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...
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 ...
An overview of bioinformatics methods for modeling biological pathways in yeast
Hou, Jie; Acharya, Lipi; Zhu, Dongxiao
2016-01-01
The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein–protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae. In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways in S. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. PMID:26476430
An overview of bioinformatics methods for modeling biological pathways in yeast.
Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin
2016-03-01
The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Young, M; Craft, D
Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less
Transcriptomic basis for drought-resistance in Brassica napus L.
NASA Astrophysics Data System (ADS)
Wang, Pei; Yang, Cuiling; Chen, Hao; Song, Chunpeng; Zhang, Xiao; Wang, Daojie
2017-01-01
Based on transcriptomic data from four experimental settings with drought-resistant and drought-sensitive cultivars under drought and well-watered conditions, statistical analysis revealed three categories encompassing 169 highly differentially expressed genes (DEGs) in response to drought in Brassica napus L., including 37 drought-resistant cultivar-related genes, 35 drought-sensitive cultivar-related genes and 97 cultivar non-specific ones. We provide evidence that the identified DEGs were fairly uniformly distributed on different chromosomes and their expression patterns are variety specific. Except commonly enriched in response to various stimuli or stresses, different categories of DEGs show specific enrichment in certain biological processes or pathways, which indicated the possibility of functional differences among the three categories. Network analysis revealed relationships among the 169 DEGs, annotated biological processes and pathways. The 169 DEGs can be classified into different functional categories via preferred pathways or biological processes. Some pathways might simultaneously involve a large number of shared DEGs, and these pathways are likely to cross-talk and have overlapping biological functions. Several members of the identified DEGs fit to drought stress signal transduction pathway in Arabidopsis thaliana. Finally, quantitative real-time PCR validations confirmed the reproducibility of the RNA-seq data. These investigations are profitable for the improvement of crop varieties through transgenic engineering.
PathJam: a new service for integrating biological pathway information.
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.
Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome
Milacic, Marija; Haw, Robin; Rothfels, Karen; Wu, Guanming; Croft, David; Hermjakob, Henning; D’Eustachio, Peter; Stein, Lincoln
2012-01-01
Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics. PMID:24213504
ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis
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
Systematic analysis of signaling pathways using an integrative environment.
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.
cPath: open source software for collecting, storing, and querying biological pathways.
Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris
2006-11-13
Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.
PathNER: a tool for systematic identification of biological pathway mentions in the literature
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
Detecting Disease Specific Pathway Substructures through an Integrated Systems Biology Approach
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
New era of biologic therapeutics in atopic dermatitis.
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.
cPath: open source software for collecting, storing, and querying biological pathways
Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris
2006-01-01
Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041
Mining and integration of pathway diagrams from imaging data.
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.
Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.
Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju
2017-04-27
Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.
A three-tiered approach for linking pharmacokinetic ...
The power of the adverse outcome pathway (AOP) framework arises from its utilization of pathway-based data to describe the initial interaction of a chemical with a molecular target (molecular initiating event; (MIE), followed by a progression through a series of key events that lead to an adverse outcome relevant for regulatory purposes. The AOP itself is not chemical specific, thus providing the biological context necessary for interpreting high throughput (HT) toxicity screening results. Application of the AOP framework and HT predictions in ecological and human health risk assessment, however, requires the consideration of chemical-specific properties that influence external exposure doses and target tissue doses. To address this requirement, a three-tiered approach was developed to provide a workflow for connecting biology-based AOPs to biochemical-based pharmacokinetic properties (absorption, distribution, metabolism, excretion; ADME), and then to chemical/human activity-based exposure pathways. This approach included: (1) The power of the adverse outcome pathway (AOP) framework arisesfrom its utilization of pathway-based data to describe the initial interaction of a chemical with a molecular target (molecular initiating event; (MIE), followed by a progression through a series of key events that lead to an adverse outcome relevant for regulatory purposes. The AOP itself is not chemical specific, thus providing the biological context necessary for interpreti
Monnereau, Claire; Vogelezang, Suzanne; Kruithof, Claudia J; Jaddoe, Vincent W V; Felix, Janine F
2016-08-18
Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures. We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models. A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area. A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards.
Pathway analysis of high-throughput biological data within a Bayesian network framework.
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.
The Hippo signaling pathway in stem cell biology and cancer
Mo, Jung-Soon; Park, Hyun Woo; Guan, Kun-Liang
2014-01-01
The Hippo signaling pathway, consisting of a highly conserved kinase cascade (MST and Lats) and downstream transcription coactivators (YAP and TAZ), plays a key role in tissue homeostasis and organ size control by regulating tissue-specific stem cells. Moreover, this pathway plays a prominent role in tissue repair and regeneration. Dysregulation of the Hippo pathway is associated with cancer development. Recent studies have revealed a complex network of upstream inputs, including cell density, mechanical sensation, and G-protein-coupled receptor (GPCR) signaling, that modulate Hippo pathway activity. This review focuses on the role of the Hippo pathway in stem cell biology and its potential implications in tissue homeostasis and cancer. PMID:24825474
Epigenetic determinants of ovarian clear cell carcinoma biology
Yamaguchi, Ken; Huang, Zhiqing; Matsumura, Noriomi; Mandai, Masaki; Okamoto, Takako; Baba, Tsukasa; Konishi, Ikuo; Berchuck, Andrew; Murphy, Susan K.
2015-01-01
Targeted approaches have revealed frequent epigenetic alterations in ovarian cancer, but the scope and relation of these changes to histologic subtype of disease is unclear. Genome-wide methylation and expression data for 14 clear cell carcinoma (CCC), 32 non-CCC, and 4 corresponding normal cell lines were generated to determine how methylation profiles differ between cells of different histological derivations of ovarian cancer. Consensus clustering showed that CCC is epigenetically distinct. Inverse relationships between expression and methylation in CCC were identified, suggesting functional regulation by methylation, and included 22 hypomethylated (UM) genes and 276 hypermethylated (HM) genes. Categorical and pathway analyses indicated that the CCC-specific UM genes were involved in response to stress and many contain hepatocyte nuclear factor (HNF) 1 binding sites, while the CCC-specific HM genes included members of the estrogen receptor alpha (ERalpha) network and genes involved in tumor development. We independently validated the methylation status of 17 of these pathway-specific genes, and confirmed increased expression of HNF1 network genes and repression of ERalpha pathway genes in CCC cell lines and primary cancer tissues relative to non-CCC specimens. Treatment of three CCC cell lines with the demethylating agent Decitabine significantly induced expression for all five genes analyzed. Coordinate changes in pathway expression were confirmed using two primary ovarian cancer datasets (p<0.0001 for both). Our results suggest that methylation regulates specific pathways and biological functions in CCC, with hypomethylation influencing the characteristic biology of the disease while hypermethylation contributes to the carcinogenic process. PMID:24382740
Impact of constitutional copy number variants on biological pathway evolution.
Poptsova, Maria; Banerjee, Samprit; Gokcumen, Omer; Rubin, Mark A; Demichelis, Francesca
2013-01-23
Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data. We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels. The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations.
Impact of constitutional copy number variants on biological pathway evolution
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
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.
Computational multiscale modeling in protein--ligand docking.
Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles
2009-01-01
In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].
PathwayAccess: CellDesigner plugins for pathway databases.
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.
The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core
Hucka, Michael; Bergmann, Frank T.; Hoops, Stefan; Keating, Sarah M.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Wilkinson, Darren J.
2017-01-01
Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528564
The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.
Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J
2015-09-04
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.
The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.
Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J
2015-06-01
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.
Chemical-agnostic hazard prediction: statistical inference of in ...
Toxicity pathways have been defined as normal cellular pathways that, when sufficiently perturbed as a consequence of chemical exposure, lead to an adverse outcome. If an exposure alters one or more normal biological pathways to an extent that leads to an adverse toxicity outcome, a significant correlation must exist between the exposure, the extent of pathway alteration, and the degree of adverse outcome. Biological pathways are regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation, each of which can affect the levels and extents of modification of proteins involved in the pathways. Significant alterations of toxicity pathways resulting from changes in regulation at any of these levels therefore are likely to be detectable as alterations in the proteome. We hypothesize that significant correlations between exposures, adverse outcomes, and changes in the proteome have the potential to identify putative toxicity pathways, facilitating selection of candidate targets for high throughput screening, even in the absence of a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations. We explored this hypothesis in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+, alone and in defined mixtures. Levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were
Hippo vs. Crab: tissue-specific functions of the mammalian Hippo pathway.
Nishio, Miki; Maehama, Tomohiko; Goto, Hiroki; Nakatani, Keisuke; Kato, Wakako; Omori, Hirofumi; Miyachi, Yosuke; Togashi, Hideru; Shimono, Yohei; Suzuki, Akira
2017-01-01
The Hippo signaling pathway is a vital suppressor of tumorigenesis that is often inactivated in human cancers. In normal cells, the Hippo pathway is triggered by external forces such as cell crowding, or changes to the extracellular matrix or cell polarity. Once activated, Hippo signaling down-regulates transcription supported by the paralogous cofactors YAP1 and TAZ. The Hippo pathway's functions in normal and cancer biology have been dissected by studies of mutant mice with null or conditional tissue-specific mutations of Hippo signaling elements. In this review, we attempt to systematically summarize results that have been gleaned from detailed in vivo characterizations of these mutants. Our goal is to describe the physiological roles of Hippo signaling in several normal organ systems, as well as to emphasize how disruption of the Hippo pathway, and particularly hyperactivation of YAP1/TAZ, can be oncogenic. © 2017 The Authors Genes to Cells published by Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.
García-Jiménez, Beatriz; Pons, Tirso; Sanchis, Araceli; Valencia, Alfonso
2014-01-01
Biological pathways are important elements of systems biology and in the past decade, an increasing number of pathway databases have been set up to document the growing understanding of complex cellular processes. Although more genome-sequence data are becoming available, a large fraction of it remains functionally uncharacterized. Thus, it is important to be able to predict the mapping of poorly annotated proteins to original pathway models. We have developed a Relational Learning-based Extension (RLE) system to investigate pathway membership through a function prediction approach that mainly relies on combinations of simple properties attributed to each protein. RLE searches for proteins with molecular similarities to specific pathway components. Using RLE, we associated 383 uncharacterized proteins to 28 pre-defined human Reactome pathways, demonstrating relative confidence after proper evaluation. Indeed, in specific cases manual inspection of the database annotations and the related literature supported the proposed classifications. Examples of possible additional components of the Electron transport system, Telomere maintenance and Integrin cell surface interactions pathways are discussed in detail. All the human predicted proteins in the 2009 and 2012 releases 30 and 40 of Reactome are available at http://rle.bioinfo.cnio.es.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ba, Qian; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing; Li, Junyang
2015-03-01
Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong tomore » the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.« less
Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.
2011-01-01
Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212
The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making...
The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making...
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
Disentangling the multigenic and pleiotropic nature of molecular function
2015-01-01
Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917
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.
Hucka, Michael; Bergmann, Frank T.; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M.; Le Novére, Nicolas; Myers, Chris J.; Olivier, Brett G.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Waltemath, Dagmar; Wilkinson, Darren J.
2017-01-01
Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528569
Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J
2015-09-04
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org.
Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J
2015-06-01
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.
Molecular profiles to biology and pathways: a systems biology approach.
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.
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.
Wu, Chia-Chou; Lin, Chih-Lung; Chen, Ting-Shou
2015-01-01
Hepatocellular carcinoma (HCC) is a major liver tumor (~80%), besides hepatoblastomas, angiosarcomas, and cholangiocarcinomas. In this study, we used a systems biology approach to construct protein-protein interaction networks (PPINs) for early-stage and late-stage liver cancer. By comparing the networks of these two stages, we found that the two networks showed some common mechanisms and some significantly different mechanisms. To obtain differential network structures between cancer and noncancer PPINs, we constructed cancer PPIN and noncancer PPIN network structures for the two stages of liver cancer by systems biology method using NGS data from cancer cells and adjacent noncancer cells. Using carcinogenesis relevance values (CRVs), we identified 43 and 80 significant proteins and their PPINs (network markers) for early-stage and late-stage liver cancer. To investigate the evolution of network biomarkers in the carcinogenesis process, a primary pathway analysis showed that common pathways of the early and late stages were those related to ordinary cancer mechanisms. A pathway specific to the early stage was the mismatch repair pathway, while pathways specific to the late stage were the spliceosome pathway, lysine degradation pathway, and progesterone-mediated oocyte maturation pathway. This study provides a new direction for cancer-targeted therapies at different stages. PMID:26366411
Fay, Kellie A; Villeneuve, Daniel L; Swintek, Joe; Edwards, Stephen W; Nelms, Mark D; Blackwell, Brett R; Ankley, Gerald T
2018-06-01
The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.
Understanding the intersections between metabolism and cancer biology
Heiden, Matthew G. Vander; DeBerardinis, Ralph J.
2017-01-01
Transformed cells adapt metabolism to support tumor initiation and progression. Specific metabolic activities can participate directly in the process of transformation or support the biological processes that enable tumor growth. Exploiting cancer metabolism for clinical benefit requires defining the pathways that are limiting for cancer progression and understanding the context specificity of metabolic preferences and liabilities in malignant cells. Progress towards answering these questions is providing new insight into cancer biology and can guide the more effective targeting of metabolism to help patients. PMID:28187287
Clinical and Biological Relevance of Genomic Heterogeneity in Chronic Lymphocytic Leukemia
Friedman, Daphne R.; Lucas, Joseph E.; Weinberg, J. Brice
2013-01-01
Background Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients’ leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL. Methods To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups. Results Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes. Conclusions Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways. PMID:23468975
Clinical and biological relevance of genomic heterogeneity in chronic lymphocytic leukemia.
Friedman, Daphne R; Lucas, Joseph E; Weinberg, J Brice
2013-01-01
Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients' leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL. To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups. Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes. Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways.
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
Heritable and Nonheritable Pathways to Early Callous-Unemotional Behaviors.
Hyde, Luke W; Waller, Rebecca; Trentacosta, Christopher J; Shaw, Daniel S; Neiderhiser, Jenae M; Ganiban, Jody M; Reiss, David; Leve, Leslie D
2016-09-01
Callous-unemotional behaviors in early childhood signal higher risk for trajectories of antisocial behavior and callous-unemotional traits that culminate in later diagnoses of conduct disorder, antisocial personality disorder, and psychopathy. Studies demonstrate high heritability of callous-unemotional traits, but little research has examined specific heritable pathways to early callous-unemotional behaviors. Studies also indicate that positive parenting protects against the development of callous-unemotional traits, but genetically informed designs have not been used to confirm that these relationships are not the product of gene-environment correlations. In a sample of adopted children and their biological and adoptive mothers, the authors tested novel heritable and nonheritable pathways to preschool callous-unemotional behaviors. In an adoption cohort of 561 families, history of severe antisocial behavior assessed in biological mothers and observations of adoptive mother positive reinforcement at 18 months were examined as predictors of callous-unemotional behaviors at 27 months. Despite limited or no contact with offspring, biological mother antisocial behavior predicted early callous-unemotional behaviors. Adoptive mother positive reinforcement protected against early callous-unemotional behaviors. High levels of adoptive mother positive reinforcement buffered the effects of heritable risk for callous-unemotional behaviors posed by biological mother antisocial behavior. The findings elucidate heritable and nonheritable pathways to early callous-unemotional behaviors. The results provide a specific heritable pathway to callous-unemotional behaviors and compelling evidence that parenting is an important nonheritable factor in the development of callous-unemotional behaviors. The finding that positive reinforcement buffered heritable risk for callous-unemotional behaviors has important translational implications for the prevention of trajectories to serious antisocial behavior.
Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex
2016-11-16
Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.
Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex
2016-01-01
Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968
Pathway index models for construction of patient-specific risk profiles.
Eng, Kevin H; Wang, Sijian; Bradley, William H; Rader, Janet S; Kendziorski, Christina
2013-04-30
Statistical methods for variable selection, prediction, and classification have proven extremely useful in moving personalized genomics medicine forward, in particular, leading to a number of genomic-based assays now in clinical use for predicting cancer recurrence. Although invaluable in individual cases, the information provided by these assays is limited. Most often, a patient is classified into one of very few groups (e.g., recur or not), limiting the potential for truly personalized treatment. Furthermore, although these assays provide information on which individuals are at most risk (e.g., those for which recurrence is predicted), they provide no information on the aberrant biological pathways that give rise to the increased risk. We have developed an approach to address these limitations. The approach models a time-to-event outcome as a function of known biological pathways, identifies important genomic aberrations, and provides pathway-based patient-specific assessments of risk. As we demonstrate in a study of ovarian cancer from The Cancer Genome Atlas project, the patient-specific risk profiles are powerful and efficient characterizations useful in addressing a number of questions related to identifying informative patient subtypes and predicting survival. Copyright © 2012 John Wiley & Sons, Ltd.
iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data
Saha, Ashis; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo
2015-01-01
Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference. PMID:26147457
The concept of Adverse Outcome Pathways (AOPs) arose as a means of addressing the challenges associated with establishing relationships between high-throughout (HT) in vitro dose response data and in vivo biological outcomes. However, AOP development has also been met with challe...
Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.
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.
Willett, Catherine; Caverly Rae, Jessica; Goyak, Katy O; Minsavage, Gary; Westmoreland, Carl; Andersen, Melvin; Avigan, Mark; Duché, Daniel; Harris, Georgina; Hartung, Thomas; Jaeschke, Hartmut; Kleensang, Andre; Landesmann, Brigitte; Martos, Suzanne; Matevia, Marilyn; Toole, Colleen; Rowan, Andrew; Schultz, Terry; Seed, Jennifer; Senior, John; Shah, Imran; Subramanian, Kalyanasundaram; Vinken, Mathieu; Watkins, Paul
2014-01-01
A workshop sponsored by the Human Toxicology Project Consortium (HTPC), "Building Shared Experience to Advance Practical Application of Pathway-Based Toxicology: Liver Toxicity Mode-of-Action" brought together experts from a wide range of perspectives to inform the process of pathway development and to advance two prototype pathways initially developed by the European Commission Joint Research Center (JRC): liver-specific fibrosis and steatosis. The first half of the workshop focused on the theory and practice of pathway development; the second on liver disease and the two prototype pathways. Participants agreed pathway development is extremely useful for organizing information and found that focusing the theoretical discussion on a specific AOP is extremely helpful. In addition, it is important to include several perspectives during pathway development, including information specialists, pathologists, human health and environmental risk assessors, and chemical and product manufacturers, to ensure the biology is well captured and end use is considered.
Developmental defects in zebrafish for classification of EGF pathway inhibitors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pruvot, Benoist; Curé, Yoann; Djiotsa, Joachim
2014-01-15
One of the major challenges when testing drug candidates targeted at a specific pathway in whole animals is the discrimination between specific effects and unwanted, off-target effects. Here we used the zebrafish to define several developmental defects caused by impairment of Egf signaling, a major pathway of interest in tumor biology. We inactivated Egf signaling by genetically blocking Egf expression or using specific inhibitors of the Egf receptor function. We show that the combined occurrence of defects in cartilage formation, disturbance of blood flow in the trunk and a decrease of myelin basic protein expression represent good indicators for impairmentmore » of Egf signaling. Finally, we present a classification of known tyrosine kinase inhibitors according to their specificity for the Egf pathway. In conclusion, we show that developmental indicators can help to discriminate between specific effects on the target pathway from off-target effects in molecularly targeted drug screening experiments in whole animal systems. - Highlights: • We analyze the functions of Egf signaling on zebrafish development. • Genetic blocking of Egf expression causes cartilage, myelin and circulatory defects. • Chemical inhibition of Egf receptor function causes similar defects. • Developmental defects can reveal the specificity of Egf pathway inhibitors.« less
The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core.
Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J
2018-03-09
Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.
Directed Evolution as a Powerful Synthetic Biology Tool
Cobb, Ryan E.; Sun, Ning; Zhao, Huimin
2012-01-01
At the heart of synthetic biology lies the goal of rationally engineering a complete biological system to achieve a specific objective, such as bioremediation and synthesis of a valuable drug, chemical, or biofuel molecule. However, the inherent complexity of natural biological systems has heretofore precluded generalized application of this approach. Directed evolution, a process which mimics Darwinian selection on a laboratory scale, has allowed significant strides to be made in the field of synthetic biology by allowing rapid identification of desired properties from large libraries of variants. Improvement in biocatalyst activity and stability, engineering of biosynthetic pathways, tuning of functional regulatory systems and logic circuits, and development of desired complex phenotypes in industrial host organisms have all been achieved by way of directed evolution. Here, we review recent contributions of directed evolution to synthetic biology at the protein, pathway, network, and whole cell levels. PMID:22465795
Effects-based monitoring and surveillance is increasingly being utilized in conjunction with chemical monitoring to determine potential biological activity associated with environmental contaminants. Supervised approaches targeting specific chemical activity or molecular pathways...
Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...
The Pathway Coexpression Network: Revealing pathway relationships
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 global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099
Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways.
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.
Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia
2016-09-09
Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.
CONTEXT: N02 and 03 are ubiquitous air toxicants capable of inducing lung damage to the respiratory epithelium. Due to their oxidizing capabilities, these pollutants have been proposed to target specific biological pathways, but few publications have compared the pathways activat...
The ToxCast chemical screening approach enables the rapid assessment of large numbers of chemicals for biological effects, primarily at the molecular level. Adverse outcome pathways (AOPs) offer a means to link biomolecular effects with potential adverse outcomes at the level of...
Ayllón, Nieves; Villar, Margarita; Galindo, Ruth C.; Kocan, Katherine M.; Šíma, Radek; López, Juan A.; Vázquez, Jesús; Alberdi, Pilar; Cabezas-Cruz, Alejandro; Kopáček, Petr; de la Fuente, José
2015-01-01
Anaplasma phagocytophilum is an emerging pathogen that causes human granulocytic anaplasmosis. Infection with this zoonotic pathogen affects cell function in both vertebrate host and the tick vector, Ixodes scapularis. Global tissue-specific response and apoptosis signaling pathways were characterized in I. scapularis nymphs and adult female midguts and salivary glands infected with A. phagocytophilum using a systems biology approach combining transcriptomics and proteomics. Apoptosis was selected for pathway-focused analysis due to its role in bacterial infection of tick cells. The results showed tissue-specific differences in tick response to infection and revealed differentiated regulation of apoptosis pathways. The impact of bacterial infection was more pronounced in tick nymphs and midguts than in salivary glands, probably reflecting bacterial developmental cycle. All apoptosis pathways described in other organisms were identified in I. scapularis, except for the absence of the Perforin ortholog. Functional characterization using RNA interference showed that Porin knockdown significantly increases tick colonization by A. phagocytophilum. Infection with A. phagocytophilum produced complex tissue-specific alterations in transcript and protein levels. In tick nymphs, the results suggested a possible effect of bacterial infection on the inhibition of tick immune response. In tick midguts, the results suggested that A. phagocytophilum infection inhibited cell apoptosis to facilitate and establish infection through up-regulation of the JAK/STAT pathway. Bacterial infection inhibited the intrinsic apoptosis pathway in tick salivary glands by down-regulating Porin expression that resulted in the inhibition of Cytochrome c release as the anti-apoptotic mechanism to facilitate bacterial infection. However, tick salivary glands may promote apoptosis to limit bacterial infection through induction of the extrinsic apoptosis pathway. These dynamic changes in response to A. phagocytophilum in I. scapularis tissue-specific transcriptome and proteome demonstrated the complexity of the tick response to infection and will contribute to characterize gene regulation in ticks. PMID:25815810
A simple biosynthetic pathway for large product generation from small substrate amounts
NASA Astrophysics Data System (ADS)
Djordjevic, Marko; Djordjevic, Magdalena
2012-10-01
A recently emerging discipline of synthetic biology has the aim of constructing new biosynthetic pathways with useful biological functions. A major application of these pathways is generating a large amount of the desired product. However, toxicity due to the possible presence of toxic precursors is one of the main problems for such production. We consider here the problem of generating a large amount of product from a potentially toxic substrate. To address this, we propose a simple biosynthetic pathway, which can be induced in order to produce a large number of the product molecules, by keeping the substrate amount at low levels. Surprisingly, we show that the large product generation crucially depends on fast non-specific degradation of the substrate molecules. We derive an optimal induction strategy, which allows as much as three orders of magnitude increase in the product amount through biologically realistic parameter values. We point to a recently discovered bacterial immune system (CRISPR/Cas in E. coli) as a putative example of the pathway analysed here. We also argue that the scheme proposed here can be used not only as a stand-alone pathway, but also as a strategy to produce a large amount of the desired molecules with small perturbations of endogenous biosynthetic pathways.
Li, Chaoxing; Liu, Li; Dinu, Valentin
2018-01-01
Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.
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
Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy
Godard, Patrice; van Eyll, Jonathan
2015-01-01
MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods. PMID:25800743
CMPF: class-switching minimized pathfinding in metabolic networks.
Lim, Kevin; Wong, Limsoon
2012-01-01
The metabolic network is an aggregation of enzyme catalyzed reactions that converts one compound to another. Paths in a metabolic network are a sequence of enzymes that describe how a chemical compound of interest can be produced in a biological system. As the number of such paths is quite large, many methods have been developed to score paths so that the k-shortest paths represent the set of paths that are biologically meaningful or efficient. However, these approaches do not consider whether the sequence of enzymes can be manufactured in the same pathway/species/localization. As a result, a predicted sequence might consist of groups of enzymes that operate in distinct pathway/species/localization and may not truly reflect the events occurring within cell. We propose a path weighting method CMPF (Class-switching Minimized Pathfinder) to search for routes in a metabolic network which minimizes pathway switching. In biological terms, a pathway is a series of chemical reactions which define a specific function (e.g. glycolysis). We conjecture that routes that cross many pathways are inefficient since different pathways define different metabolic functions. In addition, native routes are also well characterized within pathways, suggesting that reasonable paths should not involve too many pathway switches. Our method can be generalized when reactions participate in a class set (e.g., pathways, species or cellular localization) so that the paths predicted have minimal class crossings. We show that our method generates k-paths that involve the least number of class switching. In addition, we also show that native paths are recoverable and alternative paths deviates less from native paths compared to other methods. This suggests that paths ranked by our method could be a way to predict paths that are likely to occur in biological systems.
Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.
Cox, Amanda J; Zhang, Ping; Evans, Tiffany J; Scott, Rodney J; Cripps, Allan W; West, Nicholas P
Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n=21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n=11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p<0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p<0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10 -8 ; AUC: 0.909, CR: 72.7%). These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Liu, Li; Dinu, Valentin
2018-01-01
Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level. PMID:29666752
Shao, Hongwei; Peng, Tao; Ji, Zhiwei; Su, Jing; Zhou, Xiaobo
2013-01-01
Substantial effort in recent years has been devoted to analyzing data based large-scale biological networks, which provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or compounds. In this work, we proposed a novel strategy to investigate kinase inhibitor induced pathway signatures by integrating multiplex data in Library of Integrated Network-based Cellular Signatures (LINCS), e.g. KINOMEscan data and cell proliferation/mitosis imaging data. Using this strategy, we first established a PC9 cell line specific pathway model to investigate the pathway signatures in PC9 cell line when perturbed by a small molecule kinase inhibitor GW843682. This specific pathway revealed the role of PI3K/AKT in modulating the cell proliferation process and the absence of two anti-proliferation links, which indicated a potential mechanism of abnormal expansion in PC9 cell number. Incorporating the pathway model for side effects on primary human hepatocytes, it was used to screen 27 kinase inhibitors in LINCS database and PF02341066, known as Crizotinib, was finally suggested with an optimal concentration 4.6 uM to suppress PC9 cancer cell expansion while avoiding severe damage to primary human hepatocytes. Drug combination analysis revealed that the synergistic effect region can be predicted straightforwardly based on a threshold which is an inherent property of each kinase inhibitor. Furthermore, this integration strategy can be easily extended to other specific cell lines to be a powerful tool for drug screen before clinical trials. PMID:24339888
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
Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...
THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK ...
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
Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua
2016-02-25
The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.
Subcellular Redox Targeting: Bridging in Vitro and in Vivo Chemical Biology.
Long, Marcus J C; Poganik, Jesse R; Ghosh, Souradyuti; Aye, Yimon
2017-03-17
Networks of redox sensor proteins within discrete microdomains regulate the flow of redox signaling. Yet, the inherent reactivity of redox signals complicates the study of specific redox events and pathways by traditional methods. Herein, we review designer chemistries capable of measuring flux and/or mimicking subcellular redox signaling at the cellular and organismal level. Such efforts have begun to decipher the logic underlying organelle-, site-, and target-specific redox signaling in vitro and in vivo. These data highlight chemical biology as a perfect gateway to interrogate how nature choreographs subcellular redox chemistry to drive precision redox biology.
Parameter space exploration within dynamic simulations of signaling networks.
De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio
2013-02-01
We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.
Metabolic pathways for the whole community.
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.
Bown, James L; Shovman, Mark; Robertson, Paul; Boiko, Andrei; Goltsov, Alexey; Mullen, Peter; Harrison, David J
2017-05-02
Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualization toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.
Rai, Richa; Chauhan, Sudhir Kumar; Singh, Vikas Vikram; Rai, Madhukar; Rai, Geeta
2016-01-01
Systemic lupus erythematosus (SLE) patients exhibit immense heterogeneity which is challenging from the diagnostic perspective. Emerging high throughput sequencing technologies have been proved to be a useful platform to understand the complex and dynamic disease processes. SLE patients categorised based on autoantibody specificities are reported to have differential immuno-regulatory mechanisms. Therefore, we performed RNA-seq analysis to identify transcriptomics of SLE patients with distinguished autoantibody specificities. The SLE patients were segregated into three subsets based on the type of autoantibodies present in their sera (anti-dsDNA+ group with anti-dsDNA autoantibody alone; anti-ENA+ group having autoantibodies against extractable nuclear antigens (ENA) only, and anti-dsDNA+ENA+ group having autoantibodies to both dsDNA and ENA). Global transcriptome profiling for each SLE patients subsets was performed using Illumina® Hiseq-2000 platform. The biological relevance of dysregulated transcripts in each SLE subsets was assessed by ingenuity pathway analysis (IPA) software. We observed that dysregulation in the transcriptome expression pattern was clearly distinct in each SLE patients subsets. IPA analysis of transcripts uniquely expressed in different SLE groups revealed specific biological pathways to be affected in each SLE subsets. Multiple cytokine signaling pathways were specifically dysregulated in anti-dsDNA+ patients whereas Interferon signaling was predominantly dysregulated in anti-ENA+ patients. In anti-dsDNA+ENA+ patients regulation of actin based motility by Rho pathway was significantly affected. The granulocyte gene signature was a common feature to all SLE subsets; however, anti-dsDNA+ group showed relatively predominant expression of these genes. Dysregulation of Plasma cell related transcripts were higher in anti-dsDNA+ and anti-ENA+ patients as compared to anti-dsDNA+ ENA+. Association of specific canonical pathways with the uniquely expressed transcripts in each SLE subgroup indicates that specific immunological disease mechanisms are operative in distinct SLE patients’ subsets. This ‘sub-grouping’ approach could further be useful for clinical evaluation of SLE patients and devising targeted therapeutics. PMID:27835693
Willett, Catherine; Rae, Jessica Caverly; Goyak, Katy O.; Minsavage, Gary; Westmoreland, Carl; Andersen, Melvin; Avigan, Mark; Duché, Daniel; Harris, Georgina; Hartung, Thomas; Jaeschke, Hartmut; Kleensang, Andre; Landesmann, Brigitte; Martos, Suzanne; Matevia, Marilyn; Toole, Colleen; Rowan, Andrew; Schultz, Terry; Seed, Jennifer; Senior, John; Shah, Imran; Subramanian, Kalyanasundaram; Vinken, Mathieu; Watkins, Paul
2016-01-01
Summary A workshop sponsored by the Human Toxicology Project Consortium (HTPC), “Building Shared Experience to Advance Practical Application of Pathway-Based Toxicology: Liver Toxicity Mode-of-Action” brought together experts from a wide range of perspectives to inform the process of pathway development and to advance two prototype pathways initially developed by the European Commission Joint Research Center (JRC): liver-specific fibrosis and steatosis. The first half of the workshop focused on the theory and practice of pathway development; the second on liver disease and the two prototype pathways. Participants agreed pathway development is extremely useful for organizing information and found that focusing the theoretical discussion on a specific AOP is helpful. It is important to include several perspectives during pathway development, including information specialists, pathologists, human health and environmental risk assessors, and chemical and product manufacturers, to ensure the biology is well captured and end use is considered. PMID:24535319
A Role for SHIP in Stem Cell Biology and Transplantation
Kerr, William G.
2008-01-01
Inositol phospholipid signaling pathways have begun to emerge as important players in stem cell biology and bone marrow transplantation [1–4]. The SH2-containing Inositol Phosphatase (SHIP) is among the enzymes that can modify endogenous mammalian phosphoinositides. SHIP encodes an isoform specific to pluripotent stem (PS) cells [5,6] plays a role in hematopoietic stem (HS) cell biology [7,8] and allogeneic bone marrow (BM) transplantation [1,2,9,10]. Here I discuss our current understanding of the cell and molecular pathways that SHIP regulates that influence PS/HS cell biology and BM transplantation. Genetic models of SHIP-deficiency indicate this enzyme is a potential molecular target to enhance both autologous and allogeneic BM transplantation. Thus, strategies to reversibly target SHIP expression and their potential application to stem cell therapies and allogeneic BMT are also discussed. PMID:18473876
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.
Current Status on Biochemistry and Molecular Biology of Microbial Degradation of Nicotine
Gurusamy, Raman; Natarajan, Sakthivel
2013-01-01
Bioremediation is one of the most promising methods to clean up polluted environments using highly efficient potent microbes. Microbes with specific enzymes and biochemical pathways are capable of degrading the tobacco alkaloids including highly toxic heterocyclic compound, nicotine. After the metabolic conversion, these nicotinophilic microbes use nicotine as the sole carbon, nitrogen, and energy source for their growth. Various nicotine degradation pathways such as demethylation pathway in fungi, pyridine pathway in Gram-positive bacteria, pyrrolidine pathway, and variant of pyridine and pyrrolidine pathways in Gram-negative bacteria have been reported. In this review, we discussed the nicotine-degrading pathways of microbes and their enzymes and biotechnological applications of nicotine intermediate metabolites. PMID:24470788
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.
A strategy for evaluating pathway analysis methods.
Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques
2017-10-13
Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth, either established or assumed, of the pathways perturbed by a specific clinical or experimental condition. As such, our strategy allows researchers to systematically and objectively evaluate pathway analysis methods by employing any number of datasets for a variety of conditions.
Pathway-based personalized analysis of cancer
Drier, Yotam; Sheffer, Michal; Domany, Eytan
2013-01-01
We introduce Pathifier, an algorithm that infers pathway deregulation scores for each tumor sample on the basis of expression data. This score is determined, in a context-specific manner, for every particular dataset and type of cancer that is being investigated. The algorithm transforms gene-level information into pathway-level information, generating a compact and biologically relevant representation of each sample. We demonstrate the algorithm’s performance on three colorectal cancer datasets and two glioblastoma multiforme datasets and show that our multipathway-based representation is reproducible, preserves much of the original information, and allows inference of complex biologically significant information. We discovered several pathways that were significantly associated with survival of glioblastoma patients and two whose scores are predictive of survival in colorectal cancer: CXCR3-mediated signaling and oxidative phosphorylation. We also identified a subclass of proneural and neural glioblastoma with significantly better survival, and an EGF receptor-deregulated subclass of colon cancers. PMID:23547110
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.
USDA-ARS?s Scientific Manuscript database
Prolactin (PRL) acts through its receptor (PRLR) via both endocrine and local paracrine/autocrine pathways to regulate biological processes including reproduction and lactation. We analyzed the tissue and stage of gestation-specific regulation of PRL and PRLR expression in various tissues of pigs. ...
Osiewacz, Heinz D; Brust, Diana; Hamann, Andrea; Kunstmann, Birgit; Luce, Karin; Müller-Ohldach, Mathis; Scheckhuber, Christian Q; Servos, Jörg; Strobel, Ingmar
2010-06-01
Work from more than 50 years of research has unraveled a number of molecular pathways that are involved in controlling aging of the fungal model system Podospora anserina. Early research revealed that wild-type strain aging is linked to gross reorganization of the mitochondrial DNA. Later it was shown that aging of P. anserina does also take place, although at a slower pace, when the wild-type specific mitochondrial DNA rearrangements do not occur. Now it is clear that a network of different pathways is involved in the control of aging. Branches of these pathways appear to be connected and constitute a hierarchical system of responses. Although cross talk between the individual pathways seems to be fundamental in the coordination of the overall system, the precise underlying interactions remain to be unraveled. Such a systematic approach aims at a holistic understanding of the process of biological aging, the ultimate goal of modern systems biology.
EcoFlex: A Multifunctional MoClo Kit for E. coli Synthetic Biology.
Moore, Simon J; Lai, Hung-En; Kelwick, Richard J R; Chee, Soo Mei; Bell, David J; Polizzi, Karen Marie; Freemont, Paul S
2016-10-21
Golden Gate cloning is a prominent DNA assembly tool in synthetic biology for the assembly of plasmid constructs often used in combinatorial pathway optimization, with a number of assembly kits developed specifically for yeast and plant-based expression. However, its use for synthetic biology in commonly used bacterial systems such as Escherichia coli has surprisingly been overlooked. Here, we introduce EcoFlex a simplified modular package of DNA parts for a variety of applications in E. coli, cell-free protein synthesis, protein purification and hierarchical assembly of transcription units based on the MoClo assembly standard. The kit features a library of constitutive promoters, T7 expression, RBS strength variants, synthetic terminators, protein purification tags and fluorescence proteins. We validate EcoFlex by assembling a 68-part containing (20 genes) plasmid (31 kb), characterize in vivo and in vitro library parts, and perform combinatorial pathway assembly, using pooled libraries of either fluorescent proteins or the biosynthetic genes for the antimicrobial pigment violacein as a proof-of-concept. To minimize pathway screening, we also introduce a secondary module design site to simplify MoClo pathway optimization. In summary, EcoFlex provides a standardized and multifunctional kit for a variety of applications in E. coli synthetic biology.
Jang, Ja-Young; Hong, Young June; Lim, Junsup; Choi, Jin Sung; Choi, Eun Ha; Kang, Seongman; Rhim, Hyangshuk
2018-02-01
Plasma, formed by ionization of gas molecules or atoms, is the most abundant form of matter and consists of highly reactive physicochemical species. In the physics and chemistry fields, plasma has been extensively studied; however, the exact action mechanisms of plasma on biological systems, including cells and humans, are not well known. Recent evidence suggests that cold atmospheric plasma (CAP), which refers to plasma used in the biomedical field, may regulate diverse cellular processes, including neural differentiation. However, the mechanism by which these physicochemical signals, elicited by reactive oxygen and nitrogen species (RONS), are transmitted to biological system remains elusive. In this study, we elucidated the physicochemical and biological (PCB) connection between the CAP cascade and Trk/Ras/ERK signaling pathway, which resulted in neural differentiation. Excited atomic oxygen in the plasma phase led to the formation of RONS in the PCB network, which then interacted with reactive atoms in the extracellular liquid phase to form nitric oxide (NO). Production of large amounts of superoxide radical (O 2 - ) in the mitochondria of cells exposed to CAP demonstrated that extracellular NO induced the reversible inhibition of mitochondrial complex IV. We also demonstrated that cytosolic hydrogen peroxide, formed by O 2 - dismutation, act as an intracellular messenger to specifically activate the Trk/Ras/ERK signaling pathway. This study is the first to elucidate the mechanism linking physicochemical signals from the CAP cascade to the intracellular neural differentiation signaling pathway, providing physical, chemical and biological insights into the development of therapeutic techniques to treat neurological diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.
Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei
2017-12-21
In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.
Systems biology of the modified branched Entner-Doudoroff pathway in Sulfolobus solfataricus
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:28692669
Regulation of the Wnt/β-Catenin Signaling Pathway by Human Papillomavirus E6 and E7 Oncoproteins
Muñoz Bello, Jesus Omar; Olmedo Nieva, Leslie; Contreras Paredes, Adriana; Fuentes Gonzalez, Alma Mariana; Rocha Zavaleta, Leticia; Lizano, Marcela
2015-01-01
Cell signaling pathways are the mechanisms by which cells transduce external stimuli, which control the transcription of genes, to regulate diverse biological effects. In cancer, distinct signaling pathways, such as the Wnt/β-catenin pathway, have been implicated in the deregulation of critical molecular processes that affect cell proliferation and differentiation. For example, changes in β-catenin localization have been identified in Human Papillomavirus (HPV)-related cancers as the lesion progresses. Specifically, β-catenin relocates from the membrane/cytoplasm to the nucleus, suggesting that this transcription regulator participates in cervical carcinogenesis. The E6 and E7 oncoproteins are responsible for the transforming activity of HPV, and some studies have implicated these viral oncoproteins in the regulation of the Wnt/β-catenin pathway. Nevertheless, new interactions of HPV oncoproteins with cellular proteins are emerging, and the study of the biological effects of such interactions will help to understand HPV-related carcinogenesis. This review addresses the accumulated evidence of the involvement of the HPV E6 and E7 oncoproteins in the activation of the Wnt/β-catenin pathway. PMID:26295406
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.
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.
Early Iron Deficiency Has Brain and Behavior Effects Consistent with Dopaminergic Dysfunction123
Lozoff, Betsy
2011-01-01
To honor the late John Beard’s many contributions regarding iron and dopamine biology, this review focuses on recent human studies that test specific hypotheses about effects of early iron deficiency on dopamine system functioning. Short- and long-term alterations associated with iron deficiency in infancy can be related to major dopamine pathways (mesocortical, mesolimbic, nigrostriatal, tuberohypophyseal). Children and young adults who had iron deficiency anemia in infancy show poorer inhibitory control and executive functioning as assessed by neurocognitive tasks where pharmacologic and neuroimaging studies implicate frontal-striatal circuits and the mesocortical dopamine pathway. Alterations in the mesolimbic pathway, where dopamine plays a major role in behavioral activation and inhibition, positive affect, and inherent reward, may help explain altered social-emotional behavior in iron-deficient infants, specifically wariness and hesitance, lack of positive affect, diminished social engagement, etc. Poorer motor sequencing and bimanual coordination and lower spontaneous eye blink rate in iron-deficient anemic infants are consistent with impaired function in the nigrostriatal pathway. Short- and long-term changes in serum prolactin point to dopamine dysfunction in the tuberohypophyseal pathway. These hypothesis-driven findings support the adverse effects of early iron deficiency on dopamine biology. Iron deficiency also has other effects, specifically on other neurotransmitters, myelination, dendritogenesis, neurometabolism in hippocampus and striatum, gene and protein profiles, and associated behaviors. The persistence of poorer cognitive, motor, affective, and sensory system functioning highlights the need to prevent iron deficiency in infancy and to find interventions that lessen the long-term effects of this widespread nutrient disorder. PMID:21346104
Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
2016-01-01
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
Photobiomodulation: phenomenology and its mechanism
NASA Astrophysics Data System (ADS)
Liu, Timon C.; Jiao, Jian-Ling; Xu, Xiao-Yang; Liu, Xiao-Guang; Deng, Shu-Xun; Liu, Song-Hao
2005-01-01
There are two kinds of pathways mediating cellular photobiomodulation, the specific one is mediated by the resonant interaction of light with molecules such as cytochrome nitrosyl complexes of mitochondrial electron transfer chain, singlet oxygen, hemoglobin or photosensentor such as endogenous porphyrines, the non-specific one is mediated by the non-resonant interaction of light with membrane proteins. Some of specific pathways mediating photobiomodulation can damage membrane or cell compartments such as mitochondria, lysosomes, endoplasmic reticulum by photodynamic damage if the light intensity is very high so that photodynamic damage will limit the maximum intensity of the light of photobiomodulation although the non-specific pathways mediating photobiomodulation might not damage cells. As the reciprocity law, the rule of Bunsen and Roscoe, was not obeyed for almost all the studied photobiomodulation, and the light energy reaps the greatest benefit where it is most needed, photobiomodulation was thought to be dominantly mediated by the non-specific pathways although the specific pathways can act as a role, which is supported by the dose relationship research in which the photobiomodulation effects were found to be the SIN function of radiation time in many works on the dose relationship when the intensity is kept constant. The non-specific pathways were mainly mediated by membrane receptors and the ultraweak non-resonant interaction of light with membrane receptors can be physically amplified by the coherent state of membrane receptors and then chemically exemplified by signal transduction according to our biological information model of photobiomodulation supported by its successful cellular, animal and clinic applications.
