et al., 2007), we chose to study hair cell regeneration mechanism in adult zebrafish, hoping the results would be transferrable to inducing hair cell regeneration in mammals. We defined the comprehensive network of genes involved in hair cell regeneration in the inner ear of adult zebrafish with the powerful transcriptional profiling technique digital gene expression, which leverages the power of next-generation sequencing ('t Hoen et al., 2008). We also identified a key pathway, stat3/socs3, and demonstrated its role in promoting hair cell regeneration through stem cell activation, cell division, and differentiation. In addition, transient pharmacological inhibition of stat3 signaling accelerated hair cell regeneration without overproducing cells. Taking other published datasets into account (Sano et al., 1999; Schebesta et al., 2006; Dierssen et al., 2008; Riehle et al., 2008; Zhu et al., 2008; Qin et al., 2009), we propose that the stat3/socs3 pathway is a key response in all tissue regeneration and thus an important therapeutic target for a broad application in tissue repair and injury healing.

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

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

PubMed

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

2014-01-01

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

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

PubMed

Shin, Sung-Young; Nguyen, Lan K

2017-01-01

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

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

Workshop Report: Systems Biology for Organotypic Cell Cultures

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

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph; ...

2016-11-14

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Designing mental health interventions informed by child development and human biology theory: A social ecology intervention for child soldiers in Nepal

PubMed Central

Kohrt, Brandon A.; Jordans, Mark J.D.; Koirala, Suraj; Worthman, Carol M.

2017-01-01

The anthropological study of human biology, health, and child development provides a model with potential to address the gap in population-wide mental health interventions. Four key concepts from human biology can inform public mental health interventions: life history theory and tradeoffs, redundancy and plurality of pathways, cascades and multiplier effects in biological systems, and proximate feedback systems. A public mental health intervention for former child soldiers in Nepal is used to illustrate the role of these concepts in intervention design and evaluation. Future directions and recommendations for applying human biology theory in pursuit of public mental health interventions are discussed. PMID:25380194

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

PubMed Central

Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

2015-01-01

Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

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.

A mathematical model of the mevalonate cholesterol biosynthesis pathway.

PubMed

Pool, Frances; Currie, Richard; Sweby, Peter K; Salazar, José Domingo; Tindall, Marcus J

2018-04-14

We formulate, parameterise and analyse a mathematical model of the mevalonate pathway, a key pathway in the synthesis of cholesterol. Of high clinical importance, the pathway incorporates rate limiting enzymatic reactions with multiple negative feedbacks. In this work we investigate the pathway dynamics and demonstrate that rate limiting steps and negative feedbacks within it act in concert to tightly regulate intracellular cholesterol levels. Formulated using the theory of nonlinear ordinary differential equations and parameterised in the context of a hepatocyte, the governing equations are analysed numerically and analytically. Sensitivity and mathematical analysis demonstrate the importance of the two rate limiting enzymes 3-hydroxy-3-methylglutaryl-CoA reductase and squalene synthase in controlling the concentration of substrates within the pathway as well as that of cholesterol. The role of individual feedbacks, both global (between that of cholesterol and sterol regulatory element-binding protein 2; SREBP-2) and local internal (between substrates in the pathway) are investigated. We find that whilst the cholesterol SREBP-2 feedback regulates the overall system dynamics, local feedbacks activate within the pathway to tightly regulate the overall cellular cholesterol concentration. The network stability is analysed by constructing a reduced model of the full pathway and is shown to exhibit one real, stable steady-state. We close by addressing the biological question as to how farnesyl-PP levels are affected by CYP51 inhibition, and demonstrate that the regulatory mechanisms within the network work in unison to ensure they remain bounded. Copyright © 2018 Elsevier Ltd. All rights reserved.

Signaling pathways effecting crosstalk between cartilage and adjacent tissues: Seminars in cell and developmental biology: The biology and pathology of cartilage.

PubMed

Maes, Christa

2017-02-01

Endochondral ossification, the mechanism responsible for the development of the long bones, is dependent on an extremely stringent coordination between the processes of chondrocyte maturation in the growth plate, vascular expansion in the surrounding tissues, and osteoblast differentiation and osteogenesis in the perichondrium and the developing bone center. The synchronization of these processes occurring in adjacent tissues is regulated through vigorous crosstalk between chondrocytes, endothelial cells and osteoblast lineage cells. Our knowledge about the molecular constituents of these bidirectional communications is undoubtedly incomplete, but certainly some signaling pathways effective in cartilage have been recognized to play key roles in steering vascularization and osteogenesis in the perichondrial tissues. These include hypoxia-driven signaling pathways, governed by the hypoxia-inducible factors (HIFs) and vascular endothelial growth factor (VEGF), which are absolutely essential for the survival and functioning of chondrocytes in the avascular growth plate, at least in part by regulating the oxygenation of developing cartilage through the stimulation of angiogenesis in the surrounding tissues. A second coordinating signal emanating from cartilage and regulating developmental processes in the adjacent perichondrium is Indian Hedgehog (IHH). IHH, produced by pre-hypertrophic and early hypertrophic chondrocytes in the growth plate, induces the differentiation of adjacent perichondrial progenitor cells into osteoblasts, thereby harmonizing the site and time of bone formation with the developmental progression of chondrogenesis. Both signaling pathways represent vital mediators of the tightly organized conversion of avascular cartilage into vascularized and mineralized bone during endochondral ossification. Copyright © 2016. Published by Elsevier Ltd.

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

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

Fukunaga, Satoki; Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558; Kakehashi, Anna

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective ofmore » initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.« less

An efficient biological pathway layout algorithm combining grid-layout and spring embedder for complicated cellular location information

PubMed Central

2010-01-01

Background Graph drawing is one of the important techniques for understanding biological regulations in a cell or among cells at the pathway level. Among many available layout algorithms, the spring embedder algorithm is widely used not only for pathway drawing but also for circuit placement and www visualization and so on because of the harmonized appearance of its results. For pathway drawing, location information is essential for its comprehension. However, complex shapes need to be taken into account when torus-shaped location information such as nuclear inner membrane, nuclear outer membrane, and plasma membrane is considered. Unfortunately, the spring embedder algorithm cannot easily handle such information. In addition, crossings between edges and nodes are usually not considered explicitly. Results We proposed a new grid-layout algorithm based on the spring embedder algorithm that can handle location information and provide layouts with harmonized appearance. In grid-layout algorithms, the mapping of nodes to grid points that minimizes a cost function is searched. By imposing positional constraints on grid points, location information including complex shapes can be easily considered. Our layout algorithm includes the spring embedder cost as a component of the cost function. We further extend the layout algorithm to enable dynamic update of the positions and sizes of compartments at each step. Conclusions The new spring embedder-based grid-layout algorithm and a spring embedder algorithm are applied to three biological pathways; endothelial cell model, Fas-induced apoptosis model, and C. elegans cell fate simulation model. From the positional constraints, all the results of our algorithm satisfy location information, and hence, more comprehensible layouts are obtained as compared to the spring embedder algorithm. From the comparison of the number of crossings, the results of the grid-layout-based algorithm tend to contain more crossings than those of the

Metabolic Reconstruction of Setaria italica: A Systems Biology Approach for Integrating Tissue-Specific Omics and Pathway Analysis of Bioenergy Grasses.

PubMed

de Oliveira Dal'Molin, Cristiana G; Orellana, Camila; Gebbie, Leigh; Steen, Jennifer; Hodson, Mark P; Chrysanthopoulos, Panagiotis; Plan, Manuel R; McQualter, Richard; Palfreyman, Robin W; Nielsen, Lars K

2016-01-01

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated

Metabolic Reconstruction of Setaria italica: A Systems Biology Approach for Integrating Tissue-Specific Omics and Pathway Analysis of Bioenergy Grasses

PubMed Central

de Oliveira Dal'Molin, Cristiana G.; Orellana, Camila; Gebbie, Leigh; Steen, Jennifer; Hodson, Mark P.; Chrysanthopoulos, Panagiotis; Plan, Manuel R.; McQualter, Richard; Palfreyman, Robin W.; Nielsen, Lars K.

2016-01-01

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated

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

PubMed

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

2017-01-24

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

Adipose tissue NAD+ biology in obesity and insulin resistance: From mechanism to therapy.

PubMed

Yamaguchi, Shintaro; Yoshino, Jun

2017-05-01

Nicotinamide adenine dinucleotide (NAD + ) biosynthetic pathway, mediated by nicotinamide phosphoribosyltransferase (NAMPT), a key NAD + biosynthetic enzyme, plays a pivotal role in controlling many biological processes, such as metabolism, circadian rhythm, inflammation, and aging. Over the past decade, NAMPT-mediated NAD + biosynthesis, together with its key downstream mediator, namely the NAD + -dependent protein deacetylase SIRT1, has been demonstrated to regulate glucose and lipid metabolism in a tissue-dependent manner. These discoveries have provided novel mechanistic and therapeutic insights into obesity and its metabolic complications, such as insulin resistance, an important risk factor for developing type 2 diabetes and cardiovascular disease. This review will focus on the importance of adipose tissue NAMPT-mediated NAD + biosynthesis and SIRT1 in the pathophysiology of obesity and insulin resistance. We will also critically explore translational and clinical aspects of adipose tissue NAD + biology. © 2017 WILEY Periodicals, Inc.

Advances in imaging secondary ion mass spectrometry for biological samples

DOE PAGES

Boxer, Steven G.; Kraft, Mary L.; Weber, Peter K.

2008-12-16

Imaging mass spectrometry combines the power of mass spectrometry to identify complex molecules based on mass with sample imaging. Recent advances in secondary ion mass spectrometry have improved sensitivity and spatial resolution, so that these methods have the potential to bridge between high-resolution structures obtained by X-ray crystallography and cyro-electron microscopy and ultrastructure visualized by conventional light microscopy. Following background information on the method and instrumentation, we address the key issue of sample preparation. Because mass spectrometry is performed in high vacuum, it is essential to preserve the lateral organization of the sample while removing bulk water, and this hasmore » been a major barrier for applications to biological systems. Furthermore, recent applications of imaging mass spectrometry to cell biology, microbial communities, and biosynthetic pathways are summarized briefly, and studies of biological membrane organization are described in greater depth.« less

Conservation and divergence of the cyclic adenosine monophosphate-protein kinase A (cAMP–PKA) pathway in two plant-pathogenic fungi: Fusarium graminearum and F. verticillioides

USDA-ARS?s Scientific Manuscript database

The cyclic AMP (cAMP)-PKA pathway is a central signaling cascade that transmits extracellular stimuli and governs cell responses through the second messenger cAMP. The importance of cAMP signaling in fungal biology has been well documented. Two key conserved components, adenylate cyclase (AC) and ca...