Application of Adverse Outcome Pathways to U.S. EPA’s Endocrine Disruptor Screening Program
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
Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang
2011-01-01
Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426
Spencer, Netanya Y; Engelhardt, John F
2014-03-18
Redox reactions have been established as major biological players in many cellular signaling pathways. Here we review mechanisms of redox signaling with an emphasis on redox-active signaling endosomes. Signals are transduced by relatively few reactive oxygen species (ROS), through very specific redox modifications of numerous proteins and enzymes. Although ROS signals are typically associated with cellular injury, these signaling pathways are also critical for maintaining cellular health at homeostasis. An important component of ROS signaling pertains to localization and tightly regulated signal transduction events within discrete microenvironments of the cell. One major aspect of this specificity is ROS compartmentalization within membrane-enclosed organelles such as redoxosomes (redox-active endosomes) and the nuclear envelope. Among the cellular proteins that produce superoxide are the NADPH oxidases (NOXes), transmembrane proteins that are implicated in many types of redox signaling. NOXes produce superoxide on only one side of a lipid bilayer; as such, their orientation dictates the compartmentalization of ROS and the local control of signaling events limited by ROS diffusion and/or movement through channels associated with the signaling membrane. NOX-dependent ROS signaling pathways can also be self-regulating, with molecular redox sensors that limit the local production of ROS required for effective signaling. ROS regulation of the Rac-GTPase, a required co-activator of many NOXes, is an example of this type of sensor. A deeper understanding of redox signaling pathways and the mechanisms that control their specificity will provide unique therapeutic opportunities for aging, cancer, ischemia-reperfusion injury, and neurodegenerative diseases.
2015-01-01
Redox reactions have been established as major biological players in many cellular signaling pathways. Here we review mechanisms of redox signaling with an emphasis on redox-active signaling endosomes. Signals are transduced by relatively few reactive oxygen species (ROS), through very specific redox modifications of numerous proteins and enzymes. Although ROS signals are typically associated with cellular injury, these signaling pathways are also critical for maintaining cellular health at homeostasis. An important component of ROS signaling pertains to localization and tightly regulated signal transduction events within discrete microenvironments of the cell. One major aspect of this specificity is ROS compartmentalization within membrane-enclosed organelles such as redoxosomes (redox-active endosomes) and the nuclear envelope. Among the cellular proteins that produce superoxide are the NADPH oxidases (NOXes), transmembrane proteins that are implicated in many types of redox signaling. NOXes produce superoxide on only one side of a lipid bilayer; as such, their orientation dictates the compartmentalization of ROS and the local control of signaling events limited by ROS diffusion and/or movement through channels associated with the signaling membrane. NOX-dependent ROS signaling pathways can also be self-regulating, with molecular redox sensors that limit the local production of ROS required for effective signaling. ROS regulation of the Rac-GTPase, a required co-activator of many NOXes, is an example of this type of sensor. A deeper understanding of redox signaling pathways and the mechanisms that control their specificity will provide unique therapeutic opportunities for aging, cancer, ischemia-reperfusion injury, and neurodegenerative diseases. PMID:24555469
Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh
2017-01-01
Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397
Linking microarray reporters with protein functions.
Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A
2007-09-26
The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.
Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John
2016-02-24
In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.
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 and therapeutic targets.
Quantitative Profiling of DNA Damage and Apoptotic Pathways in UV Damaged Cells Using PTMScan Direct
Stokes, Matthew P.; Silva, Jeffrey C.; Jia, Xiaoying; Lee, Kimberly A.; Polakiewicz, Roberto D.; Comb, Michael J.
2013-01-01
Traditional methods for analysis of peptides using liquid chromatography and tandem mass spectrometry (LC-MS/MS) lack the specificity to comprehensively monitor specific biological processes due to the inherent duty cycle limitations of the MS instrument and the stochastic nature of the analytical platform. PTMScan Direct is a novel, antibody-based method that allows quantitative LC-MS/MS profiling of specific peptides from proteins that reside in the same signaling pathway. New PTMScan Direct reagents have been produced that target peptides from proteins involved in DNA Damage/Cell Cycle and Apoptosis/Autophagy pathways. Together, the reagents provide access to 438 sites on 237 proteins in these signaling cascades. These reagents have been used to profile the response to UV damage of DNA in human cell lines. UV damage was shown to activate canonical DNA damage response pathways through ATM/ATR-dependent signaling, stress response pathways and induce the initiation of apoptosis, as assessed by an increase in the abundance of peptides corresponding to cleaved, activated caspases. These data demonstrate the utility of PTMScan Direct as a multiplexed assay for profiling specific cellular responses to various stimuli, such as UV damage of DNA. PMID:23344034
Alternative ground states enable pathway switching in biological electron transfer
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
Does Breastfeeding Protect Against Childhood Obesity? Moving Beyond Observational Evidence.
Woo, Jessica G; Martin, Lisa J
2015-06-01
Human milk is the optimal feeding choice for infants, as it dynamically provides the nutrients, immunity support, and other bioactive factors needed for infants at specific stages during development. Observational studies and several meta-analyses have suggested that breastfeeding is protective against development of obesity in childhood and beyond. However, these findings are not without significant controversy. This review includes an overview of observational findings to date, then focuses on three specific pathways that connect human milk and infant physiology: maternal obesity, microbiome development in the infant, and the development of taste preference and diet quality. Each of these pathways involves complex interactions between mother and infant, includes both biologic and non-biologic factors, and may have both direct and indirect effects on obesity risk in the offspring. This type of integrated approach to examining breastfeeding and childhood obesity is necessary to advance research in this area beyond observational findings.
A portable expression resource for engineering cross-species genetic circuits and pathways
Kushwaha, Manish; Salis, Howard M.
2015-01-01
Genetic circuits and metabolic pathways can be reengineered to allow organisms to process signals and manufacture useful chemicals. However, their functions currently rely on organism-specific regulatory parts, fragmenting synthetic biology and metabolic engineering into host-specific domains. To unify efforts, here we have engineered a cross-species expression resource that enables circuits and pathways to reuse the same genetic parts, while functioning similarly across diverse organisms. Our engineered system combines mixed feedback control loops and cross-species translation signals to autonomously self-regulate expression of an orthogonal polymerase without host-specific promoters, achieving nontoxic and tuneable gene expression in diverse Gram-positive and Gram-negative bacteria. Combining 50 characterized system variants with mechanistic modelling, we show how the cross-species expression resource's dynamics, capacity and toxicity are controlled by the control loops' architecture and feedback strengths. We also demonstrate one application of the resource by reusing the same genetic parts to express a biosynthesis pathway in both model and non-model hosts. PMID:26184393
Phelps, Carey; Israels, Brett; Marsh, Morgan C; von Hippel, Peter H; Marcus, Andrew H
2016-12-29
Recent advances in single-molecule fluorescence imaging have made it possible to perform measurements on microsecond time scales. Such experiments have the potential to reveal detailed information about the conformational changes in biological macromolecules, including the reaction pathways and dynamics of the rearrangements involved in processes, such as sequence-specific DNA "breathing" and the assembly of protein-nucleic acid complexes. Because microsecond-resolved single-molecule trajectories often involve "sparse" data, that is, they contain relatively few data points per unit time, they cannot be easily analyzed using the standard protocols that were developed for single-molecule experiments carried out with tens-of-millisecond time resolution and high "data density." Here, we describe a generalized approach, based on time-correlation functions, to obtain kinetic information from microsecond-resolved single-molecule fluorescence measurements. This approach can be used to identify short-lived intermediates that lie on reaction pathways connecting relatively long-lived reactant and product states. As a concrete illustration of the potential of this methodology for analyzing specific macromolecular systems, we accompany the theoretical presentation with the description of a specific biologically relevant example drawn from studies of reaction mechanisms of the assembly of the single-stranded DNA binding protein of the T4 bacteriophage replication complex onto a model DNA replication fork.
Application of Adverse Outcome Pathways (AOPs) in Human ...
The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making. Because many fundamental molecular and cellular pathways are conserved across taxa, data from assays that screen chemicals for their ability to interact with specific biomolecular targets can often be credibly applied to a broad range of species, even if the apical outcomes of those perturbations may differ. Information concerning the different trajectories of adversity that molecular initiating events may take in different taxa, life stages, and sexes of organisms can be captured in the form of an AOP network. As an example, AOPs documenting divergent consequences of thyroid peroxidase (TPO) and deiodinase (DIO) inhibition in mammals, amphibians, and fish have been developed. These AOPs provide the foundation for using data from common in vitro assays for TPO or DIO activity to inform both human health and ecological risk assessments. They also provide the foundation for an integrated approach to testing and assessment, where available information and biological understanding can be integrated in order to formulate plausible and testable hypotheses which can be used to target in vivo testing on the endpoints of greatest concern. Application of this AOP knowledge in several different r
Application of adverse outcome pathways (AOPs) in human ...
The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making. Because many fundamental molecular and cellular pathways are conserved across taxa, data from assays that screen chemicals for their ability to interact with specific biomolecular targets can often be credibly applied to a broad range of species, even if the apical outcomes of those perturbations may differ. Information concerning the different trajectories of adversity that molecular initiating events may take in different taxa, life stages, and sexes of organisms can be captured in the form of an AOP network. As an example, AOPs documenting divergent consequences of thyroid peroxidase (TPO) and deiodinase (DIO) inhibition in mammals, amphibians, and fish have been developed. These AOPs provide the foundation for using data from common in vitro assays for TPO or DIO activity to inform both human health and ecological risk assessments. They also provide the foundation for an integrated approach to testing and assessment, where available information and biological understanding can be integrated in order to formulate plausible and testable hypotheses which can be used to target in vivo testing on the endpoints of greatest concern. Application of this AOP knowledge in several different r
Darst, Burcu F.; Koscik, Rebecca L.; Racine, Annie M.; Oh, Jennifer M.; Krause, Rachel A.; Carlsson, Cynthia M.; Zetterberg, Henrik; Blennow, Kaj; Christian, Bradley T.; Bendlin, Barbara B.; Okonkwo, Ozioma C.; Hogan, Kirk J.; Hermann, Bruce P.; Sager, Mark A.; Asthana, Sanjay; Johnson, Sterling C.; Engelman, Corinne D.
2016-01-01
Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in β-amyloid (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging (PET) in 168 individuals, and cerebrospinal fluid (CSF) Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD. PMID:27662287
Reid, Noah M; Whitehead, Andrew
2016-09-01
Marine pollution is ubiquitous, and is one of the key factors influencing contemporary marine biodiversity worldwide. To protect marine biodiversity, how do we surveil, document and predict the short- and long-term impacts of pollutants on at-risk species? Modern genomics tools offer high-throughput, information-rich and increasingly cost-effective approaches for characterizing biological responses to environmental stress, and are important tools within an increasing sophisticated kit for surveiling and assessing impacts of pollutants on marine species. Through the lens of recent research in marine killifish, we illustrate how genomics tools may be useful for screening chemicals and pollutants for biological activity and to reveal specific mechanisms of action. The high dimensionality of transcriptomic responses enables their usage as highly specific fingerprints of exposure, and these fingerprints can be used to diagnose environmental problems. We also emphasize that molecular pathways recruited to respond at physiological timescales are the same pathways that may be targets for natural selection during chronic exposure to pollutants. Gene complement and sequence variation in those pathways can be related to variation in sensitivity to environmental pollutants within and among species. Furthermore, allelic variation associated with evolved tolerance in those pathways could be tracked to estimate the pace of environmental health decline and recovery. We finish by integrating these paradigms into a vision of how genomics approaches could anchor a modernized framework for advancing the predictive capacity of environmental and ecotoxicological science. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Heritable and non-heritable pathways to early callous-unemotional behaviors
Hyde, Luke W.; Waller, Rebecca; Trentacosta, Christopher J.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Ganiban, Jody M.; Reiss, David; Leve, Leslie D.
2016-01-01
Objective Callous-unemotional behaviors in early childhood identify children at high risk for severe trajectories of antisocial behavior and callous-unemotional traits that culminate in later diagnoses of conduct disorder, antisocial personality disorder, and psychopathy. Studies have demonstrated high heritability of callous-unemotional traits, but little research has examined specific heritable pathways to earlier callous-unemotional behaviors. Additionally, studies indicate that positive parenting protects against the development of callous-unemotional traits, but genetically informed designs have not been used to confirm that these relationships are not the product of gene-environment correlations. Method Using an adoption cohort of 561 families, biological mothers reported their history of severe antisocial behavior. Observations of adoptive mother positive reinforcement at 18 months were examined as predictors of callous-unemotional behaviors when children were 27 months old. Results Biological mother antisocial behavior predicted early callous-unemotional behaviors despite having no or limited contact with offspring. Adoptive mother positive reinforcement protected against early callous-unemotional behaviors in children not genetically related to the parent. High levels of adoptive mother positive reinforcement buffered the effects of heritable risk for callous-unemotional behaviors posed by biological mother antisocial behavior. Conclusions The findings elucidate heritable and non-heritable pathways to early callous-unemotional behaviors. The results provide a specific heritable pathway to callous-unemotional behaviors and compelling evidence that parenting is an important non-heritable factor in the development of callous-unemotional behaviors. As positive reinforcement buffered heritable risk for callous-unemotional behaviors, these findings have important translational implications for the prevention of trajectories to serious antisocial behavior. PMID:27056607
CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets
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
Hochfeld, Lara M; Anhalt, Thomas; Reinbold, Céline S; Herrera-Rivero, Marisol; Fricker, Nadine; Nöthen, Markus M; Heilmann-Heimbach, Stefanie
2017-02-22
Human hair follicle (HF) cycling is characterised by the tight orchestration and regulation of signalling cascades. Research shows that micro(mi)RNAs are potent regulators of these pathways. However, knowledge of the expression of miRNAs and their target genes and pathways in the human HF is limited. The objective of this study was to improve understanding of the role of miRNAs and their regulatory interactions in the human HF. Expression levels of ten candidate miRNAs with reported functions in hair biology were assessed in HFs from 25 healthy male donors. MiRNA expression levels were correlated with mRNA-expression levels from the same samples. Identified target genes were tested for enrichment in biological pathways and accumulation in protein-protein interaction (PPI) networks. Expression in the human HF was confirmed for seven of the ten candidate miRNAs, and numerous target genes for miR-24, miR-31, and miR-106a were identified. While the latter include several genes with known functions in hair biology (e.g., ITGB1, SOX9), the majority have not been previously implicated (e.g., PHF1). Target genes were enriched in pathways of interest to hair biology, such as integrin and GnRH signalling, and the respective gene products showed accumulation in PPIs. Further investigation of miRNA expression in the human HF, and the identification of novel miRNA target genes and pathways via the systematic integration of miRNA and mRNA expression data, may facilitate the delineation of tissue-specific regulatory interactions, and improve our understanding of both normal hair growth and the pathobiology of hair loss disorders.
KEEPING AN EYE ON RETINOBLASTOMA CONTROL OF HUMAN EMBRYONIC STEM CELLS
Conklin, Jamie F.; Sage, Julien
2010-01-01
Human embryonic stem cells (hESCs) hold great promise in regenerative medicine. However, before the full potential of these cells is achieved, major basic biological questions need to be addressed. In particular, there are still gaps in our knowledge of the molecular mechanisms underlying the derivation of hESCs from blastocysts, the regulation of the undifferentiated, pluripotent state, and the control of differentiation into specific lineages. Furthermore, we still do not fully understand the tumorigenic potential of hESCs, limiting their use in regenerative medicine. The RB pathway is a key signaling module that controls cellular proliferation, cell survival, chromatin structure, and cellular differentiation in mammalian cells. Members of the RB pathway are important regulators of hESC biology and manipulation of the activity of this pathway may provide novel means to control the fate of hESCs. Here we review what is known about the expression and function of members of the RB pathway in hESCs and discuss areas of interest in this field. PMID:19760644
2012-01-01
Background The post-genomic era of malaria research provided unprecedented insights into the biology of Plasmodium parasites. Due to the large evolutionary distance to model eukaryotes, however, we lack a profound understanding of many processes in Plasmodium biology. One example is the cell nucleus, which controls the parasite genome in a development- and cell cycle-specific manner through mostly unknown mechanisms. To study this important organelle in detail, we conducted an integrative analysis of the P. falciparum nuclear proteome. Results We combined high accuracy mass spectrometry and bioinformatic approaches to present for the first time an experimentally determined core nuclear proteome for P. falciparum. Besides a large number of factors implicated in known nuclear processes, one-third of all detected proteins carry no functional annotation, including many phylum- or genus-specific factors. Importantly, extensive experimental validation using 30 transgenic cell lines confirmed the high specificity of this inventory, and revealed distinct nuclear localization patterns of hitherto uncharacterized proteins. Further, our detailed analysis identified novel protein domains potentially implicated in gene transcription pathways, and sheds important new light on nuclear compartments and processes including regulatory complexes, the nucleolus, nuclear pores, and nuclear import pathways. Conclusion Our study provides comprehensive new insight into the biology of the Plasmodium nucleus and will serve as an important platform for dissecting general and parasite-specific nuclear processes in malaria parasites. Moreover, as the first nuclear proteome characterized in any protist organism, it will provide an important resource for studying evolutionary aspects of nuclear biology. PMID:23181666
Huang, Yezhou; Li, Shao
2010-01-18
Pathways in biological system often cooperate with each other to function. Changes of interactions among pathways tightly associate with alterations in the properties and functions of the cell and hence alterations in the phenotype. So, the pathway interactions and especially their changes over time corresponding to specific phenotype are critical to understanding cell functions and phenotypic plasticity. With prior-defined pathways and incorporated protein-protein interaction (PPI) data, we counted PPIs between corresponding gene sets of each pair of distinct pathways to construct a comprehensive pathway network. Then we proposed a novel concept, characteristic sub pathway network (CSPN), to realize the phenotype-specific pathway interactions. By adding gene expression data regarding a given phenotype, angiogenesis, active PPIs corresponding to stimulation of interleukin-1 (IL-1) and tumor necrosis factor alpha (TNF-alpha) on human umbilical vein endothelial cells (HUVECs) respectively were derived. Two kinds of CSPN, namely the static or the dynamic CSPN, were detected by counting active PPIs. A comprehensive pathway network containing 37 signalling pathways as nodes and 263 pathway interactions were obtained. Two phenotype-specific CSPNs for angiogenesis, corresponding to stimulation of IL-1 and TNF-alpha on HUVEC respectively, were addressed. From phenotype-specific CSPNs, a static CSPN involving interactions among B cell receptor, T cell receptor, Toll-like receptor, MAPK, VEGF, and ErbB signalling pathways, and a dynamic CSPN involving interactions among TGF-beta, Wnt, p53 signalling pathways and cell cycle pathway, were detected for angiogenesis on HUVEC after stimulation of IL-1 and TNF-alpha respectively. We inferred that, in certain case, the static CSPN maintains related basic functions of the cells, whereas the dynamic CSPN manifests the cells' plastic responses to stimulus and therefore reflects the cells' phenotypic plasticity. The comprehensive pathway network helps us realize the cooperative behaviours among pathways. Moreover, two kinds of potential CSPNs found in this work, the static CSPN and the dynamic CSPN, are helpful to deeply understand the specific function of HUVEC and its phenotypic plasticity in regard to angiogenesis.
2010-01-01
Background Pathways in biological system often cooperate with each other to function. Changes of interactions among pathways tightly associate with alterations in the properties and functions of the cell and hence alterations in the phenotype. So, the pathway interactions and especially their changes over time corresponding to specific phenotype are critical to understanding cell functions and phenotypic plasticity. Methods With prior-defined pathways and incorporated protein-protein interaction (PPI) data, we counted PPIs between corresponding gene sets of each pair of distinct pathways to construct a comprehensive pathway network. Then we proposed a novel concept, characteristic sub pathway network (CSPN), to realize the phenotype-specific pathway interactions. By adding gene expression data regarding a given phenotype, angiogenesis, active PPIs corresponding to stimulation of interleukin-1 (IL-1) and tumor necrosis factor α (TNF-α) on human umbilical vein endothelial cells (HUVECs) respectively were derived. Two kinds of CSPN, namely the static or the dynamic CSPN, were detected by counting active PPIs. Results A comprehensive pathway network containing 37 signalling pathways as nodes and 263 pathway interactions were obtained. Two phenotype-specific CSPNs for angiogenesis, corresponding to stimulation of IL-1 and TNF-α on HUVEC respectively, were addressed. From phenotype-specific CSPNs, a static CSPN involving interactions among B cell receptor, T cell receptor, Toll-like receptor, MAPK, VEGF, and ErbB signalling pathways, and a dynamic CSPN involving interactions among TGF-β, Wnt, p53 signalling pathways and cell cycle pathway, were detected for angiogenesis on HUVEC after stimulation of IL-1 and TNF-α respectively. We inferred that, in certain case, the static CSPN maintains related basic functions of the cells, whereas the dynamic CSPN manifests the cells' plastic responses to stimulus and therefore reflects the cells' phenotypic plasticity. Conclusion The comprehensive pathway network helps us realize the cooperative behaviours among pathways. Moreover, two kinds of potential CSPNs found in this work, the static CSPN and the dynamic CSPN, are helpful to deeply understand the specific function of HUVEC and its phenotypic plasticity in regard to angiogenesis. PMID:20122205
Chemical genomics in plant biology.
Sadhukhan, Ayan; Sahoo, Lingaraj; Panda, Sanjib Kumar
2012-06-01
Chemical genomics is a newly emerged and rapidly progressing field in biology, where small chemical molecules bind specifically and reversibly to protein(s) to modulate their function(s), leading to the delineation and subsequent unravelling of biological processes. This approach overcomes problems like lethality and redundancy of classical genetics. Armed with the powerful techniques of combinatorial synthesis, high-throughput screening and target discovery chemical genomics expands its scope to diverse areas in biology. The well-established genetic system of Arabidopsis model allows chemical genomics to enter into the realm of plant biology exploring signaling pathways of growth regulators, endomembrane signaling cascades, plant defense mechanisms and many more events.
Martinez‐Barbera, Juan Pedro
2017-01-01
Abstract Adamantinomatous craniopharyngioma (ACP) is the commonest tumor of the sellar region in childhood. Two genetically engineered mouse models have been developed and are giving valuable insights into ACP biology. These models have identified novel pathways activated in tumors, revealed an important function of paracrine signalling and extended conventional theories about the role of organ‐specific stem cells in tumorigenesis. In this review, we summarize these mouse models, what has been learnt, their limitations and open questions for future research. We then discussed how these mouse models may be used to test novel therapeutics against potentially targetable pathways recently identified in human ACP. PMID:28414891
Integrating genomics and proteomics data to predict drug effects using binary linear programming.
Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo
2014-01-01
The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be used to elucidate potential mechanisms of a compound's efficacy.
An editor for pathway drawing and data visualization in the Biopathways Workbench.
Byrnes, Robert W; Cotter, Dawn; Maer, Andreia; Li, Joshua; Nadeau, David; Subramaniam, Shankar
2009-10-02
Pathway models serve as the basis for much of systems biology. They are often built using programs designed for the purpose. Constructing new models generally requires simultaneous access to experimental data of diverse types, to databases of well-characterized biological compounds and molecular intermediates, and to reference model pathways. However, few if any software applications provide all such capabilities within a single user interface. The Pathway Editor is a program written in the Java programming language that allows de-novo pathway creation and downloading of LIPID MAPS (Lipid Metabolites and Pathways Strategy) and KEGG lipid metabolic pathways, and of measured time-dependent changes to lipid components of metabolism. Accessed through Java Web Start, the program downloads pathways from the LIPID MAPS Pathway database (Pathway) as well as from the LIPID MAPS web server http://www.lipidmaps.org. Data arises from metabolomic (lipidomic), microarray, and protein array experiments performed by the LIPID MAPS consortium of laboratories and is arranged by experiment. Facility is provided to create, connect, and annotate nodes and processes on a drawing panel with reference to database objects and time course data. Node and interaction layout as well as data display may be configured in pathway diagrams as desired. Users may extend diagrams, and may also read and write data and non-lipidomic KEGG pathways to and from files. Pathway diagrams in XML format, containing database identifiers referencing specific compounds and experiments, can be saved to a local file for subsequent use. The program is built upon a library of classes, referred to as the Biopathways Workbench, that convert between different file formats and database objects. An example of this feature is provided in the form of read/construct/write access to models in SBML (Systems Biology Markup Language) contained in the local file system. Inclusion of access to multiple experimental data types and of pathway diagrams within a single interface, automatic updating through connectivity to an online database, and a focus on annotation, including reference to standardized lipid nomenclature as well as common lipid names, supports the view that the Pathway Editor represents a significant, practicable contribution to current pathway modeling tools.
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.
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.
Linking microarray reporters with protein functions
Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA
2007-01-01
Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448
Virtual Embryo: Systems Modeling in Developmental Toxicity
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...
Understanding the Contribution of Zinc Transporters in the Function of the Early Secretory Pathway
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.
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.
Efforts to make and apply humanized yeast
Laurent, Jon M.; Young, Jonathan H.; Kachroo, Aashiq H.
2016-01-01
Despite a billion years of divergent evolution, the baker’s yeast Saccharomyces cerevisiae has long proven to be an invaluable model organism for studying human biology. Given its tractability and ease of genetic manipulation, along with extensive genetic conservation with humans, it is perhaps no surprise that researchers have been able to expand its utility by expressing human proteins in yeast, or by humanizing specific yeast amino acids, proteins or even entire pathways. These methods are increasingly being scaled in throughput, further enabling the detailed investigation of human biology and disease-specific variations of human genes in a simplified model organism. PMID:26462863
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.
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
Discovery of cancer common and specific driver gene sets
2017-01-01
Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295
Cyclic Nucleotide Phosphodiesterases: important signaling modulators and therapeutic targets
Ahmad, Faiyaz; Murata, Taku; Simizu, Kasumi; Degerman, Eva; Maurice, Donald; Manganiello, Vincent
2014-01-01
By catalyzing hydrolysis of cAMP and cGMP, cyclic nucleotide phosphodiesterases are critical regulators of their intracellular concentrations and their biological effects. Since these intracellular second messengers control many cellular homeostatic processes, dysregulation of their signals and signaling pathways initiate or modulate pathophysiological pathways related to various disease states, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication, chronic obstructive pulmonary disease, and psoriasis. Alterations in expression of PDEs and PDE-gene mutations (especially mutations in PDE6, PDE8B, PDE11A and PDE4) have been implicated in various diseases and cancer pathologies. PDEs also play important role in formation and function of multi-molecular signaling/regulatory complexes called signalosomes. At specific intracellular locations, individual PDEs, together with pathway-specific signaling molecules, regulators, and effectors, are incorporated into specific signalosomes, where they facilitate and regulate compartmentalization of cyclic nucleotide signaling pathways and specific cellular functions. Currently, only a limited number of PDE inhibitors (PDE3, PDE4, PDE5 inhibitors) are used in clinical practice. Future paths to novel drug discovery include the crystal structure-based design approach, which has resulted in generation of more effective family-selective inhibitors, as well as burgeoning development of strategies to alter compartmentalized cyclic nucleotide signaling pathways by selectively targeting individual PDEs and their signalosome partners. PMID:25056711
In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line.
Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R; Shen, Han-Ming; Lin, Qingsong
2016-02-26
To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQ(TM) quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway Analysis(TM) (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death.
In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line
Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R.; Shen, Han-Ming; Lin, Qingsong
2016-01-01
To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQTM quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway AnalysisTM (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death. PMID:26915414
High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike
2010-01-01
We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139
Design of a prototype flow microreactor for synthetic biology in vitro.
Boehm, Christian R; Freemont, Paul S; Ces, Oscar
2013-09-07
As a reference platform for in vitro synthetic biology, we have developed a prototype flow microreactor for enzymatic biosynthesis. We report the design, implementation, and computer-aided optimisation of a three-step model pathway within a microfluidic reactor. A packed bed format was shown to be optimal for enzyme compartmentalisation after experimental evaluation of several approaches. The specific substrate conversion efficiency could significantly be improved by an optimised parameter set obtained by computational modelling. Our microreactor design provides a platform to explore new in vitro synthetic biology solutions for industrial biosynthesis.
Tongue and Taste Organ Biology and Function: Homeostasis Maintained by Hedgehog Signaling.
Mistretta, Charlotte M; Kumari, Archana
2017-02-10
The tongue is an elaborate complex of heterogeneous tissues with taste organs of diverse embryonic origins. The lingual taste organs are papillae, composed of an epithelium that includes specialized taste buds, the basal lamina, and a lamina propria core with matrix molecules, fibroblasts, nerves, and vessels. Because taste organs are dynamic in cell biology and sensory function, homeostasis requires tight regulation in specific compartments or niches. Recently, the Hedgehog (Hh) pathway has emerged as an essential regulator that maintains lingual taste papillae, taste bud and progenitor cell proliferation and differentiation, and neurophysiological function. Activating or suppressing Hh signaling, with genetic models or pharmacological agents used in cancer treatments, disrupts taste papilla and taste bud integrity and can eliminate responses from taste nerves to chemical stimuli but not to touch or temperature. Understanding Hh regulation of taste organ homeostasis contributes knowledge about the basic biology underlying taste disruptions in patients treated with Hh pathway inhibitors.
MetNetAPI: A flexible method to access and manipulate biological network data from MetNet
2010-01-01
Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api. PMID:21083943
Reconstruction of metabolic pathways for the cattle genome
Seo, Seongwon; Lewin, Harris A
2009-01-01
Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618
High-throughput screening, predictive modeling and computational embryology - Abstract
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...
The m6A pathway facilitates sex determination in Drosophila
Kan, Lijuan; Grozhik, Anya V.; Vedanayagam, Jeffrey; Patil, Deepak P.; Pang, Nan; Lim, Kok-Seong; Huang, Yi-Chun; Joseph, Brian; Lin, Ching-Jung; Despic, Vladimir; Guo, Jian; Yan, Dong; Kondo, Shu; Deng, Wu-Min; Dedon, Peter C.; Jaffrey, Samie R.; Lai, Eric C.
2017-01-01
The conserved modification N6-methyladenosine (m6A) modulates mRNA processing and activity. Here, we establish the Drosophila system to study the m6A pathway. We first apply miCLIP to map m6A across embryogenesis, characterize its m6A ‘writer’ complex, validate its YTH ‘readers’ CG6422 and YT521-B, and generate mutants in five m6A factors. While m6A factors with additional roles in splicing are lethal, m6A-specific mutants are viable but present certain developmental and behavioural defects. Notably, m6A facilitates the master female determinant Sxl, since multiple m6A components enhance female lethality in Sxl sensitized backgrounds. The m6A pathway regulates Sxl processing directly, since miCLIP data reveal Sxl as a major intronic m6A target, and female-specific Sxl splicing is compromised in multiple m6A pathway mutants. YT521-B is a dominant m6A effector for Sxl regulation, and YT521-B overexpression can induce female-specific Sxl splicing. Overall, our transcriptomic and genetic toolkit reveals in vivo biologic function for the Drosophila m6A pathway. PMID:28675155
Discovery of cashmere goat (Capra hircus) microRNAs in skin and hair follicles by Solexa sequencing.
Yuan, Chao; Wang, Xiaolong; Geng, Rongqing; He, Xiaolin; Qu, Lei; Chen, Yulin
2013-07-28
MicroRNAs (miRNAs) are a large family of endogenous, non-coding RNAs, about 22 nucleotides long, which regulate gene expression through sequence-specific base pairing with target mRNAs. Extensive studies have shown that miRNA expression in the skin changes remarkably during distinct stages of the hair cycle in humans, mice, goats and sheep. In this study, the skin tissues were harvested from the three stages of hair follicle cycling (anagen, catagen and telogen) in a fibre-producing goat breed. In total, 63,109,004 raw reads were obtained by Solexa sequencing and 61,125,752 clean reads remained for the small RNA digitalisation analysis. This resulted in the identification of 399 conserved miRNAs; among these, 326 miRNAs were expressed in all three follicular cycling stages, whereas 3, 12 and 11 miRNAs were specifically expressed in anagen, catagen, and telogen, respectively. We also identified 172 potential novel miRNAs by Mireap, 36 miRNAs were expressed in all three cycling stages, whereas 23, 29 and 44 miRNAs were specifically expressed in anagen, catagen, and telogen, respectively. The expression level of five arbitrarily selected miRNAs was analyzed by quantitative PCR, and the results indicated that the expression patterns were consistent with the Solexa sequencing results. Gene Ontology and KEGG pathway analyses indicated that five major biological pathways (Metabolic pathways, Pathways in cancer, MAPK signalling pathway, Endocytosis and Focal adhesion) accounted for 23.08% of target genes among 278 biological functions, indicating that these pathways are likely to play significant roles during hair cycling. During all hair cycle stages of cashmere goats, a large number of conserved and novel miRNAs were identified through a high-throughput sequencing approach. This study enriches the Capra hircus miRNA databases and provides a comprehensive miRNA transcriptome profile in the skin of goats during the hair follicle cycle.
Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia
2015-01-01
Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020
Huang, Chao-Ying; Chang, Cheng-Wei; Chen, Chaang-Ray; Chuang, Chun-Yu; Chiang, Chi-Shiun; Shu, Wun-Yi; Fan, Tai-Ching; Hsu, Ian C.
2014-01-01
In daily life, humans are exposed to the extremely low-frequency electromagnetic fields (ELF-EMFs) generated by electric appliances, and public concern is increasing regarding the biological effects of such exposure. Numerous studies have yielded inconsistent results regarding the biological effects of ELF-EMF exposure. Here we show that ELF-EMFs activate the ATM-Chk2-p21 pathway in HaCaT cells, inhibiting cell proliferation. To present well-founded results, we comprehensively evaluated the biological effects of ELF-EMFs at the transcriptional, protein, and cellular levels. Human HaCaT cells from an immortalized epidermal keratinocyte cell line were exposed to a 1.5 mT, 60 Hz ELF-EMF for 144 h. The ELF-EMF could cause G1 arrest and decrease colony formation. Protein expression experiments revealed that ELF-EMFs induced the activation of the ATM/Chk2 signaling cascades. In addition, the p21 protein, a regulator of cell cycle progression at G1 and G2/M, exhibited a higher level of expression in exposed HaCaT cells compared with the expression of sham-exposed cells. The ELF-EMF-induced G1 arrest was diminished when the CHK2 gene expression (which encodes checkpoint kinase 2; Chk2) was suppressed by specific small interfering RNA (siRNA). These findings indicate that ELF-EMFs activate the ATM-Chk2-p21 pathway in HaCaT cells, resulting in cell cycle arrest at the G1 phase. Based on the precise control of the ELF-EMF exposure and rigorous sham-exposure experiments, all transcriptional, protein, and cellular level experiments consistently supported the conclusion. This is the first study to confirm that a specific pathway is triggered by ELF-EMF exposure. PMID:25111195
Applying Aggregate Exposure Pathway and Adverse Outcome ...
Hazard assessment for nanomaterials often involves applying in vitro dose-response data to estimate potential health risks that arise from exposure to products that contain nanomaterials. However, much uncertainty is inherent in relating bioactivities observed in an in vitro system to the perturbations of biological mechanisms that lead to apical adverse health outcomes in living organisms. The Adverse Outcome Pathway (AOP) framework addresses this uncertainty by acting as a scaffold onto which in vitro toxicity testing and other data can be arranged to aid in the interpretation of these results in terms of biologically-relevant responses, as an AOP connects an upstream molecular initiating event (MIE) to a downstream adverse outcome. In addition to hazard assessment, risk estimation also requires reconciling in vitro concentrations sufficient to produce bioactivity with in vivo concentrations that can trigger a MIE at the relevant biological target. Such target site exposures (TSEs) can be estimated by integrating pharmacokinetic considerations with environmental and exposure factors. Environmental and exposure data have been historically scattered in various resources, such as monitoring data for air pollutants or exposure models for specific chemicals. The Aggregate Exposure Pathway (AEP) framework is introduced to organize existing knowledge concerning biologically, chemically, and physically plausible, as well as empirically supported, links between the i
CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis.
Vrahatis, Aristidis G; Dimitrakopoulou, Konstantina; Balomenos, Panos; Tsakalidis, Athanasios K; Bezerianos, Anastasios
2016-03-15
In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific 'active parts' of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical 'themes'-in the form of enriched biologically relevant microRNA-mediated subpathways-that determine the functionality of signaling networks across time. To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/ tassos.bezerianos@nus.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
The Chromatin Remodeler SPLAYED Regulates Specific Stress Signaling Pathways
Walley, Justin W.; Rowe, Heather C.; Xiao, Yanmei; Chehab, E. Wassim; Kliebenstein, Daniel J.; Wagner, Doris; Dehesh, Katayoon
2008-01-01
Organisms are continuously exposed to a myriad of environmental stresses. Central to an organism's survival is the ability to mount a robust transcriptional response to the imposed stress. An emerging mechanism of transcriptional control involves dynamic changes in chromatin structure. Alterations in chromatin structure are brought about by a number of different mechanisms, including chromatin modifications, which covalently modify histone proteins; incorporation of histone variants; and chromatin remodeling, which utilizes ATP hydrolysis to alter histone-DNA contacts. While considerable insight into the mechanisms of chromatin remodeling has been gained, the biological role of chromatin remodeling complexes beyond their function as regulators of cellular differentiation and development has remained poorly understood. Here, we provide genetic, biochemical, and biological evidence for the critical role of chromatin remodeling in mediating plant defense against specific biotic stresses. We found that the Arabidopsis SWI/SNF class chromatin remodeling ATPase SPLAYED (SYD) is required for the expression of selected genes downstream of the jasmonate (JA) and ethylene (ET) signaling pathways. SYD is also directly recruited to the promoters of several of these genes. Furthermore, we show that SYD is required for resistance against the necrotrophic pathogen Botrytis cinerea but not the biotrophic pathogen Pseudomonas syringae. These findings demonstrate not only that chromatin remodeling is required for selective pathogen resistance, but also that chromatin remodelers such as SYD can regulate specific pathways within biotic stress signaling networks. PMID:19079584
The chromatin remodeler SPLAYED regulates specific stress signaling pathways.
Walley, Justin W; Rowe, Heather C; Xiao, Yanmei; Chehab, E Wassim; Kliebenstein, Daniel J; Wagner, Doris; Dehesh, Katayoon
2008-12-01
Organisms are continuously exposed to a myriad of environmental stresses. Central to an organism's survival is the ability to mount a robust transcriptional response to the imposed stress. An emerging mechanism of transcriptional control involves dynamic changes in chromatin structure. Alterations in chromatin structure are brought about by a number of different mechanisms, including chromatin modifications, which covalently modify histone proteins; incorporation of histone variants; and chromatin remodeling, which utilizes ATP hydrolysis to alter histone-DNA contacts. While considerable insight into the mechanisms of chromatin remodeling has been gained, the biological role of chromatin remodeling complexes beyond their function as regulators of cellular differentiation and development has remained poorly understood. Here, we provide genetic, biochemical, and biological evidence for the critical role of chromatin remodeling in mediating plant defense against specific biotic stresses. We found that the Arabidopsis SWI/SNF class chromatin remodeling ATPase SPLAYED (SYD) is required for the expression of selected genes downstream of the jasmonate (JA) and ethylene (ET) signaling pathways. SYD is also directly recruited to the promoters of several of these genes. Furthermore, we show that SYD is required for resistance against the necrotrophic pathogen Botrytis cinerea but not the biotrophic pathogen Pseudomonas syringae. These findings demonstrate not only that chromatin remodeling is required for selective pathogen resistance, but also that chromatin remodelers such as SYD can regulate specific pathways within biotic stress signaling networks.
Zadran, Sohila; Levine, Raphael D
2013-01-01
Metabolic engineering seeks to redirect metabolic pathways through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant technology. Many of the chemicals synthesized via introduction of product-specific enzymes or the reconstruction of entire metabolic pathways into engineered hosts that can sustain production and can synthesize high yields of the desired product as yields of natural product-derived compounds are frequently low, and chemical processes can be both energy and material expensive; current endeavors have focused on using biologically derived processes as alternatives to chemical synthesis. Such economically favorable manufacturing processes pursue goals related to sustainable development and "green chemistry". Metabolic engineering is a multidisciplinary approach, involving chemical engineering, molecular biology, biochemistry, and analytical chemistry. Recent advances in molecular biology, genome-scale models, theoretical understanding, and kinetic modeling has increased interest in using metabolic engineering to redirect metabolic fluxes for industrial and therapeutic purposes. The use of metabolic engineering has increased the productivity of industrially pertinent small molecules, alcohol-based biofuels, and biodiesel. Here, we highlight developments in the practical and theoretical strategies and technologies available for the metabolic engineering of simple systems and address current limitations.
A computational platform to maintain and migrate manual functional annotations for BioCyc databases.
Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A
2014-10-12
BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.