Role of cellular communication in the pathways of radiation-induced biological damage

NASA Astrophysics Data System (ADS)

Ballarini, Francesca; Facoetti, Angelica; Mariotti, Luca; Nano, Rosanna; Ottolenghi, Andrea

During the last decade, a large number of experimental studies on the so-called "non-targeted effects", in particular bystander effects, outlined that cellular communication plays a signifi- cant role in the pathways leading to radiation-induced biological damage. This might imply a paradigm shift in (low-dose) radiobiology, according to which one has to consider the response of groups of cells behaving like a population rather than single cells behaving as individuals. Furthermore, bystander effects, which are observed both for lethal endpoints (e.g. clonogenic inactivation and apoptosis) and for non-lethal ones (e.g. mutations and neoplastic transformation), tend to show non-linear dose responses characterized by a sharp increase followed by a plateau. This might have significant consequences in terms of low-dose risk, which is generally calculated on the basis of the "Linear No Threshold" hypothesis. Although it is known that two types of cellular communication (i.e. via gap junctions and/or molecular messengers diffusing in the extra-cellular environment, such as cytokines) play a major role, it is of utmost importance to better understand the underlying mechanisms, and how such mechanisms can be modulated by ionizing radiation. Though the "final" goal is to elucidate the in vivo scenario, in the meanwhile also in vitro studies can provide useful insights. In the present paper we will discuss key issues on the mechanisms underlying non-targeted effects and, more generally, cell communication, with focus on candidate molecular signals. Theoretical models and simulation codes can be of help in elucidating such mechanisms. In this framework, we will present a model and Monte Carlo code, under development at the University of Pavia, simulating the release, diffusion and internalization of candidate signals (typically cytokines) travelling in the extra-cellular environment, both by unirradiated (i.e., control) cells and by irradiated cells. The focus will be on the

Syntheses and Biological Studies of Marine Terpenoids Derived from Inorganic Cyanide

PubMed Central

Schnermann, Martin J.; Shenvi, Ryan A.

2015-01-01

Isocyanoterpenes (ICTs) are marine natural products biosynthesized through an unusual pathway that adorns terpene scaffolds with nitrogenous functionality derived from cyanide. The appendage of nitrogen functional groups–isonitriles in particular–onto stereochemically-rich carbocyclic ring systems provides enigmatic, bioactive molecules that have required innovative chemical syntheses. This review discusses the challenges inherent to the synthesis of this diverse family and details the development of the field. We also present recent progress in isolation and discuss key aspects of the remarkable biological activity of these compounds. PMID:25514696

Designing mental health interventions informed by child development and human biology theory: a social ecology intervention for child soldiers in Nepal.

PubMed

Kohrt, Brandon A; Jordans, Mark J D; Koirala, Suraj; Worthman, Carol M

2015-01-01

The anthropological study of human biology, health, and child development provides a model with potential to address the gap in population-wide mental health interventions. Four key concepts from human biology can inform public mental health interventions: life history theory and tradeoffs, redundancy and plurality of pathways, cascades and multiplier effects in biological systems, and proximate feedback systems. A public mental health intervention for former child soldiers in Nepal is used to illustrate the role of these concepts in intervention design and evaluation. Future directions and recommendations for applying human biology theory in pursuit of public mental health interventions are discussed. © 2014 Wiley Periodicals, Inc.

Cell biology perspectives in phage biology.

PubMed

Ansaldi, Mireille

2012-01-01

Cellular biology has long been restricted to large cellular organisms. However, as the resolution of microscopic methods increased, it became possible to study smaller cells, in particular bacterial cells. Bacteriophage biology is one aspect of bacterial cell biology that has recently gained insight from cell biology. Despite their small size, bacteriophages could be successfully labeled and their cycle studied in the host cells. This review aims to put together, although non-extensively, several cell biology studies that recently pushed the elucidation of key mechanisms in phage biology, such as the lysis-lysogeny decision in temperate phages or genome replication and transcription, one step further.

Aging: Molecular Pathways and Implications on the Cardiovascular System

PubMed Central

Ribeiro, Thaís Porto

2017-01-01

The world's population over 60 years is growing rapidly, reaching 22% of the global population in the next decades. Despite the increase in global longevity, individual healthspan needs to follow this growth. Several diseases have their prevalence increased by age, such as cardiovascular diseases, the leading cause of morbidity and mortality worldwide. Understanding the aging biology mechanisms is fundamental to the pursuit of cardiovascular health. In this way, aging is characterized by a gradual decline in physiological functions, involving the increased number in senescent cells into the body. Several pathways lead to senescence, including oxidative stress and persistent inflammation, as well as energy failure such as mitochondrial dysfunction and deregulated autophagy, being ROS, AMPK, SIRTs, mTOR, IGF-1, and p53 key regulators of the metabolic control, connecting aging to the pathways which drive towards diseases. In addition, senescence can be induced by cellular replication, which resulted from telomere shortening. Taken together, it is possible to draw a common pathway unifying aging to cardiovascular diseases, and the central point of this process, senescence, can be the target for new therapies, which may result in the healthspan matching the lifespan. PMID:28874954

Aging: Molecular Pathways and Implications on the Cardiovascular System.

PubMed

de Almeida, Arthur José Pontes Oliveira; Ribeiro, Thaís Porto; de Medeiros, Isac Almeida

2017-01-01

The world's population over 60 years is growing rapidly, reaching 22% of the global population in the next decades. Despite the increase in global longevity, individual healthspan needs to follow this growth. Several diseases have their prevalence increased by age, such as cardiovascular diseases, the leading cause of morbidity and mortality worldwide. Understanding the aging biology mechanisms is fundamental to the pursuit of cardiovascular health. In this way, aging is characterized by a gradual decline in physiological functions, involving the increased number in senescent cells into the body. Several pathways lead to senescence, including oxidative stress and persistent inflammation, as well as energy failure such as mitochondrial dysfunction and deregulated autophagy, being ROS, AMPK, SIRTs, mTOR, IGF-1, and p53 key regulators of the metabolic control, connecting aging to the pathways which drive towards diseases. In addition, senescence can be induced by cellular replication, which resulted from telomere shortening. Taken together, it is possible to draw a common pathway unifying aging to cardiovascular diseases, and the central point of this process, senescence, can be the target for new therapies, which may result in the healthspan matching the lifespan.

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

PubMed

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

2018-01-01

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

Oxidative Stress, Amyloid-β Peptide, and Altered Key Molecular Pathways in the Pathogenesis and Progression of Alzheimer’s Disease

PubMed Central

Butterfield, D. Allan; Boyd-Kimball, Debra

2018-01-01

Oxidative stress is implicated in the pathogenesis and progression of Alzheimer’s disease (AD) and its earlier stage, amnestic mild cognitive impairment (aMCI). One source of oxidative stress in AD and aMCI brains is that associated with amyloid-β peptide, Aβ1-42 oligomers. Our laboratory first showed in AD elevated oxidative stress occurred in brain regions rich in Aβ1-42, but not in Aβ1-42-poor regions, and was among the first to demonstrate Aβ peptides led to lipid peroxidation (indexed by HNE) in AD and aMCI brains. Oxidatively modified proteins have decreased function and contribute to damaged key biochemical and metabolic pathways in which these proteins normally play a role. Identification of oxidatively modified brain proteins by the methods of redox proteomics was pioneered in the Butterfield laboratory. Four recurring altered pathways secondary to oxidative damage in brain from persons with AD, aMCI, or Down syndrome with AD are interrelated and contribute to neuronal death. This “Quadrilateral of Neuronal Death” includes altered: glucose metabolism, mTOR activation, proteostasis network, and protein phosphorylation. Some of these pathways are altered even in brains of persons with preclinical AD. We opine that targeting these pathways pharmacologically and with lifestyle changes potentially may provide strategies to slow or perhaps one day, prevent, progression or development of this devastating dementing disorder. This invited review outlines both in vitro and in vivo studies from the Butterfield laboratory related to Aβ1-42 and AD and discusses the importance and implications of some of the major achievements of the Butterfield laboratory in AD research. PMID:29562527

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Identification of the key pathway of oxazolinoanthracyclines mechanism of action in cells derived from human solid tumors

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

Denel-Bobrowska, Marta, E-mail: mdenel@biol.uni.lo

Oxazolinodoxorubicin (O-DOX) and oxazolinodaunorubicin (O-DAU) are novel anthracycline derivatives with a modified daunosamine moiety. In the present study, we evaluated the cytotoxicities, genotoxicities and abilities of O-DOX and O-DAU to induce apoptosis in cancer cell lines (SKOV-3; A549; HepG2), and compared the results with their parent drugs. We assessed antiproliferative activity by MTT assay. We evaluated apoptosis-inducing ability by double-staining with fluorescent probes (Hoechst 33258/propidium iodide), and by determining expression levels of genes involved in programmed cell death by reverse transcription-polymerase chain reaction. Genotoxicities of the compounds were tested by comet assays. Oxazolinoanthracyclines demonstrated high anti-tumor activity. O-DOX had significantlymore » higher cytotoxicity, apoptosis-inducing ability, and genotoxicity compared with parental doxorubicin (DOX) in all tested conditions, while O-DAU activity differed among cell lines. The mechanism of oxazoline analog action appeared to involve the mitochondrial pathway of programmed cell death. These results provide further information about oxazoline derivatives of commonly used anthracycline chemotherapy agents. O-DOX and O-DAU have the ability to induce apoptosis in tumor cells. - Highlights: • Substituted amino group increased the anticancer activity of anthracyclines. • Mitochondrial apoptotic pathway seems to be involved in the mechanism of action. • Favorable biological properties of oxazoline derivatives were confirmed.« less

Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

PubMed

Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

2018-03-01

Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P < .001), higher rates of chemoradiation interruption (odds ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.

Evaluating legacy contaminants and emerging chemicals in marine environments using adverse outcome pathways and biological effects-directed analysis.

PubMed

Hutchinson, Thomas H; Lyons, Brett P; Thain, John E; Law, Robin J

2013-09-30

important scientific, economic and health challenges. In order to meet these challenges and pursue cost-effective scientific approaches that can provide evidence necessary to support policy needs (e.g. the European Marine Strategy Framework Directive), it is widely recognised that there is a need to (i) provide marine exposure assessments for priority contaminants using a range of validated models, passive samplers and biomarkers; (ii) integrate chemical monitoring data with biological effects data across spatial and temporal scales (including quality controls); and (iii) strengthen the evidence base to understand the relationship between exposure to complex chemical mixtures, biological and ecological impacts through integrated approaches and molecular data (e.g. genomics, proteomics and metabolomics). Additionally, we support the widely held view that (iv) that rather than increasing the analytical chemistry monitoring of large number of emerging contaminants, it will be important to target analytical chemistry towards key groups of chemicals of concern using effects-directed analysis. It is also important to evaluate to what extent existing biomarkers and bioassays can address various classes of emerging chemicals using the adverse outcome pathway (AOP) approach now being developed by the Organization for Economic Cooperation and Development (OECD) with respect to human toxicology and ecotoxicology. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Choroid plexus papillomas: advances in molecular biology and understanding of tumorigenesis.

PubMed

Safaee, Michael; Oh, Michael C; Bloch, Orin; Sun, Matthew Z; Kaur, Gurvinder; Auguste, Kurtis I; Tihan, Tarik; Parsa, Andrew T

2013-03-01

Choroid plexus papillomas are rare, benign tumors originating from the choroid plexus. Although generally found within the ventricular system, they can arise ectopically in the brain parenchyma or disseminate throughout the neuraxis. We sought to review recent advances in our understanding of the molecular biology and oncogenic pathways associated with this disease. A comprehensive PubMed literature review was conducted to identify manuscripts discussing the clinical, molecular, and genetic features of choroid plexus papillomas. Articles concerning diagnosis, treatment, and long-term patient outcomes were also reviewed. The introduction of atypical choroid plexus papilloma as a distinct entity has increased the need for accurate histopathologic diagnosis. Advances in immunohistochemical staining have improved our ability to differentiate choroid plexus papillomas from other intracranial tumors or metastatic lesions using combinations of key markers and mitotic indices. Recent findings have implicated Notch3 signaling, the transcription factor TWIST1, platelet-derived growth factor receptor, and the tumor necrosis factor-related apoptosis-inducing ligand pathway in choroid plexus papilloma tumorigenesis. A combination of commonly occurring chromosomal duplications and deletions has also been identified. Surgical resection remains the standard of care, although chemotherapy and radiotherapy may be considered for recurrent or metastatic lesions. While generally considered benign, these tumors possess a complex biology that sheds insight into other choroid plexus tumors, particularly malignant choroid plexus carcinomas. Improving our understanding of the molecular biology, genetics, and oncogenic pathways associated with this tumor will allow for the development of targeted therapies and improved outcomes for patients with this disease.

Constructing phylogenetic trees using interacting pathways.

PubMed

Wan, Peng; Che, Dongsheng

2013-01-01

Phylogenetic trees are used to represent evolutionary relationships among biological species or organisms. The construction of phylogenetic trees is based on the similarities or differences of their physical or genetic features. Traditional approaches of constructing phylogenetic trees mainly focus on physical features. The recent advancement of high-throughput technologies has led to accumulation of huge amounts of biological data, which in turn changed the way of biological studies in various aspects. In this paper, we report our approach of building phylogenetic trees using the information of interacting pathways. We have applied hierarchical clustering on two domains of organisms-eukaryotes and prokaryotes. Our preliminary results have shown the effectiveness of using the interacting pathways in revealing evolutionary relationships.

Informatics approaches in the Biological Characterization of Adverse Outcome Pathways

EPA Science Inventory

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 ...

CD14 is a key mediator of both lysophosphatidic acid and lipopolysaccharide induction of foam cell formation.

PubMed

An, Dong; Hao, Feng; Zhang, Fuqiang; Kong, Wei; Chun, Jerold; Xu, Xuemin; Cui, Mei-Zhen

2017-09-01

Macrophage uptake of oxidized low-density lipoprotein (oxLDL) plays an important role in foam cell formation and the pathogenesis of atherosclerosis. We report here that lysophosphatidic acid (LPA) enhances lipopolysaccharide (LPS)-induced oxLDL uptake in macrophages. Our data revealed that both LPA and LPS highly induce the CD14 expression at messenger RNA and protein levels in macrophages. The role of CD14, one component of the LPS receptor cluster, in LPA-induced biological functions has been unknown. We took several steps to examine the role of CD14 in LPA signaling pathways. Knockdown of CD14 expression nearly completely blocked LPA/LPS-induced oxLDL uptake in macrophages, demonstrating for the first time that CD14 is a key mediator responsible for both LPA- and LPS-induced oxLDL uptake/foam cell formation. To determine the molecular mechanism mediating CD14 function, we demonstrated that both LPA and LPS significantly induce the expression of scavenger receptor class A type I (SR-AI), which has been implicated in lipid uptake process, and depletion of CD14 levels blocked LPA/LPS-induced SR-AI expression. We further showed that the SR-AI-specific antibody, which quenches SR-AI function, blocked LPA- and LPS-induced foam cell formation. Thus, SR-AI is the downstream mediator of CD14 in regulating LPA-, LPS-, and LPA/LPS-induced foam cell formation. Taken together, our results provide the first experimental evidence that CD14 is a novel connecting molecule linking both LPA and LPS pathways and is a key mediator responsible for LPA/LPS-induced foam cell formation. The LPA/LPS-CD14-SR-AI nexus might be the new convergent pathway, contributing to the worsening of atherosclerosis. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Evolution of JAK-STAT Pathway Components: Mechanisms and Role in Immune System Development

PubMed Central

Liongue, Clifford; O'Sullivan, Lynda A.; Trengove, Monique C.; Ward, Alister C.

2012-01-01

Background Lying downstream of a myriad of cytokine receptors, the Janus kinase (JAK) – Signal transducer and activator of transcription (STAT) pathway is pivotal for the development and function of the immune system, with additional important roles in other biological systems. To gain further insight into immune system evolution, we have performed a comprehensive bioinformatic analysis of the JAK-STAT pathway components, including the key negative regulators of this pathway, the SH2-domain containing tyrosine phosphatase (SHP), Protein inhibitors against Stats (PIAS), and Suppressor of cytokine signaling (SOCS) proteins across a diverse range of organisms. Results Our analysis has demonstrated significant expansion of JAK-STAT pathway components co-incident with the emergence of adaptive immunity, with whole genome duplication being the principal mechanism for generating this additional diversity. In contrast, expansion of upstream cytokine receptors appears to be a pivotal driver for the differential diversification of specific pathway components. Conclusion Diversification of JAK-STAT pathway components during early vertebrate development occurred concurrently with a major expansion of upstream cytokine receptors and two rounds of whole genome duplications. This produced an intricate cell-cell communication system that has made a significant contribution to the evolution of the immune system, particularly the emergence of adaptive immunity. PMID:22412924

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

PubMed

Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

Heritable temperament pathways to early callous-unemotional behaviour.

PubMed

Waller, Rebecca; Trentacosta, Christopher J; Shaw, Daniel S; Neiderhiser, Jenae M; Ganiban, Jody M; Reiss, David; Leve, Leslie D; Hyde, Luke W

2016-12-01

Early callous-unemotional behaviours identify children at risk for antisocial behaviour. Recent work suggests that the high heritability of callous-unemotional behaviours is qualified by interactions with positive parenting. To examine whether heritable temperament dimensions of fearlessness and low affiliative behaviour are associated with early callous-unemotional behaviours and whether parenting moderates these associations. Using an adoption sample (n = 561), we examined pathways from biological mother self-reported fearlessness and affiliative behaviour to child callous-unemotional behaviours via observed child fearlessness and affiliative behaviour, and whether adoptive parent observed positive parenting moderated pathways. Biological mother fearlessness predicted child callous-unemotional behaviours via earlier child fearlessness. Biological mother low affiliative behaviour predicted child callous-unemotional behaviours, although not via child affiliative behaviours. Adoptive mother positive parenting moderated the fearlessness to callous-unemotional behaviour pathway. Heritable fearlessness and low interpersonal affiliation traits contribute to the development of callous-unemotional behaviours. Positive parenting can buffer these risky pathways. © The Royal College of Psychiatrists 2016.

Heritable temperament pathways to early callous–unemotional behaviour

PubMed Central

Waller, Rebecca; Trentacosta, Christopher J.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Ganiban, Jody M.; Reiss, David; Leve, Leslie D.; Hyde, Luke W.

2016-01-01

Background Early callous–unemotional behaviours identify children at risk for antisocial behaviour. Recent work suggests that the high heritability of callous–unemotional behaviours is qualified by interactions with positive parenting. Aims To examine whether heritable temperament dimensions of fearlessness and low affiliative behaviour are associated with early callous–unemotional behaviours and whether parenting moderates these associations. Method Using an adoption sample (n = 561), we examined pathways from biological mother self-reported fearlessness and affiliative behaviour to child callous–unemotional behaviours via observed child fearlessness and affiliative behaviour, and whether adoptive parent observed positive parenting moderated pathways. Results Biological mother fearlessness predicted child callous–unemotional behaviours via earlier child fearlessness. Biological mother low affiliative behaviour predicted child callous–unemotional behaviours, although not via child affiliative behaviours. Adoptive mother positive parenting moderated the fearlessness to callous–unemotional behaviour pathway. Conclusions Heritable fearlessness and low interpersonal affiliation traits contribute to the development of callous–unemotional behaviours. Positive parenting can buffer these risky pathways. PMID:27765772

Reversing DNA Methylation: Mechanisms, Genomics, and Biological Functions

PubMed Central

Wu, Hao; Zhang, Yi

2014-01-01

Methylation of cytosines in the mammalian genome represents a key epigenetic modification and is dynamically regulated during development. Compelling evidence now suggests that dynamic regulation of DNA methylation is mainly achieved through a cyclic enzymatic cascade comprised of cytosine methylation, iterative oxidation of methyl group by TET dioxygenases, and restoration of unmodified cytosines by either replication-dependent dilution or DNA glycosylase-initiated base excision repair. In this review, we discuss the mechanism and function of DNA demethylation in mammalian genomes, focusing particularly on how developmental modulation of the cytosine-modifying pathway is coupled to active reversal of DNA methylation in diverse biological processes. PMID:24439369

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.

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

PubMed

Dougherty, Michael P

2010-01-01

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

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.

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

PubMed

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

2014-12-01

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

Proteomics for understanding miRNA biology

PubMed Central

Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh

2013-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164

Green leaf volatiles: biosynthesis, biological functions and their applications in biotechnology.

PubMed

ul Hassan, Muhammad Naeem; Zainal, Zamri; Ismail, Ismanizan

2015-08-01

Plants have evolved numerous constitutive and inducible defence mechanisms to cope with biotic and abiotic stresses. These stresses induce the expression of various genes to activate defence-related pathways that result in the release of defence chemicals. One of these defence mechanisms is the oxylipin pathway, which produces jasmonates, divinylethers and green leaf volatiles (GLVs) through the peroxidation of polyunsaturated fatty acids (PUFAs). GLVs have recently emerged as key players in plant defence, plant-plant interactions and plant-insect interactions. Some GLVs inhibit the growth and propagation of plant pathogens, including bacteria, viruses and fungi. In certain cases, GLVs released from plants under herbivore attack can serve as aerial messengers to neighbouring plants and to attract parasitic or parasitoid enemies of the herbivores. The plants that perceive these volatile signals are primed and can then adapt in preparation for the upcoming challenges. Due to their 'green note' odour, GLVs impart aromas and flavours to many natural foods, such as vegetables and fruits, and therefore, they can be exploited in industrial biotechnology. The aim of this study was to review the progress and recent developments in research on the oxylipin pathway, with a specific focus on the biosynthesis and biological functions of GLVs and their applications in industrial biotechnology. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Ensuring Biologics Advanced Development and Manufacturing Capability for the United States Government: A Summary of Key Findings and Conclusions

DTIC Science & Technology

2009-10-06

Government: A Summary of Key Findings and Conclusions. This report has passed the Department of Defense’s security review process and is approved for...manufacturing and combine advance development and production of biologics in a multi-product facility focused on satisfying USG needs. Finally, the study...MCM needs of both DoD and HHS, an extensive survey was conducted. This included a review of all published requirements, the biodefense R&D portfolio

Phosphoketolase pathway engineering for carbon-efficient biocatalysis

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

Henard, Calvin Andrew; Freed, Emily Frances; Guarnieri, Michael Thomas

2015-12-01

Recent advances in metabolic engineering have facilitated the development of microbial biocatalysts capable of producing an array of bio-products, ranging from fuels to drug molecules. These bio-products are commonly generated through an acetyl-CoA intermediate, which serves as a key precursor in the biological conversion of carbon substrates. Moreover, conventional biocatalytic upgrading strategies proceeding through this route are limited by low carbon efficiencies, in large part due to carbon losses associated with pyruvate decarboxylation to acetyl-CoA. Bypass of pyruvate decarboxylation offers a means to dramatically enhance carbon yields and, in turn, bioprocess economics. Here, we discuss recent advances and prospects formore » employing the phosphoketolase pathway for direct biosynthesis of acetyl-CoA from carbon substrates, and phosphoketolase-based metabolic engineering strategies for carbon efficient biocatalysis.« less

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

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

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

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

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

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

DOE PAGES

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

2016-11-01

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

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

PubMed

Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing

2011-07-01

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

The β-cyanoalanine synthase pathway: beyond cyanide detoxification.