Hughes, Michael W.; Wu, Ping; Jiang, Ting-Xin; Lin, Sung-Jan; Dong, Chen-Yuan; Li, Ang; Hsieh, Fon-Jou; Widelitz, Randall B.; Choung, Cheng Ming
2013-01-01
Summary The mythological story of the Golden Fleece symbolizes the magical regenerative power of skin appendages. Similar to the adventurous pursuit of the Golden Fleece by the multi-talented Argonauts, today we also need an integrated multi-disciplined approach to understand the cellular and molecular processes during development, regeneration and evolution of skin appendages. To this end, we have explored several aspects of skin appendage biology that contribute to the Turing activator / inhibitor model in feather pattern formation, the topo-biological arrangement of stem cells in organ shape determination, the macro-environmental regulation of stem cells in regenerative hair waves, and potential novel molecular pathways in the morphological evolution of feathers. Here we show our current integrative biology efforts to unravel the complex cellular behavior in patterning stem cells and the control of regional specificity in skin appendages. We use feather / scale tissue recombination to demonstrate the timing control of competence and inducibility. Feathers from different body regions are used to study skin regional specificity. Bioinformatic analyses of transcriptome microarrays show the potential involvement of candidate molecular pathways. We further show Hox genes exhibit some region specific expression patterns. To visualize real time events, we applied time-lapse movies, confocal microscopy and multiphoton microscopy to analyze the morphogenesis of cultured embryonic chicken skin explants. These modern imaging technologies reveal unexpectedly complex cellular flow and organization of extracellular matrix molecules in three dimensions. While these approaches are in preliminary stages, this perspective highlights the challenges we face and new integrative tools we will use. Future work will follow these leads to develop a systems biology view and understanding in the morphogenetic principles that govern the development and regeneration of ectodermal organs. PMID:21437328
Mass Spectrometry: A Technique of Many Faces
Olshina, Maya A.; Sharon, Michal
2016-01-01
Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928
Gil, Jeovanis; Ramírez-Torres, Alberto; Chiappe, Diego; Luna-Peñaloza, Juan; Fernandez-Reyes, Francis C; Arcos-Encarnación, Bolivar; Contreras, Sandra; Encarnación-Guevara, Sergio
2017-11-03
Lysine acetylation is a widespread posttranslational modification affecting many biological pathways. Recent studies indicate that acetylated lysine residues mainly exhibit low acetylation occupancy, but challenges in sample preparation and analysis make it difficult to confidently assign these numbers, limiting understanding of their biological significance. Here, we tested three common sample preparation methods to determine their suitability for assessing acetylation stoichiometry in three human cell lines, identifying the acetylation occupancy in more than 1,300 proteins from each cell line. The stoichiometric analysis in combination with quantitative proteomics also enabled us to explore their functional roles. We found that higher abundance of the deacetylase sirtuin 1 (SIRT1) correlated with lower acetylation occupancy and lower levels of ribosomal proteins, including those involved in ribosome biogenesis and rRNA processing. Treatment with the SIRT1 inhibitor EX-527 confirmed SIRT1's role in the regulation of pre-rRNA synthesis and processing. Specifically, proteins involved in pre-rRNA transcription, including subunits of the polymerase I and SL1 complexes and the RNA polymerase I-specific transcription initiation factor RRN3, were up-regulated after SIRT1 inhibition. Moreover, many protein effectors and regulators of pre-rRNA processing needed for rRNA maturation were also up-regulated after EX-527 treatment with the outcome that pre-rRNA and 28S rRNA levels also increased. More generally, we found that SIRT1 inhibition down-regulates metabolic pathways, including glycolysis and pyruvate metabolism. Together, these results provide the largest data set thus far of lysine acetylation stoichiometry (available via ProteomeXchange with identifier PXD005903) and set the stage for further biological investigations of this central posttranslational modification. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Durmaz, Arda; Henderson, Tim A D; Brubaker, Douglas; Bebek, Gurkan
2017-01-01
Large scale genomics studies have generated comprehensive molecular characterization of numerous cancer types. Subtypes for many tumor types have been established; however, these classifications are based on molecular characteristics of a small gene sets with limited power to detect dysregulation at the patient level. We hypothesize that frequent graph mining of pathways to gather pathways functionally relevant to tumors can characterize tumor types and provide opportunities for personalized therapies. In this study we present an integrative omics approach to group patients based on their altered pathway characteristics and show prognostic differences within breast cancer (p < 9:57E - 10) and glioblastoma multiforme (p < 0:05) patients. We were able validate this approach in secondary RNA-Seq datasets with p < 0:05 and p < 0:01 respectively. We also performed pathway enrichment analysis to further investigate the biological relevance of dysregulated pathways. We compared our approach with network-based classifier algorithms and showed that our unsupervised approach generates more robust and biologically relevant clustering whereas previous approaches failed to report specific functions for similar patient groups or classify patients into prognostic groups. These results could serve as a means to improve prognosis for future cancer patients, and to provide opportunities for improved treatment options and personalized interventions. The proposed novel graph mining approach is able to integrate PPI networks with gene expression in a biologically sound approach and cluster patients in to clinically distinct groups. We have utilized breast cancer and glioblastoma multiforme datasets from microarray and RNA-Seq platforms and identified disease mechanisms differentiating samples. Supplementary methods, figures, tables and code are available at https://github.com/bebeklab/dysprog.
Gramene 2013: comparative plant genomics resources.
Monaco, Marcela K; Stein, Joshua; Naithani, Sushma; Wei, Sharon; Dharmawardhana, Palitha; Kumari, Sunita; Amarasinghe, Vindhya; Youens-Clark, Ken; Thomason, James; Preece, Justin; Pasternak, Shiran; Olson, Andrew; Jiao, Yinping; Lu, Zhenyuan; Bolser, Dan; Kerhornou, Arnaud; Staines, Dan; Walts, Brandon; Wu, Guanming; D'Eustachio, Peter; Haw, Robin; Croft, David; Kersey, Paul J; Stein, Lincoln; Jaiswal, Pankaj; Ware, Doreen
2014-01-01
Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.
BCL-2 Antagonism to Target the Intrinsic Mitochondrial Pathway of Apoptosis
Gibson, Christopher J.; Davids, Matthew S.
2015-01-01
Despite significant improvements in treatment, cure rates for many cancers remain suboptimal. The rise of cytotoxic chemotherapy has led to curative therapy for a subset of cancers, though intrinsic treatment resistance is difficult to predict for individual patients. The recent wave of molecularly targeted therapies has focused on druggable activating mutations, and is thus limited to specific subsets of patients. The lessons learned from these two disparate approaches suggest the need for therapies that borrow aspects of both, targeting biological properties of cancer that are at once distinct from normal cells and yet common enough to make the drugs widely applicable across a range of cancer subtypes. The intrinsic mitochondrial pathway of apoptosis represents one such promising target for new therapies, and successfully targeting this pathway has the potential to alter the therapeutic landscape of therapy for a variety of cancers. Here, we discuss the biology of the intrinsic pathway of apoptosis, an assay known as BH3 profiling that can interrogate this pathway, early attempts to target BCL-2 clinically, and the recent promising results with the BCL-2 antagonist venetoclax (ABT-199) in clinical trials in hematologic malignancies. PMID:26567361
Multivariate inference of pathway activity in host immunity and response to therapeutics
Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.
2014-01-01
Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207
Assessing the bioavailability and risk from metal contaminated soils and dusts#
Exposure to contaminated soil and dust is an important pathway in human and ecological risk assessment and often is the "risk-driver" for metal contaminated soil. Site-specific soil physical and chemical characteristics, as well as biological factors, determine the bioavailabilit...
A race-specific interaction between vitamin K status and statin use
USDA-ARS?s Scientific Manuscript database
The oral anticoagulant warfarin is a vitamin K antagonist. Phylloquinone, the primary circulating form of vitamin K, is transported by triglyceride-rich lipoproteins and shares a metabolic pathway with cholesterol. Thus, there is biological plausibility for an interaction between serum phylloquinone...
Kugler, Jamie E.; Horsch, Marion; Huang, Di; Furusawa, Takashi; Rochman, Mark; Garrett, Lillian; Becker, Lore; Bohla, Alexander; Hölter, Sabine M.; Prehn, Cornelia; Rathkolb, Birgit; Racz, Ildikó; Aguilar-Pimentel, Juan Antonio; Adler, Thure; Adamski, Jerzy; Beckers, Johannes; Busch, Dirk H.; Eickelberg, Oliver; Klopstock, Thomas; Ollert, Markus; Stöger, Tobias; Wolf, Eckhard; Wurst, Wolfgang; Yildirim, Ali Önder; Zimmer, Andreas; Gailus-Durner, Valérie; Fuchs, Helmut; Hrabě de Angelis, Martin; Garfinkel, Benny; Orly, Joseph; Ovcharenko, Ivan; Bustin, Michael
2013-01-01
The nuclei of most vertebrate cells contain members of the high mobility group N (HMGN) protein family, which bind specifically to nucleosome core particles and affect chromatin structure and function, including transcription. Here, we study the biological role of this protein family by systematic analysis of phenotypes and tissue transcription profiles in mice lacking functional HMGN variants. Phenotypic analysis of Hmgn1tm1/tm1, Hmgn3tm1/tm1, and Hmgn5tm1/tm1 mice and their wild type littermates with a battery of standardized tests uncovered variant-specific abnormalities. Gene expression analysis of four different tissues in each of the Hmgntm1/tm1 lines reveals very little overlap between genes affected by specific variants in different tissues. Pathway analysis reveals that loss of an HMGN variant subtly affects expression of numerous genes in specific biological processes. We conclude that within the biological framework of an entire organism, HMGNs modulate the fidelity of the cellular transcriptional profile in a tissue- and HMGN variant-specific manner. PMID:23620591
2013-01-01
Background The availability of gene expression data that corresponds to pig immune response challenges provides compelling material for the understanding of the host immune system. Meta-analysis offers the opportunity to confirm and expand our knowledge by combining and studying at one time a vast set of independent studies creating large datasets with increased statistical power. In this study, we performed two meta-analyses of porcine transcriptomic data: i) scrutinized the global immune response to different challenges, and ii) determined the specific response to Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) infection. To gain an in-depth knowledge of the pig response to PRRSV infection, we used an original approach comparing and eliminating the common genes from both meta-analyses in order to identify genes and pathways specifically involved in the PRRSV immune response. The software Pointillist was used to cope with the highly disparate data, circumventing the biases generated by the specific responses linked to single studies. Next, we used the Ingenuity Pathways Analysis (IPA) software to survey the canonical pathways, biological functions and transcription factors found to be significantly involved in the pig immune response. We used 779 chips corresponding to 29 datasets for the pig global immune response and 279 chips obtained from 6 datasets for the pig response to PRRSV infection, respectively. Results The pig global immune response analysis showed interconnected canonical pathways involved in the regulation of translation and mitochondrial energy metabolism. Biological functions revealed in this meta-analysis were centred around translation regulation, which included protein synthesis, RNA-post transcriptional gene expression and cellular growth and proliferation. Furthermore, the oxidative phosphorylation and mitochondria dysfunctions, associated with stress signalling, were highly regulated. Transcription factors such as MYCN, MYC and NFE2L2 were found in this analysis to be potentially involved in the regulation of the immune response. The host specific response to PRRSV infection engendered the activation of well-defined canonical pathways in response to pathogen challenge such as TREM1, toll-like receptor and hyper-cytokinemia/ hyper-chemokinemia signalling. Furthermore, this analysis brought forth the central role of the crosstalk between innate and adaptive immune response and the regulation of anti-inflammatory response. The most significant transcription factor potentially involved in this analysis was HMGB1, which is required for the innate recognition of viral nucleic acids. Other transcription factors like interferon regulatory factors IRF1, IRF3, IRF5 and IRF8 were also involved in the pig specific response to PRRSV infection. Conclusions This work reveals key genes, canonical pathways and biological functions involved in the pig global immune response to diverse challenges, including PRRSV infection. The powerful statistical approach led us to consolidate previous findings as well as to gain new insights into the pig immune response either to common stimuli or specifically to PRRSV infection. PMID:23552196
Huang, Ruili; Wallqvist, Anders; Covell, David G
2006-03-01
We have analyzed the level of gene coregulation, using gene expression patterns measured across the National Cancer Institute's 60 tumor cell panels (NCI(60)), in the context of predefined pathways or functional categories annotated by KEGG (Kyoto Encyclopedia of Genes and Genomes), BioCarta, and GO (Gene Ontology). Statistical methods were used to evaluate the level of gene expression coherence (coordinated expression) by comparing intra- and interpathway gene-gene correlations. Our results show that gene expression in pathways, or groups of functionally related genes, has a significantly higher level of coherence than that of a randomly selected set of genes. Transcriptional-level gene regulation appears to be on a "need to be" basis, such that pathways comprising genes encoding closely interacting proteins and pathways responsible for vital cellular processes or processes that are related to growth or proliferation, specifically in cancer cells, such as those engaged in genetic information processing, cell cycle, energy metabolism, and nucleotide metabolism, tend to be more modular (lower degree of gene sharing) and to have genes significantly more coherently expressed than most signaling and regular metabolic pathways. Hierarchical clustering of pathways based on their differential gene expression in the NCI(60) further revealed interesting interpathway communications or interactions indicative of a higher level of pathway regulation. The knowledge of the nature of gene expression regulation and biological pathways can be applied to understanding the mechanism by which small drug molecules interfere with biological systems.
Cazzanelli, Giulia; Francisco, Rita; Azevedo, Luísa; Carvalho, Patrícia Dias; Almeida, Ana; Côrte-Real, Manuela; Oliveira, Maria José; Lucas, Cândida; Sousa, Maria João
2018-01-01
The exploitation of the yeast Saccharomyces cerevisiae as a biological model for the investigation of complex molecular processes conserved in multicellular organisms, such as humans, has allowed fundamental biological discoveries. When comparing yeast and human proteins, it is clear that both amino acid sequences and protein functions are often very well conserved. One example of the high degree of conservation between human and yeast proteins is highlighted by the members of the RAS family. Indeed, the study of the signaling pathways regulated by RAS in yeast cells led to the discovery of properties that were often found interchangeable with RAS proto-oncogenes in human pathways, and vice versa. In this work, we performed an updated critical literature review on human and yeast RAS pathways, specifically highlighting the similarities and differences between them. Moreover, we emphasized the contribution of studying yeast RAS pathways for the understanding of human RAS and how this model organism can contribute to unveil the roles of RAS oncoproteins in the regulation of mechanisms important in the tumorigenic process, like autophagy. PMID:29463063
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Chin-Rang
Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complementmore » Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.« less
Suthar, Mehul S.; Brassil, Margaret M.; Blahnik, Gabriele; McMillan, Aimee; Ramos, Hilario J.; Proll, Sean C.; Belisle, Sarah E.; Katze, Michael G.; Gale, Michael
2013-01-01
The actions of the RIG-I like receptor (RLR) and type I interferon (IFN) signaling pathways are essential for a protective innate immune response against the emerging flavivirus West Nile virus (WNV). In mice lacking RLR or IFN signaling pathways, WNV exhibits enhanced tissue tropism, indicating that specific host factors of innate immune defense restrict WNV infection and dissemination in peripheral tissues. However, the immune mechanisms by which the RLR and IFN pathways coordinate and function to impart restriction of WNV infection are not well defined. Using a systems biology approach, we defined the host innate immune response signature and actions that restrict WNV tissue tropism. Transcriptional profiling and pathway modeling to compare WNV-infected permissive (spleen) and nonpermissive (liver) tissues showed high enrichment for inflammatory responses, including pattern recognition receptors and IFN signaling pathways, that define restriction of WNV replication in the liver. Assessment of infected livers from Mavs−/−×Ifnar−/− mice revealed the loss of expression of several key components within the natural killer (NK) cell signaling pathway, including genes associated with NK cell activation, inflammatory cytokine production, and NK cell receptor signaling. In vivo analysis of hepatic immune cell infiltrates from WT mice demonstrated that WNV infection leads to an increase in NK cell numbers with enhanced proliferation, maturation, and effector action. In contrast, livers from Mavs−/−×Ifnar−/− infected mice displayed reduced immune cell infiltration, including a significant reduction in NK cell numbers. Analysis of cocultures of dendritic and NK cells revealed both cell-intrinsic and -extrinsic roles for the RLR and IFN signaling pathways to regulate NK cell effector activity. Taken together, these observations reveal a complex innate immune signaling network, regulated by the RLR and IFN signaling pathways, that drives tissue-specific antiviral effector gene expression and innate immune cellular processes that control tissue tropism to WNV infection. PMID:23544010
The functional cancer map: a systems-level synopsis of genetic deregulation in cancer.
Krupp, Markus; Maass, Thorsten; Marquardt, Jens U; Staib, Frank; Bauer, Tobias; König, Rainer; Biesterfeld, Stefan; Galle, Peter R; Tresch, Achim; Teufel, Andreas
2011-06-30
Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies. Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors. We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'. The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.
Constructing biological pathway models with hybrid functional Petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2004-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.
Constructing biological pathway models with hybrid functional petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2011-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.
Postdoctoral Fellow | Center for Cancer Research
The Neural Development Section (NDS) headed by Dr. Lino Tessarollo has an open postdoctoral fellow position. The candidate should have a background in neurobiology and basic expertise in molecular biology, cell biology, immunoistochemistry and biochemistry. Experience in confocal analysis is desired. The NDS study the biology of neurotrophin and Trk receptors function by using both in vitro and in vivo approaches. Our group makes extensive use of engineered mouse models and cell culture models. The current research emphasis is on understanding the molecular mechanisms by which activated trk receptor function. Specifically, we are dissecting the molecular mechanism responsible for modulating Trk receptors activity, including their interaction with specific scaffold proteins and proteins leading to de-activation of Trk signaling. Moreover, we are attempting to identify new signaling pathways activated by truncated Trk receptors.
Traditional toxicity testing provides insight into the mechanisms underlying toxicological responses but requires a high investment in large numbers of resources. The new paradigm of testing approaches involves rapid screening of thousands of chemicals across hundreds of biologic...
The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC).
Narrandes, Shavira; Huang, Shujun; Murphy, Leigh; Xu, Wayne
2018-01-04
Triple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype. Gene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model. Among 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes. We first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.
Ai, Rizi; Hammaker, Deepa; Boyle, David L.; Morgan, Rachel; Walsh, Alice M.; Fan, Shicai; Firestein, Gary S.; Wang, Wei
2016-01-01
Stratifying patients on the basis of molecular signatures could facilitate development of therapeutics that target pathways specific to a particular disease or tissue location. Previous studies suggest that pathogenesis of rheumatoid arthritis (RA) is similar in all affected joints. Here we show that distinct DNA methylation and transcriptome signatures not only discriminate RA fibroblast-like synoviocytes (FLS) from osteoarthritis FLS, but also distinguish RA FLS isolated from knees and hips. Using genome-wide methods, we show differences between RA knee and hip FLS in the methylation of genes encoding biological pathways, such as IL-6 signalling via JAK-STAT pathway. Furthermore, differentially expressed genes are identified between knee and hip FLS using RNA-sequencing. Double-evidenced genes that are both differentially methylated and expressed include multiple HOX genes. Joint-specific DNA signatures suggest that RA disease mechanisms might vary from joint to joint, thus potentially explaining some of the diversity of drug responses in RA patients. PMID:27282753
Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long
By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization. Copyright © 2016 Elsevier Inc. All rights reserved.
The biology of cancer: what do oncology nurses really need to know.
Eggert, Julie
2011-02-01
To describe the impact of genetics and genomics on the biology of cancer and the implications for patient care. Pubmed; CINAHL. Cancer research in genetics/genomics has identified new mechanisms influencing personalized risk assessment/management, early detection, cancer treatment, and long-term screening/surveillance. Understanding the basics of genetics/genomics on the biology of cancer will facilitate patient education and care delivery, including the administration and monitoring of genetically targeted therapies whose toxicities may in part be mediated by the molecular pathways targeted by the specific agent. Copyright © 2011 Elsevier Inc. All rights reserved.
Notch Signaling in Vascular Smooth Muscle Cells
Baeten, J.T.; Lilly, B.
2018-01-01
The Notch signaling pathway is a highly conserved pathway involved in cell fate determination in embryonic development and also functions in the regulation of physiological processes in several systems. It plays an especially important role in vascular development and physiology by influencing angiogenesis, vessel patterning, arterial/venous specification, and vascular smooth muscle biology. Aberrant or dysregulated Notch signaling is the cause of or a contributing factor to many vascular disorders, including inherited vascular diseases, such as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, associated with degeneration of the smooth muscle layer in cerebral arteries. Like most signaling pathways, the Notch signaling axis is influenced by complex interactions with mediators of other signaling pathways. This complexity is also compounded by different members of the Notch family having both overlapping and unique functions. Thus, it is vital to fully understand the roles and interactions of each Notch family member in order to effectively and specifically target their exact contributions to vascular disease. In this chapter, we will review the Notch signaling pathway in vascular smooth muscle cells as it relates to vascular development and human disease. PMID:28212801
Arrondeau, Jennifer; Huillard, Olivier; Tlemsani, Camille; Cessot, Anatole; Boudou-Rouquette, Pascaline; Blanchet, Benoit; Thomas-Schoemann, Audrey; Vidal, Michel; Tigaud, Jean-Marie; Durand, Jean-Philippe; Alexandre, Jerome; Goldwasser, Francois
2015-05-01
The platelet-derived growth factor receptor (PDGFR) pathway has important functions in cell growth and, by overexpression or mutation, could also be a driver for tumor development. Moreover, PDGFR is expressed in a tumoral microenvironment and could promote tumorigenesis. With these biological considerations, the PDGFR pathway could be an interesting target for therapeutics. Currently, there are many molecules under development that target the PDGFR pathway in different types of cancer. In this review, the authors report the different molecules under development, as well as those approved albeit briefly, which inhibit the PDGFR pathway. Furthermore, the authors summarize their specificities, their toxicities, and their development. Currently, most PDGFR kinase inhibitors are multikinase inhibitors and therefore do not simply target the PDGFR pathway. The development of more specific PDGFR inhibitors could improve drug efficacy. Moreover, selecting tumors harboring mutations or amplifications of PDGFR could improve outcomes associated with the use of these molecules. The authors believe that new technologies, such as kinome arrays or pharmacologic assays, could be of benefit to understanding resistance mechanisms and develop more selective PDGFR inhibitors.
Fan, Yan; He, Hong; Dong, Yan; Pan, Hengbiao
2013-12-01
Fungal virulence mechanisms include adhesion to epithelia, morphogenesis, production of secretory hydrolytic enzymes, and phenotype switching, all of which contribute to the process of pathogenesis. A striking feature of the biology of Candida albicans is its ability to grow in yeast, pseudohyphal, and hyphal forms. The hyphal form plays an important role in causing disease, by invading epithelial cells and causing tissue damage. In this review, we illustrate some of the main hyphae-specific genes, namely HGC1, UME6, ALS3, HWP1, and ECE1, and their relevant and reversed signal transduction pathways in reactions stimulated by environmental factors, including pH, CO2, and serum.
Jeyaseelan, S; Kannan, M S; Briggs, R E; Thumbikat, P; Maheswaran, S K
2001-10-01
The leukotoxin (LktA) produced by Mannheimia haemolytica binds to bovine lymphocyte function-associated antigen 1 (LFA-1) and induces biological effects in bovine leukocytes in a cellular and species-specific fashion. We have previously shown that LktA also binds to porcine LFA-1 without eliciting any effects. These findings suggest that the specificity of LktA effects must entail both binding to LFA-1 and activation of signaling pathways which are present in bovine leukocytes. However, the signaling pathways leading to biological effects upon LktA binding to LFA-1 have not been characterized. In this context, several reports have indicated that ligand binding to LFA-1 results in activation of a nonreceptor tyrosine kinase (NRTK) signaling cascade. We designed experiments with the following objectives: (i) to determine whether LktA binding to LFA-1 leads to activation of NRTKs, (ii) to examine whether LktA-induced NRTK activation is target cell specific, and (iii) to determine whether LktA-induced NRTK activation is required for biological effects. We used a biologically inactive mutant leukotoxin (DeltaLktA) for comparison with LktA. Our results indicate that LktA induces tyrosine phosphorylation (TP) of the CD18 tail of LFA-1 in bovine leukocytes. The DeltaLktA mutant does not induce TP of the CD18 tail, albeit binding to bovine LFA-1. LktA-induced TP of the CD18 tail was attenuated by an NRTK inhibitor, herbimycin A; a phosphatidylinositol 3'-kinase (PI 3-kinase) inhibitor, wortmannin; and a Src kinase inhibitor, PP2, in a concentration-dependent manner. Furthermore, LktA induces TP of the CD18 tail in bovine, but not porcine, leukocytes. Moreover, LktA-induced intracellular calcium ([Ca2+]i) elevation was also inhibited by herbimycin A, wortmannin, and PP2. Thus, our data represent the first evidence that binding of LktA to bovine LFA-1 induces a species-specific NRTK signaling cascade involving PI 3-kinase and Src kinases and that this signaling cascade is required for LktA-induced biological effects.
Jeyaseelan, S.; Kannan, M. S.; Briggs, R. E.; Thumbikat, P.; Maheswaran, S. K.
2001-01-01
The leukotoxin (LktA) produced by Mannheimia haemolytica binds to bovine lymphocyte function-associated antigen 1 (LFA-1) and induces biological effects in bovine leukocytes in a cellular and species-specific fashion. We have previously shown that LktA also binds to porcine LFA-1 without eliciting any effects. These findings suggest that the specificity of LktA effects must entail both binding to LFA-1 and activation of signaling pathways which are present in bovine leukocytes. However, the signaling pathways leading to biological effects upon LktA binding to LFA-1 have not been characterized. In this context, several reports have indicated that ligand binding to LFA-1 results in activation of a nonreceptor tyrosine kinase (NRTK) signaling cascade. We designed experiments with the following objectives: (i) to determine whether LktA binding to LFA-1 leads to activation of NRTKs, (ii) to examine whether LktA-induced NRTK activation is target cell specific, and (iii) to determine whether LktA-induced NRTK activation is required for biological effects. We used a biologically inactive mutant leukotoxin (ΔLktA) for comparison with LktA. Our results indicate that LktA induces tyrosine phosphorylation (TP) of the CD18 tail of LFA-1 in bovine leukocytes. The ΔLktA mutant does not induce TP of the CD18 tail, albeit binding to bovine LFA-1. LktA-induced TP of the CD18 tail was attenuated by an NRTK inhibitor, herbimycin A; a phosphatidylinositol 3′-kinase (PI 3-kinase) inhibitor, wortmannin; and a Src kinase inhibitor, PP2, in a concentration-dependent manner. Furthermore, LktA induces TP of the CD18 tail in bovine, but not porcine, leukocytes. Moreover, LktA-induced intracellular calcium ([Ca2+]i) elevation was also inhibited by herbimycin A, wortmannin, and PP2. Thus, our data represent the first evidence that binding of LktA to bovine LFA-1 induces a species-specific NRTK signaling cascade involving PI 3-kinase and Src kinases and that this signaling cascade is required for LktA-induced biological effects. PMID:11553552
Programmable genetic circuits for pathway engineering.
Hoynes-O'Connor, Allison; Moon, Tae Seok
2015-12-01
Synthetic biology has the potential to provide decisive advances in genetic control of metabolic pathways. However, there are several challenges that synthetic biologists must overcome before this vision becomes a reality. First, a library of diverse and well-characterized sensors, such as metabolite-sensing or condition-sensing promoters, must be constructed. Second, robust programmable circuits that link input conditions with a specific gene regulation response must be developed. Finally, multi-gene targeting strategies must be integrated with metabolically relevant sensors and complex, robust logic. Achievements in each of these areas, which employ the CRISPR/Cas system, in silico modeling, and dynamic sensor-regulators, among other tools, provide a strong basis for future research. Overall, the future for synthetic biology approaches in metabolic engineering holds immense promise. Copyright © 2015 Elsevier Ltd. All rights reserved.
Flavonoids: biosynthesis, biological functions, and biotechnological applications
Falcone Ferreyra, María L.; Rius, Sebastián P.; Casati, Paula
2012-01-01
Flavonoids are widely distributed secondary metabolites with different metabolic functions in plants. The elucidation of the biosynthetic pathways, as well as their regulation by MYB, basic helix-loop-helix (bHLH), and WD40-type transcription factors, has allowed metabolic engineering of plants through the manipulation of the different final products with valuable applications. The present review describes the regulation of flavonoid biosynthesis, as well as the biological functions of flavonoids in plants, such as in defense against UV-B radiation and pathogen infection, nodulation, and pollen fertility. In addition, we discuss different strategies and achievements through the genetic engineering of flavonoid biosynthesis with implication in the industry and the combinatorial biosynthesis in microorganisms by the reconstruction of the pathway to obtain high amounts of specific compounds. PMID:23060891
Fluid flows and forces in development: functions, features and biophysical principles
Freund, Jonathan B.; Goetz, Jacky G.; Hill, Kent L.; Vermot, Julien
2012-01-01
Throughout morphogenesis, cells experience intracellular tensile and contractile forces on microscopic scales. Cells also experience extracellular forces, such as static forces mediated by the extracellular matrix and forces resulting from microscopic fluid flow. Although the biological ramifications of static forces have received much attention, little is known about the roles of fluid flows and forces during embryogenesis. Here, we focus on the microfluidic forces generated by cilia-driven fluid flow and heart-driven hemodynamics, as well as on the signaling pathways involved in flow sensing. We discuss recent studies that describe the functions and the biomechanical features of these fluid flows. These insights suggest that biological flow determines many aspects of cell behavior and identity through a specific set of physical stimuli and signaling pathways. PMID:22395739
Apps, John Richard; Martinez-Barbera, Juan Pedro
2017-05-01
Adamantinomatous craniopharyngioma (ACP) is the commonest tumor of the sellar region in childhood. Two genetically engineered mouse models have been developed and are giving valuable insights into ACP biology. These models have identified novel pathways activated in tumors, revealed an important function of paracrine signalling and extended conventional theories about the role of organ-specific stem cells in tumorigenesis. In this review, we summarize these mouse models, what has been learnt, their limitations and open questions for future research. We then discussed how these mouse models may be used to test novel therapeutics against potentially targetable pathways recently identified in human ACP. © 2017 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology.
Global expression analysis of gene regulatory pathways during endocrine pancreatic development.
Gu, Guoqiang; Wells, James M; Dombkowski, David; Preffer, Fred; Aronow, Bruce; Melton, Douglas A
2004-01-01
To define genetic pathways that regulate development of the endocrine pancreas, we generated transcriptional profiles of enriched cells isolated from four biologically significant stages of endocrine pancreas development: endoderm before pancreas specification, early pancreatic progenitor cells, endocrine progenitor cells and adult islets of Langerhans. These analyses implicate new signaling pathways in endocrine pancreas development, and identified sets of known and novel genes that are temporally regulated, as well as genes that spatially define developing endocrine cells from their neighbors. The differential expression of several genes from each time point was verified by RT-PCR and in situ hybridization. Moreover, we present preliminary functional evidence suggesting that one transcription factor encoding gene (Myt1), which was identified in our screen, is expressed in endocrine progenitors and may regulate alpha, beta and delta cell development. In addition to identifying new genes that regulate endocrine cell fate, this global gene expression analysis has uncovered informative biological trends that occur during endocrine differentiation.
5-Lipoxygenase Pathway, Dendritic Cells, and Adaptive Immunity
Hedi, Harizi
2004-01-01
5-lipoxygenase (5-LO) pathway is the major source of potent proinflammatory leukotrienes (LTs) issued from the metabolism of arachidonic acid (AA), and best known for their roles in the pathogenesis of asthma. These lipid mediators are mainly released from myeloid cells and may act as physiological autocrine and paracrine signalling molecules, and play a central role in regulating the interaction between innate and adaptive immunity. The biological actions of LTs including their immunoregulatory and proinflammatory effects are mediated through extracellular specific G-protein-coupled receptors. Despite their role in inflammatory cells, such as neutrophils and macrophages, LTs may have important effects on dendritic cells (DC)-mediated adaptive immunity. Several lines of evidence show that DC not only are important source of LTs, but also become targets of their actions by producing other lipid mediators and proinflammatory molecules. This review focuses on advances in 5-LO pathway biology, the production of LTs from DC and their role on various cells of immune system and in adaptive immunity. PMID:15240920
USDA-ARS?s Scientific Manuscript database
Understanding plant resistance mechanisms at a molecular level would provide valuable insights into the biological pathways impacted by insect feeding, and help explain specific plant tolerance mechanisms. As a first step in this process, we conducted next generation sequencing using RNA extracted f...
Posttraumatic Stress Disorder in Maltreated Youth: A Review of Contemporary Research and Thought
ERIC Educational Resources Information Center
Kearney, Christopher A.; Wechsler, Adrianna; Kaur, Harpreet; Lemos-Miller, Amie
2010-01-01
Youths who have been maltreated often experience symptoms of posttraumatic stress disorder (PTSD), and this special population has received increased attention from researchers. Pathways toward maladaptive effects of maltreatment and PTSD are remarkably similar and reflect specific biological diatheses and psychological vulnerabilities that…
Control of seizures by ketogenic diet-induced modulation of metabolic pathways.
Clanton, Ryan M; Wu, Guoyao; Akabani, Gamal; Aramayo, Rodolfo
2017-01-01
Epilepsy is too complex to be considered as a disease; it is more of a syndrome, characterized by seizures, which can be caused by a diverse array of afflictions. As such, drug interventions that target a single biological pathway will only help the specific individuals where that drug's mechanism of action is relevant to their disorder. Most likely, this will not alleviate all forms of epilepsy nor the potential biological pathways causing the seizures, such as glucose/amino acid transport, mitochondrial dysfunction, or neuronal myelination. Considering our current inability to test every individual effectively for the true causes of their epilepsy and the alarming number of misdiagnoses observed, we propose the use of the ketogenic diet (KD) as an effective and efficient preliminary/long-term treatment. The KD mimics fasting by altering substrate metabolism from carbohydrates to fatty acids and ketone bodies (KBs). Here, we underscore the need to understand the underlying cellular mechanisms governing the KD's modulation of various forms of epilepsy and how a diverse array of metabolites including soluble fibers, specific fatty acids, and functional amino acids (e.g., leucine, D-serine, glycine, arginine metabolites, and N-acetyl-cysteine) may potentially enhance the KD's ability to treat and reverse, not mask, these neurological disorders that lead to epilepsy.
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
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.
Haralambieva, Iana H; Kennedy, Richard B; Simon, Whitney L; Goergen, Krista M; Grill, Diane E; Ovsyannikova, Inna G; Poland, Gregory A
2018-01-01
MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination. We performed Next Generation Sequencing (mRNA-Seq) of intracellular miRNAs in measles virus-stimulated B and CD4+ T cells from high and low antibody responders to measles vaccine. Negative binomial generalized estimating equation (GEE) models were used for miRNA assessment and the DIANA tool was used for gene/target prediction and pathway enrichment analysis. We identified a set of B cell-specific miRNAs (e.g., miR-151a-5p, miR-223, miR-29, miR-15a-5p, miR-199a-3p, miR-103a, and miR-15a/16 cluster) and biological processes/pathways, including regulation of adherens junction proteins, Fc-receptor signaling pathway, phosphatidylinositol-mediated signaling pathway, growth factor signaling pathway/pathways, transcriptional regulation, apoptosis and virus-related processes, significantly associated with neutralizing antibody titers after measles vaccination. No CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found. Our study demonstrates that miRNA expression directly or indirectly influences humoral immunity to measles vaccination and suggests that B cell-specific miRNAs may serve as useful predictive biomarkers of vaccine humoral immune response.
Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data
Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie
2016-01-01
Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine. PMID:27774993
A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest
Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.
2015-01-01
As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726
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.
Environmental surveillance and monitoring. The next frontiers ...
High throughput toxicity testing (HTT) technologies along with the world-wide web are revolutionizing both generation and access to data regarding the bioactivities that chemicals can elicit when they interact with specific proteins, genes, or other targets in the body of an organism. However, to date, most of the focus has been on the application of such data to assessment of individual chemicals. We suggest that environmental surveillance and monitoring represent the next frontiers for HTT. Resources already exist in curated databases of chemical-biological interactions, including highly standardized quantitative dose-response data generated from nascent HTT programs like ToxCast and Tox21, to link chemicals detected through environmental analytical chemistry to known biological activities. The emergence of the adverse outcome pathway framework and associated knowledgebase for linking molecular or pathway-level perturbations of biological systems to adverse outcomes traditionally considered in risk assessment and regulatory decision-making through a series of measureable biological changes provides a critical link between activity and hazard. Furthermore, environmental samples can be directly analyzed via HTT platforms to provide an unprecedented breadth of biological activity characterization that integrates the effects of all compounds present in a mixture, whether known or not. Novel application of these chemical-biological interaction data provide an oppor
Schmitz, Judith; Lor, Stephanie; Klose, Rena; Güntürkün, Onur; Ocklenburg, Sebastian
2017-01-01
Handedness and language lateralization are partially determined by genetic influences. It has been estimated that at least 40 (and potentially more) possibly interacting genes may influence the ontogenesis of hemispheric asymmetries. Recently, it has been suggested that analyzing the genetics of hemispheric asymmetries on the level of gene ontology sets, rather than at the level of individual genes, might be more informative for understanding the underlying functional cascades. Here, we performed gene ontology, pathway and disease association analyses on genes that have previously been associated with handedness and language lateralization. Significant gene ontology sets for handedness were anatomical structure development, pattern specification (especially asymmetry formation) and biological regulation. Pathway analysis highlighted the importance of the TGF-beta signaling pathway for handedness ontogenesis. Significant gene ontology sets for language lateralization were responses to different stimuli, nervous system development, transport, signaling, and biological regulation. Despite the fact that some authors assume that handedness and language lateralization share a common ontogenetic basis, gene ontology sets barely overlap between phenotypes. Compared to genes involved in handedness, which mostly contribute to structural development, genes involved in language lateralization rather contribute to activity-dependent cognitive processes. Disease association analysis revealed associations of genes involved in handedness with diseases affecting the whole body, while genes involved in language lateralization were specifically engaged in mental and neurological diseases. These findings further support the idea that handedness and language lateralization are ontogenetically independent, complex phenotypes.
Schmitz, Judith; Lor, Stephanie; Klose, Rena; Güntürkün, Onur; Ocklenburg, Sebastian
2017-01-01
Handedness and language lateralization are partially determined by genetic influences. It has been estimated that at least 40 (and potentially more) possibly interacting genes may influence the ontogenesis of hemispheric asymmetries. Recently, it has been suggested that analyzing the genetics of hemispheric asymmetries on the level of gene ontology sets, rather than at the level of individual genes, might be more informative for understanding the underlying functional cascades. Here, we performed gene ontology, pathway and disease association analyses on genes that have previously been associated with handedness and language lateralization. Significant gene ontology sets for handedness were anatomical structure development, pattern specification (especially asymmetry formation) and biological regulation. Pathway analysis highlighted the importance of the TGF-beta signaling pathway for handedness ontogenesis. Significant gene ontology sets for language lateralization were responses to different stimuli, nervous system development, transport, signaling, and biological regulation. Despite the fact that some authors assume that handedness and language lateralization share a common ontogenetic basis, gene ontology sets barely overlap between phenotypes. Compared to genes involved in handedness, which mostly contribute to structural development, genes involved in language lateralization rather contribute to activity-dependent cognitive processes. Disease association analysis revealed associations of genes involved in handedness with diseases affecting the whole body, while genes involved in language lateralization were specifically engaged in mental and neurological diseases. These findings further support the idea that handedness and language lateralization are ontogenetically independent, complex phenotypes. PMID:28729848
BioPAX – A community standard for pathway data sharing
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
Transcriptomic characterization of temperature stress responses in larval zebrafish.
Long, Yong; Li, Linchun; Li, Qing; He, Xiaozhen; Cui, Zongbin
2012-01-01
Temperature influences nearly all biochemical, physiological and life history activities of fish, but the molecular mechanisms underlying the temperature acclimation remains largely unknown. Previous studies have identified many temperature-regulated genes in adult tissues; however, the transcriptional responses of fish larvae to temperature stress are not well understood. In this study, we characterized the transcriptional responses in larval zebrafish exposed to cold or heat stress using microarray analysis. In comparison with genes expressed in the control at 28 °C, a total of 2680 genes were found to be affected in 96 hpf larvae exposed to cold (16 °C) or heat (34 °C) for 2 and 48h and most of these genes were expressed in a temperature-specific and temporally regulated manner. Bioinformatic analysis identified multiple temperature-regulated biological processes and pathways. Biological processes overrepresented among the earliest genes induced by temperature stress include regulation of transcription, nucleosome assembly, chromatin organization and protein folding. However, processes such as RNA processing, cellular metal ion homeostasis and protein transport and were enriched in genes up-regulated under cold exposure for 48 h. Pathways such as mTOR signalling, p53 signalling and circadian rhythm were enriched among cold-induced genes, while adipocytokine signalling, protein export and arginine and praline metabolism were enriched among heat-induced genes. Although most of these biological processes and pathways were specifically regulated by cold or heat, common responses to both cold and heat stresses were also found. Thus, these findings provide new interesting clues for elucidation of mechanisms underlying the temperature acclimation in fish.
Expansion of Protein Farnesyltransferase Specificity Using “Tunable” Active Site Interactions
Hougland, James L.; Gangopadhyay, Soumyashree A.; Fierke, Carol A.
2012-01-01
Post-translational modifications play essential roles in regulating protein structure and function. Protein farnesyltransferase (FTase) catalyzes the biologically relevant lipidation of up to several hundred cellular proteins. Site-directed mutagenesis of FTase coupled with peptide selectivity measurements demonstrates that molecular recognition is determined by a combination of multiple interactions. Targeted randomization of these interactions yields FTase variants with altered and, in some cases, bio-orthogonal selectivity. We demonstrate that FTase specificity can be “tuned” using a small number of active site contacts that play essential roles in discriminating against non-substrates in the wild-type enzyme. This tunable selectivity extends in vivo, with FTase variants enabling the creation of bioengineered parallel prenylation pathways with altered substrate selectivity within a cell. Engineered FTase variants provide a novel avenue for probing both the selectivity of prenylation pathway enzymes and the effects of prenylation pathway modifications on the cellular function of a protein. PMID:22992747
Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer
Börnigen, Daniela; Tyekucheva, Svitlana; Wang, Xiaodong; Rider, Jennifer R.; Lee, Gwo-Shu; Mucci, Lorelei A.; Sweeney, Christopher; Huttenhower, Curtis
2016-01-01
Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer-related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFκB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members’ biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFκB pathway members. A newly predicted interaction between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9's potential biological role in prostate cancer cell growth regulation. We combined 651 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFκB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFκB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies. PMID:27078000
From bedside to cell biology: a century of history on lysosomal dysfunction.
Coutinho, Maria Francisca; Matos, Liliana; Alves, Sandra
2015-01-15
Lysosomal storage disorders (LSDs) are a group of rare genetic diseases, generally caused by a deficiency of specific lysosomal enzymes, which results in abnormal accumulation of undegraded substrates. The first clinical reports describing what were later shown to be LSDs were published more than a hundred years ago. In general, the history and pathophysiology of LSDs has impacted on our current knowledge of lysosomal biology. Classically, depending on the nature of the substrates, LSDs can be divided into different subgroups. The mucopolysaccharidoses (MPSs) are those caused by impaired degradation of glycosaminoglycans (GAGs). Amongst LSDs, the MPSs are a major group of pathologies with crucial historical relevance, since their study has revealed important biological pathways and highlighted interconnecting pathological cascades which are still being unveiled nowadays. Here we review the major historical discoveries in the field of LSDs and their impact on basic cellular knowledge and practical applications. Attention will be focused on the MPSs, with occasional references to other LSDs. We will show as studies on the metabolic basis of this group of diseases have increased our knowledge of the complex degradative pathways associated with the lysosome and established the basis to the development of specific therapeutic approaches aiming at correcting or, at least ameliorating their associated phenotypes. Copyright © 2014 Elsevier B.V. All rights reserved.