PubMed

Machingura, Marylou; Salomon, Eitan; Jez, Joseph M; Ebbs, Stephen D

2016-10-01

Production of cyanide through biological and environmental processes requires the detoxification of this metabolic poison. In the 1960s, discovery of the β-cyanoalanine synthase (β-CAS) pathway in cyanogenic plants provided the first insight on cyanide detoxification in nature. Fifty years of investigations firmly established the protective role of the β-CAS pathway in cyanogenic plants and its role in the removal of cyanide produced from ethylene synthesis in plants, but also revealed the importance of this pathway for plant growth and development and the integration of nitrogen and sulfur metabolism. This review describes the β-CAS pathway, its distribution across and within higher plants, and the diverse biological functions of the pathway in cyanide assimilation, plant growth and development, stress tolerance, regulation of cyanide and sulfide signalling, and nitrogen and sulfur metabolism. The collective roles of the β-CAS pathway highlight its potential evolutionary and ecological importance in plants. © 2016 John Wiley & Sons Ltd.

A Western blot-based investigation of the yeast secretory pathway designed for an intermediate-level undergraduate cell biology laboratory.

PubMed

Hood-Degrenier, Jennifer K

2008-01-01

The movement of newly synthesized proteins through the endomembrane system of eukaryotic cells, often referred to generally as the secretory pathway, is a topic covered in most intermediate-level undergraduate cell biology courses. An article previously published in this journal described a laboratory exercise in which yeast mutants defective in two distinct steps of protein secretion were differentiated using a genetic reporter designed specifically to identify defects in the first step of the pathway, the insertion of proteins into the endoplasmic reticulum (Vallen, 2002). We have developed two versions of a Western blotting assay that serves as a second way of distinguishing the two secretory mutants, which we pair with the genetic assay in a 3-wk laboratory module. A quiz administered before and after students participated in the lab activities revealed significant postlab gains in their understanding of the secretory pathway and experimental techniques used to study it. A second survey administered at the end of the lab module assessed student perceptions of the efficacy of the lab activities; the results of this survey indicated that the experiments were successful in meeting a set of educational goals defined by the instructor.

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment

PubMed Central

Brockmeier, Erica K.; Hodges, Geoff; Hutchinson, Thomas H.; Butler, Emma; Hecker, Markus; Tollefsen, Knut Erik; Garcia-Reyero, Natalia; Kille, Peter; Becker, Dörthe; Chipman, Kevin; Colbourne, John; Collette, Timothy W.; Cossins, Andrew; Cronin, Mark; Graystock, Peter; Gutsell, Steve; Knapen, Dries; Katsiadaki, Ioanna; Lange, Anke; Marshall, Stuart; Owen, Stewart F.; Perkins, Edward J.; Plaistow, Stewart; Schroeder, Anthony; Taylor, Daisy; Viant, Mark; Ankley, Gerald; Falciani, Francesco

2017-01-01

Abstract In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework. PMID:28525648

Evidence for the Induction of Key Components of the NOTCH Signaling Pathway via Deltamethrin and Azamethiphos Treatment in the Sea Louse Caligus rogercresseyi

PubMed Central

Boltaña, Sebastian; Chávez-Mardones, Jaqueline; Valenzuela-Muñoz, Valentina; Gallardo-Escárate, Cristian

2016-01-01

The extensive use of organophosphates and pyrethroids in the aquaculture industry has negatively impacted parasite sensitivity to the delousing effects of these antiparasitics, especially among sea lice species. The NOTCH signaling pathway is a positive regulator of ABC transporter subfamily C expression and plays a key role in the generation and modulation of pesticide resistance. However, little is known about the molecular mechanisms behind pesticide resistance, partly due to the lack of genomic and molecular information on the processes involved in the resistance mechanism of sea lice. Next-generation sequencing technologies provide an opportunity for rapid and cost-effective generation of genome-scale data. The present study, through RNA-seq analysis, determined that the sea louse Caligus rogercresseyi (C. rogercresseyi) specifically responds to the delousing drugs azamethiphos and deltamethrin at the transcriptomic level by differentially activating mRNA of the NOTCH signaling pathway and of ABC genes. These results suggest that frequent antiparasitic application may increase the activity of inhibitory mRNA components, thereby promoting inhibitory NOTCH output and conditions for increased resistance to delousing drugs. Moreover, data analysis underscored that key functions of NOTCH/ABC components were regulated during distinct phases of the drug response, thus indicating resistance modifications in C. rogercresseyi resulting from the frequent use of organophosphates and pyrethroids. PMID:27187362

Evidence for the Induction of Key Components of the NOTCH Signaling Pathway via Deltamethrin and Azamethiphos Treatment in the Sea Louse Caligus rogercresseyi.

PubMed

Boltaña, Sebastian; Chávez-Mardones, Jaqueline; Valenzuela-Muñoz, Valentina; Gallardo-Escárate, Cristian

2016-05-12

The extensive use of organophosphates and pyrethroids in the aquaculture industry has negatively impacted parasite sensitivity to the delousing effects of these antiparasitics, especially among sea lice species. The NOTCH signaling pathway is a positive regulator of ABC transporter subfamily C expression and plays a key role in the generation and modulation of pesticide resistance. However, little is known about the molecular mechanisms behind pesticide resistance, partly due to the lack of genomic and molecular information on the processes involved in the resistance mechanism of sea lice. Next-generation sequencing technologies provide an opportunity for rapid and cost-effective generation of genome-scale data. The present study, through RNA-seq analysis, determined that the sea louse Caligus rogercresseyi (C. rogercresseyi) specifically responds to the delousing drugs azamethiphos and deltamethrin at the transcriptomic level by differentially activating mRNA of the NOTCH signaling pathway and of ABC genes. These results suggest that frequent antiparasitic application may increase the activity of inhibitory mRNA components, thereby promoting inhibitory NOTCH output and conditions for increased resistance to delousing drugs. Moreover, data analysis underscored that key functions of NOTCH/ABC components were regulated during distinct phases of the drug response, thus indicating resistance modifications in C. rogercresseyi resulting from the frequent use of organophosphates and pyrethroids.

Premetazoan origin of the Hippo signaling pathway

PubMed Central

Sebé-Pedrós, Arnau; Zheng, Yonggang; Ruiz-Trillo, Iñaki; Pan, Duojia

2012-01-01

Summary Non-aggregative multicellularity requires strict control of cell number. The Hippo signaling pathway coordinates cell proliferation and apoptosis and is a central regulator of organ size in animals. Recent studies have shown the presence of key members of the Hippo pathway in non-bilaterian animals, but failed to identify this pathway outside Metazoa. Through comparative analyses of recently sequenced holozoan genomes, we show that Hippo pathway components, such as the kinases Hippo and Warts, the co-activator Yorkie and the transcription factor Scalloped, were already present in the unicellular ancestors of animals. Remarkably, functional analysis of Hippo components of the amoeboid holozoan Capsaspora owczarzaki, performed in Drosophila, demonstrate that the growth-regulatory activity of the Hippo pathway is conserved in this unicellular lineage. Our findings show that the Hippo pathway evolved well before the origin of Metazoa and highlight the importance of Hippo signaling as a key developmental mechanism pre-dating the origin of Metazoa. PMID:22832104

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

PubMed

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

2017-02-15

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

Key data elements for use in cost-utility modeling of biological treatments for rheumatoid arthritis.

PubMed

Ganz, Michael L; Hansen, Brian Bekker; Valencia, Xavier; Strandberg-Larsen, Martin

2015-05-01

Economic evaluation is becoming more common and important as new biologic therapies for rheumatoid arthritis (RA) are developed. While much has been published about how to design cost-utility models for RA to conduct these evaluations, less has been written about the sources of data populating those models. The goal is to review the literature and to provide recommendations for future data collection efforts. This study reviewed RA cost-utility models published between January 2006 and February 2014 focusing on five key sources of data (health-related quality-of-life and utility, clinical outcomes, disease progression, course of treatment, and healthcare resource use and costs). It provided recommendations for collecting the appropriate data during clinical and other studies to support modeling of biologic treatments for RA. Twenty-four publications met the selection criteria. Almost all used two steps to convert clinical outcomes data to utilities rather than more direct methods; most did not use clinical outcomes measures that captured absolute levels of disease activity and physical functioning; one-third of them, in contrast with clinical reality, assumed zero disease progression for biologic-treated patients; little more than half evaluated courses of treatment reflecting guideline-based or actual clinical care; and healthcare resource use and cost data were often incomplete. Based on these findings, it is recommended that future studies collect clinical outcomes and health-related quality-of-life data using appropriate instruments that can convert directly to utilities; collect data on actual disease progression; be designed to capture real-world courses of treatment; and collect detailed data on a wide range of healthcare resources and costs.

Dopamine signaling and myopia development: What are the key challenges.

PubMed

Zhou, Xiangtian; Pardue, Machelle T; Iuvone, P Michael; Qu, Jia

2017-11-01

In the face of an "epidemic" increase in myopia over the last decades and myopia prevalence predicted to reach 2.5 billion people by the end of this decade, there is an urgent need to develop effective and safe therapeutic interventions to slow down this "myopia booming" and prevent myopia-related complications and vision loss. Dopamine (DA) is an important neurotransmitter in the retina and mediates diverse functions including retina development, visual signaling, and refractive development. Inspired by the convergence of epidemiological and animal studies in support of the inverse relationship between outdoor activity and risk of developing myopia and by the close biological relationship between light exposure and dopamine release/signaling, we felt it is timely and important to critically review the role of DA in myopia development. This review will revisit several key points of evidence for and against DA mediating light control of myopia: 1) the causal role of extracellular retinal DA levels, 2) the mechanism and action of dopamine D1 and D2 receptors and 3) the roles of cellular/circuit retinal pathways. We examine the experiments that show causation by altering DA, DA receptors and visual pathways using pharmacological, transgenic, or visual environment approaches. Furthermore, we critically evaluate the safety issues of a DA-based treatment strategy and some approaches to address these issues. The review identifies the key questions and challenges in translating basic knowledge on DA signaling and myopia from animal studies into effective pharmacological treatments for myopia in children. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Pathway modulations and epigenetic alterations in ovarian tumorbiogenesis

PubMed Central

Saldanha, Sabita N.; Tollefsbol, Trygve O.