Implant Surface Design Regulates Mesenchymal Stem Cell Differentiation and Maturation
Boyan, B.D.; Cheng, A.; Olivares-Navarrete, R.; Schwartz, Z.
2016-01-01
Changes in dental implant materials, structural design, and surface properties can all affect biological response. While bulk properties are important for mechanical stability of the implant, surface design ultimately contributes to osseointegration. This article reviews the surface parameters of dental implant materials that contribute to improved cell response and osseointegration. In particular, we focus on how surface design affects mesenchymal cell response and differentiation into the osteoblast lineage. Surface roughness has been largely studied at the microscale, but recent studies have highlighted the importance of hierarchical micron/submicron/nanosurface roughness, as well as surface roughness in combination with surface wettability. Integrins are transmembrane receptors that recognize changes in the surface and mediate downstream signaling pathways. Specifically, the noncanonical Wnt5a pathway has been implicated in osteoblastic differentiation of cells on titanium implant surfaces. However, much remains to be elucidated. Only recently have studies been conducted on the differences in biological response to implants based on sex, age, and clinical factors; these all point toward differences that advocate for patient-specific implant design. Finally, challenges in implant surface characterization must be addressed to optimize and compare data across studies. An understanding of both the science and the biology of the materials is crucial for developing novel dental implant materials and surface modifications for improved osseointegration. PMID:26927483
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.
The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less
Raad, Mohamad; El Tal, Tala; Gul, Rukhsana; Mondello, Stefania; Zhang, Zhiqun; Boustany, Rose-Mary; Guingab, Joy; Wang, Kevin K; Kobeissy, Firas
2012-12-01
Several common degenerative mechanisms and mediators underlying the neuronal injury pathways characterize several neurodegenerative diseases including Alzheimer's, Parkinson's, and Huntington's disease, as well as brain neurotrauma. Such common ground invites the emergence of new approaches and tools to study the altered pathways involved in neural injury alongside with neuritogenesis, an intricate process that commences with neuronal differentiation. Achieving a greater understanding of the impaired pathways of neuritogenesis would significantly help in uncovering detailed mechanisms of axonal regeneration. Among the several agents involved in neuritogenesis are the Rho and Rho kinases (ROCKs), which constitute key integral points in the Rho/ROCK pathway that is known to be disrupted in multiple neuropathologies such as spinal cord injury, traumatic brain injury, and Alzheimer's disease. This in turn renders ROCK inhibition as a promising candidate for therapeutic targets for treatment of neurodegenerative diseases. Among the novel tools to investigate the mechanisms involved in a specific disorder is the use of neuroproteomics/systems biology approach, a growing subfield of bioinformatics aiming to study and establishing a global assessment of the entire neuronal proteome, addressing the dynamic protein changes and interactions. This review aims to examine recent updates regarding how neuroproteomics aids in the understanding of molecular mechanisms of activation and inhibition in the area of neurogenesis and how Rho/ROCK pathway/ROCK inhibitors, primarily Y-27632 and Fasudil compounds, are applied in biological settings, promoting neuronal survival and neuroprotection that has direct future implications in neurotrauma. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Abril, M A; Michan, C; Timmis, K N; Ramos, J L
1989-01-01
The TOL plasmid upper pathway operon encodes enzymes involved in the catabolism of aromatic hydrocarbons such as toluene and xylenes. The regulator of the gene pathway, the XylR protein, exhibits a very broad effector specificity, being able to recognize as effectors not only pathway substrates but also a wide variety of mono- and disubstituted methyl-, ethyl-, and chlorotoluenes, benzyl alcohols, and p-chlorobenzaldehyde. Benzyl alcohol dehydrogenase and benzaldehyde dehydrogenase, two upper pathway enzymes, exhibit very broad substrate specificities and transform unsubstituted substrates and m- and p-methyl-, m- and p-ethyl-, and m- and p-chloro-substituted benzyl alcohols and benzaldehydes, respectively, at a high rate. In contrast, toluene oxidase only oxidizes toluene, m- and p-xylene, m-ethyltoluene, and 1,2,4-trimethylbenzene [corrected], also at a high rate. A biological test showed that toluene oxidase attacks m- and p-chlorotoluene, albeit at a low rate. No evidence for the transformation of p-ethyltoluene by toluene oxidase has been found. Hence, toluene oxidase acts as the bottleneck step for the catabolism of p-ethyl- and m- and p-chlorotoluene through the TOL upper pathway. A mutant toluene oxidase able to transform p-ethyltoluene was isolated, and a mutant strain capable of fully degrading p-ethyltoluene was constructed with a modified TOL plasmid meta-cleavage pathway able to mineralize p-ethylbenzoate. By transfer of a TOL plasmid into Pseudomonas sp. strain B13, a clone able to slowly degrade m-chlorotoluene was also obtained. PMID:2687253
2011-01-01
Background Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged in vivo with S. aureus, E. coli, and S. uberis, samples from goats challenged in vivo with S. aureus, as well as cattle macrophages and ovine dendritic cells infected in vitro with S. aureus. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific. Results Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including XBP1 and SREBF1. The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of E. coli and S. aureus infections in cattle in vivo revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that E. coli caused a stronger host response. Conclusions This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources. PMID:21569310
Radiation Quality Effects on Transcriptome Profiles in 3-d Cultures After Particle Irradiation
NASA Technical Reports Server (NTRS)
Patel, Z. S.; Kidane, Y. H.; Huff, J. L.
2014-01-01
In this work, we evaluate the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Reducing uncertainties in current risk models requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. We are utilizing novel 3-D organotypic human tissue models that provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information. We identified 45 statistically significant gene sets at 0.05 q-value cutoff, including 14 gene sets common to gamma and titanium irradiation, 19 gene sets specific to gamma irradiation, and 12 titanium-specific gene sets. Common gene sets largely align with DNA damage, cell cycle, early immune response, and inflammatory cytokine pathway activation. The top gene set enriched for the gamma- and titanium-irradiated samples involved KRAS pathway activation and genes activated in TNF-treated cells, respectively. Another difference noted for the high-LET samples was an apparent enrichment in gene sets involved in cycle cycle/mitotic control. It is plausible that the enrichment in these particular pathways results from the complex DNA damage resulting from high-LET exposure where repair processes are not completed during the same time scale as the less complex damage resulting from low-LET radiation.
Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru
2010-01-01
Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.
Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru
2011-01-01
Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.
Service-based analysis of biological pathways
Zheng, George; Bouguettaya, Athman
2009-01-01
Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403
An Adverse Outcome Pathway (AOP) represents the organization of current and newly acquired knowledge of biological pathways. These pathways contain a series of nodes (Key Events, KEs) that when sufficiently altered influence the next node on the pathway, beginning from an Molecul...
Quantitative Biology of Exercise-Induced Signal Transduction Pathways.
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.
Modeling biochemical pathways in the gene ontology
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
Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees
2018-06-07
The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.
2012-01-01
Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440
Modeling Drug- and Chemical-Induced Hepatotoxicity with Systems Biology Approaches
Bhattacharya, Sudin; Shoda, Lisl K.M.; Zhang, Qiang; Woods, Courtney G.; Howell, Brett A.; Siler, Scott Q.; Woodhead, Jeffrey L.; Yang, Yuching; McMullen, Patrick; Watkins, Paul B.; Andersen, Melvin E.
2012-01-01
We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales. PMID:23248599
Identification of mutated driver pathways in cancer using a multi-objective optimization model.
Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng
2016-05-01
New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.
Safety and feasibility of targeted agent combinations in solid tumours.
Park, Sook Ryun; Davis, Myrtle; Doroshow, James H; Kummar, Shivaani
2013-03-01
The plethora of novel molecular-targeted agents (MTAs) has provided an opportunity to selectively target pathways involved in carcinogenesis and tumour progression. Combination strategies of MTAs are being used to inhibit multiple aberrant pathways in the hope of optimizing antitumour efficacy and to prevent development of resistance. While the selection of specific agents in a given combination has been based on biological considerations (including the role of the putative targets in cancer) and the interactions of the agents used in combination, there has been little exploration of the possible enhanced toxicity of combinations resulting from alterations in multiple signalling pathways in normal cell biology. Owing to the complex networks and crosstalk that govern normal and tumour cell proliferation, inhibiting multiple pathways with MTA combinations can result in unpredictable disturbances in normal physiology. This Review focuses on the main toxicities and the lack of tolerability of some common MTA combinations, particularly where evidence of enhanced toxicity compared to either agent alone is documented or there is development of unexpected toxicity. Toxicities caused by MTA combinations highlight the need to introduce new preclinical testing paradigms early in the drug development process for the assessment of chronic toxicities resulting from such combinations.
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.
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 new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.
Passing messages between biological networks to refine predicted interactions.
Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng
2013-01-01
Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.
The N-end rule pathway and regulation by proteolysis
Varshavsky, Alexander
2011-01-01
The N-end rule relates the regulation of the in vivo half-life of a protein to the identity of its N-terminal residue. Degradation signals (degrons) that are targeted by the N-end rule pathway include a set called N-degrons. The main determinant of an N-degron is a destabilizing N-terminal residue of a protein. In eukaryotes, the N-end rule pathway is a part of the ubiquitin system and consists of two branches, the Ac/N-end rule and the Arg/N-end rule pathways. The Ac/N-end rule pathway targets proteins containing Nα-terminally acetylated (Nt-acetylated) residues. The Arg/N-end rule pathway recognizes unacetylated N-terminal residues and involves N-terminal arginylation. Together, these branches target for degradation a majority of cellular proteins. For example, more than 80% of human proteins are cotranslationally Nt-acetylated. Thus, most proteins harbor a specific degradation signal, termed AcN-degron, from the moment of their birth. Specific N-end rule pathways are also present in prokaryotes and in mitochondria. Enzymes that produce N-degrons include methionine-aminopeptidases, caspases, calpains, Nt-acetylases, Nt-amidases, arginyl-transferases, and leucyl-transferases. Regulated degradation of specific proteins by the N-end rule pathway mediates a legion of physiological functions, including the sensing of heme, oxygen, and nitric oxide; selective elimination of misfolded proteins; the regulation of DNA repair, segregation, and condensation; the signaling by G proteins; the regulation of peptide import, fat metabolism, viral and bacterial infections, apoptosis, meiosis, spermatogenesis, neurogenesis, and cardiovascular development; and the functioning of adult organs, including the pancreas and the brain. Discovered 25 years ago, this pathway continues to be a fount of biological insights. PMID:21633985
The Environmental Protection Agency has implemented a high throughput screening program, ToxCast, to quickly evaluate large numbers of chemicals for their effects on hundreds of different biological targets. To understand how these measurements relate to adverse effects in an or...
Arachidonic-acid-derived eicosanoids: roles in biology and immunopathology.
Harizi, Hedi; Corcuff, Jean-Benoît; Gualde, Norbert
2008-10-01
Arachidonic acid (AA)-derived eicosanoids belong to a complex family of lipid mediators that regulate a wide variety of physiological responses and pathological processes. They are produced by various cell types through distinct enzymatic pathways and act on target cells via specific G-protein-coupled receptors. Although originally recognized for their capacity to elicit biological responses such as vascular homeostasis, protection of the gastric mucosa and platelet aggregation, eicosanoids are now understood to regulate immunopathological processes ranging from inflammatory responses to chronic tissue remodelling, cancer, asthma, rheumatoid arthritis and autoimmune disorders. Here, we review the major properties of eicosanoids and their expanding roles in biology and medicine.
The binding, transport and fate of aluminium in biological cells.
Exley, Christopher; Mold, Matthew J
2015-04-01
Aluminium is the most abundant metal in the Earth's crust and yet, paradoxically, it has no known biological function. Aluminium is biochemically reactive, it is simply that it is not required for any essential process in extant biota. There is evidence neither of element-specific nor evolutionarily conserved aluminium biochemistry. This means that there are no ligands or chaperones which are specific to its transport, there are no transporters or channels to selectively facilitate its passage across membranes, there are no intracellular storage proteins to aid its cellular homeostasis and there are no pathways which evolved to enable the metabolism and excretion of aluminium. Of course, aluminium is found in every compartment of every cell of every organism, from virus through to Man. Herein we have investigated each of the 'silent' pathways and metabolic events which together constitute a form of aluminium homeostasis in biota, identifying and evaluating as far as is possible what is known and, equally importantly, what is unknown about its uptake, transport, storage and excretion. Copyright © 2014 Elsevier GmbH. All rights reserved.
Integrated Network Analyses for Functional Genomic Studies in Cancer
Wilson, Jennifer L.; Hemann, Michael T.; Fraenkel, Ernest; Lauffenburger, Douglas A.
2013-01-01
RNA-interference (RNAi) studies hold great promise for functional investigation of the significance of genetic variations and mutations, as well as potential synthetic lethalities, for understanding and treatment of cancer, yet technical and conceptual issues currently diminish the potential power of this approach. While numerous research groups are usefully employing this kind of functional genomic methodology to identify molecular mediators of disease severity, response, and resistance to treatment, findings are generally confounded by “off-target” effects. These effects arise from a variety of issues beyond non-specific reagent behavior, such as biological cross-talk and feedback processes so thus can occur even with specific perturbation. Interpreting RNAi results in a network framework instead of merely as individual “hits” or “targets” leverages contributions from all hit/target contributions to pathways via their relationships with other network nodes. This interpretation can ameliorate dependence on individual reagent performance and increase confidence in biological validation. Here we provide background on RNAi studies in cancer applications, review key challenges with functional genomics, and motivate the use of network models grounded in pathway analyses. PMID:23811269
NASA Astrophysics Data System (ADS)
Zhang, Jinmai; Luo, Huajie; Liu, Hao; Ye, Wei; Luo, Ray; Chen, Hai-Feng
2016-04-01
Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.
Targeting protein neddylation: a novel therapeutic strategy for the treatment of cancer.
Wang, Meng; Medeiros, Bruno C; Erba, Harry P; DeAngelo, Daniel J; Giles, Francis J; Swords, Ronan T
2011-03-01
The NEDD8 (neural precursor cell-expressed developmentally downregulated 8) conjugation pathway regulates the post-translational modification of oncogenic proteins. This pathway has important potential for cancer therapeutics. Several proteins vital in cancer biology are regulated by protein neddylation. These observations led to the development of a small molecule inhibitor that disrupts protein neddylation and leads to cancer cell death and important activity in early phase clinical trials. This review provides an extensive coverage of cellular protein homeostasis with particular emphasis on the NEDD8 conjugation pathway. Insights into a new investigational drug that specifically disrupts the NEDD8 pathway are discussed. The clinical data for this agent are also updated. Neddylation controls key cellular pathways found to be dysregulated in many cancers. Protein neddylation is a relatively under-explored pathway for pharmacologic inhibition in cancer. Selective disruption of this pathway has demonstrated clinical activity in patients with myeloid neoplasms and is worth exploring further in combination with other anti-leukemia agents.
Advances in targeting cyclic nucleotide phosphodiesterases
Maurice, Donald H.; Ke, Hengming; Ahmad, Faiyaz; Wang, Yousheng; Chung, Jay; Manganiello, Vincent C.
2014-01-01
Cyclic nucleotide phosphodiesterases (PDEs) catalyse the hydrolysis of cyclic AMP and cyclic GMP, thereby regulating the intracellular concentrations of these cyclic nucleotides, their signalling pathways and, consequently, myriad biological responses in health and disease. Currently, a small number of PDE inhibitors are used clinically for treating the pathophysiological dysregulation of cyclic nucleotide signalling in several disorders, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication and chronic obstructive pulmonary disease. However, pharmaceutical interest in PDEs has been reignited by the increasing understanding of the roles of individual PDEs in regulating the subcellular compartmentalization of specific cyclic nucleotide signalling pathways, by the structure-based design of novel specific inhibitors and by the development of more sophisticated strategies to target individual PDE variants. PMID:24687066
Reverse engineering the mechanical and molecular pathways in stem cell morphogenesis.
Lu, Kai; Gordon, Richard; Cao, Tong
2015-03-01
The formation of relevant biological structures poses a challenge for regenerative medicine. During embryogenesis, embryonic cells differentiate into somatic tissues and undergo morphogenesis to produce three-dimensional organs. Using stem cells, we can recapitulate this process and create biological constructs for therapeutic transplantation. However, imperfect imitation of nature sometimes results in in vitro artifacts that fail to recapitulate the function of native organs. It has been hypothesized that developing cells may self-organize into tissue-specific structures given a correct in vitro environment. This proposition is supported by the generation of neo-organoids from stem cells. We suggest that morphogenesis may be reverse engineered to uncover its interacting mechanical pathway and molecular circuitry. By harnessing the latent architecture of stem cells, novel tissue-engineering strategies may be conceptualized for generating self-organizing transplants. Copyright © 2013 John Wiley & Sons, Ltd.
Souza, Terezinha M; Kleinjans, Jos C S; Jennen, Danyel G J
2017-01-01
Perturbation of biological networks is often observed during exposure to xenobiotics, and the identification of disturbed processes, their dynamic traits, and dose-response relationships are some of the current challenges for elucidating the mechanisms determining adverse outcomes. In this scenario, reverse engineering of gene regulatory networks (GRNs) from expression data may provide a system-level snapshot embedded within accurate molecular events. Here, we investigate the composition of GRNs inferred from groups of chemicals with two distinct outcomes, namely carcinogenicity [azathioprine (AZA) and cyclophosphamide (CYC)] and drug-induced liver injury (DILI; diclofenac, nitrofurantoin, and propylthiouracil), and a non-carcinogenic/non-DILI group (aspirin, diazepam, and omeprazole). For this, we analyzed publicly available exposed in vitro human data, taking into account dose and time dependencies. Dose-Time Network Identification (DTNI) was applied to gene sets from exposed primary human hepatocytes using four stress pathways, namely endoplasmic reticulum (ER), NF-κB, NRF2, and TP53. Inferred GRNs suggested case specificity, varying in interactions, starting nodes, and target genes across groups. DILI and carcinogenic compounds were shown to directly affect all pathway-based GRNs, while non-DILI/non-carcinogenic chemicals only affected NF-κB. NF-κB-based GRNs clearly illustrated group-specific disturbances, with the cancer-related casein kinase CSNK2A1 being a target gene only in the carcinogenic group, and opposite regulation of NF-κB subunits being observed in DILI and non-DILI/non-carcinogenic groups. Target genes in NRF2-based GRNs shared by DILI and carcinogenic compounds suggested markers of hepatotoxicity. Finally, we indicate several of these group-specific interactions as potentially novel. In summary, our reversed-engineered GRNs are capable of revealing dose dependent, chemical-specific mechanisms of action in stress-related biological networks.
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.
Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D
2007-01-01
Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344
Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia
2015-01-01
Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.
Thellung, Stefano; Favoni, Roberto E; Würth, Roberto; Nizzari, Mario; Pattarozzi, Alessandra; Daga, Antonio; Florio, Tullio; Barbieri, Federica
2016-01-01
Malignant pleural mesothelioma (MPM) is one of the deadliest and most heterogeneous tumors, highly refractory to multimodal therapeutic approach, including surgery, chemo- and radiotherapy. Preclinical and clinical studies exploring the efficacy of drugs targeting tyrosine kinases, angiogenesis and histone deacetylases, did not fulfil the expected clinical benefits. Thus, novel molecular targets should be identified from a definite knowledge of the unique biology and most relevant transduction pathways of MPM cells. Cancer stem cells (CSCs) are a subset of malignant precursors responsible for initiation, progression, resistance to cytotoxic drugs, recurrence and metastatic diffusion of tumor cells. CSCs are putative driving factors for MPM development and contribute to its clinical and biological heterogeneity; hence, targeted eradication of CSCs represents an ineludible goal to counteract MPM aggressiveness. In this context, innovative preclinical models could be exploited to identify novel intracellular pathway inhibitors able to target CSC viability. Novel drug targets have been identified among key factors responsible for the oncogenic transformation of mesothelial cells, often directly induced by asbestos. These include mitogenic and anti-apoptotic signaling that may also be activated by autocrine and paracrine cytokine pathways controlling cell plasticity. Both signaling pathways affecting proto-oncogene and transcription factor expression, or genetic and epigenetic alterations, such as mutations in cell cycle genes and silencing of tumor suppressor genes, represent promising disease-specific targets. In this review we describe current knowledge of MPM cell biology, focusing on potential targets to be tested in pharmacological studies, and highlighting results and challenges of clinical translation.
New challenges for text mining: mapping between text and manually curated pathways
Oda, Kanae; Kim, Jin-Dong; Ohta, Tomoko; Okanohara, Daisuke; Matsuzaki, Takuya; Tateisi, Yuka; Tsujii, Jun'ichi
2008-01-01
Background Associating literature with pathways poses new challenges to the Text Mining (TM) community. There are three main challenges to this task: (1) the identification of the mapping position of a specific entity or reaction in a given pathway, (2) the recognition of the causal relationships among multiple reactions, and (3) the formulation and implementation of required inferences based on biological domain knowledge. Results To address these challenges, we constructed new resources to link the text with a model pathway; they are: the GENIA pathway corpus with event annotation and NF-kB pathway. Through their detailed analysis, we address the untapped resource, ‘bio-inference,’ as well as the differences between text and pathway representation. Here, we show the precise comparisons of their representations and the nine classes of ‘bio-inference’ schemes observed in the pathway corpus. Conclusions We believe that the creation of such rich resources and their detailed analysis is the significant first step for accelerating the research of the automatic construction of pathway from text. PMID:18426550
Eschweiler, Joseph D.; Martini, Rachel M.; Ruotolo, Brandon T.
2017-01-01
Despite the growing application of gas-phase measurements in structural biology and drug discovery, the factors that govern protein stabilities and structures in a solvent-free environment are still poorly understood. Here, we examine the solvent-free unfolding pathway for a group of homologous serum albumins. Utilizing a combination of chemical probes and non-covalent reconstructions, we draw new specific conclusions regarding the unfolding of albumins in the gas-phase, as well as more-general inferences regarding the sensitivity of collision induced unfolding to changes in protein primary and tertiary structure. Our findings suggest that the general unfolding pathway of low charge state albumin ions is largely unaffected by changes in primary structure; however, the stabilities of intermediates along these pathways vary widely as sequences diverge. Additionally, we find that human albumin follows a domain associated unfolding pathway, and are able to assign each unfolded form observed in our gas-phase dataset to the disruption of specific domains within the protein. The totality of our data informs the first detailed mechanism for multi-domain protein unfolding in the gas phase, and highlights key similarities and differences from the known the solution-phase pathway. PMID:27959526
Phosphatidylcholine and the CDP-Choline Cycle
Fagone, Paolo; Jackowski, Suzanne
2012-01-01
The CDP-choline pathway of phosphatidylcholine (PtdCho) biosynthesis was first described more than 50 years ago. Investigation of the CDP-choline pathway in yeast provides a basis for understanding the CDP-choline pathway in mammals. PtdCho is considered as an intermediate in a cycle of synthesis and degradation, and the activity of a CDP-choline cycle is linked to subcellular membrane lipid movement. The components of the mammalian CDP-choline pathway include choline transport, choline kinase, phosphocholine cytidylyltransferase, and choline phosphotransferase activities. The protein isoforms and biochemical mechanisms of regulation of the pathway enzymes are related to their cell and tissue-specific functions. Regulated PtdCho turnover mediated by phospholipases or neuropathy target esterase participates in the mammalian CDP-choline cycle. Knockout mouse models define the biological functions of the CDP-choline cycle in mammalian cells and tissues. This article is part of a Special Issue entitled Phospholipids and Phospholipid Metabolism. PMID:23010477
Haralambieva, Iana H.; Kennedy, Richard B.; Simon, Whitney L.; Goergen, Krista M.; Grill, Diane E.; Ovsyannikova, Inna G.
2018-01-01
Background MicroRNAs are important mediators of post-transcriptional regulation of gene expression through RNA degradation and translational repression, and are emerging biomarkers of immune system activation/response after vaccination. Methods We performed Next Generation Sequencing (mRNA-Seq) of intracellular miRNAs in measles virus-stimulated B and CD4+ T cells from high and low antibody responders to measles vaccine. Negative binomial generalized estimating equation (GEE) models were used for miRNA assessment and the DIANA tool was used for gene/target prediction and pathway enrichment analysis. Results We identified a set of B cell-specific miRNAs (e.g., miR-151a-5p, miR-223, miR-29, miR-15a-5p, miR-199a-3p, miR-103a, and miR-15a/16 cluster) and biological processes/pathways, including regulation of adherens junction proteins, Fc-receptor signaling pathway, phosphatidylinositol-mediated signaling pathway, growth factor signaling pathway/pathways, transcriptional regulation, apoptosis and virus-related processes, significantly associated with neutralizing antibody titers after measles vaccination. No CD4+ T cell-specific miRNA expression differences between high and low antibody responders were found. Conclusion Our study demonstrates that miRNA expression directly or indirectly influences humoral immunity to measles vaccination and suggests that B cell-specific miRNAs may serve as useful predictive biomarkers of vaccine humoral immune response. PMID:29381765
Relation extraction for biological pathway construction using node2vec.
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.
Zhang, Fengjuan; Peng, Donghai; Cheng, Chunsheng; Zhou, Wei; Ju, Shouyong; Wan, Danfeng; Yu, Ziquan; Shi, Jianwei; Deng, Yaoyao; Wang, Fenshan; Ye, Xiaobo; Hu, Zhenfei; Lin, Jian; Ruan, Lifang; Sun, Ming
2016-01-01
Cell death plays an important role in host-pathogen interactions. Crystal proteins (toxins) are essential components of Bacillus thuringiensis (Bt) biological pesticides because of their specific toxicity against insects and nematodes. However, the mode of action by which crystal toxins to induce cell death is not completely understood. Here we show that crystal toxin triggers cell death by necrosis signaling pathway using crystal toxin Cry6Aa-Caenorhabditis elegans toxin-host interaction system, which involves an increase in concentrations of cytoplasmic calcium, lysosomal lyses, uptake of propidium iodide, and burst of death fluorescence. We find that a deficiency in the necrosis pathway confers tolerance to Cry6Aa toxin. Intriguingly, the necrosis pathway is specifically triggered by Cry6Aa, not by Cry5Ba, whose amino acid sequence is different from that of Cry6Aa. Furthermore, Cry6Aa-induced necrosis pathway requires aspartic protease (ASP-1). In addition, ASP-1 protects Cry6Aa from over-degradation in C. elegans. This is the first demonstration that deficiency in necrosis pathway confers tolerance to Bt crystal protein, and that Cry6A triggers necrosis represents a newly added necrosis paradigm in the C. elegans. Understanding this model could lead to new strategies for nematode control. PMID:26795495
Becnel, Lauren B; Ochsner, Scott A; Darlington, Yolanda F; McOwiti, Apollo; Kankanamge, Wasula H; Dehart, Michael; Naumov, Alexey; McKenna, Neil J
2017-04-25
We previously developed a web tool, Transcriptomine, to explore expression profiling data sets involving small-molecule or genetic manipulations of nuclear receptor signaling pathways. We describe advances in biocuration, query interface design, and data visualization that enhance the discovery of uncharacterized biology in these pathways using this tool. Transcriptomine currently contains about 45 million data points encompassing more than 2000 experiments in a reference library of nearly 550 data sets retrieved from public archives and systematically curated. To make the underlying data points more accessible to bench biologists, we classified experimental small molecules and gene manipulations into signaling pathways and experimental tissues and cell lines into physiological systems and organs. Incorporation of these mappings into Transcriptomine enables the user to readily evaluate tissue-specific regulation of gene expression by nuclear receptor signaling pathways. Data points from animal and cell model experiments and from clinical data sets elucidate the roles of nuclear receptor pathways in gene expression events accompanying various normal and pathological cellular processes. In addition, data sets targeting non-nuclear receptor signaling pathways highlight transcriptional cross-talk between nuclear receptors and other signaling pathways. We demonstrate with specific examples how data points that exist in isolation in individual data sets validate each other when connected and made accessible to the user in a single interface. In summary, Transcriptomine allows bench biologists to routinely develop research hypotheses, validate experimental data, or model relationships between signaling pathways, genes, and tissues. Copyright © 2017, American Association for the Advancement of Science.
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.
2015-01-01
Background Sufficient knowledge of molecular and genetic interactions, which comprise the entire basis of the functioning of living systems, is one of the necessary requirements for successfully answering almost any research question in the field of biology and medicine. To date, more than 24 million scientific papers can be found in PubMed, with many of them containing descriptions of a wide range of biological processes. The analysis of such tremendous amounts of data requires the use of automated text-mining approaches. Although a handful of tools have recently been developed to meet this need, none of them provide error-free extraction of highly detailed information. Results The ANDSystem package was developed for the reconstruction and analysis of molecular genetic networks based on an automated text-mining technique. It provides a detailed description of the various types of interactions between genes, proteins, microRNA's, metabolites, cellular components, pathways and diseases, taking into account the specificity of cell lines and organisms. Although the accuracy of ANDSystem is comparable to other well known text-mining tools, such as Pathway Studio and STRING, it outperforms them in having the ability to identify an increased number of interaction types. Conclusion The use of ANDSystem, in combination with Pathway Studio and STRING, can improve the quality of the automated reconstruction of molecular and genetic networks. ANDSystem should provide a useful tool for researchers working in a number of different fields, including biology, biotechnology, pharmacology and medicine. PMID:25881313
Reconstructing the regulatory circuit of cell fate determination in yeast mating response.
Shao, Bin; Yuan, Haiyu; Zhang, Rongfei; Wang, Xuan; Zhang, Shuwen; Ouyang, Qi; Hao, Nan; Luo, Chunxiong
2017-07-01
Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.
An “ADME Module” in the Adverse Outcome Pathway ...
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
Endothelins in regulating ovarian and oviductal function
Bridges, Phillip J.; Cho, Jongki; Ko, CheMyong
2011-01-01
In the last 30 years, remarkable progress has been made in our understanding of the biological role of endothelins in the regulation of reproductive function and fertility. A peptide hormone identified for its ability to regulate blood pressure has now been shown as a potent mediator of several reproductive pathways. Ligand- and receptor-specific roles have been identified and/or postulated during follicular development and ovulation as well as in the function and regression of the corpus luteum. In this review we have attempted to organize endothelin-mediated ovarian processes in a process-specific manner, rather than compile a review of ligand- or isoform-specific actions. Further, we have included a discussion on “post-ovarian” or oviductal function, as well as the future directions that we believe will increase our understanding of endothelin biology as a whole. PMID:21196365
Jia, Peilin; Chen, Xiangning; Fanous, Ayman H; Zhao, Zhongming
2018-05-24
Genetic components susceptible to complex disease such as schizophrenia include a wide spectrum of variants, including common variants (CVs) and de novo mutations (DNMs). Although CVs and DNMs differ by origin, it remains elusive whether and how they interact at the gene, pathway, and network levels that leads to the disease. In this work, we characterized the genes harboring schizophrenia-associated CVs (CVgenes) and the genes harboring DNMs (DNMgenes) using measures from network, tissue-specific expression profile, and spatiotemporal brain expression profile. We developed an algorithm to link the DNMgenes and CVgenes in spatiotemporal brain co-expression networks. DNMgenes tended to have central roles in the human protein-protein interaction (PPI) network, evidenced in their high degree and high betweenness values. DNMgenes and CVgenes connected with each other significantly more often than with other genes in the networks. However, only CVgenes remained significantly connected after adjusting for their degree. In our gene co-expression PPI network, we found DNMgenes and CVgenes connected in a tissue-specific fashion, and such a pattern was similar to that in GTEx brain but not in other GTEx tissues. Importantly, DNMgene-CVgene subnetworks were enriched with pathways of chromatin remodeling, MHC protein complex binding, and neurotransmitter activities. In summary, our results unveiled that both DNMgenes and CVgenes contributed to a core set of biologically important pathways and networks, and their interactions may attribute to the risk for schizophrenia. Our results also suggested a stronger biological effect of DNMgenes than CVgenes in schizophrenia.
Nigam, Deepti; Sawant, Samir V
2013-01-01
Technological development led to an increased interest in systems biological approaches in plants to characterize developmental mechanism and candidate genes relevant to specific tissue or cell morphology. AUX-IAA proteins are important plant-specific putative transcription factors. There are several reports on physiological response of this family in Arabidopsis but in cotton fiber the transcriptional network through which AUX-IAA regulated its target genes is still unknown. in-silico modelling of cotton fiber development specific gene expression data (108 microarrays and 22,737 genes) using Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) reveals 3690 putative AUX-IAA target genes of which 139 genes were known to be AUX-IAA co-regulated within Arabidopsis. Further AUX-IAA targeted gene regulatory network (GRN) had substantial impact on the transcriptional dynamics of cotton fiber, as showed by, altered TF networks, and Gene Ontology (GO) biological processes and metabolic pathway associated with its target genes. Analysis of the AUX-IAA-correlated gene network reveals multiple functions for AUX-IAA target genes such as unidimensional cell growth, cellular nitrogen compound metabolic process, nucleosome organization, DNA-protein complex and process related to cell wall. These candidate networks/pathways have a variety of profound impacts on such cellular functions as stress response, cell proliferation, and cell differentiation. While these functions are fairly broad, their underlying TF networks may provide a global view of AUX-IAA regulated gene expression and a GRN that guides future studies in understanding role of AUX-IAA box protein and its targets regulating fiber development. PMID:24497725
Rennenberg, Heinz; Herschbach, Cornelia
2014-11-01
Understanding the dynamics of physiological process in the systems biology era requires approaches at the genome, transcriptome, proteome, and metabolome levels. In this context, metabolite flux experiments have been used in mapping metabolite pathways and analysing metabolic control. In the present review, sulphur metabolism was taken to illustrate current challenges of metabolic flux analyses. At the cellular level, restrictions in metabolite flux analyses originate from incomplete knowledge of the compartmentation network of metabolic pathways. Transport of metabolites through membranes is usually not considered in flux experiments but may be involved in controlling the whole pathway. Hence, steady-state and snapshot readings need to be expanded to time-course studies in combination with compartment-specific metabolite analyses. Because of species-specific differences, differences between tissues, and stress-related responses, the quantitative significance of different sulphur sinks has to be elucidated; this requires the development of methods for whole-sulphur metabolome approaches. Different cell types can contribute to metabolite fluxes to different extents at the tissue and organ level. Cell type-specific analyses are needed to characterize these contributions. Based on such approaches, metabolite flux analyses can be expanded to the whole-plant level by considering long-distance transport and, thus, the interaction of roots and the shoot in metabolite fluxes. However, whole-plant studies need detailed empirical and mathematical modelling that have to be validated by experimental analyses. © 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.
Biological sex and the risk of cerebral palsy in Victoria, Australia.
Reid, Susan M; Meehan, Elaine; Gibson, Catherine S; Scott, Heather; Delacy, Michael J
2016-02-01
Males typically outnumber females in cerebral palsy (CP) cohorts. To better understand this 'male disadvantage' and provide insight into causal pathways to CP, this study used 1983 to 2009 Australian CP and population birth cohorts to identify associations and trends with respect to biological sex and CP. Within birth gestation groups, sex ratios were calculated to evaluate any male excess in the CP cohort compared with livebirths, neonatal deaths, neonatal mortality and survival rates, neonatal survivors, and CP rates in survivors. Sex- and gestation-specific trends in neonatal mortality, CP rates, and CP sex ratios were assessed by plotting their annual frequencies and fitting quadratic curves. Over-representation of males in preterm live births partly explained the male excess in the CP cohort after preterm birth, especially at 28 to 31 weeks. Higher CP rates in male neonatal survivors also contributed to the male excess in CP, particularly at <28 and 37+ weeks. Higher neonatal mortality rates in males at all gestations had little impact on the CP sex ratio. There was no clearly discernible change over time in the CP sex ratio. Gestation-specific associations between sex and CP provide insight into causal pathways to CP and suggest sex-specific differences in response to neuroprotective strategies. © 2016 The Authors. Developmental Medicine & Child Neurology © 2016 Mac Keith Press.
Handa, Robert J.; Pak, Toni R.; Kudwa, Andrea E.; Lund, Trent D.; Hinds, Laura
2008-01-01
The complexity of gonadal steroid hormone actions is reflected in their broad and diverse effects on a host of integrated systems including reproductive physiology, sexual behavior, stress responses, immune function, cognition, and neural protection. Understanding the specific contributions of androgens and estrogens in neurons that mediate these important biological processes is central to the study of neuroendocrinology. Of particular interest in recent years has been the biological role of androgen metabolites. The goal of this review is to highlight recent data delineating the specific brain targets for the dihydrotestosterone metabolite, 5α-androstane, 3β, 17β-diol (3β-Diol). Studies using both in vitro and in vivo approaches provide compelling evidence that 3β-Diol is an important modulator of the stress response mediated by the hypothalmo-pituitary-adrenal axis. Further, the actions of 3β-Diol are mediated by estrogen receptors, and not androgen receptors, often through a canonical estrogen response element in the promoter of a given target gene. These novel findings compel us to re-evaluate the interpretation of past studies and the design of future experiments aimed at elucidating the specific effects of androgen receptor signaling pathways. PMID:18067894
Sasaki, Kanako; Tsurumaru, Yusuke; Yamamoto, Hirobumi; Yazaki, Kazufumi
2011-01-01
Prenylated isoflavones are secondary metabolites that are mainly distributed in legume plants. They often possess divergent biological activities such as anti-bacterial, anti-fungal, and anti-oxidant activities and thus attract much attention in food, medicinal, and agricultural research fields. Prenyltransferase is the key enzyme in the biosynthesis of prenylated flavonoids by catalyzing a rate-limiting step, i.e. the coupling process of two major metabolic pathways, the isoprenoid pathway and shikimate/polyketide pathway. However, so far only two genes have been isolated as prenyltransferases involved in the biosynthesis of prenylated flavonoids, namely naringenin 8-dimethylallyltransferase from Sophora flavescens (SfN8DT-1) specific for some limited flavanones and glycinol 4-dimethylallyltransferase from Glycine max (G4DT), specific for pterocarpan substrate. We have in this study isolated two novel genes coding for membrane-bound flavonoid prenyltransferases from S. flavescens, an isoflavone-specific prenyltransferase (SfG6DT) responsible for the prenylation of the genistein at the 6-position and a chalcone-specific prenyltransferase designated as isoliquiritigenin dimethylallyltransferase (SfiLDT). These prenyltransferases were enzymatically characterized using a yeast expression system. Analysis on the substrate specificity of chimeric enzymes between SfN8DT-1 and SfG6DT suggested that the determinant region for the specificity of the flavonoids was the domain neighboring the fifth transmembrane α-helix of the prenyltransferases. PMID:21576242
Sasaki, Kanako; Tsurumaru, Yusuke; Yamamoto, Hirobumi; Yazaki, Kazufumi
2011-07-08
Prenylated isoflavones are secondary metabolites that are mainly distributed in legume plants. They often possess divergent biological activities such as anti-bacterial, anti-fungal, and anti-oxidant activities and thus attract much attention in food, medicinal, and agricultural research fields. Prenyltransferase is the key enzyme in the biosynthesis of prenylated flavonoids by catalyzing a rate-limiting step, i.e. the coupling process of two major metabolic pathways, the isoprenoid pathway and shikimate/polyketide pathway. However, so far only two genes have been isolated as prenyltransferases involved in the biosynthesis of prenylated flavonoids, namely naringenin 8-dimethylallyltransferase from Sophora flavescens (SfN8DT-1) specific for some limited flavanones and glycinol 4-dimethylallyltransferase from Glycine max (G4DT), specific for pterocarpan substrate. We have in this study isolated two novel genes coding for membrane-bound flavonoid prenyltransferases from S. flavescens, an isoflavone-specific prenyltransferase (SfG6DT) responsible for the prenylation of the genistein at the 6-position and a chalcone-specific prenyltransferase designated as isoliquiritigenin dimethylallyltransferase (SfiLDT). These prenyltransferases were enzymatically characterized using a yeast expression system. Analysis on the substrate specificity of chimeric enzymes between SfN8DT-1 and SfG6DT suggested that the determinant region for the specificity of the flavonoids was the domain neighboring the fifth transmembrane α-helix of the prenyltransferases.
Chen, Bor-Sen
2016-01-01
Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella’s rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the “brake component” in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each “brake component” were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the “brake component”. Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate “brake component” in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains. PMID:27096615
Geng, Yu; Wu, Rui; Wee, Choon Wei; Xie, Fei; Wei, Xueliang; Chan, Penny Mei Yeen; Tham, Cliff; Duan, Lina; Dinneny, José R.
2013-01-01
Plant environmental responses involve dynamic changes in growth and signaling, yet little is understood as to how progress through these events is regulated. Here, we explored the phenotypic and transcriptional events involved in the acclimation of the Arabidopsis thaliana seedling root to a rapid change in salinity. Using live-imaging analysis, we show that growth is dynamically regulated with a period of quiescence followed by recovery then homeostasis. Through the use of a new high-resolution spatio-temporal transcriptional map, we identify the key hormone signaling pathways that regulate specific transcriptional programs, predict their spatial domain of action, and link the activity of these pathways to the regulation of specific phases of growth. We use tissue-specific approaches to suppress the abscisic acid (ABA) signaling pathway and demonstrate that ABA likely acts in select tissue layers to regulate spatially localized transcriptional programs and promote growth recovery. Finally, we show that salt also regulates many tissue-specific and time point–specific transcriptional responses that are expected to modify water transport, Casparian strip formation, and protein translation. Together, our data reveal a sophisticated assortment of regulatory programs acting together to coordinate spatially patterned biological changes involved in the immediate and long-term response to a stressful shift in environment. PMID:23898029
Engineering Robustness of Microbial Cell Factories.
Gong, Zhiwei; Nielsen, Jens; Zhou, Yongjin J
2017-10-01
Metabolic engineering and synthetic biology offer great prospects in developing microbial cell factories capable of converting renewable feedstocks into fuels, chemicals, food ingredients, and pharmaceuticals. However, prohibitively low production rate and mass concentration remain the major hurdles in industrial processes even though the biosynthetic pathways are comprehensively optimized. These limitations are caused by a variety of factors unamenable for host cell survival, such as harsh industrial conditions, fermentation inhibitors from biomass hydrolysates, and toxic compounds including metabolic intermediates and valuable target products. Therefore, engineered microbes with robust phenotypes is essential for achieving higher yield and productivity. In this review, the recent advances in engineering robustness and tolerance of cell factories is described to cope with these issues and briefly introduce novel strategies with great potential to enhance the robustness of cell factories, including metabolic pathway balancing, transporter engineering, and adaptive laboratory evolution. This review also highlights the integration of advanced systems and synthetic biology principles toward engineering the harmony of overall cell function, more than the specific pathways or enzymes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Activation and Resolution of Periodontal Inflammation and Its Systemic Impact
Hasturk, Hatice; Kantarci, Alpdogan
2015-01-01
Inflammation is a highly organized event impacting upon organs, tissues and biological systems. Periodontal diseases are characterized by dysregulation or dysfunction of resolution pathways of inflammation resulting in a failure of healing and a dominant chronic, progressive, destructive and predominantly unresolved inflammation. The biological consequences of inflammatory processes may be independent of the etiological agents such as trauma, microbial organisms and stress. The impact of the inflammatory pathological process depends upon the affected tissues or organ system. Whilst mediators are similar, there is a tissue specificity for the inflammatory events. It is plausible that inflammatory processes in one organ could directly lead to pathologies in another organ or tissue. Communication between distant parts of the body and their inflammatory status is also mediated by common signaling mechanisms mediated via cells and soluble mediators. This review focuses on periodontal inflammation, its systemic associations and advances in therapeutic approaches based on mediators acting through orchestration of natural pathway to resolution of inflammation. We also discuss a new treatment concept where natural pathways of resolution of periodontal inflammation can be used to limit systemic inflammation and promote healing and regeneration. PMID:26252412
Entourage: Visualizing Relationships between Biological Pathways using Contextual Subsets
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
Cavill, Rachel; Kamburov, Atanas; Ellis, James K; Athersuch, Toby J; Blagrove, Marcus S C; Herwig, Ralf; Ebbels, Timothy M D; Keun, Hector C
2011-03-01
Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response.
Synthetic biology era: Improving antibiotic's world.
Guzmán-Trampe, Silvia; Ceapa, Corina D; Manzo-Ruiz, Monserrat; Sánchez, Sergio
2017-06-15
The emergence of antibiotic-resistant pathogen microorganisms is problematic in the context of the current spectrum of available medication. The poor specificity and the high toxicity of some available molecules have made imperative the search for new strategies to improve the specificity and to pursue the discovery of novel compounds with increased bioactivity. Using living cells as platforms, synthetic biology has counteracted this problem by offering novel pathways to create synthetic systems with improved and desired functions. Among many other biotechnological approaches, the advances in synthetic biology have made it possible to design and construct novel biological systems in order to look for new drugs with increased bioactivity. Advancements have also been made in the redesigning of RNA and DNA molecules in order to engineer antibiotic clusters for antibiotic overexpression. As for the production of these antibacterial compounds, yeasts and filamentous fungi as well as gene therapy are utilized to enhance protein solubility. Specific delivery is achieved by creating chimeras using plant genes into bacterial hosts. Some of these synthetic systems are currently in clinical trials, proving the proficiency of synthetic biology in terms of both pharmacological activities as well as an increase in the biosafety of treatments. It is possible that we may just be seeing the tip of the iceberg, and synthetic biology applications will overpass expectations beyond our present knowledge. Copyright © 2017. Published by Elsevier Inc.
Responsive eLearning exercises to enhance student interaction with metabolic pathways.
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.
Differentiating high priority pathway-based toxicity from non ...
The ToxCast chemical screening approach enables the rapid assessment of large numbers of chemicals for biological effects, primarily at the molecular level. Adverse outcome pathways (AOPs) offer a means to link biomolecular effects with potential adverse outcomes at the level of the individual or population, thus enhancing the utility of the ToxCast effort for hazard assessment. Thus, efforts are underway to develop AOPs relevant to the pathway perturbations detected in ToxCast assays. However, activity (?‘hits’) determined for chemical-assay pairs may reflect target-specific activity relevant to a molecular initiating event of an AOP, or more generalized cell stress and cytotoxicity-mediated effects. Previous work identified a ?‘cytotoxic burst’ phenomenon wherein large numbers of assays begin to respond at or near concentrations that elicit cytotoxicity. The concentration range at which the “burst” occurs is definable, statistically. Consequently, in order to focus AOP development on the ToxCast assay targetswhich are most sensitive and relevant to pathway-specific effects, we conducted a meta-analysis to identify which assays were frequently responding at concentrations well below the cytotoxic burst. Assays were ranked by the fraction of chemical hits below the burst concentration range compared to the number of chemicals tested, resulting in a preliminary list of potentially important, target-specific assays. After eliminating cytotoxicity a
Organophosphate pesticides exposure among farmworkers: pathways and risk of adverse health effects.
Suratman, Suratman; Edwards, John William; Babina, Kateryna
2015-01-01
Organophosphate (OP) compounds are the most widely used pesticides with more than 100 OP compounds in use around the world. The high-intensity use of OP pesticides contributes to morbidity and mortality in farmworkers and their families through acute or chronic pesticides-related illnesses. Many factors contributing to adverse health effects have been investigated by researchers to determine pathways of OP-pesticide exposure among farmers in developed and developing countries. Factors like wind/agricultural pesticide drift, mixing and spraying pesticides, use of personal protective equipment (PPE), knowledge, perceptions, washing hands, taking a shower, wearing contaminated clothes, eating, drinking, smoking, and hot weather are common in both groups of countries. Factors including low socioeconomic status areas, workplace conditions, duration of exposure, pesticide safety training, frequency of applying pesticides, spraying against the wind, and reuse of pesticide containers for storage are specific contributors in developing countries, whereas housing conditions, social contextual factors, and mechanical equipment were specific pathways in developed countries. This paper compares existing research in environmental and behavioural exposure modifying factors and biological monitoring between developing and developed countries. The main objective of this review is to explore the current depth of understanding of exposure pathways and factors increasing the risk of exposure potentially leading to adverse health effects specific to each group of countries.
Li, Wan; Chen, Lina; Li, Xia; Jia, Xu; Feng, Chenchen; Zhang, Liangcai; He, Weiming; Lv, Junjie; He, Yuehan; Li, Weiguo; Qu, Xiaoli; Zhou, Yanyan; Shi, Yuchen
2013-12-01
Network motifs in central positions are considered to not only have more in-coming and out-going connections but are also localized in an area where more paths reach the networks. These central motifs have been extensively investigated to determine their consistent functions or associations with specific function categories. However, their functional potentials in the maintenance of cross-talk between different functional communities are unclear. In this paper, we constructed an integrated human signaling network from the Pathway Interaction Database. We identified 39 essential cancer-related motifs in central roles, which we called cancer-related marketing centrality motifs, using combined centrality indices on the system level. Our results demonstrated that these cancer-related marketing centrality motifs were pivotal units in the signaling network, and could mediate cross-talk between 61 biological pathways (25 could be mediated by one motif on average), most of which were cancer-related pathways. Further analysis showed that molecules of most marketing centrality motifs were in the same or adjacent subcellular localizations, such as the motif containing PI3K, PDK1 and AKT1 in the plasma membrane, to mediate signal transduction between 32 cancer-related pathways. Finally, we analyzed the pivotal roles of cancer genes in these marketing centrality motifs in the pathogenesis of cancers, and found that non-cancer genes were potential cancer-related genes.
Extensive cargo identification reveals distinct biological roles of the 12 importin pathways.
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.
Recent advances in understanding the biology of marginal zone lymphoma
Zucca, Emanuele
2018-01-01
There are three different marginal zone lymphomas (MZLs): the extranodal MZL of mucosa-associated lymphoid tissue (MALT) type (MALT lymphoma), the splenic MZL, and the nodal MZL. The three MZLs share common lesions and deregulated pathways but also present specific alterations that can be used for their differential diagnosis. Although trisomies of chromosomes 3 and 18, deletions at 6q23, deregulation of nuclear factor kappa B, and chromatin remodeling genes are frequent events in all of them, the three MZLs differ in the presence of recurrent translocations, mutations affecting the NOTCH pathway, and the transcription factor Kruppel like factor 2 ( KLF2) or the receptor-type protein tyrosine phosphatase delta ( PTPRD). Since a better understanding of the molecular events underlying each subtype may have practical relevance, this review summarizes the most recent and main advances in our understanding of the genetics and biology of MZLs. PMID:29657712
Plant TOR signaling components
John, Florian; Roffler, Stefan; Wicker, Thomas; Ringli, Christoph
2011-01-01
Cell growth is a process that needs to be tightly regulated. Cells must be able to sense environmental factors like nutrient abundance, the energy level or stress signals and coordinate growth accordingly. The Target Of Rapamycin (TOR) pathway is a major controller of growth-related processes in all eukaryotes. If environmental conditions are favorable, the TOR pathway promotes cell and organ growth and restrains catabolic processes like autophagy. Rapamycin is a specific inhibitor of the TOR kinase and acts as a potent inhibitor of TOR signaling. As a consequence, interfering with TOR signaling has a strong impact on plant development. This review summarizes the progress in the understanding of the biological significance and the functional analysis of the TOR pathway in plants. PMID:22057328
Chemical genetics and regeneration.
Sengupta, Sumitra; Zhang, Liyun; Mumm, Jeff S
2015-01-01
Regeneration involves interactions between multiple signaling pathways acting in a spatially and temporally complex manner. As signaling pathways are highly conserved, understanding how regeneration is controlled in animal models exhibiting robust regenerative capacities should aid efforts to stimulate repair in humans. One way to discover molecular regulators of regeneration is to alter gene/protein function and quantify effect(s) on the regenerative process: dedifferentiation/reprograming, stem/progenitor proliferation, migration/remodeling, progenitor cell differentiation and resolution. A powerful approach for applying this strategy to regenerative biology is chemical genetics, the use of small-molecule modulators of specific targets or signaling pathways. Here, we review advances that have been made using chemical genetics for hypothesis-focused and discovery-driven studies aimed at furthering understanding of how regeneration is controlled.
Two is better than one; toward a rational design of combinatorial therapy.
Chen, Sheng-Hong; Lahav, Galit
2016-12-01
Drug combination is an appealing strategy for combating the heterogeneity of tumors and evolution of drug resistance. However, the rationale underlying combinatorial therapy is often not well established due to lack of understandings of the specific pathways responding to the drugs, and their temporal dynamics following each treatment. Here we present several emerging trends in harnessing properties of biological systems for the optimal design of drug combinations, including the type of drugs, specific concentration, sequence of addition and the temporal schedule of treatments. We highlight recent studies showing different approaches for efficient design of drug combinations including single-cell signaling dynamics, adaption and pathway crosstalk. Finally, we discuss novel and feasible approaches that can facilitate the optimal design of combinatorial therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Skeleton and Glucose Metabolism: A Bone-Pancreas Loop
Luce, Vincenza; Ventura, Annamaria; Colucci, Silvia; Cavallo, Luciano; Grano, Maria
2015-01-01
Bone has been considered a structure essential for mobility, calcium homeostasis, and hematopoietic function. Recent advances in bone biology have highlighted the importance of skeleton as an endocrine organ which regulates some metabolic pathways, in particular, insulin signaling and glucose tolerance. This review will point out the role of bone as an endocrine “gland” and, specifically, of bone-specific proteins, as the osteocalcin (Ocn), and proteins involved in bone remodeling, as osteoprotegerin, in the regulation of insulin function and glucose metabolism. PMID:25873957
Pim-1: A Molecular Target to Modulate Cellular Resistance to Therapy in Prostate Cancer
2007-10-01
submitted to the Journal of Biological Chemistry . BODY We will outline our progress through reference to the specific aims described above. The first... Chemistry (see manuscript in appendix). The goal of specific aim #2 was to define pathways through which the PIM1 kinase could activate NFkB...or with three other flavonoids , has been determined. We have also shown that quercetagetin is able to inhibit the activity of the PIM1 kinase in
Aiding and abetting roles of NOX oxidases in cellular transformation
Block, Karen; Gorin, Yves
2013-01-01
NADPH oxidases of the NADPH oxidase (NOX) family are dedicated reactive oxygen species-generating enzymes that broadly and specifically regulate redox-sensitive signalling pathways that are involved in cancer development and progression. They act at specific cellular membranes and microdomains through the activation of oncogenes and the inactivation of tumour suppressor proteins. In this Review, we discuss primary targets and redox-linked signalling systems that are influenced by NOX-derived ROS, and the biological role of NOX oxidases in the aetiology of cancer. PMID:22918415
Loh, Nellie Y; Neville, Matt J; Marinou, Kyriakoula; Hardcastle, Sarah A; Fielding, Barbara A; Duncan, Emma L; McCarthy, Mark I; Tobias, Jonathan H; Gregson, Celia L; Karpe, Fredrik; Christodoulides, Constantinos
2015-02-03
Common variants in WNT pathway genes have been associated with bone mass and fat distribution, the latter predicting diabetes and cardiovascular disease risk. Rare mutations in the WNT co-receptors LRP5 and LRP6 are similarly associated with bone and cardiometabolic disorders. We investigated the role of LRP5 in human adipose tissue. Subjects with gain-of-function LRP5 mutations and high bone mass had enhanced lower-body fat accumulation. Reciprocally, a low bone mineral density-associated common LRP5 allele correlated with increased abdominal adiposity. Ex vivo LRP5 expression was higher in abdominal versus gluteal adipocyte progenitors. Equivalent knockdown of LRP5 in both progenitor types dose-dependently impaired β-catenin signaling and led to distinct biological outcomes: diminished gluteal and enhanced abdominal adipogenesis. These data highlight how depot differences in WNT/β-catenin pathway activity modulate human fat distribution via effects on adipocyte progenitor biology. They also identify LRP5 as a potential pharmacologic target for the treatment of cardiometabolic disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Loh, Nellie Y.; Neville, Matt J.; Marinou, Kyriakoula; Hardcastle, Sarah A.; Fielding, Barbara A.; Duncan, Emma L.; McCarthy, Mark I.; Tobias, Jonathan H.; Gregson, Celia L.; Karpe, Fredrik; Christodoulides, Constantinos
2015-01-01
Summary Common variants in WNT pathway genes have been associated with bone mass and fat distribution, the latter predicting diabetes and cardiovascular disease risk. Rare mutations in the WNT co-receptors LRP5 and LRP6 are similarly associated with bone and cardiometabolic disorders. We investigated the role of LRP5 in human adipose tissue. Subjects with gain-of-function LRP5 mutations and high bone mass had enhanced lower-body fat accumulation. Reciprocally, a low bone mineral density-associated common LRP5 allele correlated with increased abdominal adiposity. Ex vivo LRP5 expression was higher in abdominal versus gluteal adipocyte progenitors. Equivalent knockdown of LRP5 in both progenitor types dose-dependently impaired β-catenin signaling and led to distinct biological outcomes: diminished gluteal and enhanced abdominal adipogenesis. These data highlight how depot differences in WNT/β-catenin pathway activity modulate human fat distribution via effects on adipocyte progenitor biology. They also identify LRP5 as a potential pharmacologic target for the treatment of cardiometabolic disorders. PMID:25651180
WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data
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
Woodcock, K A; Oliver, C; Humphreys, G W
2009-06-01
Behavioural phenotypes associated with genetic syndromes have been extensively investigated in order to generate rich descriptions of phenomenology, determine the degree of specificity of behaviours for a particular syndrome, and examine potential interactions between genetic predispositions for behaviour and environmental influences. However, relationships between different aspects of behavioural phenotypes have been less frequently researched and although recent interest in potential cognitive phenotypes or endophenotypes has increased, these are frequently studied independently of the behavioural phenotypes. Taking Prader-Willi syndrome (PWS) as an example, we discuss evidence suggesting specific relationships between apparently distinct aspects of the PWS behavioural phenotype and relate these to specific endophenotypic characteristics. The framework we describe progresses through biological, cognitive, physiological and behavioural levels to develop a pathway from genetic characteristics to behaviour with scope for interaction with the environment at any stage. We propose this multilevel approach as useful in setting out hypotheses in order to structure research that can more rapidly advance theory.
Responses to Cytokines and Interferons that Depend upon JAKs and STATs.
Stark, George R; Cheon, HyeonJoo; Wang, Yuxin
2018-01-02
Many cytokines and all interferons activate members of a small family of kinases (the Janus kinases [JAKs]) and a slightly larger family of transcription factors (the signal transducers and activators of transcription [STATs]), which are essential components of pathways that induce the expression of specific sets of genes in susceptible cells. JAK-STAT pathways are required for many innate and acquired immune responses, and the activities of these pathways must be finely regulated to avoid major immune dysfunctions. Regulation is achieved through mechanisms that include the activation or induction of potent negative regulatory proteins, posttranslational modification of the STATs, and other modulatory effects that are cell-type specific. Mutations of JAKs and STATs can result in gains or losses of function and can predispose affected individuals to autoimmune disease, susceptibility to a variety of infections, or cancer. Here we review recent developments in the biochemistry, genetics, and biology of JAKs and STATs. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.
Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.
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.
MIMO: an efficient tool for molecular interaction maps overlap
2013-01-01
Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344
Recent Developments in the Application of Biologically Inspired Computation to Chemical Sensing
NASA Astrophysics Data System (ADS)
Marco, S.; Gutierrez-Gálvez, A.
2009-05-01
Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.
Convergence between biological, behavioural and genetic determinants of obesity.
Ghosh, Sujoy; Bouchard, Claude
2017-12-01
Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
A taxonomy of visualization tasks for the analysis of biological pathway data.
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.
Hara, Takato; Kojima, Takayuki; Matsuzaki, Hiroka; Nakamura, Takehiro; Yoshida, Eiko; Fujiwara, Yasuyuki; Yamamoto, Chika; Saito, Shinichi; Kaji, Toshiyuki
2017-02-08
Organic-inorganic hybrid molecules constitute analytical tools used in biological systems. Vascular endothelial cells synthesize and secrete proteoglycans, which are macromolecules consisting of a core protein and glycosaminoglycan side chains. Although the expression of endothelial proteoglycans is regulated by several cytokines/growth factors, there may be alternative pathways for proteoglycan synthesis aside from downstream pathways activated by these cytokines/growth factors. Here, we investigated organic-inorganic hybrid molecules to determine a variant capable of analyzing the expression of syndecan-4, a transmembrane heparan-sulfate proteoglycan, and identified 1,10-phenanthroline ( o -Phen) with or without zinc (Zn-Phen) or rhodium (Rh-Phen). Bovine aortic endothelial cells in culture were treated with these compounds, and the expression of syndecan-4 mRNA and core proteins was determined by real-time reverse transcription polymerase chain reaction and Western blot analysis, respectively. Our findings indicated that o -Phen and Zn-Phen specifically and strongly induced syndecan-4 expression in cultured vascular endothelial cells through activation of the hypoxia-inducible factor-1α/β pathway via inhibition of prolyl hydroxylase-domain-containing protein 2. These results demonstrated an alternative pathway involved in mediating induction of endothelial syndecan-4 expression and revealed organic-inorganic hybrid molecules as effective tools for analyzing biological systems.
Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P
2015-11-06
Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.
Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae.
Li, Mingji; Borodina, Irina
2015-02-01
Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
Knowledge-driven genomic interactions: an application in ovarian cancer.
Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D
2014-01-01
Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.
Lu, Xunli; Dittgen, Jan; Piślewska-Bednarek, Mariola; Molina, Antonio; Schneider, Bernd; Doubský, Jan; Schneeberger, Korbinian; Schulze-Lefert, Paul
2015-01-01
Arabidopsis (Arabidopsis thaliana) PENETRATION (PEN) genes quantitatively contribute to the execution of different forms of plant immunity upon challenge with diverse leaf pathogens. PEN3 encodes a plasma membrane-resident pleiotropic drug resistance-type ATP-binding cassette transporter and is thought to act in a pathogen-inducible and PEN2 myrosinase-dependent metabolic pathway in extracellular defense. This metabolic pathway directs the intracellular biosynthesis and activation of tryptophan-derived indole glucosinolates for subsequent PEN3-mediated efflux across the plasma membrane at pathogen contact sites. However, PEN3 also functions in abiotic stress responses to cadmium and indole-3-butyric acid (IBA)-mediated auxin homeostasis in roots, raising the possibility that PEN3 exports multiple functionally unrelated substrates. Here, we describe the isolation of a pen3 allele, designated pen3-5, that encodes a dysfunctional protein that accumulates in planta like wild-type PEN3. The specific mutation in pen3-5 uncouples PEN3 functions in IBA-stimulated root growth modulation, callose deposition induced with a conserved peptide epitope of bacterial flagellin (flg22), and pathogen-inducible salicylic acid accumulation from PEN3 activity in extracellular defense, indicating the engagement of multiple PEN3 substrates in different PEN3-dependent biological processes. We identified 4-O-β-d-glucosyl-indol-3-yl formamide (4OGlcI3F) as a pathogen-inducible, tryptophan-derived compound that overaccumulates in pen3 leaf tissue and has biosynthesis that is dependent on an intact PEN2 metabolic pathway. We propose that a precursor of 4OGlcI3F is the PEN3 substrate in extracellular pathogen defense. These precursors, the shared indole core present in IBA and 4OGlcI3F, and allele-specific uncoupling of a subset of PEN3 functions suggest that PEN3 transports distinct indole-type metabolites in distinct biological processes. PMID:26023163
Adverse outcome pathway (AOP) development I: Strategies and principles
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...
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
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.
Sharma, Rahul; Sharma, Bhumika; Gupta, Ashish; Dhar, Suman Kumar
2018-05-01
Malaria parasites use an extensive secretory pathway to traffic a number of proteins within itself and beyond. In higher eukaryotes, Endoplasmic Reticulum (ER) membrane bound transcription factors such as SREBP are reported to get processed en route and migrate to nucleus under the influence of specific cues. However, a protein constitutively trafficked to the nucleus via classical secretory pathway has not been reported. Herein, we report the presence of a novel trafficking pathway in an apicomplexan, Plasmodium falciparum where a homologue of an Origin Recognition Complex 2 (Orc2) goes to the nucleus following its association with the ER. Our work highlights the unconventional role of ER in protein trafficking and reports for the first time an ORC homologue getting trafficked through such a pathway to the nucleus where it may be involved in DNA replication and other ancillary functions. Such trafficking pathways may have a profound impact on the cell biology of a malaria parasite and have significant implications in strategizing new antimalarials. Copyright © 2018 Elsevier B.V. All rights reserved.
Passing Messages between Biological Networks to Refine Predicted Interactions
Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng
2013-01-01
Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402
Green leaf volatiles: biosynthesis, biological functions and their applications in biotechnology.
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.
Methods and approaches in the topology-based analysis of biological pathways
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
The molecular biology of soft-tissue sarcomas and current trends in therapy.
Quesada, Jorge; Amato, Robert
2012-01-01
Basic research in sarcoma models has been fundamental in the discovery of scientific milestones leading to a better understanding of the molecular biology of cancer. Yet, clinical research in sarcoma has lagged behind other cancers because of the multiple clinical and pathological entities that characterize sarcomas and their rarity. Sarcomas encompass a very heterogeneous group of tumors with diverse pathological and clinical overlapping characteristics. Molecular testing has been fundamental in the identification and better definition of more specific entities among this vast array of malignancies. A group of sarcomas are distinguished by specific molecular aberrations such as somatic mutations, intergene deletions, gene amplifications, reciprocal translocations, and complex karyotypes. These and other discoveries have led to a better understanding of the growth signals and the molecular pathways involved in the development of these tumors. These findings are leading to treatment strategies currently under intense investigation. Disruption of the growth signals is being targeted with antagonistic antibodies, tyrosine kinase inhibitors, and inhibitors of several downstream molecules in diverse molecular pathways. Preliminary clinical trials, supported by solid basic research and strong preclinical evidence, promises a new era in the clinical management of these broad spectrum of malignant tumors.
Dahlberg, Caroline Lund; Nguyen, Elizabeth Z.; Goodlett, David; Kimelman, David
2009-01-01
Background Members of the Casein Kinase I (CKI) family of serine/threonine kinases regulate diverse biological pathways. The seven mammalian CKI isoforms contain a highly conserved kinase domain and divergent amino- and carboxy-termini. Although they share a preferred target recognition sequence and have overlapping expression patterns, individual isoforms often have specific substrates. In an effort to determine how substrates recognize differences between CKI isoforms, we have examined the interaction between CKIε and two substrates from different signaling pathways. Methodology/Principal Findings CKIε, but not CKIα, binds to and phosphorylates two proteins: Period, a transcriptional regulator of the circadian rhythms pathway, and Disheveled, an activator of the planar cell polarity pathway. We use GST-pull-down assays data to show that two key residues in CKIα's kinase domain prevent Disheveled and Period from binding. We also show that the unique C-terminus of CKIε does not determine Dishevelled's and Period's preference for CKIε nor is it essential for binding, but instead plays an auxillary role in stabilizing the interactions of CKIε with its substrates. We demonstrate that autophosphorylation of CKIε's C-terminal tail prevents substrate binding, and use mass spectrometry and chemical crosslinking to reveal how a phosphorylation-dependent interaction between the C-terminal tail and the kinase domain prevents substrate phosphorylation and binding. Conclusions/Significance The biochemical interactions between CKIε and Disheveled, Period, and its own C-terminus lead to models that explain CKIε's specificity and regulation. PMID:19274088
Computational analysis of microRNA function in heart development.
Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong
2010-09-01
Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.
2014-01-01
Background Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Methods We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. Results Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. Conclusions We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability. PMID:24965703
Haviland, Julia A; Tonelli, Marco; Haughey, Dermot T; Porter, Warren P; Assadi-Porter, Fariba M
2012-08-01
Metabolomics is the study of a unique fingerprint of small molecules present in biological systems under healthy and disease conditions. One of the major challenges in metabolomics is validation of fingerprint molecules to identify specifically perturbed pathways in metabolic aberrations. This step is crucial to the understanding of budding metabolic pathologies and the ability to identify early indicators of common diseases such as obesity, type 2 diabetes mellitus, metabolic syndrome, polycystic ovary syndrome, and cancer. We present a novel approach to diagnosing aberrations in glucose utilization including metabolic pathway switching in a disease state. We used a well-defined prenatally exposed glucocorticoid mouse model that results in adult females with metabolic dysfunction. We applied the complementary technologies of nuclear magnetic resonance spectroscopy and cavity ring-down spectroscopy to analyze serial plasma samples and real-time breath measurements following selective (13)C-isotope-assisted labeling. These platforms allowed us to trace metabolic markers in whole animals and identify key metabolic pathway switching in prenatally glucocorticoid-treated animals. Total glucose flux is significantly proportionally increased through the major oxidative pathways of glycolysis and the pentose phosphate pathway in the prenatally glucocorticoid-treated animals relative to the control animals. This novel diagnostics approach is fast, noninvasive, and sensitive for determining specific pathway utilization, and provides a direct translational application in the health care field. Copyright © 2012 Elsevier Inc. All rights reserved.
Khaldun, A. B. M.; Huang, Wenjun; Liao, Sihong; Lv, Haiyan; Wang, Ying
2015-01-01
Although Lycium chinense (goji berry) is an important traditional Chinese medicinal plant, little genome information is available for this plant, particularly at the small-RNA level. Recent findings indicate that the evolutionary role of miRNAs is very important for a better understanding of gene regulation in different plant species. To elucidate small RNAs and their potential target genes in fruit and shoot tissues, high-throughput RNA sequencing technology was used followed by qRT-PCR and RLM 5’-RACE experiments. A total of 60 conserved miRNAs belonging to 31 families and 30 putative novel miRNAs were identified. A total of 62 significantly differentially expressed miRNAs were identified, of which 15 (14 known and 1 novel) were shoot-specific, and 12 (7 known and 5 novel) were fruit-specific. Additionally, 28 differentially expressed miRNAs were recorded as up-regulated in fruit tissues. The predicted potential targets were involved in a wide range of metabolic and regulatory pathways. GO (Gene Ontology) enrichment analysis and the KEGG (Kyoto Encyclopedia of Genes and Genomes) database revealed that “metabolic pathways” is the most significant pathway with respect to the rich factor and gene numbers. Moreover, five miRNAs were related to fruit maturation, lycopene biosynthesis and signaling pathways, which might be important for the further study of fruit molecular biology. This study is the first, to detect known and novel miRNAs, and their potential targets, of L. chinense. The data and findings that are presented here might be a good source for the functional genomic study of medicinal plants and for understanding the links among diversified biological pathways. PMID:25587984
Assembling old tricks for new tasks: a neural model of instructional learning and control.
Huang, Tsung-Ren; Hazy, Thomas E; Herd, Seth A; O'Reilly, Randall C
2013-06-01
We can learn from the wisdom of others to maximize success. However, it is unclear how humans take advice to flexibly adapt behavior. On the basis of data from neuroanatomy, neurophysiology, and neuroimaging, a biologically plausible model is developed to illustrate the neural mechanisms of learning from instructions. The model consists of two complementary learning pathways. The slow-learning parietal pathway carries out simple or habitual stimulus-response (S-R) mappings, whereas the fast-learning hippocampal pathway implements novel S-R rules. Specifically, the hippocampus can rapidly encode arbitrary S-R associations, and stimulus-cued responses are later recalled into the basal ganglia-gated pFC to bias response selection in the premotor and motor cortices. The interactions between the two model learning pathways explain how instructions can override habits and how automaticity can be achieved through motor consolidation.
Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.
2018-01-01
The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400
Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A
2018-02-22
The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.
An Integrative data mining approach to identifying Adverse Outcome Pathway (AOP) Signatures
The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or populatio...
Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine
Chen, Xiao-Wu; Di, Yuan Ming; Zhang, Jian; Zhou, Zhi-Wei; Li, Chun Guang; Zhou, Shu-Feng
2012-01-01
Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis), which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer's disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach. PMID:23213296
GOSAP: Gene Ontology-Based Semantic Alignment of Biological Pathways.
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.
Free Energy Wells and Barriers to Ion Transport Across Membranes
NASA Astrophysics Data System (ADS)
Rempe, Susan
2014-03-01
The flow of ions across cellular membranes is essential to many biological processes. Ion transport is also important in synthetic materials used as battery electrolytes. Transport often involves specific ions and fast conduction. To achieve those properties, ion conduction pathways must solvate specific ions by just the ``right amount.'' The right amount of solvation avoids ion traps due to deep free energy wells, and avoids ion block due to high free energy barriers. Ion channel proteins in cellular membranes demonstrate this subtle balance in solvation of specific ions. Using ab initio molecular simulations, we have interrogated the link between binding site structure and ion solvation free energies in biological ion binding sites. Our results emphasize the surprisingly important role of the environment that surrounds ion-binding sites for fast transport of specific ions. We acknowledge support from Sandia's LDRD program. Sandia National Labs is a multi-program laboratory operated by Sandia Corp., a wholly owned subsidiary of Lockheed Martin Corp., for the US DOE's NNSA under contract DE-AC04-94AL85000.
The UVR8 UV-B Photoreceptor: Perception, Signaling and Response
Tilbrook, Kimberley; Arongaus, Adriana B.; Binkert, Melanie; Heijde, Marc; Yin, Ruohe; Ulm, Roman
2013-01-01
Ultraviolet-B radiation (UV-B) is an intrinsic part of sunlight that is accompanied by significant biological effects. Plants are able to perceive UV-B using the UV-B photoreceptor UVR8 which is linked to a specific molecular signaling pathway and leads to UV-B acclimation. Herein we review the biological process in plants from initial UV-B perception and signal transduction through to the known UV-B responses that promote survival in sunlight. The UVR8 UV-B photoreceptor exists as a homodimer that instantly monomerises upon UV-B absorption via specific intrinsic tryptophans which act as UV-B chromophores. The UVR8 monomer interacts with COP1, an E3 ubiquitin ligase, initiating a molecular signaling pathway that leads to gene expression changes. This signaling output leads to UVR8-dependent responses including UV-B-induced photomorphogenesis and the accumulation of UV-B-absorbing flavonols. Negative feedback regulation of the pathway is provided by the WD40-repeat proteins RUP1 and RUP2, which facilitate UVR8 redimerization, disrupting the UVR8-COP1 interaction. Despite rapid advancements in the field of recent years, further components of UVR8 UV-B signaling are constantly emerging, and the precise interplay of these and the established players UVR8, COP1, RUP1, RUP2 and HY5 needs to be defined. UVR8 UV-B signaling represents our further understanding of how plants are able to sense their light environment and adjust their growth accordingly. PMID:23864838
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.
... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...
Expanding the Interactome of TES by Exploiting TES Modules with Different Subcellular Localizations.
Sala, Stefano; Van Troys, Marleen; Medves, Sandrine; Catillon, Marie; Timmerman, Evy; Staes, An; Schaffner-Reckinger, Elisabeth; Gevaert, Kris; Ampe, Christophe
2017-05-05
The multimodular nature of many eukaryotic proteins underlies their temporal or spatial engagement in a range of protein cocomplexes. Using the multimodule protein testin (TES), we here report a proteomics approach to increase insight in cocomplex diversity. The LIM-domain containing and tumor suppressor protein TES is present at different actin cytoskeleton adhesion structures in cells and influences cell migration, adhesion and spreading. TES module accessibility has been proposed to vary due to conformational switching and variants of TES lacking specific domains target to different subcellular locations. By applying iMixPro AP-MS ("intelligent Mixing of Proteomes"-affinity purification-mass spectrometry) to a set of tagged-TES modular variants, we identified proteins residing in module-specific cocomplexes. The obtained distinct module-specific interactomes combine to a global TES interactome that becomes more extensive and richer in information. Applying pathway analysis to the module interactomes revealed expected actin-related canonical pathways and also less expected pathways. We validated two new TES cocomplex partners: TGFB1I1 and a short form of the glucocorticoid receptor. TES and TGFB1I1 are shown to oppositely affect cell spreading providing biological validity for their copresence in complexes since they act in similar processes.
The impact of genetics on future drug discovery in schizophrenia.
Matsumoto, Mitsuyuki; Walton, Noah M; Yamada, Hiroshi; Kondo, Yuji; Marek, Gerard J; Tajinda, Katsunori
2017-07-01
Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.
Adverse Outcome Pathways – Organizing Toxicological ...
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,
Systematic reconstruction of TRANSPATH data into Cell System Markup Language
Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru
2008-01-01
Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683
Systematic reconstruction of TRANSPATH data into cell system markup language.
Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru
2008-06-23
Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.
Data-Driven Discovery of Extravasation Pathway in Circulating Tumor Cells
Yadavalli, S.; Jayaram, S.; Manda, S. S.; Madugundu, A. K.; Nayakanti, D. S.; Tan, T. Z.; Bhat, R.; Rangarajan, A.; Chatterjee, A.; Gowda, H.; Thiery, J. P.; Kumar, P.
2017-01-01
Circulating tumor cells (CTCs) play a crucial role in cancer dissemination and provide a promising source of blood-based markers. Understanding the spectrum of transcriptional profiles of CTCs and their corresponding regulatory mechanisms will allow for a more robust analysis of CTC phenotypes. The current challenge in CTC research is the acquisition of useful clinical information from the multitude of high-throughput studies. To gain a deeper understanding of CTC heterogeneity and identify genes, pathways and processes that are consistently affected across tumors, we mined the literature for gene expression profiles in CTCs. Through in silico analysis and the integration of CTC-specific genes, we found highly significant biological mechanisms and regulatory processes acting in CTCs across various cancers, with a particular enrichment of the leukocyte extravasation pathway. This pathway appears to play a pivotal role in the migration of CTCs to distant metastatic sites. We find that CTCs from multiple cancers express both epithelial and mesenchymal markers in varying amounts, which is suggestive of dynamic and hybrid states along the epithelial-mesenchymal transition (EMT) spectrum. Targeting the specific molecular nodes to monitor disease and therapeutic control of CTCs in real time will likely improve the clinical management of cancer progression and metastases. PMID:28262832
Giant virus Megavirus chilensis encodes the biosynthetic pathway for uncommon acetamido sugars.
Piacente, Francesco; De Castro, Cristina; Jeudy, Sandra; Molinaro, Antonio; Salis, Annalisa; Damonte, Gianluca; Bernardi, Cinzia; Abergel, Chantal; Tonetti, Michela G
2014-08-29
Giant viruses mimicking microbes, by the sizes of their particles and the heavily glycosylated fibrils surrounding their capsids, infect Acanthamoeba sp., which are ubiquitous unicellular eukaryotes. The glycans on fibrils are produced by virally encoded enzymes, organized in gene clusters. Like Mimivirus, Megavirus glycans are mainly composed of virally synthesized N-acetylglucosamine (GlcNAc). They also contain N-acetylrhamnosamine (RhaNAc), a rare sugar; the enzymes involved in its synthesis are encoded by a gene cluster specific to Megavirus close relatives. We combined activity assays on two enzymes of the pathway with mass spectrometry and NMR studies to characterize their specificities. Mg534 is a 4,6-dehydratase 5-epimerase; its three-dimensional structure suggests that it belongs to a third subfamily of inverting dehydratases. Mg535, next in the pathway, is a bifunctional 3-epimerase 4-reductase. The sequential activity of the two enzymes leads to the formation of UDP-l-RhaNAc. This study is another example of giant viruses performing their glycan synthesis using enzymes different from their cellular counterparts, raising again the question of the origin of these pathways. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng
2018-03-08
Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.
Plant MetGenMAP: an integrative analysis system for plant systems biology
USDA-ARS?s Scientific Manuscript database
We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...
Steroid receptors and their ligands: Effects on male gamete functions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aquila, Saveria; De Amicis, Francesca, E-mail: francesca.deamicis@unical.it
In recent years a new picture of human sperm biology is emerging. It is now widely recognized that sperm contain nuclear encoded mRNA, mitochondrial encoded RNA and different transcription factors including steroid receptors, while in the past sperm were considered incapable of transcription and translation. One of the main targets of steroid hormones and their receptors is reproductive function. Expression studies on Progesterone Receptor, estrogen receptor, androgen receptor and their specific ligands, demonstrate the presence of these systems in mature spermatozoa as surface but also as nuclear conventional receptors, suggesting that both systemic and local steroid hormones, through sperm receptors,more » may influence male reproduction. However, the relationship between the signaling events modulated by steroid hormones and sperm fertilization potential as well as the possible involvement of the specific receptors are still controversial issues. The main line of this review highlights the current research in human sperm biology examining new molecular systems of response to the hormones as well as specific regulatory pathways controlling sperm cell fate and biological functions. Most significant studies regarding the identification of steroid receptors are reported and the mechanistic insights relative to signaling pathways, together with the change in sperm metabolism energy influenced by steroid hormones are discussed.The reviewed evidences suggest important effects of Progesterone, Estrogen and Testosterone and their receptors on spermatozoa and implicate the involvement of both systemic and local steroid action in the regulation of male fertility potential. - Highlights: • One of the main targets of steroid hormones and their receptors is reproductive function. • Pg/PR co-work to stimulate enzymatic activities to sustain a capacitation process. • E2/ERs regulate sperm motility, capacitation and acrosome reaction and act as survival factors. • Androgens/AR mediate sperm death which is a novel field of investigation in sperm biology.« less
Degradation of Serotonin N-Acetyltransferase, a Circadian Regulator, by the N-end Rule Pathway.
Wadas, Brandon; Borjigin, Jimo; Huang, Zheping; Oh, Jang-Hyun; Hwang, Cheol-Sang; Varshavsky, Alexander
2016-08-12
Serotonin N-acetyltransferase (AANAT) converts serotonin to N-acetylserotonin (NAS), a distinct biological regulator and the immediate precursor of melatonin, a circulating hormone that influences circadian processes, including sleep. N-terminal sequences of AANAT enzymes vary among vertebrates. Mechanisms that regulate the levels of AANAT are incompletely understood. Previous findings were consistent with the possibility that AANAT may be controlled through its degradation by the N-end rule pathway. By expressing the rat and human AANATs and their mutants not only in mammalian cells but also in the yeast Saccharomyces cerevisiae, and by taking advantage of yeast genetics, we show here that two "complementary" forms of rat AANAT are targeted for degradation by two "complementary" branches of the N-end rule pathway. Specifically, the N(α)-terminally acetylated (Nt-acetylated) Ac-AANAT is destroyed through the recognition of its Nt-acetylated N-terminal Met residue by the Ac/N-end rule pathway, whereas the non-Nt-acetylated AANAT is targeted by the Arg/N-end rule pathway, which recognizes the unacetylated N-terminal Met-Leu sequence of rat AANAT. We also show, by constructing lysine-to-arginine mutants of rat AANAT, that its degradation is mediated by polyubiquitylation of its Lys residue(s). Human AANAT, whose N-terminal sequence differs from that of rodent AANATs, is longer-lived than its rat counterpart and appears to be refractory to degradation by the N-end rule pathway. Together, these and related results indicate both a major involvement of the N-end rule pathway in the control of rodent AANATs and substantial differences in the regulation of rodent and human AANATs that stem from differences in their N-terminal sequences. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Del Sorbo, Maria Rosaria; Balzano, Walter; Donato, Michele; Draghici, Sorin
2013-11-01
Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components. Copyright © 2013. Published by Elsevier Ireland Ltd.
Marcu, Loredana Gabriela; Moghaddasi, Leyla; Bezak, Eva
2018-05-04
Improvements in personalized therapy are made possible by the advances in molecular biology that led to developments in molecular imaging, allowing highly specific in vivo imaging of biological processes. Positron emission tomography (PET) is the most specific and sensitive imaging technique for in vivo molecular targets and pathways, offering quantification and evaluation of functional properties of the targeted anatomy. This work is an integrative research review that summarizes and evaluates the accumulated current status of knowledge of recent advances in PET imaging for cancer diagnosis and treatment, concentrating on novel radiotracers and evaluating their advantages and disadvantages in cancer characterization. Medline search was conducted, limited to English publications from 2007 onward. Identified manuscripts were evaluated for most recent developments in PET imaging of cancer hypoxia, angiogenesis, proliferation, and clonogenic cancer stem cells (CSC). There is an expansion observed from purely metabolic-based PET imaging toward antibody-based PET to achieve more information on cancer characteristics to identify hypoxia, proangiogenic factors, CSC, and others. 64 Cu-ATSM, for example, can be used both as a hypoxia and a CSC marker. Progress in the field of functional imaging will possibly lead to more specific tumor targeting and personalized treatment, increasing tumor control and improving quality of life. Copyright © 2018 Elsevier Inc. All rights reserved.
Tetrazine ligation for chemical proteomics.
Kang, Kyungtae; Park, Jongmin; Kim, Eunha
2016-01-01
Determining small molecule-target protein interaction is essential for the chemical proteomics. One of the most important keys to explore biological system in chemical proteomics field is finding first-class molecular tools. Chemical probes can provide great spatiotemporal control to elucidate biological functions of proteins as well as for interrogating biological pathways. The invention of bioorthogonal chemistry has revolutionized the field of chemical biology by providing superior chemical tools and has been widely used for investigating the dynamics and function of biomolecules in live condition. Among 20 different bioorthogonal reactions, tetrazine ligation has been spotlighted as the most advanced bioorthogonal chemistry because of their extremely faster kinetics and higher specificity than others. Therefore, tetrazine ligation has a tremendous potential to enhance the proteomic research. This review highlights the current status of tetrazine ligation reaction as a molecular tool for the chemical proteomics.
Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy
2013-08-01
Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.
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...