2013-01-01

Cellular pathways are numerous and are highly integrated in function in the control of cellular systems. They collectively regulate cell division, proliferation, survival and apoptosis of cells and mutagenesis of key genes that control these pathways can initiate neoplastic transformations. Understanding these pathways is crucial to future therapeutic and preventive strategies of the disease. Ovarian cancers are of three major types; epithelial, germ-cell and stromal. However, ovarian cancers of epithelial origin, arising from the mesothelium, are the predominant form. Of the subtypes of ovarian cancer, the high-grade serous tumors are fatal, with low survival rate due to late detection and poor response to treatments. Close examination of preserved ovarian tissues and in vitro studies have provided insights into the mechanistic changes occurring in cells mediated by a few key genes. This review will focus on pathways and key genes of the pathways that are mutated or have aberrant functions in the pathology of ovarian cancer. Non-genetic mechanisms that are gaining prominence in the pathology of ovarian cancer, miRNAs and epigenetics, will also be discussed in the review. PMID:24105793

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

A Skyline Plugin for Pathway-Centric Data Browsing

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

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach SRM assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). Themore » same plugin can be used for hypothesis-drive DIA data analysis, again utilizing the pathway view to help narrow down the set of proteins which will be investigated. The plugin is backed by the PNNL Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.« less

Epoxide pathways improve model predictions of isoprene markers and reveal key role of acidity in aerosol formation.

PubMed

Pye, Havala O T; Pinder, Robert W; Piletic, Ivan R; Xie, Ying; Capps, Shannon L; Lin, Ying-Hsuan; Surratt, Jason D; Zhang, Zhenfa; Gold, Avram; Luecken, Deborah J; Hutzell, William T; Jaoui, Mohammed; Offenberg, John H; Kleindienst, Tadeusz E; Lewandowski, Michael; Edney, Edward O

2013-10-01

Isoprene significantly contributes to organic aerosol in the southeastern United States where biogenic hydrocarbons mix with anthropogenic emissions. In this work, the Community Multiscale Air Quality model is updated to predict isoprene aerosol from epoxides produced under both high- and low-NOx conditions. The new aqueous aerosol pathways allow for explicit predictions of two key isoprene-derived species, 2-methyltetrols and 2-methylglyceric acid, that are more consistent with observations than estimates based on semivolatile partitioning. The new mechanism represents a significant source of organic carbon in the lower 2 km of the atmosphere and captures the abundance of 2-methyltetrols relative to organosulfates during the simulation period. For the parametrization considered here, a 25% reduction in SOx emissions effectively reduces isoprene aerosol, while a similar reduction in NOx leads to small increases in isoprene aerosol.

Synthetic biology for CO2 fixation.

PubMed

Gong, Fuyu; Cai, Zhen; Li, Yin

2016-11-01

Recycling of carbon dioxide (CO 2 ) into fuels and chemicals is a potential approach to reduce CO 2 emission and fossil-fuel consumption. Autotrophic microbes can utilize energy from light, hydrogen, or sulfur to assimilate atmospheric CO 2 into organic compounds at ambient temperature and pressure. This provides a feasible way for biological production of fuels and chemicals from CO 2 under normal conditions. Recently great progress has been made in this research area, and dozens of CO 2 -derived fuels and chemicals have been reported to be synthesized by autotrophic microbes. This is accompanied by investigations into natural CO 2 -fixation pathways and the rapid development of new technologies in synthetic biology. This review first summarizes the six natural CO 2 -fixation pathways reported to date, followed by an overview of recent progress in the design and engineering of CO 2 -fixation pathways as well as energy supply patterns using the concept and tools of synthetic biology. Finally, we will discuss future prospects in biological fixation of CO 2 .

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...

Improving pathways to primary health care among LGBTQ populations and health care providers: key findings from Nova Scotia, Canada.

PubMed

Gahagan, Jacqueline; Subirana-Malaret, Montse

2018-06-13

This study explores the perceived barriers to primary health care as identified among a sample of Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ) identified individuals and health care providers in Nova Scotia, Canada. These findings, based on a province-wide anonymous online survey, suggest that additional efforts are needed to improve pathways to primary health among LGBTQ populations and in deepening our understanding of how to advance the unique primary health needs of these populations. Data were collected from the LGBTQ community through an online, closed-ended anonymous survey. Inclusion criteria for participation were self-identifying as LGBTQ, offering primary health care to LGBTQ patients, being able to understand English, being 16 years of age or older, and having lived in Nova Scotia for at least one year. A total of 283 LGBTQ respondents completed the online survey which included sociodemographic questions, perceptions of respondents' health status, and their primary health care experiences. In addition, a total of 109 health care providers completed the survey based on their experiences providing care in Nova Scotia, and in particular, their experiences and perceptions regarding LGBTQ access to primary health care and physician-patient interactions. Our results indicate that, in several key areas, the primary health care needs of LGBTQ populations in Nova Scotia are not being met and this may in turn contribute to their poor health outcomes across the life course. A framework of intersectionality and health equity was used to interpret and analyze the survey data. The key findings indicate the need to continue improving pathways to primary health care among LGBTQ populations, specifically in relation to additional training and related supports for health care providers who work with these populations.

Understanding the Contribution of Zinc Transporters in the Function of the Early Secretory Pathway

PubMed Central

Matsunaga, Mayu; Takeda, Taka-aki

2017-01-01

More than one-third of newly synthesized proteins are targeted to the early secretory pathway, which is comprised of the endoplasmic reticulum (ER), Golgi apparatus, and other intermediate compartments. The early secretory pathway plays a key role in controlling the folding, assembly, maturation, modification, trafficking, and degradation of such proteins. A considerable proportion of the secretome requires zinc as an essential factor for its structural and catalytic functions, and recent findings reveal that zinc plays a pivotal role in the function of the early secretory pathway. Hence, a disruption of zinc homeostasis and metabolism involving the early secretory pathway will lead to pathway dysregulation, resulting in various defects, including an exacerbation of homeostatic ER stress. The accumulated evidence indicates that specific members of the family of Zn transporters (ZNTs) and Zrt- and Irt-like proteins (ZIPs), which operate in the early secretory pathway, play indispensable roles in maintaining zinc homeostasis by regulating the influx and efflux of zinc. In this review, the biological functions of these transporters are discussed, focusing on recent aspects of their roles. In particular, we discuss in depth how specific ZNT transporters are employed in the activation of zinc-requiring ectoenzymes. The means by which early secretory pathway functions are controlled by zinc, mediated by specific ZNT and ZIP transporters, are also subjects of this review. PMID:29048339

Understanding the Contribution of Zinc Transporters in the Function of the Early Secretory Pathway.

PubMed

Kambe, Taiho; Matsunaga, Mayu; Takeda, Taka-Aki

2017-10-19

More than one-third of newly synthesized proteins are targeted to the early secretory pathway, which is comprised of the endoplasmic reticulum (ER), Golgi apparatus, and other intermediate compartments. The early secretory pathway plays a key role in controlling the folding, assembly, maturation, modification, trafficking, and degradation of such proteins. A considerable proportion of the secretome requires zinc as an essential factor for its structural and catalytic functions, and recent findings reveal that zinc plays a pivotal role in the function of the early secretory pathway. Hence, a disruption of zinc homeostasis and metabolism involving the early secretory pathway will lead to pathway dysregulation, resulting in various defects, including an exacerbation of homeostatic ER stress. The accumulated evidence indicates that specific members of the family of Zn transporters (ZNTs) and Zrt- and Irt-like proteins (ZIPs), which operate in the early secretory pathway, play indispensable roles in maintaining zinc homeostasis by regulating the influx and efflux of zinc. In this review, the biological functions of these transporters are discussed, focusing on recent aspects of their roles. In particular, we discuss in depth how specific ZNT transporters are employed in the activation of zinc-requiring ectoenzymes. The means by which early secretory pathway functions are controlled by zinc, mediated by specific ZNT and ZIP transporters, are also subjects of this review.

Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery.

PubMed

Drawnel, Faye Marie; Zhang, Jitao David; Küng, Erich; Aoyama, Natsuyo; Benmansour, Fethallah; Araujo Del Rosario, Andrea; Jensen Zoffmann, Sannah; Delobel, Frédéric; Prummer, Michael; Weibel, Franziska; Carlson, Coby; Anson, Blake; Iacone, Roberto; Certa, Ulrich; Singer, Thomas; Ebeling, Martin; Prunotto, Marco

2017-05-18

Today, novel therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping was applicable to compounds with a range of binding specificities and triaged false positives derived from high-content screening assays. The technique identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. Our results advocate for application of molecular phenotyping in early drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome-wide expression profiling analysis to identify key genes in the anti-HIV mechanism of CD4+ and CD8+ T cells.

PubMed

Gao, Lijie; Wang, Yunqi; Li, Yi; Dong, Ya; Yang, Aimin; Zhang, Jie; Li, Fengying; Zhang, Rongqiang

2018-07-01

Comprehensive bioinformatics analyses were performed to explore the key biomarkers in response to HIV infection of CD4 + and CD8 + T cells. The numbers of CD4 + and CD8 + T cells of HIV infected individuals were analyzed and the GEO database (GSE6740) was screened for differentially expressed genes (DEGs) in HIV infected CD4 + and CD8 + T cells. Gene Ontology enrichment, KEGG pathway analyses, and protein-protein interaction (PPI) network were performed to identify the key pathway and core proteins in anti-HIV virus process of CD4 + and CD8 + T cells. Finally, we analyzed the expressions of key proteins in HIV-infected T cells (GSE6740 dataset) and peripheral blood mononuclear cells(PBMCs) (GSE511 dataset). 1) CD4 + T cells counts and ratio of CD4 + /CD8 + T cells decreased while CD8 + T cells counts increased in HIV positive individuals; 2) 517 DEGs were found in HIV infected CD4 + and CD8 + T cells at acute and chronic stage with the criterial of P-value <0.05 and fold change (FC) ≥2; 3) In acute HIV infection, type 1 interferon (IFN-1) pathway might played a critical role in response to HIV infection of T cells. The main biological processes of the DEGs were response to virus and defense response to virus. At chronic stage, ISG15 protein, in conjunction with IFN-1 pathway might play key roles in anti-HIV responses of CD4 + T cells; and 4) The expression of ISG15 increased in both T cells and PBMCs after HIV infection. Gene expression profile of CD4 + and CD8 + T cells changed significantly in HIV infection, in which ISG15 gene may play a central role in activating the natural antiviral process of immune cells. © 2018 Wiley Periodicals, Inc.

Nano-risk Science: application of toxicogenomics in an adverse outcome pathway framework for risk assessment of multi-walled carbon nanotubes.