Wang, Peng-Qian; Liu, Qiong; Xu, Wen-Juan; Yu, Ya-Nan; Zhang, Ying-Ying; Li, Bing; Liu, Jun; Wang, Zhong
2018-06-01
Both baicalin (BA) and jasminoidin (JA) are active ingredients in Chinese herb medicine Scutellaria baicalensis and Fructus gardeniae, respectively. They have been shown to exert additive neuroprotective action in ischemic stroke models. In this study we used transcriptome analysis to explore the pure therapeutic mechanisms of BA, JA and their combination (BJ) contributing to phenotype variation and reversal of pathological processes. Mice with middle cerebral artery obstruction were treated with BA, JA, their combination (BJ), or concha margaritifera (CM). Cerebral infarct volume was examined to determine the effect of these compounds on phenotype. Using the hippocampus microarray and ingenuity pathway analysis (IPA) software, we exacted the differentially expressed genes, networks, pathways, and functions in positive-phenotype groups (BA, JA and BJ) by comparing with the negative-phenotype group (CM). In the BA, JA, and BJ groups, a total of 7, 4, and 11 specific target molecules, 1, 1, and 4 networks, 51, 59, and 18 canonical pathways and 70, 53, and 64 biological functions, respectively, were identified. Pure therapeutic mechanisms of BA and JA were mainly overlapped in specific target molecules, functions and pathways, which were related to the nervous system, inflammation and immune response. The specific mechanisms of BA and JA were associated with apoptosis and cancer-related signaling and endocrine and hormone regulation, respectively. In the BJ group, novel target profiles distinct from mono-therapies were revealed, including 11 specific target molecules, 10 functions, and 10 pathways, the majority of which were related to a virus-mediated immune response. The pure additive effects between BA and JA were based on enhanced action in virus-mediated immune response. This pure mechanistic analysis may provide a clearer outline of the target profiles of multi-target compounds and combination therapies.
Fang, Yu; Feng, Mao; Han, Bin; Lu, Xiaoshan; Ramadan, Haitham; Li, Jianke
2014-09-01
Identifying proteome changes of honey bee embryogenesis is of prime importance for unraveling the molecular mechanisms that they underlie. However, many proteomic changes during the embryonic period are not well characterized. We analyzed the proteomic alterations over the complete time course of honey bee worker embryogenesis at 24, 48, and 72 h of age, using mass spectrometry-based proteomics, label-free quantitation, and bioinformatics. Of the 1460 proteins identified the embryo of all three ages, the core proteome (proteins shared by the embryos of all three ages, accounting for 40%) was mainly involved in protein synthesis, metabolic energy, development, and molecular transporter, which indicates their centrality in driving embryogenesis. However, embryos at different developmental stages have their own specific proteome and pathway signatures to coordinate and modulate developmental events. The young embryos (<24 h) stronger expression of proteins related to nutrition storage and nucleic acid metabolism may correlate with the cell proliferation occurring at this stage. The middle aged embryos (24-48 h) enhanced expression of proteins associated with cell cycle control, transporters, antioxidant activity, and the cytoskeleton suggest their roles to support rudimentary organogenesis. Among these proteins, the biological pathways of aminoacyl-tRNA biosynthesis, β-alanine metabolism, and protein export are intensively activated in the embryos of middle age. The old embryos (48-72 h) elevated expression of proteins implicated in fatty acid metabolism and morphogenesis indicate their functionality for the formation and development of organs and dorsal closure, in which the biological pathways of fatty acid metabolism and RNA transport are highly activated. These findings add novel understanding to the molecular details of honey bee embryogenesis, in which the programmed activation of the proteome matches with the physiological transition observed during embryogenesis. The identified biological pathways and key node proteins allow for further functional analysis and genetic manipulation for both the honey bee embryos and other eusocial insects. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
Saadatian-Elahi, Mitra; Aaby, Peter; Shann, Frank; Netea, Mihai G; Levy, Ofer; Louis, Jacques; Picot, Valentina; Greenberg, Michael; Warren, William
2016-07-25
The heterologous or non-specific effects (NSEs) of vaccines, at times defined as "off-target effects" suggest that they can affect the immune response to organisms other than their pathogen-specific intended purpose. These NSEs have been the subject of clinical, immunological and epidemiological studies and are increasingly recognized as an important biological process by a growing group of immunologists and epidemiologists. Much remain to be learned about the extent and underlying mechanisms for these effects. The conference "Off-target effects of vaccination" held in Annecy-France (June 8-10 2015) intended to take a holistic approach drawing from the fields of immunology, systems biology, epidemiology, bioinformatics, public health and regulatory science to address fundamental questions of immunological mechanisms, as well as translational questions about vaccines NSEs. NSE observations were examined using case-studies on live attenuated vaccines and non-live vaccines followed by discussion of studies of possible biological mechanisms. Some possible pathways forward in the study of vaccines NSE were identified and discussed by the expert group. Copyright © 2016.
Neurovascular patterning cues and implications for central and peripheral neurological disease
Gamboa, Nicholas T.; Taussky, Philipp; Park, Min S.; Couldwell, William T.; Mahan, Mark A.; Kalani, M. Yashar S.
2017-01-01
The highly branched nervous and vascular systems run along parallel trajectories throughout the human body. This stereotyped pattern of branching shared by the nervous and vascular systems stems from a common reliance on specific cues critical to both neurogenesis and angiogenesis. Continually emerging evidence supports the notion of later-evolving vascular networks co-opting neural molecular mechanisms to ensure close proximity and adequate delivery of oxygen and nutrients to nervous tissue. As our understanding of these biologic pathways and their phenotypic manifestations continues to advance, identification of where pathways go awry will provide critical insight into central and peripheral nervous system pathology. PMID:28966815
Dal Pra, Alan; Locke, Jennifer A.; Borst, Gerben; Supiot, Stephane; Bristow, Robert G.
2016-01-01
Radiation therapy (RT) is one of the mainstay treatments for prostate cancer (PCa). The potentially curative approaches can provide satisfactory results for many patients with non-metastatic PCa; however, a considerable number of individuals may present disease recurrence and die from the disease. Exploiting the rich molecular biology of PCa will provide insights into how the most resistant tumor cells can be eradicated to improve treatment outcomes. Important for this biology-driven individualized treatment is a robust selection procedure. The development of predictive biomarkers for RT efficacy is therefore of utmost importance for a clinically exploitable strategy to achieve tumor-specific radiosensitization. This review highlights the current status and possible opportunities in the modulation of four key processes to enhance radiation response in PCa by targeting the: (1) androgen signaling pathway; (2) hypoxic tumor cells and regions; (3) DNA damage response (DDR) pathway; and (4) abnormal extra-/intracell signaling pathways. In addition, we discuss how and which patients should be selected for biomarker-based clinical trials exploiting and validating these targeted treatment strategies with precision RT to improve cure rates in non-indolent, localized PCa. PMID:26909338
NASA Astrophysics Data System (ADS)
Baya, P. A.; Point, D.; Amouroux, D. P.; Lebreton, B.; Guillou, G.
2015-12-01
Methylmercury (CH3Hg) is a potent neurotoxin which is readily assimilated by organisms and bio-accumulates in aquatic food webs. In humans, consumption of CH3Hg contaminated marine fish is the major route of mercury exposure. However, our understanding of CH3Hg transformation pathways is still incomplete. To close this knowledge gap, we propose to explore the stable carbon isotopic composition (δ13C) of the methyl group of CH3Hg for a better understanding of its sources and transformation mechanisms. The method developed for the determination of the δ13C value of CH3Hg in biological samples involves (i) CH3Hg selective extraction, (ii) derivatization, and (iii) separation by gas chromatography (GC) prior to analysis by combustion isotope ratio mass spectrometry (C-IRMS). We present the figures of merit of this novel method and the first δ13C signatures for certified materials (ERM-CE464, BCR414) and biological samples at different marine trophic levels (i.e., tuna fish, zooplankton). The implications of this new approach to trace the pathways associated with Hg methylation and the mechanisms involved will be discussed.
Asthma pharmacogenetics and the development of genetic profiles for personalized medicine
Ortega, Victor E; Meyers, Deborah A; Bleecker, Eugene R
2015-01-01
Human genetics research will be critical to the development of genetic profiles for personalized or precision medicine in asthma. Genetic profiles will consist of gene variants that predict individual disease susceptibility and risk for progression, predict which pharmacologic therapies will result in a maximal therapeutic benefit, and predict whether a therapy will result in an adverse response and should be avoided in a given individual. Pharmacogenetic studies of the glucocorticoid, leukotriene, and β2-adrenergic receptor pathways have focused on candidate genes within these pathways and, in addition to a small number of genome-wide association studies, have identified genetic loci associated with therapeutic responsiveness. This review summarizes these pharmacogenetic discoveries and the future of genetic profiles for personalized medicine in asthma. The benefit of a personalized, tailored approach to health care delivery is needed in the development of expensive biologic drugs directed at a specific biologic pathway. Prior pharmacogenetic discoveries, in combination with additional variants identified in future studies, will form the basis for future genetic profiles for personalized tailored approaches to maximize therapeutic benefit for an individual asthmatic while minimizing the risk for adverse events. PMID:25691813
Presenilin-Based Genetic Screens in Drosophila melanogaster Identify Novel Notch Pathway Modifiers
Mahoney, Matt B.; Parks, Annette L.; Ruddy, David A.; Tiong, Stanley Y. K.; Esengil, Hanife; Phan, Alexander C.; Philandrinos, Panos; Winter, Christopher G.; Chatterjee, Runa; Huppert, Kari; Fisher, William W.; L'Archeveque, Lynn; Mapa, Felipa A.; Woo, Wendy; Ellis, Michael C.; Curtis, Daniel
2006-01-01
Presenilin is the enzymatic component of γ-secretase, a multisubunit intramembrane protease that processes several transmembrane receptors, such as the amyloid precursor protein (APP). Mutations in human Presenilins lead to altered APP cleavage and early-onset Alzheimer's disease. Presenilins also play an essential role in Notch receptor cleavage and signaling. The Notch pathway is a highly conserved signaling pathway that functions during the development of multicellular organisms, including vertebrates, Drosophila, and C. elegans. Recent studies have shown that Notch signaling is sensitive to perturbations in subcellular trafficking, although the specific mechanisms are largely unknown. To identify genes that regulate Notch pathway function, we have performed two genetic screens in Drosophila for modifiers of Presenilin-dependent Notch phenotypes. We describe here the cloning and identification of 19 modifiers, including nicastrin and several genes with previously undescribed involvement in Notch biology. The predicted functions of these newly identified genes are consistent with extracellular matrix and vesicular trafficking mechanisms in Presenilin and Notch pathway regulation and suggest a novel role for γ-tubulin in the pathway. PMID:16415372
Presenilin-based genetic screens in Drosophila melanogaster identify novel notch pathway modifiers.
Mahoney, Matt B; Parks, Annette L; Ruddy, David A; Tiong, Stanley Y K; Esengil, Hanife; Phan, Alexander C; Philandrinos, Panos; Winter, Christopher G; Chatterjee, Runa; Huppert, Kari; Fisher, William W; L'Archeveque, Lynn; Mapa, Felipa A; Woo, Wendy; Ellis, Michael C; Curtis, Daniel
2006-04-01
Presenilin is the enzymatic component of gamma-secretase, a multisubunit intramembrane protease that processes several transmembrane receptors, such as the amyloid precursor protein (APP). Mutations in human Presenilins lead to altered APP cleavage and early-onset Alzheimer's disease. Presenilins also play an essential role in Notch receptor cleavage and signaling. The Notch pathway is a highly conserved signaling pathway that functions during the development of multicellular organisms, including vertebrates, Drosophila, and C. elegans. Recent studies have shown that Notch signaling is sensitive to perturbations in subcellular trafficking, although the specific mechanisms are largely unknown. To identify genes that regulate Notch pathway function, we have performed two genetic screens in Drosophila for modifiers of Presenilin-dependent Notch phenotypes. We describe here the cloning and identification of 19 modifiers, including nicastrin and several genes with previously undescribed involvement in Notch biology. The predicted functions of these newly identified genes are consistent with extracellular matrix and vesicular trafficking mechanisms in Presenilin and Notch pathway regulation and suggest a novel role for gamma-tubulin in the pathway.
Animal models of contraception: utility and limitations
Liechty, Emma R; Bergin, Ingrid L; Bell, Jason D
2015-01-01
Appropriate animal modeling is vital for the successful development of novel contraceptive devices. Advances in reproductive biology have identified novel pathways for contraceptive intervention. Here we review species-specific anatomic and physiologic considerations impacting preclinical contraceptive testing, including efficacy testing, mechanistic studies, device design, and modeling off-target effects. Emphasis is placed on the use of nonhuman primate models in contraceptive device development. PMID:29386922
Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane
2017-09-13
The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.
[Advance in flavonoids biosynthetic pathway and synthetic biology].
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.
The emerging genomics and systems biology research lead to systems genomics studies.
Yang, Mary Qu; Yoshigoe, Kenji; Yang, William; Tong, Weida; Qin, Xiang; Dunker, A; Chen, Zhongxue; Arbania, Hamid R; Liu, Jun S; Niemierko, Andrzej; Yang, Jack Y
2014-01-01
Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes, MBC is further utilizing differential gene and isoform/exon expression from RNA-seq and co-regulation from the ChiP-seq specific for different phenotypes in combination with protein-protein interactions, and protein-DNA interactions to construct high-level gene networks for an integrative genome-phoneme investigation at systems biology level.
Bayesian parameter estimation for nonlinear modelling of biological pathways.
Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang
2011-01-01
The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.
Quantification of growth factor signaling and pathway cross talk by live-cell imaging.
Gross, Sean M; Rotwein, Peter
2017-03-01
Peptide growth factors stimulate cellular responses through activation of their transmembrane receptors. Multiple intracellular signaling cascades are engaged following growth factor-receptor binding, leading to short- and long-term biological effects. Each receptor-activated signaling pathway does not act in isolation but rather interacts at different levels with other pathways to shape signaling networks that are distinctive for each growth factor. To gain insights into the specifics of growth factor-regulated interactions among different signaling cascades, we developed a HeLa cell line stably expressing fluorescent live-cell imaging reporters that are readouts for two major growth factor-stimulated pathways, Ras-Raf-Mek-ERK and phosphatidylinositol (PI) 3-kinase-Akt. Incubation of cells with epidermal growth factor (EGF) resulted in rapid, robust, and sustained ERK signaling but shorter-term activation of Akt. In contrast, hepatocyte growth factor induced sustained Akt signaling but weak and short-lived ERK activity, and insulin-like growth factor-I stimulated strong long-term Akt responses but negligible ERK signaling. To address potential interactions between signaling pathways, we employed specific small-molecule inhibitors. In cells incubated with EGF or platelet-derived growth factor-AA, Raf activation and the subsequent stimulation of ERK reduced Akt signaling, whereas Mek inhibition, which blocked ERK activation, enhanced Akt and turned transient effects into sustained responses. Our results reveal that individual growth factors initiate signaling cascades that vary markedly in strength and duration and demonstrate in living cells the dramatic effects of cross talk from Raf and Mek to PI 3-kinase and Akt. Our data further indicate how specific growth factors can encode distinct cellular behaviors by promoting complex interactions among signaling pathways. Copyright © 2017 the American Physiological Society.
Quantification of growth factor signaling and pathway cross talk by live-cell imaging
Gross, Sean M.
2017-01-01
Peptide growth factors stimulate cellular responses through activation of their transmembrane receptors. Multiple intracellular signaling cascades are engaged following growth factor–receptor binding, leading to short- and long-term biological effects. Each receptor-activated signaling pathway does not act in isolation but rather interacts at different levels with other pathways to shape signaling networks that are distinctive for each growth factor. To gain insights into the specifics of growth factor-regulated interactions among different signaling cascades, we developed a HeLa cell line stably expressing fluorescent live-cell imaging reporters that are readouts for two major growth factor-stimulated pathways, Ras–Raf–Mek–ERK and phosphatidylinositol (PI) 3-kinase–Akt. Incubation of cells with epidermal growth factor (EGF) resulted in rapid, robust, and sustained ERK signaling but shorter-term activation of Akt. In contrast, hepatocyte growth factor induced sustained Akt signaling but weak and short-lived ERK activity, and insulin-like growth factor-I stimulated strong long-term Akt responses but negligible ERK signaling. To address potential interactions between signaling pathways, we employed specific small-molecule inhibitors. In cells incubated with EGF or platelet-derived growth factor-AA, Raf activation and the subsequent stimulation of ERK reduced Akt signaling, whereas Mek inhibition, which blocked ERK activation, enhanced Akt and turned transient effects into sustained responses. Our results reveal that individual growth factors initiate signaling cascades that vary markedly in strength and duration and demonstrate in living cells the dramatic effects of cross talk from Raf and Mek to PI 3-kinase and Akt. Our data further indicate how specific growth factors can encode distinct cellular behaviors by promoting complex interactions among signaling pathways. PMID:28100485
Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics
2009-01-01
Background The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language. Results Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components (e.g., MEK-PP, Ras-GTP), and negative feedback loops that help promote signal adaptation and stabilization. Conclusions The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks. PMID:20028552
Lan, Daoliang; Xiong, Xianrong; Huang, Cai; Mipam, Tserang Donko; Li, Jian
2016-01-01
Yaks (Bos grunniens) are endemic species that can adapt well to thin air, cold temperatures, and high altitude. These species can survive in harsh plateau environments and are major source of animal production for local residents, being an important breed in the Qinghai-Tibet Plateau. However, compared with ordinary cattle that live in the plains, yaks generally have lower fertility. Investigating the basic physiological molecular features of yak ovary and identifying the biological events underlying the differences between the ovaries of yak and plain cattle is necessary to understand the specificity of yak reproduction. Therefore, RNA-seq technology was applied to analyze transcriptome data comparatively between the yak and plain cattle estrous ovaries. After deep sequencing, 3,653,032 clean reads with a total of 4,828,772,880 base pairs were obtained from yak ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome, among which, 12,731 and 14,631 genes were assigned to Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, comparison of yak and cattle ovary transcriptome data revealed that 1307 genes were significantly and differentially expressed between the two libraries, wherein 661 genes were upregulated and 646 genes were downregulated in yak ovary. Functional analysis showed that the differentially expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. GO annotations indicated that the genes related to "cell adhesion," "hormonal" biological processes, and "calcium ion binding," "cation transmembrane transport" molecular events were significantly active. KEGG pathway analysis showed that the "complement and coagulation cascade" pathway was the most enriched in yak ovary transcriptome data, followed by the "cytochrome P450" related and "ECM-receptor interaction" pathways. Moreover, several novel pathways, such as "circadian rhythm," were significantly enriched despite having no evident associations with the reproductive function. Our findings provide a molecular resource for further investigation of the general molecular mechanism of yak ovary and offer new insights to understand comprehensively the specificity of yak reproduction.
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.
Inference of Evolutionary Forces Acting on Human Biological Pathways
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
Genetic and pharmacological suppression of oncogenic mutations in RAS genes of yeast and humans
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schafer, W.R.; Sterne, R.; Thorner, J.
1989-07-28
The activity of an oncoprotein and the secretion of a pheromone can be affected by an unusual protein modification. Specifically, posttranslational modification of yeast-a-factor and Ras protein requires an intermediate of the cholesterol biosynthetic pathway. This modification is apparently essential for biological activity. Studies of yeast mutants blocked in sterol biosynthesis demonstrated that the membrane association and biological activation of the yeast Ras2 protein require mevalonate, a precursor of sterols and other isoprenes such as farnesyl pyrophosphate. Furthermore, drugs that inhibit mevalonate biosynthesis blocked the in vivo action of oncogenic derivatives of human Ras protein in the Xenopus oocyte assay.more » The same drugs and mutations also prevented the posttranslational processing and secretion of yeast a-factor, a peptide that is farnesylated. Thus, the mevalonate requirement for Ras activation may indicate that attachment of a mevalonate-derived (isoprenoid) moiety to Ras proteins is necessary for membrane association and biological function. These observations establish a connection between the cholesterol biosynthetic pathway and transformation by the ras oncogene and offer a novel pharmacological approach to investigating, and possibly controlling, ras-mediated malignant transformations. 50 refs., 3 figs., 3 tabs.« less
Pathophysiologic mechanisms of biomedical nanomaterials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Liming, E-mail: wangliming@ihep.ac.cn; Chen, Chunying, E-mail: chenchy@nanoctr.cn
Nanomaterials (NMs) have been widespread used in biomedical fields, daily consuming, and even food industry. It is crucial to understand the safety and biomedical efficacy of NMs. In this review, we summarized the recent progress about the physiological and pathological effects of NMs from several levels: protein-nano interface, NM-subcellular structures, and cell–cell interaction. We focused on the detailed information of nano-bio interaction, especially about protein adsorption, intracellular trafficking, biological barriers, and signaling pathways as well as the associated mechanism mediated by nanomaterials. We also introduced related analytical methods that are meaningful and helpful for biomedical effect studies in the future.more » We believe that knowledge about pathophysiologic effects of NMs is not only significant for rational design of medical NMs but also helps predict their safety and further improve their applications in the future. - Highlights: • Rapid protein adsorption onto nanomaterials that affects biomedical effects • Nanomaterials and their interaction with biological membrane, intracellular trafficking and specific cellular effects • Nanomaterials and their interaction with biological barriers • The signaling pathways mediated by nanomaterials and related biomedical effects • Novel techniques for studying translocation and biomedical effects of NMs.« less
PDGF-C is an EWS/FLI induced transforming growth factor in Ewing Family Tumors
Zwerner, Jeffrey P.; May, William A.
2013-01-01
The aberrant transcription factors associated with many human malignancies function by deregulation of tumorigenic pathways. However, identification of these pathways has come slowly. Virtually all cases of Ewing’s Sarcoma and peripheral Primitive Neuroectodermal Tumor (PNET) are associated with aberrant transcription factors which fuse amino-terminal EWS with the DNA binding moiety of an ETS transcription factor (FLI-1 in 90% of cases). Attempts to identify the downstream targets of these chimeras in the Ewing Family Tumors (EFT) on the basis of differential gene regulation have produced little association with tumor biology. As an alternative approach, we have used highly efficient retroviral systems to biologically screen cDNA derived from cells transformed by EWS/FLI-1. We have identified the recently described PDGF-C as target of EWS/ETS transcriptional deregulation. This transcriptional deregulation is specific to EWS/FLI. PDGF-C possesses substantial biologic activity in vitro and in vivo. It is expressed in EFT cell lines and in primary tumors. Within these EFT cell lines, PDGF-C expression is dependent upon EWS/FLI activity. These results suggest that PDGF-C may be a significant mediator of EWS/FLI driven oncogenesis. PMID:11313995
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
Pathway Distiller - multisource biological pathway consolidation
2012-01-01
Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636
Pathway Distiller - multisource biological pathway consolidation.
Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong
2012-01-01
One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.
Tissue-specific tumorigenesis – Context matters
Schneider, Günter; Schmidt-Supprian, Marc; Rad, Roland; Saur, Dieter
2018-01-01
Preface How can we treat cancer more effectively? Traditionally, tumours from the same anatomical site are treated as one tumour entity. This concept has been challenged by recent breakthroughs in cancer genomics and translational research enabling molecular tumour profiling. The identification and validation of cancer drivers, which are shared between different tumour types, spurred the new paradigm to target driver pathways across anatomical sites by off-label drug use, or within so called “basket or umbrella trials”, which are designed to test whether molecular alterations in one tumour entity can be extrapolated to all others. However, recent clinical and preclinical studies suggest that there are tissue- and cell type-specific differences in tumourigenesis and the organization of oncogenic signalling pathways. In this Opinion article, we focus on the molecular, cellular, systemic and environmental determinants of organ-specific tumourigenesis and mechanisms of context-specific oncogenic signalling outputs. Investigation, recognition and in-depth biological understanding of these differences will be vital for the design of next-generation clinical trials and the implementation of molecularly-guided cancer therapies in the future. PMID:28256574
An overview of transcriptional regulation in response to toxicological insult.
Jennings, Paul; Limonciel, Alice; Felice, Luca; Leonard, Martin O
2013-01-01
The completion of the human genome project and the subsequent advent of DNA microarray and high-throughput sequencing technologies have led to a renaissance in molecular toxicology. Toxicogenomic data sets, from both in vivo and in vitro studies, are growing exponentially, providing a wealth of information on regulation of stress pathways at the transcriptome level. Through such studies, we are now beginning to appreciate the diversity and complexity of biological responses to xenobiotics. In this review, we aim to consolidate and summarise the major toxicologically relevant transcription factor-governed molecular pathways. It is becoming clear that different chemical entities can cause oxidative, genotoxic and proteotoxic stress, which induce cellular responses in an effort to restore homoeostasis. Primary among the response pathways involved are NFE2L2 (Nrf2), NFE2L1 (Nrf1), p53, heat shock factor and the unfolded protein response. Additionally, more specific mechanisms exist where xenobiotics act as ligands, including the aryl hydrocarbon receptor, metal-responsive transcription factor-1 and the nuclear receptor family of transcription factors. Other pathways including the immunomodulatory transcription factors NF-κB and STAT together with the hypoxia-inducible transcription factor HIF are also implicated in cellular responses to xenobiotic exposure. A less specific but equally important aspect to cellular injury controlled by transcriptional activity is loss of tissue-specific gene expression, resulting in dedifferentiation of target cells and compromise of tissue function. Here, we review these pathways and the genes they regulate in order to provide an overview of this growing field of molecular toxicology.
Emerging molecular phenotypes of asthma
Ray, Anuradha; Oriss, Timothy B.
2014-01-01
Although asthma has long been considered a heterogeneous disease, attempts to define subgroups of asthma have been limited. In recent years, both clinical and statistical approaches have been utilized to better merge clinical characteristics, biology, and genetics. These combined characteristics have been used to define phenotypes of asthma, the observable characteristics of a patient determined by the interaction of genes and environment. Identification of consistent clinical phenotypes has now been reported across studies. Now the addition of various 'omics and identification of specific molecular pathways have moved the concept of clinical phenotypes toward the concept of molecular phenotypes. The importance of these molecular phenotypes is being confirmed through the integration of molecularly targeted biological therapies. Thus the global term asthma is poised to become obsolete, being replaced by terms that more specifically identify the pathology associated with the disease. PMID:25326577
Scarlatti, Francesca; Sala, Giusy; Somenzi, Giulia; Signorelli, Paola; Sacchi, Nicoletta; Ghidoni, Riccardo
2003-12-01
Resveratrol (3,4',5-trans-trihydroxystilbene), a phytoalexin present in grapes and red wine, is emerging as a natural compound with potential anticancer properties. Here we show that resveratrol can induce growth inhibition and apoptosis in MDA-MB-231, a highly invasive and metastatic breast cancer cell line, in concomitance with a dramatic endogenous increase of growth inhibitory/proapoptotic ceramide. We found that accumulation of ceramide derives from both de novo ceramide synthesis and sphingomyelin hydrolysis. More specifically we demonstrated that ceramide accumulation induced by resveratrol can be traced to the activation of serine palmitoyltransferase (SPT), the key enzyme of de novo ceramide biosynthetic pathway, and neutral sphingomyelinase (nSMase), a main enzyme involved in the sphingomyelin/ceramide pathway. However, by using specific inhibitors of SPT, myriocin and L-cycloserine, and nSMase, gluthatione and manumycin, we found that only the SPT inhibitors could counteract the biological effects induced by resveratrol. Thus, resveratrol seems to exert its growth inhibitory/apoptotic effect on the metastatic breast cancer cell line MDA-MB-231 by activating the de novo ceramide synthesis pathway.
Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J
2016-01-01
Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).
Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.
Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R
2018-06-07
Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.
Biological profiling and dose-response modeling tools ...
Through its ToxCast project, the U.S. EPA has developed a battery of in vitro high throughput screening (HTS) assays designed to assess the potential toxicity of environmental chemicals. At present, over 1800 chemicals have been tested in up to 600 assays, yielding a large number of concentration-response data sets. Standard processing of these data sets involves finding a best fitting mathematical model and set of model parameters that specify this model. The model parameters include quantities such as the half-maximal activity concentration (or “AC50”) that have biological significance and can be used to inform the efficacy or potency of a given chemical with respect to a given assay. All of this data is processed and stored in an online-accessible database and website: http://actor.epa.gov/dashboard2. Results from these in vitro assays are used in a multitude of ways. New pathways and targets can be identified and incorporated into new or existing adverse outcome pathways (AOPs). Pharmacokinetic models such as those implemented EPA’s HTTK R package can be used to translate an in vitro concentration into an in vivo dose; i.e., one can predict the oral equivalent dose that might be expected to activate a specific biological pathway. Such predicted values can then be compared with estimated actual human exposures prioritize chemicals for further testing.Any quantitative examination should be accompanied by estimation of uncertainty. We are developing met
Quantitative trait loci and metabolic pathways
McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.
1998-01-01
The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823
Lipidomics of oxidized polyunsaturated fatty acids
Massey, Karen A.; Nicolaou, Anna
2013-01-01
Lipid mediators are produced from the oxidation of polyunsaturated fatty acids through enzymatic and free radical-mediated reactions. When subject to oxygenation via cyclooxygenases, lipoxygenases, and cytochrome P450 monooxygenases, polyunsaturated fatty acids give rise to an array of metabolites including eicosanoids, docosanoids, and octadecanoids. These potent bioactive lipids are involved in many biochemical and signaling pathways, with inflammation being of particular importance. Moreover, because they are produced by more than one pathway and substrate, and are present in a variety of biological milieus, their analysis is not always possible with conventional assays. Liquid chromatography coupled to electrospray mass spectrometry offers a versatile and sensitive approach for the analysis of bioactive lipids, allowing specific and accurate quantitation of multiple species present in the same sample. Here we explain the principles of this approach to mediator lipidomics and present detailed protocols for the assay of enzymatically produced oxygenated metabolites of polyunsaturated fatty acids that can be tailored to answer biological questions or facilitate assessment of nutritional and pharmacological interventions. PMID:22940496
Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming
2009-01-01
Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators. PMID:19851479
Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming
2009-01-01
Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators.
All-atom molecular dynamics of virus capsids as drug targets
Perilla, Juan R.; Hadden, Jodi A.; Goh, Boon Chong; ...
2016-04-29
Virus capsids are protein shells that package the viral genome. Although their morphology and biological functions can vary markedly, capsids often play critical roles in regulating viral infection pathways. A detailed knowledge of virus capsids, including their dynamic structure, interactions with cellular factors, and the specific roles that they play in the replication cycle, is imperative for the development of antiviral therapeutics. The following Perspective introduces an emerging area of computational biology that focuses on the dynamics of virus capsids and capsid–protein assemblies, with particular emphasis on the effects of small-molecule drug binding on capsid structure, stability, and allosteric pathways.more » When performed at chemical detail, molecular dynamics simulations can reveal subtle changes in virus capsids induced by drug molecules a fraction of their size. Finally, the current challenges of performing all-atom capsid–drug simulations are discussed, along with an outlook on the applicability of virus capsid simulations to reveal novel drug targets.« less
Pneumaticos, Spyros G; Triantafyllopoulos, Georgios K; Basdra, Efthimia K; Papavassiliou, Athanasios G
2010-01-01
Abstract Several conditions in clinical orthopaedic practice can lead to the development of a diaphyseal segmental bone defect, which cannot heal without intervention. Segmental bone defects have been traditionally treated with bone grafting and/or distraction osteogenesis, methods that have many advantages, but also major drawbacks, such as limited availability, risk of disease transmission and prolonged treatment. In order to overcome such limitations, biological treatments have been developed based on specific pathways of bone physiology and healing. Bone tissue engineering is a dynamic field of research, combining osteogenic cells, osteoinductive factors, such as bone morphogenetic proteins, and scaffolds with osteoconductive and osteoinductive attributes, to produce constructs that could be used as bone graft substitutes for the treatment of segmental bone defects. Scaffolds are usually made of ceramic or polymeric biomaterials, or combinations of both in composite materials. The purpose of the present review is to discuss in detail the molecular and cellular basis for the development of bone tissue engineering constructs. PMID:20345845
EML4-ALK Variants: Biological and Molecular Properties, and the Implications for Patients
Yeoh, Sharon; Jackson, George
2017-01-01
Since the discovery of the fusion between EML4 (echinoderm microtubule associated protein-like 4) and ALK (anaplastic lymphoma kinase), EML4-ALK, in lung adenocarcinomas in 2007, and the subsequent identification of at least 15 different variants in lung cancers, there has been a revolution in molecular-targeted therapy that has transformed the outlook for these patients. Our recent focus has been on understanding how and why the expression of particular variants can affect biological and molecular properties of cancer cells, as well as identifying the key signalling pathways triggered, as a result. In the clinical setting, this understanding led to the discovery that the type of variant influences the response of patients to ALK therapy. Here, we discuss what we know so far about the EML4-ALK variants in molecular signalling pathways and what questions remain to be answered. In the longer term, this analysis may uncover ways to specifically treat patients for a better outcome. PMID:28872581
EML4-ALK Variants: Biological and Molecular Properties, and the Implications for Patients.
Sabir, Sarah R; Yeoh, Sharon; Jackson, George; Bayliss, Richard
2017-09-05
Since the discovery of the fusion between EML4 (echinoderm microtubule associated protein-like 4) and ALK (anaplastic lymphoma kinase), EML4-ALK, in lung adenocarcinomas in 2007, and the subsequent identification of at least 15 different variants in lung cancers, there has been a revolution in molecular-targeted therapy that has transformed the outlook for these patients. Our recent focus has been on understanding how and why the expression of particular variants can affect biological and molecular properties of cancer cells, as well as identifying the key signalling pathways triggered, as a result. In the clinical setting, this understanding led to the discovery that the type of variant influences the response of patients to ALK therapy. Here, we discuss what we know so far about the EML4-ALK variants in molecular signalling pathways and what questions remain to be answered. In the longer term, this analysis may uncover ways to specifically treat patients for a better outcome.
All-atom molecular dynamics of virus capsids as drug targets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perilla, Juan R.; Hadden, Jodi A.; Goh, Boon Chong
Virus capsids are protein shells that package the viral genome. Although their morphology and biological functions can vary markedly, capsids often play critical roles in regulating viral infection pathways. A detailed knowledge of virus capsids, including their dynamic structure, interactions with cellular factors, and the specific roles that they play in the replication cycle, is imperative for the development of antiviral therapeutics. The following Perspective introduces an emerging area of computational biology that focuses on the dynamics of virus capsids and capsid–protein assemblies, with particular emphasis on the effects of small-molecule drug binding on capsid structure, stability, and allosteric pathways.more » When performed at chemical detail, molecular dynamics simulations can reveal subtle changes in virus capsids induced by drug molecules a fraction of their size. Finally, the current challenges of performing all-atom capsid–drug simulations are discussed, along with an outlook on the applicability of virus capsid simulations to reveal novel drug targets.« less
Vrahatis, Aristidis G; Balomenos, Panos; Tsakalidis, Athanasios K; Bezerianos, Anastasios
2016-12-15
DEsubs is a network-based systems biology R package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the subpathway analysis, enabling so a case-specific approach. The operation modes include pathway network construction and processing, subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render DEsubs a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level drug targets and biomarkers for complex diseases. DEsubs is implemented as an R package following Bioconductor guidelines: http://bioconductor.org/packages/DEsubs/ CONTACT: tassos.bezerianos@nus.edu.sgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
New insights about host response to smallpox using microarray data.
Esteves, Gustavo H; Simoes, Ana C Q; Souza, Estevao; Dias, Rodrigo A; Ospina, Raydonal; Venancio, Thiago M
2007-08-24
Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems.
Stellar, Jennifer E; John-Henderson, Neha; Anderson, Craig L; Gordon, Amie M; McNeil, Galen D; Keltner, Dacher
2015-04-01
Negative emotions are reliably associated with poorer health (e.g., Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002), but only recently has research begun to acknowledge the important role of positive emotions for our physical health (Fredrickson, 2003). We examine the link between dispositional positive affect and one potential biological pathway between positive emotions and health-proinflammatory cytokines, specifically levels of interleukin-6 (IL-6). We hypothesized that greater trait positive affect would be associated with lower levels of IL-6 in a healthy sample. We found support for this hypothesis across two studies. We also explored the relationship between discrete positive emotions and IL-6 levels, finding that awe, measured in two different ways, was the strongest predictor of lower levels of proinflammatory cytokines. These effects held when controlling for relevant personality and health variables. This work suggests a potential biological pathway between positive emotions and health through proinflammatory cytokines. (c) 2015 APA, all rights reserved).
Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila
2016-10-20
The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.
2-Keto acids based biosynthesis pathways for renewable fuels and chemicals.
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.
Rager, Julia E.; Yosim, Andrew; Fry, Rebecca C.
2014-01-01
There is increasing evidence that environmental agents mediate susceptibility to infectious disease. Studies support the impact of prenatal/early life exposure to the environmental metals inorganic arsenic (iAs) and cadmium (Cd) on increased risk for susceptibility to infection. The specific biological mechanisms that underlie such exposure-mediated effects remain understudied. This research aimed to identify key genes/signal transduction pathways that associate prenatal exposure to these toxic metals with changes in infectious disease susceptibility using a Comparative Genomic Enrichment Method (CGEM). Using CGEM an infectious disease gene (IDG) database was developed comprising 1085 genes with known roles in viral, bacterial, and parasitic disease pathways. Subsequently, datasets collected from human pregnancy cohorts exposed to iAs or Cd were examined in relationship to the IDGs, specifically focusing on data representing epigenetic modifications (5-methyl cytosine), genomic perturbations (mRNA expression), and proteomic shifts (protein expression). A set of 82 infection and exposure-related genes was identified and found to be enriched for their role in the glucocorticoid receptor signal transduction pathway. Given their common identification across numerous human cohorts and their known toxicological role in disease, the identified genes within the glucocorticoid signal transduction pathway may underlie altered infectious disease susceptibility associated with prenatal exposures to the toxic metals iAs and Cd in humans. PMID:25479081
Mijatovic, Tatjana; Kiss, Robert
2013-03-01
Many cancer patients fail to respond to chemotherapy because of the intrinsic resistance of their cancer to pro-apoptotic stimuli or the acquisition of the multidrug resistant phenotype during chronic treatment. Previous data from our groups and from others point to the sodium/potassium pump (the Na+/K+-ATPase, i.e., NaK) with its highly specific ligands (i.e., cardiotonic steroids) as a new target for combating cancers associated with dismal prognoses, including gliomas, melanomas, non-small cell lung cancers, renal cell carcinomas, and colon cancers. Cardiotonic steroid-mediated Na+/K+-ATPase targeting could circumvent various resistance pathways. The most probable pathways include the involvement of Na+/K+-ATPase β subunits in invasion features and Na+/K+-ATPase α subunits in chemosensitisation by specific cardiotonic steroid-mediated apoptosis and anoïkis-sensitisation; the regulation of the expression of multidrug resistant-related genes; post-translational regulation, including glycosylation and ubiquitinylation of multidrug resistant-related proteins; c-Myc downregulation; hypoxia-inducible factor downregulation; NF-κB downregulation and deactivation; the inhibition of the glycolytic pathway with a reduction of intra-cellular ATP levels and an induction of non-apoptotic cell death. The aims of this review are to examine the various molecular pathways by which the NaK targeting can be more deleterious to biologically aggressive cancer cells than to normal cells. Georg Thieme Verlag KG Stuttgart · New York.
Targeting death receptors to fight cancer: from biological rational to clinical implementation.
Mocellin, S
2010-01-01
Considering that most currently available chemotherapeutic drugs work by inducing cell apoptosis, it is not surprising that many expectations in cancer research come from the therapeutic exploitation of the naturally occurring death pathways. Receptor mediated apoptosis depends upon the engagement of specific ligands with their respective membrane receptors and - within the frame of complex regulatory networks - modulates some key physiological and pathological processes such as lymphocyte survival, inflammation and infectious diseases. A pivotal observation was that some of these pathways may be over activated in cancer under particular circumstances, which opened the avenue for tumor-specific therapeutic interventions. Although one death-related ligand (e.g., tumor necrosis factor, TNF) is currently the basis of effective anticancer regimens in the clinical setting, the systemic toxicity is hampering its wide therapeutic exploitation. However, strategies to split the therapeutic from the toxic TNF activity are being devised. Furthermore, other death receptor pathways (e.g., Fas/FasL, TRAIL/TRAIL receptor) are being intensively investigated in order to therapeutically exploit their activity against cancer. This article summarizes the current knowledge on the molecular features of death receptor pathways that make them an attractive target for anticancer therapeutics. In addition, the results so far obtained in the clinical oncology setting as well as the issues to be faced while interfering with these pathways for therapeutic purposes will be overviewed.
Campbell, Iain L
2005-04-01
Cytokines are plurifunctional mediators of cellular communication. The CNS biology of this family of molecules has been explored by transgenic approaches that targeted the expression of individual cytokine genes to specific cells in the CNS of mice. Such transgenic animals exhibit wide-ranging structural and functional alterations that are linked to the development of distinct neuroinflammatory responses and gene expression profiles specific for each cytokine. The unique actions of individual cytokines result from the activation of specific receptor-coupled cellular signal transduction pathways such as the JAK/STAT tyrosine kinase signaling cascade. The cerebral expression of various STATs, their activation, as well as that of the major physiological inhibitors of this pathway, SOCS1 and SOCS3, is highly regulated in a stimulus- and cell-specific fashion. The role of the key IFN signaling molecules STAT1 or STAT2 was studied in transgenic mice (termed GIFN) with astrocyte-production of IFN-alpha that were null or haploinsufficient for these STAT genes. Surprisingly, these animals developed either more severe and accelerated neurodegeneration with calcification and inflammation (GIFN/STAT1 deficient) or severe immunoinflammation and medulloblastoma (GIFN/STAT2 deficient). STAT dysregulation may result in a signal switch phenomenon in which one cytokine acquires the apparent function of an entirely different cytokine. Therefore, for cytokines such as the IFNs, the receptor-coupled signaling process is complex, involving the coexistence of multiple JAK/STAT as well as alternative pathways. The cellular compartmentalization and balance in the activity of these pathways ultimately determines the repertoire and nature of CNS cytokine actions.
Assembling the Puzzle: Pathways of Oxytocin Signaling in the Brain.
Grinevich, Valery; Knobloch-Bollmann, H Sophie; Eliava, Marina; Busnelli, Marta; Chini, Bice
2016-02-01
Oxytocin (OT) is a neuropeptide, which can be seen to be one of the molecules of the decade due to its profound prosocial effects in nonvertebrate and vertebrate species, including humans. Although OT can be detected in various physiological fluids (blood, saliva, urine, cerebrospinal fluid) and brain tissue, it is unclear whether peripheral and central OT releases match and synergize. Moreover, the pathways of OT delivery to brain regions involved in specific behaviors are far from clear. Here, we discuss the evolutionarily and ontogenetically determined pathways of OT delivery and OT signaling, which orchestrate activity of the mesolimbic social decision-making network. Furthermore, we speculate that both the alteration in OT delivery and OT receptor expression may cause behavioral abnormalities in patients afflicted with psychosocial diseases. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
The Neuroprotective Role of Acupuncture and Activation of the BDNF Signaling Pathway
Lin, Dong; De La Pena, Ike; Lin, Lili; Zhou, Shu-Feng; Borlongan, Cesar V.; Cao, Chuanhai
2014-01-01
Recent studies have been conducted to examine the neuroprotective effects of acupuncture in many neurological disorders. Although the neuroprotective effects of acupuncture has been linked to changes in signaling pathways, accumulating evidence suggest the participation of endogenous biological mediators, such as the neurotrophin (NT) family of proteins, specifically, the brain derived neurotrophic factor (BDNF). Accordingly, acupuncture can inhibit neurodegeneration via expression and activation of BDNF. Moreover, recent studies have reported that acupuncture can increase ATP levels at local stimulated points. We have also demonstrated that acupuncture could activate monocytes and increase the expression of BDNF via the stimulation of ATP. The purpose of this article is to review the recent findings and ongoing studies on the neuroprotective roles of acupuncture and therapeutic implications of acupuncture-induced activation of BDNF and its signaling pathway. PMID:24566146
Current and emerging biologics for ulcerative colitis.