PubMed

Labib, Sarah; Williams, Andrew; Yauk, Carole L; Nikota, Jake K; Wallin, Håkan; Vogel, Ulla; Halappanavar, Sabina

2016-03-15

A diverse class of engineered nanomaterials (ENMs) exhibiting a wide array of physical-chemical properties that are associated with toxicological effects in experimental animals is in commercial use. However, an integrated framework for human health risk assessment (HHRA) of ENMs has yet to be established. Rodent 2-year cancer bioassays, clinical chemistry, and histopathological endpoints are still considered the 'gold standard' for detecting substance-induced toxicity in animal models. However, the use of data derived from alternative toxicological tools, such as genome-wide expression profiling and in vitro high-throughput assays, are gaining acceptance by the regulatory community for hazard identification and for understanding the underlying mode-of-action. Here, we conducted a case study to evaluate the application of global gene expression data in deriving pathway-based points of departure (PODs) for multi-walled carbon nanotube (MWCNT)-induced lung fibrosis, a non-cancer endpoint of regulatory importance. Gene expression profiles from the lungs of mice exposed to three individual MWCNTs with different physical-chemical properties were used within the framework of an adverse outcome pathway (AOP) for lung fibrosis to identify key biological events linking MWCNT exposure to lung fibrosis. Significantly perturbed pathways were categorized along the key events described in the AOP. Benchmark doses (BMDs) were calculated for each perturbed pathway and were used to derive transcriptional BMDs for each MWCNT. Similar biological pathways were perturbed by the different MWCNT types across the doses and post-exposure time points studied. The pathway BMD values showed a time-dependent trend, with lower BMDs for pathways perturbed at the earlier post-exposure time points (24 h, 3d). The transcriptional BMDs were compared to the apical BMDs derived by the National Institute for Occupational Safety and Health (NIOSH) using alveolar septal thickness and fibrotic lesions

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

PubMed

Pashaiasl, Maryam; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2016-09-01

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

AOP: An R Package For Sufficient Causal Analysis in Pathway ...

EPA Pesticide Factsheets

Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. By identifying these sufficient causal key events, we have fewer events to monitor for a pathway, thereby decreasing assay costs and time, while maximizing the value of the information. I have developed the “aop” package which uses backdoor analysis of causal net-works to identify these minimal sets of key events that are suf-ficient for making causal predictions. Availability and Implementation: The source and binary are available online through the Bioconductor project (http://www.bioconductor.org/) as an R package titled “aop”. The R/Bioconductor package runs within the R statistical envi-ronment. The package has functions that can take pathways (as directed graphs) formatted as a Cytoscape JSON file as input, or pathways can be represented as directed graphs us-ing the R/Bioconductor “graph” package. The “aop” package has functions that can perform backdoor analysis to identify the minimal set of key events for making causal predictions.Contact: burgoon.lyle@epa.gov This paper describes an R/Bioconductor package that was developed to facilitate the identification of key events within an AOP that are the minimal set of sufficient key events that need to be tested/monit

Targeting Cytosolic Nucleic Acid-Sensing Pathways for Cancer Immunotherapies.

PubMed

Iurescia, Sandra; Fioretti, Daniela; Rinaldi, Monica

2018-01-01

The innate immune system provides the first line of defense against pathogen infection though also influences pathways involved in cancer immunosurveillance. The innate immune system relies on a limited set of germ line-encoded sensors termed pattern recognition receptors (PRRs), signaling proteins and immune response factors. Cytosolic receptors mediate recognition of danger damage-associated molecular patterns (DAMPs) signals. Once activated, these sensors trigger multiple signaling cascades, converging on the production of type I interferons and proinflammatory cytokines. Recent studies revealed that PRRs respond to nucleic acids (NA) released by dying, damaged, cancer cells, as danger DAMPs signals, and presence of signaling proteins across cancer types suggests that these signaling mechanisms may be involved in cancer biology. DAMPs play important roles in shaping adaptive immune responses through the activation of innate immune cells and immunological response to danger DAMPs signals is crucial for the host response to cancer and tumor rejection. Furthermore, PRRs mediate the response to NA in several vaccination strategies, including DNA immunization. As route of double-strand DNA intracellular entry, DNA immunization leads to expression of key components of cytosolic NA-sensing pathways. The involvement of NA-sensing mechanisms in the antitumor response makes these pathways attractive drug targets. Natural and synthetic agonists of NA-sensing pathways can trigger cell death in malignant cells, recruit immune cells, such as DCs, CD8 + T cells, and NK cells, into the tumor microenvironment and are being explored as promising adjuvants in cancer immunotherapies. In this minireview, we discuss how cGAS-STING and RIG-I-MAVS pathways have been targeted for cancer treatment in preclinical translational researches. In addition, we present a targeted selection of recent clinical trials employing agonists of cytosolic NA-sensing pathways showing how these pathways

Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

PubMed

Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

2016-01-01

Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

Angiosperms Are Unique among Land Plant Lineages in the Occurrence of Key Genes in the RNA-Directed DNA Methylation (RdDM) Pathway

PubMed Central

Ma, Lu; Hatlen, Andrea; Kelly, Laura J.; Becher, Hannes; Wang, Wencai; Kovarik, Ales; Leitch, Ilia J.; Leitch, Andrew R.

2015-01-01

The RNA-directed DNA methylation (RdDM) pathway can be divided into three phases: 1) small interfering RNA biogenesis, 2) de novo methylation, and 3) chromatin modification. To determine the degree of conservation of this pathway we searched for key genes among land plants. We used OrthoMCL and the OrthoMCL Viridiplantae database to analyze proteomes of species in bryophytes, lycophytes, monilophytes, gymnosperms, and angiosperms. We also analyzed small RNA size categories and, in two gymnosperms, cytosine methylation in ribosomal DNA. Six proteins were restricted to angiosperms, these being NRPD4/NRPE4, RDM1, DMS3 (defective in meristem silencing 3), SHH1 (SAWADEE homeodomain homolog 1), KTF1, and SUVR2, although we failed to find the latter three proteins in Fritillaria persica, a species with a giant genome. Small RNAs of 24 nt in length were abundant only in angiosperms. Phylogenetic analyses of Dicer-like (DCL) proteins showed that DCL2 was restricted to seed plants, although it was absent in Gnetum gnemon and Welwitschia mirabilis. The data suggest that phases (1) and (2) of the RdDM pathway, described for model angiosperms, evolved with angiosperms. The absence of some features of RdDM in F. persica may be associated with its large genome. Phase (3) is probably the most conserved part of the pathway across land plants. DCL2, involved in virus defense and interaction with the canonical RdDM pathway to facilitate methylation of CHH, is absent outside seed plants. Its absence in G. gnemon, and W. mirabilis coupled with distinctive patterns of CHH methylation, suggest a secondary loss of DCL2 following the divergence of Gnetales. PMID:26338185

Engineering plant metabolism into microbes: from systems biology to synthetic biology.

PubMed

Xu, Peng; Bhan, Namita; Koffas, Mattheos A G

2013-04-01

Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

The adverse outcome pathway concept: a pragmatic tool in toxicology.

PubMed

Vinken, Mathieu

2013-10-04

Adverse outcome pathways (AOPs) are novel tools in toxicology and human risk assessment with broad potential. AOPs are designed to provide a clear-cut mechanistic representation of critical toxicological effects that span over different layers of biological organization. AOPs share a common structure consisting of a molecular initiating event, a series of intermediate steps and key events, and an adverse outcome. Development of AOPs ideally complies with OECD guidelines. This also holds true for AOP evaluation, which includes consideration of the Bradford Hill criteria for weight-of-evidence assessment and meeting a set of key questions defined by the OECD. Elaborate AOP frameworks have yet been proposed for chemical-induced skin sensitization, cholestasis, liver fibrosis and liver steatosis. These newly postulated AOPs can serve a number of ubiquitous purposes, including the establishment of (quantitative) structure-activity relationships, the development of novel in vitro toxicity screening tests and the elaboration of prioritization strategies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Reputation-based collaborative network biology.

PubMed

Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Fields, R Brett; Hayes, William; Hoeng, Julia; Park, Jennifer S; Peitsch, Manuel C

2015-01-01

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

EphA2 is a key effector of the MEK/ERK/RSK pathway regulating glioblastoma cell proliferation.

PubMed

Hamaoka, Yuho; Negishi, Manabu; Katoh, Hironori

2016-08-01

EphA2, a member of the Eph receptor tyrosine kinases, is frequently overexpressed in a variety of malignancies, including glioblastoma, and its expression is correlated with poor prognosis. EphA2 acts as a tumor promoter through a ligand ephrin-independent mechanism, which requires phosphorylation of EphA2 on serine 897 (S897), leading to increased cell migration and invasion. In this study, we show that ligand-independent EphA2 signaling occurs downstream of the MEK/ERK/RSK pathway and mediates epidermal growth factor (EGF)-induced cell proliferation in glioblastoma cells. Suppression of EphA2 expression by long-term exposure to ligand ephrinA1 or EphA2-targeted shRNA inhibited EGF-induced cell proliferation. Stimulation of the cells with EGF induced EphA2 S897 phosphorylation, which was suppressed by MEK and RSK inhibitors, but not by phosphatidylinositol 3-kinase (PI3K) and Akt inhibitors. The RSK inhibitor or RSK2-targeted shRNA also suppressed EGF-induced cell proliferation. Furthermore, overexpression of wild-type EphA2 promoted cell proliferation without EGF stimulation, whereas overexpression of EphA2-S897A mutant suppressed EGF- or RSK2-induced proliferation. Taken together, these results suggest that EphA2 is a key downstream target of the MEK/ERK/RSK signaling pathway in the regulation of glioblastoma cell proliferation. Copyright © 2016 Elsevier Inc. All rights reserved.

Proteomics for understanding miRNA biology.

PubMed

Huang, Tai-Chung; Pinto, Sneha M; Pandey, Akhilesh

2013-02-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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...

Molecular Signaling Pathways Behind the Biological Effects of Salvia Species Diterpenes in Neuropharmacology and Cardiology.

PubMed

Akaberi, M; Iranshahi, M; Mehri, S

2016-06-01

The genus Salvia, from the Lamiaceae family, has diverse biological properties that are primarily attributable to their diterpene contents. There is no comprehensive review on the molecular signaling pathways of these active components. In this review, we investigated the molecular targets of bioactive Salvia diterpenes responsible for the treatment of nervous and cardiovascular diseases. The effects on different pathways, including apoptosis signaling, oxidative stress phenomena, the accumulation of amyloid beta plaques, and tau phosphorylation, have all been considered to be mechanisms of the anti-Alzheimer properties of Salvia diterpenes. Additionally, effects on the benzodiazepine and kappa opioid receptors and neuroprotective effects are noted as neuropharmacological properties of Salvia diterpenes, including tanshinone IIA, salvinorin A, cryptotanshinone, and miltirone. Tanshinone IIA, as the primary diterpene of Salvia miltiorrhiza, has beneficial activities in heart diseases because of its ability to scavenge free radicals and its effects on transcription factors, such as nuclear transcription factor-kappa B (NF-κB) and the mitogen-activated protein kinases (MAPKs). Additionally, tanshinone IIA has also been proposed to have cardioprotective properties including antiarrhythmic activities and effects on myocardial infarction. With respect to the potential therapeutic effects of Salvia diterpenes, comprehensive clinical trials are warranted to evaluate these valuable molecules as lead compounds. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

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

Biological valorization of low molecular weight lignin.