Park, Sung Chul; Jeen, Yoon Tae
2015-01-01
Conventional medical treatment for ulcerative colitis can have limited efficacy or severe adverse reactions requiring additional treatment or colectomy. Hence, different biological agents that target specific immunological pathways are be-ing investigated for treating ulcerative colitis. Anti-tumor necrosis factor (TNF) agents were the first biologics to be used for treating inflammatory bowel disease. For example, infliximab and adalimumab, which are anti-TNF agents, are be-ing used for treating ulcerative colitis. Recently, golimumab, another anti-TNF agent, and vedolizumab, an anti-adhesion therapy, have been approved for ulcerative colitis by the U.S. Food and Drug Administration. In addition, new medications such as tofacitinib, a Janus kinase inhibitor, and etrolizumab, another anti-adhesion therapy, are emerging as therapeutic agents. Therefore, there is a need for further studies to select appropriate patient groups for these biologics and to improve the outcomes of ulcerative colitis treatment through appropriate medical usage.
Current and Emerging Biologics for Ulcerative Colitis
Park, Sung Chul; Jeen, Yoon Tae
2015-01-01
Conventional medical treatment for ulcerative colitis can have limited efficacy or severe adverse reactions requiring additional treatment or colectomy. Hence, different biological agents that target specific immunological pathways are being investigated for treating ulcerative colitis. Anti-tumor necrosis factor (TNF) agents were the first biologics to be used for treating inflammatory bowel disease. For example, infliximab and adalimumab, which are anti-TNF agents, are being used for treating ulcerative colitis. Recently, golimumab, another anti-TNF agent, and vedolizumab, an anti-adhesion therapy, have been approved for ulcerative colitis by the U.S. Food and Drug Administration. In addition, new medications such as tofacitinib, a Janus kinase inhibitor, and etrolizumab, another anti-adhesion therapy, are emerging as therapeutic agents. Therefore, there is a need for further studies to select appropriate patient groups for these biologics and to improve the outcomes of ulcerative colitis treatment through appropriate medical usage. PMID:25547087
Molecular Aspects of Head and Neck Cancer Therapy
Puram, Sidharth V.; Rocco, James W.
2015-01-01
Synopsis In spite of a rapidly expanding understanding of head and neck tumor biology as well as optimization of radiation, chemotherapy, and surgical treatment modalities, head and neck squamous cell carcinoma (HNSCC) remains a major cause of cancer related morbidity and mortality. Although our biologic understanding of these tumors had largely been limited to pathways driving proliferation, survival, and differentiation, the identification of HPV as a major driver of HNSCC, specifically oropharyngeal SCC, as well as recent genomic sequencing analyses of HNSCC has dramatically influenced our understanding of the underlying biology behind carcinogenesis, and in part, our approach to therapy. In particular, we are at a major molecular and clinical crossroads with an explosion of promising diagnostic and therapeutic agents that hold great promise. Here, we summarize our current understanding of HNSCC biology, including a review of recent sequencing analyses, and identify promising areas for potential diagnostic and therapeutic agents. PMID:26568543
Venkatesan, Arjun K.; Halden, Rolf U.
2015-01-01
Traditionally, hazardous chemicals have been regulated in the U.S. on a one-by-one basis, an approach that is slow, expensive and can be inefficient, as illustrated by a decades-long succession of replacing one type of organohalogen flame retardants (OHFRs) with another one, without addressing the root cause of toxicity and associated public health threats posed. The present article expounds on the need for efficient monitoring strategies and pragmatic steps in reducing environmental pollution and adverse human health impacts. A promising approach is to combine specific bioassays with state-of-the-art chemical screening to identify chemicals and chemical mixtures sharing specific modes of action (MOAs) and pathways of toxicity (PoTs). This approach could be used to identify and regulate hazardous chemicals as classes or compound families, featuring similar biological end-points, such as endocrine disruption and mutagenicity. Opportunities and potential obstacles of implementing this approach are discussed. PMID:26343697
Genome-based analysis of heme biosynthesis and uptake in prokaryotic systems.
Cavallaro, Gabriele; Decaria, Leonardo; Rosato, Antonio
2008-11-01
Heme is the prosthetic group of many proteins that carry out a variety of key biological functions. In addition, for many pathogenic organisms, heme (acquired from the host) may constitute a very important source of iron. Organisms can meet their heme demands by taking it up from external sources, by producing the cofactor through a dedicated biosynthetic pathway, or both. Here we analyzed the distribution of proteins specifically involved in the processes of heme biosynthesis and heme uptake in 474 prokaryotic organisms. These data allowed us to identify which organisms are capable of performing none, one, or both processes, based on the similarity to known systems. Some specific instances where one or more proteins along the pathways had unusual modifications were singled out. For two key protein domains involved in heme uptake, we could build a series of structural models, which suggested possible alternative modes of heme binding. Future directions for experimental work are given.
Pathways Impacted by Genomic Alterations in Pulmonary Carcinoid Tumors.
Asiedu, Michael K; Thomas, Charles F; Dong, Jie; Schulte, Sandra C; Khadka, Prasidda; Sun, Zhifu; Kosari, Farhad; Jen, Jin; Molina, Julian; Vasmatzis, George; Kuang, Ray; Aubry, Marie Christine; Yang, Ping; Wigle, Dennis A
2018-04-01
Purpose: Pulmonary carcinoid tumors account for up to 5% of all lung malignancies in adults, comprise 30% of all carcinoid malignancies, and are defined histologically as typical carcinoid (TC) and atypical carcinoid (AC) tumors. The role of specific genomic alterations in the pathogenesis of pulmonary carcinoid tumors remains poorly understood. We sought to identify genomic alterations and pathways that are deregulated in these tumors to find novel therapeutic targets for pulmonary carcinoid tumors. Experimental Design: We performed integrated genomic analysis of carcinoid tumors comprising whole genome and exome sequencing, mRNA expression profiling and SNP genotyping of specimens from normal lung, TC and AC, and small cell lung carcinoma (SCLC) to fully represent the lung neuroendocrine tumor spectrum. Results: Analysis of sequencing data found recurrent mutations in cancer genes including ATP1A2, CNNM1, MACF1, RAB38, NF1, RAD51C, TAF1L, EPHB2, POLR3B , and AGFG1 The mutated genes are involved in biological processes including cellular metabolism, cell division cycle, cell death, apoptosis, and immune regulation. The top most significantly mutated genes were TMEM41B, DEFB127, WDYHV1, and TBPL1 Pathway analysis of significantly mutated and cancer driver genes implicated MAPK/ERK and amyloid beta precursor protein (APP) pathways whereas analysis of CNV and gene expression data suggested deregulation of the NF-κB and MAPK/ERK pathways. The mutation signature was predominantly C>T and T>C transitions with a minor contribution of T>G transversions. Conclusions: This study identified mutated genes affecting cancer relevant pathways and biological processes that could provide opportunities for developing targeted therapies for pulmonary carcinoid tumors. Clin Cancer Res; 24(7); 1691-704. ©2018 AACR . ©2018 American Association for Cancer Research.
Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G
2015-01-01
Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.
Fortuna, Jeffrey L
2010-06-01
Contemporary research has shown that a high number of alcohol-dependent and other drug-dependent individuals have a sweet preference, specifically for foods with a high sucrose concentration. Moreover, both human and animal studies have demonstrated that in some brains the consumption of sugar-rich foods or drinks primes the release of euphoric endorphins and dopamine within the nucleus accumbens, in a manner similar to some drugs of abuse. The neurobiological pathways of drug and "sugar addiction" involve similar neural receptors, neurotransmitters, and hedonic regions in the brain. Craving, tolerance, withdrawal and sensitization have been documented in both human and animal studies. In addition, there appears to be cross sensitization between sugar addiction and narcotic dependence in some individuals. It has also been observed that the biological children of alcoholic parents, particularly alcoholic fathers, are at greater risk to have a strong sweet preference, and this may manifest in some with an eating disorder. In the last two decades research has noted that specific genes may underlie the sweet preference in alcohol- and drug-dependent individuals, as well as in biological children of paternal alcoholics. There also appears to be some common genetic markers between alcohol dependence, bulimia, and obesity, such as the A1 allele gene and the dopamine 2 receptor gene.
Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants
Hill, Camilla Beate; Czauderna, Tobias; Klapperstück, Matthias; Roessner, Ute; Schreiber, Falk
2015-01-01
Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions. PMID:26557642
Lessons from Toxicology: Developing a 21st-Century Paradigm for Medical Research
Austin, Christopher P.; Balapure, Anil K.; Birnbaum, Linda S.; Bucher, John R.; Fentem, Julia; Fitzpatrick, Suzanne C.; Fowle, John R.; Kavlock, Robert J.; Kitano, Hiroaki; Lidbury, Brett A.; Muotri, Alysson R.; Peng, Shuang-Qing; Sakharov, Dmitry; Seidle, Troy; Trez, Thales; Tonevitsky, Alexander; van de Stolpe, Anja; Whelan, Maurice; Willett, Catherine
2015-01-01
Summary Biomedical developments in the 21st century provide an unprecedented opportunity to gain a dynamic systems-level and human-specific understanding of the causes and pathophysiologies of disease. This understanding is a vital need, in view of continuing failures in health research, drug discovery, and clinical translation. The full potential of advanced approaches may not be achieved within a 20th-century conceptual framework dominated by animal models. Novel technologies are being integrated into environmental health research and are also applicable to disease research, but these advances need a new medical research and drug discovery paradigm to gain maximal benefits. We suggest a new conceptual framework that repurposes the 21st-century transition underway in toxicology. Human disease should be conceived as resulting from integrated extrinsic and intrinsic causes, with research focused on modern human-specific models to understand disease pathways at multiple biological levels that are analogous to adverse outcome pathways in toxicology. Systems biology tools should be used to integrate and interpret data about disease causation and pathophysiology. Such an approach promises progress in overcoming the current roadblocks to understanding human disease and successful drug discovery and translation. A discourse should begin now to identify and consider the many challenges and questions that need to be solved. PMID:26523530
Hancock, David G; Shklovskaya, Elena; Guy, Thomas V; Falsafi, Reza; Fjell, Chris D; Ritchie, William; Hancock, Robert E W; Fazekas de St Groth, Barbara
2014-01-01
Dendritic cells (DCs) are critical for regulating CD4 and CD8 T cell immunity, controlling Th1, Th2, and Th17 commitment, generating inducible Tregs, and mediating tolerance. It is believed that distinct DC subsets have evolved to control these different immune outcomes. However, how DC subsets mount different responses to inflammatory and/or tolerogenic signals in order to accomplish their divergent functions remains unclear. Lipopolysaccharide (LPS) provides an excellent model for investigating responses in closely related splenic DC subsets, as all subsets express the LPS receptor TLR4 and respond to LPS in vitro. However, previous studies of the LPS-induced DC transcriptome have been performed only on mixed DC populations. Moreover, comparisons of the in vivo response of two closely related DC subsets to LPS stimulation have not been reported in the literature to date. We compared the transcriptomes of murine splenic CD8 and CD11b DC subsets after in vivo LPS stimulation, using RNA-Seq and systems biology approaches. We identified subset-specific gene signatures, which included multiple functional immune mediators unique to each subset. To explain the observed subset-specific differences, we used a network analysis approach. While both DC subsets used a conserved set of transcription factors and major signalling pathways, the subsets showed differential regulation of sets of genes that 'fine-tune' the network Hubs expressed in common. We propose a model in which signalling through common pathway components is 'fine-tuned' by transcriptional control of subset-specific modulators, thus allowing for distinct functional outcomes in closely related DC subsets. We extend this analysis to comparable datasets from the literature and confirm that our model can account for cell subset-specific responses to LPS stimulation in multiple subpopulations in mouse and man.
Lee, Jinoo; Valkova, Nelly; White, Mark P; Kültz, Dietmar
2006-09-01
We used dogfish shark (Squalus acanthias) as a model for proteome analysis of six different tissues to evaluate tissue-specific protein expression on a global scale and to deduce specific functions and the relatedness of multiple tissues from their proteomes. Proteomes of heart, brain, kidney, intestine, gill, and rectal gland were separated by two-dimensional gel electrophoresis (2DGE), gel images were matched using Delta 2D software and then evaluated for tissue-specific proteins. Sixty-one proteins (4%) were found to be in only a single type of tissue and 535 proteins (36%) were equally abundant in all six tissues. Relatedness between tissues was assessed based on tissue-specific expression patterns of all 1465 consistently resolved protein spots. This analysis revealed that tissues with osmoregulatory function (kidney, intestine, gill, rectal gland) were more similar in their overall proteomes than non-osmoregulatory tissues (heart, brain). Sixty-one proteins were identified by MALDI-TOF/TOF mass spectrometry and biological functions characteristic of osmoregulatory tissues were derived from gene ontology and molecular pathway analysis. Our data demonstrate that the molecular machinery for energy and urea metabolism and the Rho-GTPase/cytoskeleton pathway are enriched in osmoregulatory tissues of sharks. Our work provides a strong rationale for further study of the contribution of these mechanisms to the osmoregulation of marine sharks.
FMM: a web server for metabolic pathway reconstruction and comparative analysis.
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/.
Feng, Mao; Ramadan, Haitham; Han, Bin; Fang, Yu; Li, Jianke
2014-07-05
Hemolymph plays key roles in honey bee molecule transport, immune defense, and in monitoring the physiological condition. There is a lack of knowledge regarding how the proteome achieves these biological missions for both the western and eastern honey bees (Apis mellifera and Apis cerana). A time-resolved proteome was compared using two-dimensional electrophoresis-based proteomics to reveal the mechanistic differences by analysis of hemolymph proteome changes between the worker bees of two bee species during the larval to pupal stages. The brood body weight of Apis mellifera was significantly heavier than that of Apis cerana at each developmental stage. Significantly, different protein expression patterns and metabolic pathways were observed in 74 proteins (166 spots) that were differentially abundant between the two bee species. The function of hemolymph in energy storage, odor communication, and antioxidation is of equal importance for the western and eastern bees, indicated by the enhanced expression of different protein species. However, stronger expression of protein folding, cytoskeletal and developmental proteins, and more highly activated energy producing pathways in western bees suggests that the different bee species have developed unique strategies to match their specific physiology using hemolymph to deliver nutrients and in immune defense. Our disparate findings constitute a proof-of-concept of molecular details that the ecologically shaped different physiological conditions of different bee species match with the hemolymph proteome during the brood stage. This also provides a starting point for future research on the specific hemolymph proteins or pathways related to the differential phenotypes or physiology.
Genome-wide expression profiling in the peripheral blood of patients with fibromyalgia
Jones, Kim D.; Gelbart, Terri; Whisenant, Thomas C.; Waalen, Jill; Mondala, Tony S.; Iklé, David N.; Salomon, Daniel R.; Bennett, Robert M.; Kurian, Sunil M.
2016-01-01
Objective Fibromyalgia (FM) is a common pain disorder characterised by nociceptive dysregulation. The basic biology of FM is poorly understood. Herein we have used agnostic gene expression as a potential probe for informing its underlying biology and the development of a proof-of-concept diagnostic gene expression signature. Methods We analysed RNA expression in 70 FM patients and 70 healthy controls. The isolated RNA was amplified and hybridised to Affymetrix® Human Gene 1.1 ST Peg arrays. The data was analysed using Partek Genomics Suite v. 6.6. Results Fibromyalgia patients exhibited a differential expression of 421 genes (p<0.001), several relevant to pathways for pain processing, such as glutamine/glutamate signaling and axonal development. There was also an upregulation of several inflammatory pathways and downregulation of pathways related to hypersensitivity and allergy. Using rigorous diagnostic modeling strategies, we show “locked” gene signatures discovered on Training and Test cohorts, that have a mean Area Under the Curve (AUC) of 0.81 on randomised, independent external data cohorts. Lastly, we identified a subset of 10 probesets that provided a diagnostic sensitivity for FM of 95% and a specificity of 96%. We also show that the signatures for FM were very specific to FM rather than common FM comorbidities. Conclusion These findings provide new insights relevant to the pathogenesis of FM, and provide several testable hypotheses that warrant further exploration and also establish the foundation for a first blood-based molecular signature in FM that needs to be validated in larger cohorts of patients. PMID:27157394
Bredel, Markus; Ferrarese, Roberto; Harsh, Griffith R.; Yadav, Ajay K.; Bug, Eva; Maticzka, Daniel; Reichardt, Wilfried; Masilamani, Anie P.; Dai, Fangping; Kim, Hyunsoo; Hadler, Michael; Scholtens, Denise M.; Yu, Irene L.Y.; Beck, Jürgen; Srinivasasainagendra, Vinodh; Costa, Fabrizio; Baxan, Nicoleta; Pfeifer, Dietmar; Elverfeldt, Dominik v.; Backofen, Rolf; Weyerbrock, Astrid; Duarte, Christine W.; He, Xiaolin; Prinz, Marco; Chandler, James P.; Vogel, Hannes; Chakravarti, Arnab; Rich, Jeremy N.; Carro, Maria S.
2014-01-01
BACKGROUND: Tissue-specific alternative splicing is known to be critical to emergence of tissue identity during development, yet its role in malignant transformation is undefined. Tissue-specific splicing involves evolutionary-conserved, alternative exons, which represent only a minority of total alternative exons. Many, however, have functional features that influence activity in signaling pathways to profound biological effect. Given that tissue-specific splicing has a determinative role in brain development and the enrichment of genes containing tissue-specific exons for proteins with roles in signaling and development, it is thus plausible that changes in such exons could rewire normal neurogenesis towards malignant transformation. METHODS: We used integrated molecular genetic and cell biology analyses, computational biology, animal modeling, and clinical patient profiles to characterize the effect of aberrant splicing of a brain-enriched alternative exon in the membrane-binding tumor suppressor Annexin A7 (ANXA7) on oncogene regulation and brain tumorigenesis. RESULTS: We show that aberrant splicing of a tissue-specific cassette exon in ANXA7 diminishes endosomal targeting and consequent termination of the signal of the EGFR oncoprotein during brain tumorigenesis. Splicing of this exon is mediated by the ribonucleoprotein Polypyrimidine Tract-Binding Protein 1 (PTBP1), which is normally repressed during brain development but, we find, is excessively expressed in glioblastomas through either gene amplification or loss of a neuron-specific microRNA, miR-124. Silencing of PTBP1 attenuates both malignancy and angiogenesis in a stem cell-derived glioblastoma animal model characterized by a high native propensity to generate tumor endothelium or vascular pericytes to support tumor growth. We show that EGFR amplification and PTBP1 overexpression portend a similarly poor clinical outcome, further highlighting the importance of PTBP1-mediated activation of EGFR. CONCLUSIONS: Our data illustrate how anomalous splicing of a tissue-regulated exon in a constituent of an oncogenic signaling pathway eliminates its tumor suppressor function and promotes tumorigenesis. This paradigm of malignant glial transformation as a consequence of tissue-specific alternative exon splicing in a tumor suppressor, may have widespread applicability in explaining how changes in critical tissue-specific regulatory mechanisms reprogram normal development to oncogenesis. SECONDARY CATEGORY: n/a.
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.
Joo, Kyeung Min; Kim, Jinkuk; Jin, Juyoun; Kim, Misuk; Seol, Ho Jun; Muradov, Johongir; Yang, Heekyoung; Choi, Yoon-La; Park, Woong-Yang; Kong, Doo-Sik; Lee, Jung-Il; Ko, Young-Hyeh; Woo, Hyun Goo; Lee, Jeongwu; Kim, Sunghoon; Nam, Do-Hyun
2013-01-31
Frequent discrepancies between preclinical and clinical results of anticancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable "patient tumor's phenocopy" that represents molecular and functional heterogeneity of GBMs. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Tausend, William; Downing, Christopher; Tyring, Stephen
2014-01-01
Monoclonal antibodies known as biologic agents specifically targeted against interleukin-12 (IL-12), interleukin-17A (IL-17), and interleukin-23 (IL-23) have been the focus of research for moderate-to-severe chronic plaque psoriasis in recent years. To discuss the immune-mediated model of psoriasis and to summarize current knowledge of the clinical efficacy and safety of new biologic agents for moderate-to-severe chronic plaque psoriasis. The PubMed database was searched for relevant articles on ustekinumab, briakinumab, tildrakizumab (MK-322), guselkumab, secukinumab, ixekizumab, and brodalumab published between January 2005 and July 2013. Fifty-five articles were identified. These studies suggest that the biologic agents specifically targeting IL-12, IL-17, and IL-23 are efficacious and safe in the treatment of moderate-to-severe psoriasis in adults. Current data from clinical trials suggest that biologic agents targeting IL-12, IL-17, and IL-23 are safe and efficacious drugs for use in moderate-to-severe chronic plaque psoriasis. Long-term data still need to be established.
A guide for building biological pathways along with two case studies: hair and breast development.
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.
Ahir, Bhavesh K.; Sanders, Alison P.; Rager, Julia E.
2013-01-01
Background: The biological mechanisms by which environmental metals are associated with birth defects are largely unknown. Systems biology–based approaches may help to identify key pathways that mediate metal-induced birth defects as well as potential targets for prevention. Objectives: First, we applied a novel computational approach to identify a prioritized biological pathway that associates metals with birth defects. Second, in a laboratory setting, we sought to determine whether inhibition of the identified pathway prevents developmental defects. Methods: Seven environmental metals were selected for inclusion in the computational analysis: arsenic, cadmium, chromium, lead, mercury, nickel, and selenium. We used an in silico strategy to predict genes and pathways associated with both metal exposure and developmental defects. The most significant pathway was identified and tested using an in ovo whole chick embryo culture assay. We further evaluated the role of the pathway as a mediator of metal-induced toxicity using the in vitro midbrain micromass culture assay. Results: The glucocorticoid receptor pathway was computationally predicted to be a key mediator of multiple metal-induced birth defects. In the chick embryo model, structural malformations induced by inorganic arsenic (iAs) were prevented when signaling of the glucocorticoid receptor pathway was inhibited. Further, glucocorticoid receptor inhibition demonstrated partial to complete protection from both iAs- and cadmium-induced neurodevelopmental toxicity in vitro. Conclusions: Our findings highlight a novel approach to computationally identify a targeted biological pathway for examining birth defects prevention. PMID:23458687
Construction and engineering of large biochemical pathways via DNA assembler
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
The multiscale backbone of the human phenotype network based on biological pathways.
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.
Electrophysiological experiments in microgravity: lessons learned and future challenges.
Wuest, Simon L; Gantenbein, Benjamin; Ille, Fabian; Egli, Marcel
2018-01-01
Advances in electrophysiological experiments have led to the discovery of mechanosensitive ion channels (MSCs) and the identification of the physiological function of specific MSCs. They are believed to play important roles in mechanosensitive pathways by allowing for cells to sense their mechanical environment. However, the physiological function of many MSCs has not been conclusively identified. Therefore, experiments have been developed that expose cells to various mechanical loads, such as shear flow, membrane indentation, osmotic challenges and hydrostatic pressure. In line with these experiments, mechanical unloading, as experienced in microgravity, represents an interesting alternative condition, since exposure to microgravity leads to a series of physiological adaption processes. As outlined in this review, electrophysiological experiments performed in microgravity have shown an influence of gravity on biological functions depending on ion channels at all hierarchical levels, from the cellular level to organs. In this context, calcium signaling represents an interesting cellular pathway, as it involves the direct action of calcium-permeable ion channels, and specific gravitatic cells have linked graviperception to this pathway. Multiple key proteins in the graviperception pathways have been identified. However, measurements on vertebrae cells have revealed controversial results. In conclusion, electrophysiological experiments in microgravity have shown that ion-channel-dependent physiological processes are altered in mechanically unloaded conditions. Future experiments may provide a better understanding of the underlying mechanisms.
Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.
Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo
2018-05-17
In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.
Genetic and Epigenetic Events Generate Multiple Pathways in Colorectal Cancer Progression
Pancione, Massimo; Remo, Andrea; Colantuoni, Vittorio
2012-01-01
Colorectal cancer (CRC) is one of the most common causes of death, despite decades of research. Initially considered as a disease due to genetic mutations, it is now viewed as a complex malignancy because of the involvement of epigenetic abnormalities. A functional equivalence between genetic and epigenetic mechanisms has been suggested in CRC initiation and progression. A hallmark of CRC is its pathogenetic heterogeneity attained through at least three distinct pathways: a traditional (adenoma-carcinoma sequence), an alternative, and more recently the so-called serrated pathway. While the alternative pathway is more heterogeneous and less characterized, the traditional and serrated pathways appear to be more homogeneous and clearly distinct. One unsolved question in colon cancer biology concerns the cells of origin and from which crypt compartment the different pathways originate. Based on molecular and pathological evidences, we propose that the traditional and serrated pathways originate from different crypt compartments explaining their genetic/epigenetic and clinicopathological differences. In this paper, we will discuss the current knowledge of CRC pathogenesis and, specifically, summarize the role of genetic/epigenetic changes in the origin and progression of the multiple CRC pathways. Elucidation of the link between the molecular and clinico-pathological aspects of CRC would improve our understanding of its etiology and impact both prevention and treatment. PMID:22888469
Graphite Web: web tool for gene set analysis exploiting pathway topology
Sales, Gabriele; Calura, Enrica; Martini, Paolo; Romualdi, Chiara
2013-01-01
Graphite web is a novel web tool for pathway analyses and network visualization for gene expression data of both microarray and RNA-seq experiments. Several pathway analyses have been proposed either in the univariate or in the global and multivariate context to tackle the complexity and the interpretation of expression results. These methods can be further divided into ‘topological’ and ‘non-topological’ methods according to their ability to gain power from pathway topology. Biological pathways are, in fact, not only gene lists but can be represented through a network where genes and connections are, respectively, nodes and edges. To this day, the most used approaches are non-topological and univariate although they miss the relationship among genes. On the contrary, topological and multivariate approaches are more powerful, but difficult to be used by researchers without bioinformatic skills. Here we present Graphite web, the first public web server for pathway analysis on gene expression data that combines topological and multivariate pathway analyses with an efficient system of interactive network visualizations for easy results interpretation. Specifically, Graphite web implements five different gene set analyses on three model organisms and two pathway databases. Graphite Web is freely available at http://graphiteweb.bio.unipd.it/. PMID:23666626
The Paradox of Oestradiol-Induced Breast Cancer Cell Growth and Apoptosis.
Maximov, Philipp Y; Lewis-Wambi, Joan S; Jordan, V Craig
2009-05-01
High dose oestrogen therapy was used as a treatment for postmenopausal patients with breast cancer from the 1950s until the introduction of the safer antioestrogen, tamoxifen in the 1970s. The anti-tumour mechanism of high dose oestrogen therapy remained unknown. There was no enthusiasm to study these signal transduction pathways as oestrogen therapy has almost completely been eliminated from the treatment paradigm. Current use of tamoxifen and the aromatase inhibitors seek to create oestrogen deprivation that prevents the growth of oestrogen stimulated oestrogen receptor (ER) positive breast cancer cells. However, acquired resistance to antihormonal therapy does occur, but it is through investigation of laboratory models that a vulnerability of the cancer cell has been discovered and is being investigated to provide new opportunities in therapy with the potential for discovering new cancer-specific apoptotic drugs. Laboratory models of resistance to raloxifene and tamoxifen, the selective oestrogen receptor modulators (SERMs) and aromatase inhibitors demonstrate an evolution of drug resistance so that after many years of oestrogen deprivation, the ER positive cancer cell reconfigures the survival signal transduction pathways so oestrogen now becomes an apoptotic trigger rather than a survival signal. Current efforts are evaluating the mechanisms of oestrogen-induced apoptosis and how this new biology of oestrogen action can be amplified and enhanced, thereby increasing the value of this therapeutic opportunity for the treatment of breast cancer. Several synergistic approaches to therapeutic enhancement are being advanced which involve drug combinations to impair survival signaling with the use of specific agents and to impair bcl-2 that protects the cancer cell from apoptosis. We highlight the historical understanding of oestrogen's role in cell survival and death and specifically illustrate the progress that has been made in the last five years to understand the mechanisms of oestrogen-induced apoptosis. There are opportunities to harness knowledge from this new signal transduction pathway to discover the precise mechanism of this oestrogen-induced apoptotic trigger. Indeed, the new biology of oestrogen action also has significance for understanding the physiology of bone remodeling. Thus, the pathway has a broad appeal in both physiology and cancer research.
Parental smoking and adolescent problem behavior: an adoption study of general and specific effects.
Keyes, Margaret; Legrand, Lisa N; Iacono, William G; McGue, Matt
2008-10-01
It is essential to understand the effect of parental smoking on offspring tobacco use. In biologically related families, parents who smoke may transmit a nonspecific genetic risk for offspring disinhibited behavior, including tobacco use. Studying adoptive families allows one to control for genetic confounding when examining the environmental effect of exposure to parental smoking. The purpose of this study was to examine the genetic and environmental contributions to the risk represented by exposure to parental smoking and to assess the specificity of that risk. Adolescents adopted in infancy were systematically ascertained from records of three private Minnesota adoption agencies; nonadopted adolescents were ascertained from Minnesota birth records. Adolescents and their rearing parents participated in all assessments in person. The main outcome measures were self-reports of behavioral deviance, substance use, and personality, as well as DSM-IV clinical assessments of childhood disruptive disorders. The data from adoptive families suggest that exposure to parental smoking represents an environmental risk for substance use in adolescent offspring. In biologically related families, the effect of exposure to parental smoking is larger and more diverse, including substance use, disruptive behavior disorders, delinquency, deviant peer affiliations, aggressive attitudes, and preference for risk taking. This study provides evidence for an environmentally mediated pathway by which parental smoking increases risk specifically for substance use in adolescent offspring. The data are also consistent with a genetically mediated pathway by which nonadoptive parents who smoke may also transmit a nonspecific genetic risk to their offspring for disinhibited behavior.
Pain Amplification Syndrome: A Biopsychosocial Approach.
Namerow, Lisa B; Kutner, Emily C; Wakefield, Emily C; Rzepski, Barbara R; Sahl, Robert A
2016-08-01
Pediatric neurologists frequently encounter patients who present with significant musculoskeletal pain that cannot be attributed to a specific injury or illness, which can often be defined as pain amplification syndrome (PAS). PAS in children and adolescents is the result of a heightened pain sensitivity pathway, which is intensified by significant biological, psychological, and social contributors. Appropriate assessment and multimodal intervention of PAS are crucial to treatment success, including neurology and behavioral health collaborative treatment plans to restore patient function and reduce pain perception. Pediatric neurologists are imperative in the identification of patients with PAS, providing the family assurance in diagnosis and validation of pain, and directing patients to the appropriate multidisciplinary treatment pathway. Copyright © 2016 Elsevier Inc. All rights reserved.
Biological Conversion of Sugars to Hydrocarbons Technology Pathway
DOE Office of Scientific and Technical Information (OSTI.GOV)
Davis, R.; Biddy, M.; Tan, E.
2013-03-01
This technology pathway case investigates the biological conversion of biomass-derived sugars to hydrocarbon biofuels, utilizing data from recent literature references and information consistent with recent pilot-scale demonstrations at NREL. Technical barriers and key research needs have been identified that should be pursued for the pathway to become competitive with petroleum-derived gasoline-, diesel-, and jet-range hydrocarbon blendstocks.
Deciphering the biological effects of acupuncture treatment modulating multiple metabolism pathways.
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.
Karakas, Filiz; Imamoglu, Ipek
2017-04-01
This study aims to estimate anaerobic debromination rate constants (k m ) of PBDE pathways using previously reported laboratory soil data. k m values of pathways are estimated by modifying a previously developed model as Anaerobic Dehalogenation Model. Debromination activities published in the literature in terms of bromine substitutions as well as specific microorganisms and their combinations are used for identification of pathways. The range of estimated k m values is between 0.0003 and 0.0241 d -1 . The median and maximum of k m values are found to be comparable to the few available biologically confirmed rate constants published in the literature. The estimated k m values can be used as input to numerical fate and transport models for a better and more detailed investigation of the fate of individual PBDEs in contaminated sediments. Various remediation scenarios such as monitored natural attenuation or bioremediation with bioaugmentation can be handled in a more quantitative manner with the help of k m estimated in this study.
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.
Vincent, Julian F V
2003-01-01
Biomimetics is seen as a path from biology to engineering. The only path from engineering to biology in current use is the application of engineering concepts and models to biological systems. However, there is another pathway: the verification of biological mechanisms by manufacture, leading to an iterative process between biology and engineering in which the new understanding that the engineering implementation of a biological system can bring is fed back into biology, allowing a more complete and certain understanding and the possibility of further revelations for application in engineering. This is a pathway as yet unformalized, and one that offers the possibility that engineers can also be scientists. PMID:14561351
Do, Duy N.; Strathe, Anders B.; Ostersen, Tage; Pant, Sameer D.; Kadarmideen, Haja N.
2014-01-01
Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher’s exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs. PMID:25250046
Formal reasoning about systems biology using theorem proving
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
Gandhi, Deepa; Sivanesan, Saravanadevi; Kannan, Krishnamurthi
2018-06-01
Manganese (Mn) is an essential trace element required for many physiological functions including proper biochemical and cellular functioning of the central nervous system (CNS). However, exposure to excess level of Mn through occupational settings or from environmental sources has been associated with neurotoxicity. The cellular and molecular mechanism of Mn-induced neurotoxicity remains unclear. In the current study, we investigated the effects of 30-day exposure to a sub-lethal concentration of Mn (100 μM) in human neuroblastoma cells (SH-SY5Y) using transcriptomic approach. Microarray analysis revealed differential expression of 1057 transcripts in Mn-exposed SH-SY5Y cells as compared to control cells. Gene functional annotation cluster analysis exhibited that the differentially expressed genes were associated with several biological pathways. Specifically, genes involved in neuronal pathways including neuron differentiation and development, regulation of neurogenesis, synaptic transmission, and neuronal cell death (apoptosis) were found to be significantly altered. KEGG pathway analysis showed upregulation of p53 signaling pathways and neuroactive ligand-receptor interaction pathways, and downregulation of neurotrophin signaling pathway. On the basis of the gene expression profile, possible molecular mechanisms underlying Mn-induced neuronal toxicity were predicted.
Qu, Xudong
2014-01-01
Fluorination has been widely used in chemical synthesis, but is rare in nature. The only known biological fluorination scope is represented by the fl pathway from Streptomyces cattleya that produces fluoroacetate (FAc) and 4-fluorothreonine (4-FT). Here we report the identification of a novel pathway for FAc and 4-FT biosynthesis from the actinomycetoma-causing pathogen Nocardia brasiliensis ATCC 700358. The new pathway shares overall conservation with the fl pathway in S. cattleya. Biochemical characterization of the conserved domains revealed a novel fluorinase NobA that can biosynthesize 5’-fluoro-5’-deoxyadenosine (5’-FDA) from inorganic fluoride and S-adenosyl-l-methionine (SAM). The NobA shows similar halide specificity and characteristics to the fluorination enzyme FlA of the fl pathway. Kinetic parameters for fluoride ( K m 4153 μM, k cat 0.073 min -1) and SAM ( K m 416 μM, k cat 0.139 min -1) have been determined, revealing that NobA is slightly (2.3 fold) slower than FlA. Upon sequence comparison, we finally identified a distinct loop region in the fluorinases that probably accounts for the disparity of fluorination activity. PMID:24795808
Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.
Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice
2015-09-04
The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.
NASA Astrophysics Data System (ADS)
Mulcan, Amanda
This thesis aims to facilitate the siting and implementation of Florida Atlantic University Southeast National Marine Renewable Energy Center (FAU SNMREC) ocean current energy (OCE) projects offshore southeastern Florida through the analysis of benthic anchoring conditions. Specifically, a suitability analysis considering all presently available biologic and geologic datasets within the legal framework of OCE policy and regulation was done. OCE related literature sources were consulted to assign suitability levels to each dataset, ArcGIS interpolations generated seafloor substrate maps, and existing submarine cable pathways were considered for OCE power cables. The finalized suitability map highlights the eastern study area as most suitable for OCE siting due to its abundance of sand/sediment substrate, existing underwater cable route access, and minimal biologic presence. Higher resolution datasets are necessary to locate specific OCE development locales, better understand their benthic conditions, and minimize potentially negative OCE environmental impacts.
[Molecular biology of renal cancer: bases for genetic directed therapy in advanced disease].
Maroto Rey, José Pablo; Cillán Narvaez, Elena
2013-06-01
There has been expansion of therapeutic options in the management of metastatic renal cell carcinoma due to a better knowledge of the molecular biology of kidney cancers. There are different tumors grouped under the term renal cell carcinoma, being clear cell cancer the most frequent and accounting for 80% of kidney tumors. Mutations in the Von Hippel-Lindau gene can be identified in up to 80% of sporadic clear cell cancer, linking a genetically inheritable disease where vascular tumors are frequent, with renal cell cancer. Other histologic types present specific alterations in molecular pathways, like c-MET in papillary type I tumors, and Fumarase Hydratase in papillary type II tumors. Identification of the molecular alteration for a specific tumor may offer an opportunity for treatment selection based on biomarkers, and, in the future, for developing an engineering designed genetic treatment.
BIOLOGICAL NETWORK EXPLORATION WITH CYTOSCAPE 3
Su, Gang; Morris, John H.; Demchak, Barry; Bader, Gary D.
2014-01-01
Cytoscape is one of the most popular open-source software tools for the visual exploration of biomedical networks composed of protein, gene and other types of interactions. It offers researchers a versatile and interactive visualization interface for exploring complex biological interconnections supported by diverse annotation and experimental data, thereby facilitating research tasks such as predicting gene function and pathway construction. Cytoscape provides core functionality to load, visualize, search, filter and save networks, and hundreds of Apps extend this functionality to address specific research needs. The latest generation of Cytoscape (version 3.0 and later) has substantial improvements in function, user interface and performance relative to previous versions. This protocol aims to jump-start new users with specific protocols for basic Cytoscape functions, such as installing Cytoscape and Cytoscape Apps, loading data, visualizing and navigating the network, visualizing network associated data (attributes) and identifying clusters. It also highlights new features that benefit experienced users. PMID:25199793
FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants1
Tohge, Takayuki; Klie, Sebastian; Fernie, Alisdair R.
2016-01-01
Gene duplications generate new genes that can acquire similar but often diversified functions. Recent studies of gene coexpression networks have indicated that, not only genes, but also pathways can be multiplied and diversified to perform related functions in different parts of an organism. Identification of such diversified pathways, or modules, is needed to expand our knowledge of biological processes in plants and to understand how biological functions evolve. However, systematic explorations of modules remain scarce, and no user-friendly platform to identify them exists. We have established a statistical framework to identify modules and show that approximately one-third of the genes of a plant’s genome participate in hundreds of multiplied modules. Using this framework as a basis, we implemented a platform that can explore and visualize multiplied modules in coexpression networks of eight plant species. To validate the usefulness of the platform, we identified and functionally characterized pollen- and root-specific cell wall modules that multiplied to confer tip growth in pollen tubes and root hairs, respectively. Furthermore, we identified multiplied modules involved in secondary metabolite synthesis and corroborated them by metabolite profiling of tobacco (Nicotiana tabacum) tissues. The interactive platform, referred to as FamNet, is available at http://www.gene2function.de/famnet.html. PMID:26754669
Biomass recalcitrance: a multi-scale, multi-factor, and conversion-specific property.
McCann, Maureen C; Carpita, Nicholas C
2015-07-01
Recalcitrance of plant biomass to enzymatic hydrolysis for biofuel production is thought to be a property conferred by lignin or lignin-carbohydrate complexes. However, chemical catalytic and thermochemical conversion pathways, either alone or in combination with biochemical and fermentative pathways, now provide avenues to utilize lignin and to expand the product range beyond ethanol or butanol. To capture all of the carbon in renewable biomass, both lignin-derived aromatics and polysaccharide-derived sugars need to be transformed by catalysts to liquid hydrocarbons and high-value co-products. We offer a new definition of recalcitrance as those features of biomass which disproportionately increase energy requirements in conversion processes, increase the cost and complexity of operations in the biorefinery, and/or reduce the recovery of biomass carbon into desired products. The application of novel processing technologies applied to biomass reveal new determinants of recalcitrance that comprise a broad range of molecular, nanoscale, and macroscale factors. Sampling natural genetic diversity within a species, transgenic approaches, and synthetic biology approaches are all strategies that can be used to select biomass for reduced recalcitrance in various pretreatments and conversion pathways. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
2007-05-01
BODY: Revised Specific Aim 1: Elucidate the biochemistry of stratifin within the context of normal mammary gland development and homeostasis...keratinocyte proliferation and lack of differentiation into keratin squames. The excessive skin thickening closes the mouths of pups, resulting in suffocation ...the Department of Molecular and Cell Biology Honours Research Symposium - Gave a poster presentation at the Department of Comparative Biochemistry
30 years of NF-κB: a blossoming of relevance to human pathobiology
Zhang, Qian; Lenardo, Michael J.; Baltimore, David
2016-01-01
NF-κB was discovered thirty years ago as a rapidly inducible transcription factor. Since that time it has been found to have a broad role in gene induction in diverse cellular responses, particularly throughout the immune system. Here we summarize elaborate regulatory pathways involving this transcription factor and use recent discoveries in human genetic diseases to place specific proteins within their relevant medical and biological contexts. PMID:28086098
Role of phytohormones in insect-specific plant reactions
Erb, Matthias; Meldau, Stefan; Howe, Gregg A.
2012-01-01
The capacity to perceive and respond is integral to biological immune systems, but to what extent can plants specifically recognize and respond to insects? Recent findings suggest that plants possess surveillance systems that are able to detect general patterns of cellular damage as well as highly specific herbivore-associated cues. The jasmonate (JA) pathway has emerged as the major signaling cassette that integrates information perceived at the plant–insect interface into broad-spectrum defense responses. Specificity can be achieved via JA-independent processes and spatio-temporal changes of JA-modulating hormones, including ethylene, salicylic acid, abscisic acid, auxin, cytokinins, brassinosteroids and gibberellins. The identification of receptors and ligands and an integrative view of hormone-mediated response systems are crucial to understand specificity in plant immunity to herbivores. PMID:22305233
Biomimetic approaches to modulate cellular adhesion in biomaterials: A review.
Rahmany, Maria B; Van Dyke, Mark
2013-03-01
Natural extracellular matrix (ECM) proteins possess critical biological characteristics that provide a platform for cellular adhesion and activation of highly regulated signaling pathways. However, ECM-based biomaterials can have several limitations, including poor mechanical properties and risk of immunogenicity. Synthetic biomaterials alleviate the risks associated with natural biomaterials but often lack the robust biological activity necessary to direct cell function beyond initial adhesion. A thorough understanding of receptor-mediated cellular adhesion to the ECM and subsequent signaling activation has facilitated development of techniques that functionalize inert biomaterials to provide a biologically active surface. Here we review a range of approaches used to modify biomaterial surfaces for optimal receptor-mediated cell interactions, as well as provide insights into specific mechanisms of downstream signaling activation. In addition to a brief overview of integrin receptor-mediated cell function, so-called "biomimetic" techniques reviewed here include (i) surface modification of biomaterials with bioadhesive ECM macromolecules or specific binding motifs, (ii) nanoscale patterning of the materials and (iii) the use of "natural-like" biomaterials. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Resistance to Cell Death and Its Modulation in Cancer Stem Cells
Safa, Ahmad R.