PubMed

Abdelaziz, Omar Y; Brink, Daniel P; Prothmann, Jens; Ravi, Krithika; Sun, Mingzhe; García-Hidalgo, Javier; Sandahl, Margareta; Hulteberg, Christian P; Turner, Charlotta; Lidén, Gunnar; Gorwa-Grauslund, Marie F

2016-12-01

Lignin is a major component of lignocellulosic biomass and as such, it is processed in enormous amounts in the pulp and paper industry worldwide. In such industry it mainly serves the purpose of a fuel to provide process steam and electricity, and to a minor extent to provide low grade heat for external purposes. Also from other biorefinery concepts, including 2nd generation ethanol, increasing amounts of lignin will be generated. Other uses for lignin - apart from fuel production - are of increasing interest not least in these new biorefinery concepts. These new uses can broadly be divided into application of the polymer as such, native or modified, or the use of lignin as a feedstock for the production of chemicals. The present review focuses on the latter and in particular the advances in the biological routes for chemicals production from lignin. Such a biological route will likely involve an initial depolymerization, which is followed by biological conversion of the obtained smaller lignin fragments. The conversion can be either a short catalytic conversion into desired chemicals, or a longer metabolic conversion. In this review, we give a brief summary of sources of lignin, methods of depolymerization, biological pathways for conversion of the lignin monomers and the analytical tools necessary for characterizing and evaluating key lignin attributes. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

MicroRNA expression, target genes, and signaling pathways in infants with a ventricular septal defect.

PubMed

Chai, Hui; Yan, Zhaoyuan; Huang, Ke; Jiang, Yuanqing; Zhang, Lin

2018-02-01

This study aimed to systematically investigate the relationship between miRNA expression and the occurrence of ventricular septal defect (VSD), and characterize the miRNA target genes and pathways that can lead to VSD. The miRNAs that were differentially expressed in blood samples from VSD and normal infants were screened and validated by implementing miRNA microarrays and qRT-PCR. The target genes regulated by differentially expressed miRNAs were predicted using three target gene databases. The functions and signaling pathways of the target genes were enriched using the GO database and KEGG database, respectively. The transcription and protein expression of specific target genes in critical pathways were compared in the VSD and normal control groups using qRT-PCR and western blotting, respectively. Compared with the normal control group, the VSD group had 22 differentially expressed miRNAs; 19 were downregulated and three were upregulated. The 10,677 predicted target genes participated in many biological functions related to cardiac development and morphogenesis. Four target genes (mGLUR, Gq, PLC, and PKC) were involved in the PKC pathway and four (ECM, FAK, PI3 K, and PDK1) were involved in the PI3 K-Akt pathway. The transcription and protein expression of these eight target genes were significantly upregulated in the VSD group. The 22 miRNAs that were dysregulated in the VSD group were mainly downregulated, which may result in the dysregulation of several key genes and biological functions related to cardiac development. These effects could also be exerted via the upregulation of eight specific target genes, the subsequent over-activation of the PKC and PI3 K-Akt pathways, and the eventual abnormal cardiac development and VSD.

A safety assessment of biological therapies targeting the IL-23/IL-17 axis in inflammatory bowel diseases.

PubMed

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

2017-07-01

Many different compounds targeting the interleukin 23/17 axis have been developed and successfully studied in several autoimmune diseases, including inflammatory bowel diseases. Nevertheless, interfering with key immunological pathways raises potential safety concerns. This review focuses on the safety profile of these novel biological therapies. Areas covered: A literature search until March 2017 was performed to collect safety data on different compounds targeting this pathway, with emphasis on ustekinumab and secukinumab. Firstly, the authors discuss briefly how genetics can inform about potential safety issues. Secondly, they extensively describe safety issues (common adverse events, infections, malignancies…), immunogenicity, exposure to ustekinumab in specific populations and provide advice for vaccination. Finally, they address safety profiles of secukinumab and other biological targeting the IL-23/17 axis in IBD. Expert opinion: Current evidence suggests that ustekinumab therapy overweigh the potential drug-related risks. Additional safety data beyond randomized-controlled trials, derived from statistically powered, large prospective studies with long-term follow-up are urgently needed to assess the real-life ustekinumab-related risks and to establish the correct position of these novel class of biologicals in IBD treatment. Combining immunomodulators with ustekinumab seems to be safe, though prospective data specifically addressing this topic are currently missing. Similarly, the combination of different biological therapies still has to be studied.

S100A13-C2A binary complex structure-a key component in the acidic fibroblast growth factor for the non-classical pathway

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

Mohan, Sepuru K.; Rani, Sandhya G.; Kumar, Sriramoju M.

2009-03-13

Fibroblast growth factors (FGFs) are key regulators of cell proliferation, differentiation, tumor-induced angiogenesis and migration. FGFs are essential for early embryonic development, organ formation and angiogenesis. They play important roles in tumor formation, inflammation, wound healing and restenosis. The biological effects of FGFs are mediated through the activation of the four transmembrane phosphotyrosine kinase receptors (FGFRs) in the presence of heparin sulfate proteoglycans (HSPGs) and therefore require the release of FGFs into the extracellular space. However, FGF-1 lacks the signal peptide required for the releasing of these proteins through the classical endoplasmic reticulum (ER)-Golgi secretary pathway. Maciag et al. demonstratedmore » that FGF-1 is exported through a non-classical release pathway involving the formation of a specific multiprotein complex [M. Landriscina, R. Soldi, C. Bagala, I. Micucci, S. Bellum, F. Tarantini, I. Prudovsky, T. Maciag, S100A13 participates in the release of fibroblast growth factor 1 in response to heat shock in vitro, J. Biol. Chem. 276 (2001) 22544-22552; C.M. Carreira, T.M. LaVallee, F. Tarantini, A. Jackson, J.T. Lathrop, B. Hampton, W.H. Burgess, T. Maciag, S100A13 is involved in the regulation of fibroblast growth factor-1 and p40 synaptotagmin-1 release in vitro, J. Biol. Chem. 273 (1998) 22224-22231; T.M. LaValle, F. Tarantini, S. Gamble, C.M. Carreira, A. Jackson, T. Maciag, Synaptotagmin-1 is required for fibroblast growth factor-1 release, J. Biol. Chem. 273 (1998) 22217-22223; C. Bagala, V. Kolev, A. Mandinova, R. Soldi, C. Mouta, I. Graziani, I, Prudovsky, T. Maciag, The alternative translation of synaptotagmin 1 mediates the non-classical release of FGF1, Biochem. Biophys. Res. Commun. 310 (2003) 1041-1047]. The protein constituents of this complex include FGF-1, S100A13 (a Ca{sup 2+}-binding protein), and the p40 form of synaptotagmin 1 (Syt1). To understand the molecular events in the FGF-1

Systems Biology Approach Reveals a Calcium-Dependent Mechanism for Basal Toxicity in Daphnia magna.

PubMed

Antczak, Philipp; White, Thomas A; Giri, Anirudha; Michelangeli, Francesco; Viant, Mark R; Cronin, Mark T D; Vulpe, Chris; Falciani, Francesco

2015-09-15

The expanding diversity and ever increasing amounts of man-made chemicals discharged to the environment pose largely unknown hazards to ecosystem and human health. The concept of adverse outcome pathways (AOPs) emerged as a comprehensive framework for risk assessment. However, the limited mechanistic information available for most chemicals and a lack of biological pathway annotation in many species represent significant challenges to effective implementation of this approach. Here, a systems level, multistep modeling strategy demonstrates how to integrate information on chemical structure with mechanistic insight from genomic studies, and phenotypic effects to define a putative adverse outcome pathway. Results indicated that transcriptional changes indicative of intracellular calcium mobilization were significantly overrepresented in Daphnia magna (DM) exposed to sublethal doses of presumed narcotic chemicals with log Kow ≥ 1.8. Treatment of DM with a calcium ATPase pump inhibitor substantially recapitulated the common transcriptional changes. We hypothesize that calcium mobilization is a potential key molecular initiating event in DM basal (narcosis) toxicity. Heart beat rate analysis and metabolome analysis indicated sublethal effects consistent with perturbations of calcium preceding overt acute toxicity. Together, the results indicate that altered calcium homeostasis may be a key early event in basal toxicity or narcosis induced by lipophilic compounds.

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

PubMed

Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L

2018-01-04

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Waste-Activated Sludge Fermentation for Polyacrylamide Biodegradation Improved by Anaerobic Hydrolysis and Key Microorganisms Involved in Biological Polyacrylamide Removal

PubMed Central

Dai, Xiaohu; Luo, Fan; Zhang, Dong; Dai, Lingling; Chen, Yinguang; Dong, Bin

2015-01-01

During the anaerobic digestion of dewatered sludge, polyacrylamide (PAM), a chemical conditioner, can usually be consumed as a carbon and nitrogen source along with other organic matter (e.g., proteins and carbohydrates in the sludge). However, a significant accumulation of acrylamide monomers (AMs) was observed during the PAM biodegradation process. To improve the anaerobic hydrolysis of PAM, especially the amide hydrolysis process, and to avoid the generation of the intermediate product AM, a new strategy is reported herein that uses an initial pH of 9, 200 mg COD/L of PAM and a fermentation time of 17 d. First, response surface methodology (RSM) was applied to optimize PAM removal in the anaerobic digestion of the sludge. The biological hydrolysis of PAM reached 86.64% under the optimal conditions obtained from the RSM. Then, the mechanisms for the optimized parameters that significantly improved the biological hydrolysis of PAM were investigated by the synergistic effect of the main organic compounds in the sludge, the floc size distribution, and the enzymatic activities. Finally, semi-continuous-flow experiments for a microbial community study were investigated based on the determination of key microorganisms involved in the biological hydrolysis of PAM. PMID:26144551

Waste-Activated Sludge Fermentation for Polyacrylamide Biodegradation Improved by Anaerobic Hydrolysis and Key Microorganisms Involved in Biological Polyacrylamide Removal.

PubMed

Dai, Xiaohu; Luo, Fan; Zhang, Dong; Dai, Lingling; Chen, Yinguang; Dong, Bin

2015-07-06

During the anaerobic digestion of dewatered sludge, polyacrylamide (PAM), a chemical conditioner, can usually be consumed as a carbon and nitrogen source along with other organic matter (e.g., proteins and carbohydrates in the sludge). However, a significant accumulation of acrylamide monomers (AMs) was observed during the PAM biodegradation process. To improve the anaerobic hydrolysis of PAM, especially the amide hydrolysis process, and to avoid the generation of the intermediate product AM, a new strategy is reported herein that uses an initial pH of 9, 200 mg COD/L of PAM and a fermentation time of 17 d. First, response surface methodology (RSM) was applied to optimize PAM removal in the anaerobic digestion of the sludge. The biological hydrolysis of PAM reached 86.64% under the optimal conditions obtained from the RSM. Then, the mechanisms for the optimized parameters that significantly improved the biological hydrolysis of PAM were investigated by the synergistic effect of the main organic compounds in the sludge, the floc size distribution, and the enzymatic activities. Finally, semi-continuous-flow experiments for a microbial community study were investigated based on the determination of key microorganisms involved in the biological hydrolysis of PAM.

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/.

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.

ACTH Action on StAR Biology

PubMed Central

Clark, Barbara J.

2016-01-01

Adrenocorticotropin hormone (ACTH) produced by the anterior pituitary stimulates glucocorticoid synthesis by the adrenal cortex. The first step in glucocorticoid synthesis is the delivery of cholesterol to the mitochondrial matrix where the first enzymatic reaction in the steroid hormone biosynthetic pathway occurs. A key response of adrenal cells to ACTH is activation of the cAMP-protein kinase A (PKA) signaling pathway. PKA activation results in an acute increase in expression and function of the Steroidogenic Acute Regulatory protein (StAR). StAR plays an essential role in steroidogenesis- it controls the hormone-dependent movement of cholesterol across the mitochondrial membranes. Currently StAR's mechanism of action remains a major unanswered question in the field. However, some insight may be gained from understanding the mechanism(s) controlling the PKA-dependent phosphorylation of StAR at S194/195 (mouse/human StAR), a modification that is required for function. This mini-review provides a background on StAR's biology with a focus on StAR phosphorylation. The model for StAR translation and phosphorylation at the outer mitochondrial membrane, the location for StAR function, is presented to highlight a unifying theme emerging from diverse studies. PMID:27999527

ACTH Action on StAR Biology.

PubMed

Clark, Barbara J

2016-01-01

Adrenocorticotropin hormone (ACTH) produced by the anterior pituitary stimulates glucocorticoid synthesis by the adrenal cortex. The first step in glucocorticoid synthesis is the delivery of cholesterol to the mitochondrial matrix where the first enzymatic reaction in the steroid hormone biosynthetic pathway occurs. A key response of adrenal cells to ACTH is activation of the cAMP-protein kinase A (PKA) signaling pathway. PKA activation results in an acute increase in expression and function of the Steroidogenic Acute Regulatory protein (StAR). StAR plays an essential role in steroidogenesis- it controls the hormone-dependent movement of cholesterol across the mitochondrial membranes. Currently StAR's mechanism of action remains a major unanswered question in the field. However, some insight may be gained from understanding the mechanism(s) controlling the PKA-dependent phosphorylation of StAR at S194/195 (mouse/human StAR), a modification that is required for function. This mini-review provides a background on StAR's biology with a focus on StAR phosphorylation. The model for StAR translation and phosphorylation at the outer mitochondrial membrane, the location for StAR function, is presented to highlight a unifying theme emerging from diverse studies.

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

PubMed Central

Luo, Shouling; Cao, Nannan; Tang, Yao; Gu, Weirong

2017-01-01

Preeclampsia is a leading cause of perinatal maternal–foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia. PMID:28594854

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

Synthetic Biology: Putting Synthesis into Biology

PubMed Central

Liang, Jing; Luo, Yunzi; Zhao, Huimin

2010-01-01

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

Knockdown of stem cell regulator Oct4A in ovarian cancer reveals cellular reprogramming associated with key regulators of cytoskeleton-extracellular matrix remodelling

PubMed Central

Samardzija, Chantel; Greening, David W.; Escalona, Ruth; Chen, Maoshan; Bilandzic, Maree; Luwor, Rodney; Kannourakis, George; Findlay, Jock K.; Ahmed, Nuzhat

2017-01-01

Oct4A is a master regulator of self-renewal and pluripotency in embryonic stem cells. It is a well-established marker for cancer stem cell (CSC) in malignancies. Recently, using a loss of function studies, we have demonstrated key roles for Oct4A in tumor cell survival, metastasis and chemoresistance in in vitro and in vivo models of ovarian cancer. In an effort to understand the regulatory role of Oct4A in tumor biology, we employed the use of an ovarian cancer shRNA Oct4A knockdown cell line (HEY Oct4A KD) and a global mass spectrometry (MS)-based proteomic analysis to investigate novel biological targets of Oct4A in HEY samples (cell lysates, secretomes and mouse tumor xenografts). Based on significant differential expression, pathway and protein network analyses, and comprehensive literature search we identified key proteins involved with biologically relevant functions of Oct4A in tumor biology. Across all preparations of HEY Oct4A KD samples significant alterations in protein networks associated with cytoskeleton, extracellular matrix (ECM), proliferation, adhesion, metabolism, epithelial-mesenchymal transition (EMT), cancer stem cells (CSCs) and drug resistance was observed. This comprehensive proteomics study for the first time presents the Oct4A associated proteome and expands our understanding on the biological role of this stem cell regulator in carcinomas. PMID:28406185

Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures

PubMed Central

Foroushani, Amir B.K.; Brinkman, Fiona S.L.

2013-01-01

Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/. PMID:24432194

General morphological and biological features of neoplasms: integration of molecular findings.

PubMed

Diaz-Cano, S J

2008-07-01

This review highlights the importance of morphology-molecular correlations for a proper implementation of new markers. It covers both general aspects of tumorigenesis (which are normally omitted in papers analysing molecular pathways) and the general mechanisms for the acquired capabilities of neoplasms. The mechanisms are also supported by appropriate diagrams for each acquired capability that include overlooked features such as mobilization of cellular resources and changes in chromatin, transcription and epigenetics; fully accepted oncogenes and tumour suppressor genes are highlighted, while the pathways are also presented as activating or inactivating with appropriate colour coding. Finally, the concepts and mechanisms presented enable us to understand the basic requirements for the appropriate implementation of molecular tests in clinical practice. In summary, the basic findings are presented to serve as a bridge to clinical applications. The current definition of neoplasm is descriptive and difficult to apply routinely. Biologically, neoplasms develop through acquisition of capabilities that involve tumour cell aspects and modified microenvironment interactions, resulting in unrestricted growth due to a stepwise accumulation of cooperative genetic alterations that affect key molecular pathways. The correlation of these molecular aspects with morphological changes is essential for better understanding of essential concepts as early neoplasms/precancerous lesions, progression/dedifferentiation, and intratumour heterogeneity. The acquired capabilities include self-maintained replication (cell cycle dysregulation), extended cell survival (cell cycle arrest, apoptosis dysregulation, and replicative lifespan), genetic instability (chromosomal and microsatellite), changes of chromatin, transcription and epigenetics, mobilization of cellular resources, and modified microenvironment interactions (tumour cells, stromal cells, extracellular, endothelium). The acquired

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.

Biochemical Pathways: An Atlas of Biochemistry and Molecular Biology (edited by Gerhard Michal)

NASA Astrophysics Data System (ADS)

Voige, Reviewed By William H.

2000-02-01

For decades, a wall chart detailing living organisms' metabolic pathways has been a fixture in many classrooms and laboratories where biochemistry is taught. One of the most popular of those charts first appeared 30 years ago. Now its editor, Gerhard Michal, has produced a book that summarizes metabolism (broadly defined) in graphical and textual formats. The book retains the elegance of the chart. Names of molecules are printed in a crisp, easy-to-read font, and structural formulas are shown with exemplary clarity. Color coding serves multiple purposes: to differentiate enzymes, substrates, cofactors, and effector molecules; to indicate in which group or groups of organisms a reaction has been observed; and to distinguish enzymatic reactions from regulatory effects. The primary advantage of presenting this information in book format is immediately apparent. A typical metabolic chart covers about 2 m2; the book has a total surface area nearly 10 times greater. The extra space is used to add explanatory text to the figures and to include many topics not covered by the traditional definition of metabolism. Examples include replication, transcription, translation, reaction mechanisms for proteolytic enzymes, and the role of chaperones in protein folding. Illustrating these topics is not as straightforward as delineating a metabolic pathway, but the author has done an admirable job of designing figures that clarify these and other aspects of biochemistry and complement the accompanying text. A potential deficiency of book format is the inability to clearly show links between different realms of metabolism: carbohydrate and amino acid pathways, for example. The book overcomes this problem in two ways. A diagrammatic overview of metabolism (with references to applicable sections of the book) is printed inside its front cover, and key compounds (pyruvate, for example) have a distinctive green background to provide a visual link between pathways. (The author compares this

A Skyline Plugin for Pathway-Centric Data Browsing

NASA Astrophysics Data System (ADS)

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.; Wilkins, Christopher S.; Lichti, Cheryl F.; Payne, Samuel H.

2016-11-01

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach selected reaction monitoring (SRM) and parallel reaction monitoring (PRM) assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks, and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). The same plugin can be used for hypothesis-driven data-independent acquisition (DIA) data analysis, again utilizing the pathway view to help narrow down the set of proteins that will be investigated. The plugin is backed by the Pacific Northwest National Laboratory (PNNL) Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment.

PubMed

Brockmeier, Erica K; Hodges, Geoff; Hutchinson, Thomas H; Butler, Emma; Hecker, Markus; Tollefsen, Knut Erik; Garcia-Reyero, Natalia; Kille, Peter; Becker, Dörthe; Chipman, Kevin; Colbourne, John; Collette, Timothy W; Cossins, Andrew; Cronin, Mark; Graystock, Peter; Gutsell, Steve; Knapen, Dries; Katsiadaki, Ioanna; Lange, Anke; Marshall, Stuart; Owen, Stewart F; Perkins, Edward J; Plaistow, Stewart; Schroeder, Anthony; Taylor, Daisy; Viant, Mark; Ankley, Gerald; Falciani, Francesco

2017-08-01

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology.

The Mucin MUC4 and Its Membrane Partner ErbB2 Regulate Biological Properties of Human CAPAN-2 Pancreatic Cancer Cells via Different Signalling Pathways

PubMed Central

Jonckheere, Nicolas; Skrypek, Nicolas; Merlin, Johann; Dessein, Anne Frédérique; Dumont, Patrick; Leteurtre, Emmanuelle; Harris, Ann; Desseyn, Jean-Luc; Susini, Christiane; Frénois, Frédéric; Van Seuningen, Isabelle

2012-01-01

The mucin MUC4 and its membrane partner the ErbB2 oncogenic receptor are potential interacting partners in human pancreatic tumour development. However, the way they function is still largely unknown. In this work, we aimed to identify the cellular mechanisms and the intracellular signalling pathways under the control of both ErbB2 and MUC4 in a human pancreatic adenocarcinomatous cell line. Using co-immunoprecipitation and GST pull-down, we show that MUC4 and ErbB2 interact in the human pancreatic adenocarcinomatous cell line CAPAN-2 via the EGF domains of MUC4. Stable cell clones were generated in which either MUC4 or ErbB2 were knocked down (KD) by a shRNA approach. Biological properties of these cells were then studied in vitro and in vivo. Our results show that ErbB2-KD cells are more apoptotic and less proliferative (decreased cyclin D1 and increased p27kip1 expression) while migration and invasive properties were not altered. MUC4-KD clones were less proliferative with decreased cyclin D1 expression, G1 cell cycle arrest and altered ErbB2/ErbB3 expression. Their migration properties were reduced whereas invasive properties were increased. Importantly, inhibition of ErbB2 and MUC4 expression did not impair the same signalling pathways (inhibition of MUC4 expression affected the JNK pathway whereas that of ErbB2 altered the MAPK pathway). Finally, ErbB2-KD and MUC4-KD cells showed impaired tumour growth in vivo. Our results show that ErbB2 and MUC4, which interact physically, activate different intracellular signalling pathways to regulate biological properties of CAPAN-2 pancreatic cancer cells. PMID:22393391