2017-01-01
Accumulating evidence has demonstrated that human cancers arise from various tissues of origin that initiate from cancer stem cells (CSCs) or cancer-initiating cells. The extrinsic and intrinsic apoptotic pathways are dysregulated in CSCs, and these cells play crucial roles in tumor initiation, progression, cell death resistance, chemo- and radiotherapy resistance, and tumor recurrence. Understanding CSC-specific signaling proteins and pathways is necessary to identify specific therapeutic targets that may lead to the development of more efficient therapies selectively targeting CSCs. Several signaling pathways—including the phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), maternal embryonic leucine zipper kinase (MELK), NOTCH1, and Wnt/β-catenin—and expression of the CSC markers CD133, CD24, CD44, Oct4, Sox2, Nanog, and ALDH1A1 maintain CSC properties. Studying such pathways may help to understand CSC biology and lead to the development of potential therapeutic interventions to render CSCs more sensitive to cell death triggered by chemotherapy and radiation therapy. Moreover, recent demonstrations of dedifferentiation of differentiated cancer cells into CSC-like cells have created significant complexity in the CSCs hypothesis. Therefore, any successful therapeutic agent or combination of drugs for cancer therapy must eliminate not only CSCs but differentiated cancer cells and the entire bulk of tumor cells. This review article expands on the CSC hypothesis and paradigm with respect to major signaling pathways and effectors that regulate CSC apoptosis resistance. Moreover, selective CSC apoptotic modulators and their therapeutic potential for making tumors more responsive to therapy are discussed. The use of novel therapies, including small-molecule inhibitors of specific proteins in signaling pathways that regulate stemness, proliferation and migration of CSCs, immunotherapy, and noncoding microRNAs may provide better means of treating CSCs. PMID:27915972
Minimal metabolic pathway structure is consistent with associated biomolecular interactions
Bordbar, Aarash; Nagarajan, Harish; Lewis, Nathan E; Latif, Haythem; Ebrahim, Ali; Federowicz, Stephen; Schellenberger, Jan; Palsson, Bernhard O
2014-01-01
Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated. PMID:24987116
Adverse Outcome Pathway (AOP) Network Development for Fatty Liver
Adverse outcome pathways (AOPs) are descriptive biological sequences that start from a molecular initiating event (MIE) and end with an adverse health outcome. AOPs provide biological context for high throughput chemical testing and further prioritize environmental health risk re...
Refining Pathways: A Model Comparison Approach
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
Abraham, Karan J; Zhang, Xiao; Vidal, Ricardo; Paré, Geneviève C; Feilotter, Harriet E; Tron, Victor A
2016-04-01
Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
Wong, W Z; H'ng, P S; Chin, K L; Sajap, Ahmad Said; Tan, G H; Paridah, M T; Othman, Soni; Chai, E W; Go, W Z
2015-10-01
The lower termite, Coptotermes curvignathus, is one of the most prominent plantation pests that feed upon, digest, and receive nourishment from exclusive lignocellulose diets. The objective of this study was to examine the utilization of sole carbon sources by isolated culturable aerobic bacteria among communities from the gut and foraging pathway of C. curvignathus. We study the bacteria occurrence from the gut of C. curvignathus and its surrounding feeding area by comparing the obtained phenotypic fingerprint with Biolog's extensive species library. A total of 24 bacteria have been identified mainly from the family Enterobacteriaceae from the identification of Biolog Gen III. Overall, the bacteria species in the termite gut differ from those of foraging pathway within a location, except Acintobacter baumannii, which was the only bacteria species found in both habitats. Although termites from a different study area do not have the same species of bacteria in the gut, they do have a bacterial community with similar role in degrading certain carbon sources. Sugars were preferential in termite gut isolates, while nitrogen carbon sources were preferential in foraging pathway isolates. The preferential use of specific carbon sources by these two bacterial communities reflects the role of bacteria for regulation of carbon metabolism in the termite gut and foraging pathway. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Identification and pathway analysis of microRNAs with no previous involvement in breast cancer.
Romero-Cordoba, Sandra; Rodriguez-Cuevas, Sergio; Rebollar-Vega, Rosa; Quintanar-Jurado, Valeria; Maffuz-Aziz, Antonio; Jimenez-Sanchez, Gerardo; Bautista-Piña, Veronica; Arellano-Llamas, Rocio; Hidalgo-Miranda, Alfredo
2012-01-01
microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value = 0.05, Fold Change = 2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The expression of 14 microRNAs was replicated in an independent set of 55 tumors. Bioinformatic analysis of mRNA targets of the altered miRNAs, identified oncogenes like ERBB2, YY1, several MAP kinases, and known tumor-suppressors like FOXA1 and SMAD4. Pathway analysis identified that some biological process which are important in breast carcinogenesis are affected by the altered microRNA expression, including signaling through MAP kinases and TP53 pathways, as well as biological processes like cell death and communication, focal adhesion and ERBB2-ERBB3 signaling. Our data identified the altered expression of several microRNAs whose aberrant expression might have an important impact on cancer-related cellular pathways and whose role in breast cancer has not been previously described.
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.
Identifying Differentially Abundant Metabolic Pathways in Metagenomic Datasets
NASA Astrophysics Data System (ADS)
Liu, Bo; Pop, Mihai
Enabled by rapid advances in sequencing technology, metagenomic studies aim to characterize entire communities of microbes bypassing the need for culturing individual bacterial members. One major goal of such studies is to identify specific functional adaptations of microbial communities to their habitats. Here we describe a powerful analytical method (MetaPath) that can identify differentially abundant pathways in metagenomic data-sets, relying on a combination of metagenomic sequence data and prior metabolic pathway knowledge. We show that MetaPath outperforms other common approaches when evaluated on simulated datasets. We also demonstrate the power of our methods in analyzing two, publicly available, metagenomic datasets: a comparison of the gut microbiome of obese and lean twins; and a comparison of the gut microbiome of infant and adult subjects. We demonstrate that the subpathways identified by our method provide valuable insights into the biological activities of the microbiome.
Targeting HSP70-induced thermotolerance for design of thermal sensitizers.
Calderwood, S K; Asea, A
2002-01-01
Thermal therapy has been shown to be an extremely powerful anti-cancer agent and a potent radiation sensitizer. However, the full potential of thermal therapy is hindered by a number of considerations including highly conserved heat resistance pathways in tumour cells and inhomogeneous heating of deep-seated tumours due to energy deposition and perfusion issues. This report reviews recent progress in the development of hyperthermia sensitizing drugs designed to specifically amplify the effects of hyperthermia. Such agents might be particularly useful in situations where heating is not adequate for the full biological effect or is not homogeneously delivered to tumours. The particular pathway concentrated on is thermotolerance, a complex, inducible cellular response that leads to heat resistance. This paper will concentrate on the molecular pathways of thermotolerance induction for designing inhibitors of heat resistance/thermal sensitizers, which may allow the full potential of thermal therapy to be utilized.
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.
Finding pathway-modulating genes from a novel Ontology Fingerprint-derived gene network.
Qin, Tingting; Matmati, Nabil; Tsoi, Lam C; Mohanty, Bidyut K; Gao, Nan; Tang, Jijun; Lawson, Andrew B; Hannun, Yusuf A; Zheng, W Jim
2014-10-01
To enhance our knowledge regarding biological pathway regulation, we took an integrated approach, using the biomedical literature, ontologies, network analyses and experimental investigation to infer novel genes that could modulate biological pathways. We first constructed a novel gene network via a pairwise comparison of all yeast genes' Ontology Fingerprints--a set of Gene Ontology terms overrepresented in the PubMed abstracts linked to a gene along with those terms' corresponding enrichment P-values. The network was further refined using a Bayesian hierarchical model to identify novel genes that could potentially influence the pathway activities. We applied this method to the sphingolipid pathway in yeast and found that many top-ranked genes indeed displayed altered sphingolipid pathway functions, initially measured by their sensitivity to myriocin, an inhibitor of de novo sphingolipid biosynthesis. Further experiments confirmed the modulation of the sphingolipid pathway by one of these genes, PFA4, encoding a palmitoyl transferase. Comparative analysis showed that few of these novel genes could be discovered by other existing methods. Our novel gene network provides a unique and comprehensive resource to study pathway modulations and systems biology in general. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Finding pathway-modulating genes from a novel Ontology Fingerprint-derived gene network
Qin, Tingting; Matmati, Nabil; Tsoi, Lam C.; Mohanty, Bidyut K.; Gao, Nan; Tang, Jijun; Lawson, Andrew B.; Hannun, Yusuf A.; Zheng, W. Jim
2014-01-01
To enhance our knowledge regarding biological pathway regulation, we took an integrated approach, using the biomedical literature, ontologies, network analyses and experimental investigation to infer novel genes that could modulate biological pathways. We first constructed a novel gene network via a pairwise comparison of all yeast genes’ Ontology Fingerprints—a set of Gene Ontology terms overrepresented in the PubMed abstracts linked to a gene along with those terms’ corresponding enrichment P-values. The network was further refined using a Bayesian hierarchical model to identify novel genes that could potentially influence the pathway activities. We applied this method to the sphingolipid pathway in yeast and found that many top-ranked genes indeed displayed altered sphingolipid pathway functions, initially measured by their sensitivity to myriocin, an inhibitor of de novo sphingolipid biosynthesis. Further experiments confirmed the modulation of the sphingolipid pathway by one of these genes, PFA4, encoding a palmitoyl transferase. Comparative analysis showed that few of these novel genes could be discovered by other existing methods. Our novel gene network provides a unique and comprehensive resource to study pathway modulations and systems biology in general. PMID:25063300
Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online
Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary
2018-01-01
Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574
Targeting the relaxin hormonal pathway in prostate cancer.
Neschadim, Anton; Summerlee, Alastair J S; Silvertown, Joshua D
2015-11-15
Targeting the androgen signalling pathway has long been the hallmark of anti-hormonal therapy for prostate cancer. However, development of androgen-independent prostate cancer is an inevitable outcome to therapies targeting this pathway, in part, owing to the shift from cancer dependence on androgen signalling for growth in favor of augmentation of other cellular pathways that provide proliferation-, survival- and angiogenesis-promoting signals. This review focuses on the role of the hormone relaxin in the development and progression of prostate cancer, prior to and after the onset of androgen independence, as well as its role in cancers of other reproductive tissues. As the body of literature expands, examining relaxin expression in cancerous tissues and its role in a growing number of in vitro and in vivo cancer models, our understanding of the important involvement of this hormone in cancer biology is becoming clearer. Specifically, the pleiotropic functions of relaxin affecting cell growth, angiogenesis, blood flow, cell migration and extracellular matrix remodeling are examined in the context of cancer progression. The interactions and intercepts of the intracellular signalling pathways of relaxin with the androgen pathway are explored in the context of progression of castration-resistant and androgen-independent prostate cancers. We provide an overview of current anti-hormonal therapeutic treatment options for prostate cancer and delve into therapeutic approaches and development of agents aimed at specifically antagonizing relaxin signalling to curb tumor growth. We also discuss the rationale and challenges utilizing such agents as novel anti-hormonals in the clinic, and their potential to supplement current therapeutic modalities. © 2014 UICC.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Appolaire, Alexandre; Girard, Eric; Colombo, Matteo
2014-11-01
The present work illustrates that small-angle neutron scattering, deuteration and contrast variation, combined with in vitro particle reconstruction, constitutes a very efficient approach to determine subunit architectures in large, symmetric protein complexes. In the case of the 468 kDa heterododecameric TET peptidase machine, it was demonstrated that the assembly of the 12 subunits is a highly controlled process and represents a way to optimize the catalytic efficiency of the enzyme. The specific self-association of proteins into oligomeric complexes is a common phenomenon in biological systems to optimize and regulate their function. However, de novo structure determination of these important complexesmore » is often very challenging for atomic-resolution techniques. Furthermore, in the case of homo-oligomeric complexes, or complexes with very similar building blocks, the respective positions of subunits and their assembly pathways are difficult to determine using many structural biology techniques. Here, an elegant and powerful approach based on small-angle neutron scattering is applied, in combination with deuterium labelling and contrast variation, to elucidate the oligomeric organization of the quaternary structure and the assembly pathways of 468 kDa, hetero-oligomeric and symmetric Pyrococcus horikoshii TET2–TET3 aminopeptidase complexes. The results reveal that the topology of the PhTET2 and PhTET3 dimeric building blocks within the complexes is not casual but rather suggests that their quaternary arrangement optimizes the catalytic efficiency towards peptide substrates. This approach bears important potential for the determination of quaternary structures and assembly pathways of large oligomeric and symmetric complexes in biological systems.« less
Duffy, Anne; Lewitzka, Ute; Doucette, Sarah; Andreazza, Ana; Grof, Paul
2012-05-01
The study aims to provide a selective review of the literature pertaining to the hypothalamic-pituitary-adrenal (HPA) axis and immune abnormalities as informative biological indicators of vulnerability in bipolar disorder (BD). We summarize key findings relating to HPA axis and immunological abnormalities in bipolar patients and their high-risk offspring. Findings derive from a review of selected original papers published in the literature, and supplemented by papers identified through bibliography review. Neurobiological findings are discussed in the context of emergent BD in those at genetic risk and synthesized into a neurodevelopmental model of illness onset and progression. BD is associated with a number of genetic and possibly epigenetic abnormalities associated with neurotransmitter, hormonal and immunologically mediated neurobiological pathways. Data from clinical and high-risk studies implicate HPA axis and immune system abnormalities, which may represent inherited vulnerabilities important for the transition to illness onset. Post-mortem and clinical studies implicate intracellular signal transduction processes and disturbance in energy metabolism associated with established BD. Specifically, long-standing maladaptive alterations such as changes in neuronal systems may be mediated through changes in intracellular signalling pathways, oxidative stress, cellular energy metabolism and apoptosis associated with substantial burden of illness. Prospective longitudinal studies of endophenotypes and biomarkers such as HPA axis and immune abnormalities in high-risk offspring will be helpful to understand genetically mediated biological pathways associated with illness onset and progression. A clinical staging model describing emergent illness in those at genetic risk should facilitate this line of investigation. © 2011 Blackwell Publishing Asia Pty Ltd.
Gastrointestinal Toxicities With Combined Antiangiogenic and Stereotactic Body Radiation Therapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pollom, Erqi L.; Deng, Lei; Pai, Reetesh K.
2015-07-01
Combining the latest targeted biologic agents with the most advanced radiation technologies has been an exciting development in the treatment of cancer patients. Stereotactic body radiation therapy (SBRT) is an ablative radiation approach that has become established for the treatment of a variety of malignancies, and it has been increasingly used in combination with biologic agents, including those targeting angiogenesis-specific pathways. Multiple reports have emerged describing unanticipated toxicities arising from the combination of SBRT and angiogenesis-targeting agents, particularly of late luminal gastrointestinal toxicities. In this review, we summarize the literature describing these toxicities, explore the biological mechanism of action ofmore » toxicity with the combined use of antiangiogenic therapies, and discuss areas of future research, so that this combination of treatment modalities can continue to be used in broader clinical contexts.« less
Extraintestinal roles of bombesin-like peptides and their receptors: lung.
Qin, Xiao-Qun; Qu, Xiangping
2013-02-01
Description of the recent findings of the biological roles of bombesin-like peptides and their receptors in lungs. Gastrin-releasing peptide (GRP) was involved in the airway inflammation in murine models of airway hyperreactivity. The circulating proGRP could serve as a valuable tumor marker for small-cell lung cancers, and the plasma level of proGRP is more stable compared with that of serum proGRP. Recent studies also shed light on the intracellular signaling pathways of bombesin receptor subtype-3 (BRS-3) activation in cultured human lung cancer cells. The relevant biology of BLPs and their receptors in lung cancers and other lung diseases still remains largely unknown. With the development of several highly specific BRS-3 agonists, recent studies provided some insights into the biological effects of BRS-3 in lungs.
Campa, Molly; Mansouri, Bobbak; Warren, Richard; Menter, Alan
2016-03-01
The development of several highly effective biologic drugs in the past decade has revolutionized the treatment of moderate-to-severe plaque psoriasis. With increased understanding of the immunopathogenesis of psoriasis, the emphasis has turned toward more specific targets for psoriasis drugs. Although the complex immunological pathway of psoriasis is not yet completely understood, current models emphasize the significant importance of interleukin (IL)-23 and IL-17. Several biologic drugs targeting these cytokines are now in various stages of drug development. Drugs targeting IL-23 include BI-655066, briakinumab, guselkumab, tildrakizumab, and ustekinumab. Drugs targeting IL-17 include brodalumab, ixekizumab, and secukinumab. While many of these have shown safety and good efficacy in clinical trials of moderate-to-severe plaque psoriasis, long-term safety is still to be established.
Morrison, Michael; Moraia, Linda Briceño; Steele, Jane C
2016-01-01
This paper describes a traceability system developed for the Stem cells for Biological Assays of Novel drugs and prediCtive toxiCology consortium. The system combines records and labels that to biological material across geographical locations and scientific processes from sample donation to induced pluripotent stem cell line. The labeling system uses a unique identification number to link every aliquot of sample at every stage of the reprogramming pathway back to the original donor. Only staff at the clinical recruitment site can reconnect the unique identification number to the identifying details of a specific donor. This ensures the system meets ethical and legal requirements for protecting privacy while allowing full traceability of biological material. The system can be adapted to other projects and for use with different primary sample types.
Ponts, Nadia; Yang, Jianfeng; Chung, Duk-Won Doug; Prudhomme, Jacques; Girke, Thomas; Horrocks, Paul; Le Roch, Karine G
2008-06-11
Reversible modification of proteins through the attachment of ubiquitin or ubiquitin-like modifiers is an essential post-translational regulatory mechanism in eukaryotes. The conjugation of ubiquitin or ubiquitin-like proteins has been demonstrated to play roles in growth, adaptation and homeostasis in all eukaryotes, with perturbation of ubiquitin-mediated systems associated with the pathogenesis of many human diseases, including cancer and neurodegenerative disorders. Here we describe the use of an HMM search of functional Pfam domains found in the key components of the ubiquitin-mediated pathway necessary to activate and reversibly modify target proteins in eight apicomplexan parasitic protozoa for which complete or late-stage genome projects exist. In parallel, the same search was conducted on five model organisms, single-celled and metazoans, to generate data to validate both the search parameters employed and aid paralog classification in Apicomplexa. For each of the 13 species investigated, a set of proteins predicted to be involved in the ubiquitylation pathway has been identified and demonstrates increasing component members of the ubiquitylation pathway correlating with organism and genome complexity. Sequence homology and domain architecture analyses facilitated prediction of apicomplexan-specific protein function, particularly those involved in regulating cell division during these parasite's complex life cycles. This study provides a comprehensive analysis of proteins predicted to be involved in the apicomplexan ubiquitin-mediated pathway. Given the importance of such pathway in a wide variety of cellular processes, our data is a key step in elucidating the biological networks that, in part, direct the pathogenicity of these parasites resulting in a massive impact on global health. Moreover, apicomplexan-specific adaptations of the ubiquitylation pathway may represent new therapeutic targets for much needed drugs against apicomplexan parasites.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karam, Manale; Legay, Christine; Auclair, Christian
2012-03-10
Protein kinase D1, PKD1, is a novel serine/threonine kinase whose altered expression and dysregulation in many tumors as well as its activation by several mitogens suggest that this protein could regulate proliferation and tumorigenesis. Nevertheless, the precise signaling pathways used are still unclear and the potential direct role of PKD1 in tumor development and progression has not been yet investigated. In order to clarify the role of PKD1 in cell proliferation and tumorigenesis, we studied the effects of PKD1 overexpression in a human adenocarcinoma breast cancer cell line, MCF-7 cells. We demonstrated that overexpression of PKD1 specifically promotes MCF-7 cellmore » proliferation through accelerating G0/G1 to S phase transition of the cell cycle. Moreover, inhibition of endogenous PKD1 significantly reduced cell proliferation. Taken together, these results clearly strengthen the regulatory role of PKD1 in cell growth. We also demonstrated that overexpression of PKD1 specifically diminished serum- and anchorage-dependence for proliferation and survival in vitro and allowed MCF-7 cells to form tumors in vivo. Thus, all these data highlight the central role of PKD1 in biological processes which are hallmarks of malignant transformation. Analysis of two major signaling pathways implicated in MCF-7 cell proliferation showed that PKD1 overexpression significantly increased ERK1/2 phosphorylation state without affecting Akt phosphorylation. Moreover, PKD1 overexpression-stimulated cell proliferation and anchorage-independent growth were totally impaired by inhibition of the MEK/ERK kinase cascade. However, neither of these effects was affected by blocking the PI 3-kinase/Akt signaling pathway. Thus, the MEK/ERK signaling appears to be a determining pathway mediating the biological effects of PKD1 in MCF-7 cells. Taken together, all these data demonstrate that PKD1 overexpression increases the aggressiveness of MCF-7 breast cancer cells through enhancing their oncogenic properties and would, therefore, define PKD1 as a potentially new promising anti-tumor therapeutic target.« less
Yi, Minhan; Chen, Feng; Luo, Majing; Cheng, Yibin; Zhao, Huabin; Cheng, Hanhua; Zhou, Rongjia
2014-05-19
The Piwi-interacting RNA (piRNA) pathway is responsible for germline specification, gametogenesis, transposon silencing, and genome integrity. Transposable elements can disrupt genome and its functions. However, piRNA pathway evolution and its adaptation to transposon diversity in the teleost fish remain unknown. This article unveils evolutionary scene of piRNA pathway and its association with diverse transposons by systematically comparative analysis on diverse teleost fish genomes. Selective pressure analysis on piRNA pathway and miRNA/siRNA (microRNA/small interfering RNA) pathway genes between teleosts and mammals showed an accelerated evolution of piRNA pathway genes in the teleost lineages, and positive selection on functional PAZ (Piwi/Ago/Zwille) and Tudor domains involved in the Piwi-piRNA/Tudor interaction, suggesting that the amino acid substitutions are adaptive to their functions in piRNA pathway in the teleost fish species. Notably five piRNA pathway genes evolved faster in the swamp eel, a kind of protogynous hermaphrodite fish, than the other teleosts, indicating a differential evolution of piRNA pathway between the swamp eel and other gonochoristic fishes. In addition, genome-wide analysis showed higher diversity of transposons in the teleost fish species compared with mammals. Our results suggest that rapidly evolved piRNA pathway in the teleost fish is likely to be involved in the adaption to transposon diversity. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Ligand cluster-based protein network and ePlatton, a multi-target ligand finder.
Du, Yu; Shi, Tieliu
2016-01-01
Small molecules are information carriers that make cells aware of external changes and couple internal metabolic and signalling pathway systems with each other. In some specific physiological status, natural or artificial molecules are used to interact with selective biological targets to activate or inhibit their functions to achieve expected biological and physiological output. Millions of years of evolution have optimized biological processes and pathways and now the endocrine and immune system cannot work properly without some key small molecules. In the past thousands of years, the human race has managed to find many medicines against diseases by trail-and-error experience. In the recent decades, with the deepening understanding of life and the progress of molecular biology, researchers spare no effort to design molecules targeting one or two key enzymes and receptors related to corresponding diseases. But recent studies in pharmacogenomics have shown that polypharmacology may be necessary for the effects of drugs, which challenge the paradigm, 'one drug, one target, one disease'. Nowadays, cheminformatics and structural biology can help us reasonably take advantage of the polypharmacology to design next-generation promiscuous drugs and drug combination therapies. 234,591 protein-ligand interactions were extracted from ChEMBL. By the 2D structure similarity, 13,769 ligand emerged from 156,151 distinct ligands which were recognized by 1477 proteins. Ligand cluster- and sequence-based protein networks (LCBN, SBN) were constructed, compared and analysed. For assisting compound designing, exploring polypharmacology and finding possible drug combination, we integrated the pathway, disease, drug adverse reaction and the relationship of targets and ligand clusters into the web platform, ePlatton, which is available at http://www.megabionet.org/eplatton. Although there were some disagreements between the LCBN and SBN, communities in both networks were largely the same with normalized mutual information at 0.9. The study of target and ligand cluster promiscuity underlying the LCBN showed that light ligand clusters were more promiscuous than the heavy one and that highly connected nodes tended to be protein kinases and involved in phosphorylation. ePlatton considerably reduced the redundancy of the ligand set of targets and made it easy to deduce the possible relationship between compounds and targets, pathways and side effects. ePlatton behaved reliably in validation experiments and also fast in virtual screening and information retrieval.Graphical abstractCluster exemplars and ePlatton's mechanism.
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.
Alvarez-Ponce, David; Guirao-Rico, Sara; Orengo, Dorcas J; Segarra, Carmen; Rozas, Julio; Aguadé, Montserrat
2012-01-01
The IT-insulin/target of rapamycin (TOR)-signal transduction pathway is a relatively well-characterized pathway that plays a central role in fundamental biological processes. Network-level analyses of DNA divergence in Drosophila and vertebrates have revealed a clear gradient in the levels of purifying selection along this pathway, with the downstream genes being the most constrained. Remarkably, this feature does not result from factors known to affect selective constraint such as gene expression, codon bias, protein length, and connectivity. The present work aims to establish whether the selective constraint gradient detected along the IT pathway at the between-species level can also be observed at a shorter time scale. With this purpose, we have surveyed DNA polymorphism in Drosophila melanogaster and divergence from D. simulans along the IT pathway. Our network-level analysis shows that DNA polymorphism exhibits the same polarity in the strength of purifying selection as previously detected at the divergence level. This equivalent feature detected both within species and between closely and distantly related species points to the action of a general mechanism, whose action is neither organism specific nor evolutionary time dependent. The detected polarity would be, therefore, intrinsic to the IT pathway architecture and function.
Evolution of JAK-STAT Pathway Components: Mechanisms and Role in Immune System Development
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
Proteomics and metabolomics in ageing research: from biomarkers to systems biology.
Hoffman, Jessica M; Lyu, Yang; Pletcher, Scott D; Promislow, Daniel E L
2017-07-15
Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
Proteomics and metabolomics in ageing research: from biomarkers to systems biology
Hoffman, Jessica M.; Lyu, Yang; Pletcher, Scott D.; Promislow, Daniel E.L.
2017-01-01
Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible ‘biomarkers’, which are predictors of one’s biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying ‘endophenotypes’ in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity. PMID:28698311
Previous literature on the biological effects of engineered nanomaterials has focused largely on oxidative stress and inflammation endpoints without further investigating potential pathways. Here we examine time-sensitive biological response pathways affected by engineered nanoma...
Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells
Burnik Papler, Tanja; Vrtacnik Bokal, Eda; Maver, Ales; Kopitar, Andreja Natasa; Lovrečić, Luca
2015-01-01
Specific gene expression in oocytes and its surrounding cumulus (CC) and granulosa (GC) cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10−4); of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2), higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK), higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology. PMID:26313571
Understanding Biological Rates and their Temperature Dependence, from Enzymes to Ecosystems
NASA Astrophysics Data System (ADS)
Prentice, E.; Arcus, V. L.
2017-12-01
Temperature responses over various scales in biological systems follow a similar pattern; negative curvature results in an optimum temperature (Topt) for activity/growth/turnover, with decreases in rates on either side of Topt. Previously this downturn in rates at high temperatures has been attributed to enzyme denaturation, where a failing of the basic driving units of metabolism was used to describe curvature at the enzyme and organism level. However, recent developments in our understanding of the factors governing enzyme rates at different temperatures have guided a new understanding of the responses of biological systems. Enzymes catalyse reactions by driving the substrate through a high energy species, which is tightly bound to the enzyme. Macromolecular rate theory (MMRT) has recently been developed to account for the changes in the system brought about by this tight binding, specifically the change in the physical parameter heat capacity (ΔCǂp), and the effect this has on the temperature dependence of enzyme reactions. A negative ΔCǂp imparts the signature negative curvature to rates in the absence of denaturation, and finds that Topt, ΔCǂp and curvature are all correlated, placing constraints on biological systems. The simplest of cells comprise thousands of enzymatically catalysed reactions, functioning in series and in parallel in metabolic pathways to determine the overall growth rate of an organism. Intuitively, the temperature effects of enzymes play a role in determining the overall temperature dependence of an organism, in tandem with cellular level regulatory responses. However, the effect of individual Topt values and curvature on overall pathway behaviour is less apparent. Here, this is investigated in the context of MMRT through the in vitro characterisation of a six-step metabolic pathway to understand the steps in isolation and functioning in series. Pathway behaviour is found to be approximately an average of the properties of the individual steps, indicating all enzymes have an influence on organism temperature dependence. This has implications for our understanding of how organisms respond to fluctuations in environmental temperature.
Phylogenetic Origin and Diversification of RNAi Pathway Genes in Insects.
Dowling, Daniel; Pauli, Thomas; Donath, Alexander; Meusemann, Karen; Podsiadlowski, Lars; Petersen, Malte; Peters, Ralph S; Mayer, Christoph; Liu, Shanlin; Zhou, Xin; Misof, Bernhard; Niehuis, Oliver
2016-12-01
RNA interference (RNAi) refers to the set of molecular processes found in eukaryotic organisms in which small RNA molecules mediate the silencing or down-regulation of target genes. In insects, RNAi serves a number of functions, including regulation of endogenous genes, anti-viral defense, and defense against transposable elements. Despite being well studied in model organisms, such as Drosophila, the distribution of core RNAi pathway genes and their evolution in insects is not well understood. Here we present the most comprehensive overview of the distribution and diversity of core RNAi pathway genes across 100 insect species, encompassing all currently recognized insect orders. We inferred the phylogenetic origin of insect-specific RNAi pathway genes and also identified several hitherto unrecorded gene expansions using whole-body transcriptome data from the international 1KITE (1000 Insect Transcriptome Evolution) project as well as other resources such as i5K (5000 Insect Genome Project). Specifically, we traced the origin of the double stranded RNA binding protein R2D2 to the last common ancestor of winged insects (Pterygota), the loss of Sid-1/Tag-130 orthologs in Antliophora (fleas, flies and relatives, and scorpionflies in a broad sense), and confirm previous evidence for the splitting of the Argonaute proteins Aubergine and Piwi in Brachyceran flies (Diptera, Brachycera). Our study offers new reference points for future experimental research on RNAi-related pathway genes in insects. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Network design and analysis for multi-enzyme biocatalysis.
Blaß, Lisa Katharina; Weyler, Christian; Heinzle, Elmar
2017-08-10
As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasingly complex. The manual design of multi-step biosynthesis routes involving enzymes from different organisms is very challenging. To harness the full enzymatic potential, we developed a computational tool for the directed design of biosynthetic production pathways for multi-step catalysis with in vitro enzyme cascades, cell hydrolysates and permeabilized cells. We present a method which encompasses the reconstruction of a genome-scale pan-organism metabolic network, path-finding and the ranking of the resulting pathway candidates for proposing suitable synthesis pathways. The network is based on reaction and reaction pair data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the thermodynamics calculator eQuilibrator. The pan-organism network is especially useful for finding the most suitable pathway to a target metabolite from a thermodynamic or economic standpoint. However, our method can be used with any network reconstruction, e.g. for a specific organism. We implemented a path-finding algorithm based on a mixed-integer linear program (MILP) which takes into account both topology and stoichiometry of the underlying network. Unlike other methods we do not specify a single starting metabolite, but our algorithm searches for pathways starting from arbitrary start metabolites to a target product of interest. Using a set of biochemical ranking criteria including pathway length, thermodynamics and other biological characteristics such as number of heterologous enzymes or cofactor requirement, it is possible to obtain well-designed meaningful pathway alternatives. In addition, a thermodynamic profile, the overall reactant balance and potential side reactions as well as an SBML file for visualization are generated for each pathway alternative. We present an in silico tool for the design of multi-enzyme biosynthetic production pathways starting from a pan-organism network. The method is highly customizable and each module can be adapted to the focus of the project at hand. This method is directly applicable for (i) in vitro enzyme cascades, (ii) cell hydrolysates and (iii) permeabilized cells.
Jasin, Maria; Haber, James E
2016-08-01
DNA double-strand breaks (DSBs) are dangerous lesions that if not properly repaired can lead to genomic change or cell death. Organisms have developed several pathways and have many factors devoted to repairing DSBs, which broadly occurs by homologous recombination, which relies on an identical or homologous sequence to template repair, or nonhomologous end-joining. Much of our understanding of these repair mechanisms has come from the study of induced DNA cleavage by site-specific endonucleases. In addition to their biological role, these cellular pathways can be co-opted for gene editing to study gene function or for gene therapy or other applications. While the first gene editing experiments were done more than 20 years ago, the recent discovery of RNA-guided endonucleases has simplified approaches developed over the years to make gene editing an approach that is available to the entire biomedical research community. Here, we review DSB repair mechanisms and site-specific cleavage systems that have provided insight into these mechanisms and led to the current gene editing revolution. Copyright © 2016. Published by Elsevier B.V.
Jasin, Maria; Haber, James E.
2017-01-01
DNA double-strand breaks (DSBs) are dangerous lesions that if not properly repaired can lead to genomic change or cell death. Organisms have developed several pathways and have many factors devoted to repairing DSBs, which broadly occur by homologous recombination that relies on an identical or homologous sequence to template repair, or nonhomologous end-joining. Much of our understanding of these repair mechanisms has come from the study of induced DNA cleavage by site-specific endonucleases. In addition to their biological role, these cellular pathways can be co-opted for gene editing to study gene function or for gene therapy or other applications. While the first gene editing experiments were done more than 20 years ago, the recent discovery of RNA-guided endonucleases has simplified approaches developed over the years to make gene editing an approach that is available to the entire biomedical research community. Here, we review DSB repair mechanisms and site-specific cleavage systems that have provided insight into these mechanisms and led to the current gene editing revolution. PMID:27261202
EcoFlex: A Multifunctional MoClo Kit for E. coli Synthetic Biology.
Lai, Hung-En; Moore, Simon; Polizzi, Karen; Freemont, Paul
2018-01-01
Development of advanced synthetic biology tools is always in demand since they act as a platform technology to enable rapid prototyping of biological constructs in a high-throughput manner. EcoFlex is a modular cloning (MoClo) kit for Escherichia coli and is based on the Golden Gate principles, whereby Type IIS restriction enzymes (BsaI, BsmBI, BpiI) are used to construct modular genetic elements (biological parts) in a bottom-up approach. Here, we describe a collection of plasmids that stores various biological parts including promoters, RBSs, terminators, ORFs, and destination vectors, each encoding compatible overhangs allowing hierarchical assembly into single transcription units or a full-length polycistronic operon or biosynthetic pathway. A secondary module cloning site is also available for pathway optimization, in order to limit library size if necessary. Here, we show the utility of EcoFlex using the violacein biosynthesis pathway as an example.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Hua; Sichuan Tourism College, Chengdu, 610000, Sichuan; He, Xiujing
The heavy metal cadmium (Cd), acts as a widespread environmental contaminant, which has shown to adversely affect human health, food safety and ecosystem safety in recent years. However, research on how plant respond to various kinds of heavy metal stress is scarcely reported, especially for understanding of complex molecular regulatory mechanisms and elucidating the gene networks of plant respond to Cd stress. Here, transcriptomic changes during Mo17 and B73 seedlings development responsive to Cd pollution were investigated and comparative RNAseq-based approach in both genotypes were performed. 115 differential expression genes (DEGs) with significant alteration in expression were found co-modulated inmore » both genotypes during the maize seedling development; of those, most of DGEs were found comprised of stress and defense responses proteins, transporters, as well as transcription factors, such as thaumatin-like protein, ZmOPR2 and ZmOPR5. More interestingly, genotype-specific transcriptional factors changes induced by Cd stress were found contributed to the regulatory mechanism of Cd sensitivity in both different genotypes. Moreover, 12 co-expression modules associated with specific biological processes or pathways (M1 to M12) were identified by consensus co-expression network. These results will expand our understanding of complex molecular mechanism of response and defense to Cd exposure in maize seedling roots. - Highlights: • Transcriptomic changes responsive to Cd pollution using comparative RNAseq-based approach. • 115 differential expression genes (DEGs) were found co-modulated in both genotypes. • Most of DGEs belong to stress and defense responses proteins, transporters, transcription factors. • 12 co-expression modules associated with specific biological processes or pathways. • Genotype-specific transcriptional factors changes induced by Cd stress were found.« less
Diaz de Cerio, Oihane; Bilbao, Eider; Ruiz, Pamela; Pardo, Belén G; Martínez, Paulino; Cajaraville, Miren P; Cancio, Ibon
2017-02-01
Oil and chemical spills in the marine environment, although sporadic, are highly dangerous to biota inhabiting coastal and estuarine areas. Effects of spilled compounds in exposed organisms occur at different biological organization levels: from molecular, cellular or tissue levels to the physiological one. The present study aims to determine the specific hepatic gene transcription profiles observed in turbot juveniles under exposure to fuel oil n °6 and styrene vs controls using an immune enriched turbot (Scophthalmus maximus) oligo-microarray containing 2716 specific gene probes. After 3 days of exposure, fuel oil specifically induced aryl hydrocarbon receptor mediated transcriptional response through up-regulation of genes, such as ahrr and cyp1a1. More gene transcripts were regulated after 14 days of exposure involved in ribosomal biosynthesis, immune modulation, and oxidative response among the most significantly regulated functional pathways. On the contrary, gene transcription alterations caused by styrene did not highlight any significantly regulated molecular or metabolic pathway. This was also previously reported at cell and tissue level where no apparent responses were distinguishable. For the fuel oil experiment, obtained specific gene profiles could be related to changes in cell-tissue organization in the same individuals, such as increased hepatocyte vacuolization, decrease in melano-macrophage centers and the regulation of leukocyte numbers. In conclusion, the mode of action reflected by gene transcription profiles analyzed hereby in turbot livers could be linked with the responses previously reported at higher biological organization levels. Molecular alterations described hereby could be preceding observed alterations at cell and tissue levels. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hinck, Jo E.; Linder, Greg L.; Finger, Susan E.; Little, Edward E.; Tillitt, Donald E.; Kuhne, Wendy
2010-01-01
This chapter compiles available chemical and radiation toxicity information for plants and animals from the scientific literature on naturally occurring uranium and associated radionuclides. Specifically, chemical and radiation hazards associated with radionuclides in the uranium decay series including uranium, thallium, thorium, bismuth, radium, radon, protactinium, polonium, actinium, and francium were the focus of the literature compilation. In addition, exposure pathways and a food web specific to the segregation areas were developed. Major biological exposure pathways considered were ingestion, inhalation, absorption, and bioaccumulation, and biota categories included microbes, invertebrates, plants, fishes, amphibians, reptiles, birds, and mammals. These data were developed for incorporation into a risk assessment to be conducted as part of an environmental impact statement for the Bureau of Land Management, which would identify representative plants and animals and their relative sensitivities to exposure of uranium and associated radionuclides. This chapter provides pertinent information to aid in the development of such an ecological risk assessment but does not estimate or derive guidance thresholds for radionuclides associated with uranium. Previous studies have not attempted to quantify the risks to biota caused directly by the chemical or radiation releases at uranium mining sites, although some information is available for uranium mill tailings and uranium mine closure activities. Research into the biological impacts of uranium exposure is strongly biased towards human health and exposure related to enriched or depleted uranium associated with the nuclear energy industry rather than naturally occurring uranium associated with uranium mining. Nevertheless, studies have reported that uranium and other radionuclides can affect the survival, growth, and reproduction of plants and animals. Exposure to chemical and radiation hazards is influenced by a plant’s or an animal’s life history and surrounding environment. Various species of plants, invertebrates, fishes, amphibians, reptiles, birds, and mammals found in the segregation areas that are considered species of concern by State and Federal agencies were included in the development of the site-specific food web. The utilization of subterranean habitats (burrows in uranium-rich areas, burrows in waste rock piles or reclaimed mining areas, mine tunnels) in the seasonally variable but consistently hot, arid environment is of particular concern in the segregation areas. Certain species of reptiles, amphibians, birds, and mammals in the segregation areas spend significant amounts of time in burrows where they can inhale or ingest uranium and other radionuclides through digging, eating, preening, and hibernating. Herbivores may also be exposed though the ingestion of radionuclides that have been aerially deposited on vegetation. Measured tissues concentrations of uranium and other radionuclides are not available for any species of concern in the segregation areas. The sensitivity of these animals to uranium exposure is unknown based on the existing scientific literature, and species-specific uranium presumptive effects levels were only available for two endangered fish species known to inhabit the segregation areas. Overall, the chemical toxicity data available for biological receptors of concern were limited, although chemical and radiation toxicity guidance values are available from several sources. However, caution should be used when directly applying these values to northern Arizona given the unique habitat and life history strategies of biological receptors in the segregation areas and the fact that some guidance values are based on models rather than empirical (laboratory or field) data. No chemical toxicity information based on empirical data is available for reptiles, birds, or wild mammals; therefore, the risks associated with uranium and other radionuclides are unknown for these biota.
Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks
USDA-ARS?s Scientific Manuscript database
Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...
2014-01-01
Background Neurotrophin-4 (NT-4) and brain derived neurotrophic factor (BDNF) bind to the same receptor, Ntrk2/TrkB, but play distinct roles in the development of the rodent gustatory system. However, the mechanisms underlying these processes are lacking. Results Here, we demonstrate, in vivo, that single or combined point mutations in major adaptor protein docking sites on TrkB receptor affect specific aspects of the mouse gustatory development, known to be dependent on BDNF or NT-4. In particular, mice with a mutation in the TrkB-SHC docking site had reduced gustatory neuron survival at both early and later stages of development, when survival is dependent on NT-4 and BDNF, respectively. In addition, lingual innervation and taste bud morphology, both BDNF-dependent functions, were altered in these mutants. In contrast, mutation of the TrkB-PLCγ docking site alone did not affect gustatory neuron survival. Moreover, innervation to the tongue was delayed in these mutants and taste receptor expression was altered. Conclusions We have genetically dissected pathways activated downstream of the TrkB receptor that are required for specific aspects of the taste system controlled by the two neurotrophins NT-4 and BDNF. In addition, our results indicate that TrkB also regulate the expression of specific taste receptors by distinct signalling pathways. These results advance our knowledge of the biology of the taste system, one of the fundamental sensory systems crucial for an organism to relate to the environment. PMID:25256039
Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow
Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...
2016-05-19
Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less
Huang, Cai; Mipam, Tserang Donko; Li, Jian
2016-01-01
Background Yaks (Bos grunniens) are endemic species that can adapt well to thin air, cold temperatures, and high altitude. These species can survive in harsh plateau environments and are major source of animal production for local residents, being an important breed in the Qinghai–Tibet Plateau. However, compared with ordinary cattle that live in the plains, yaks generally have lower fertility. Investigating the basic physiological molecular features of yak ovary and identifying the biological events underlying the differences between the ovaries of yak and plain cattle is necessary to understand the specificity of yak reproduction. Therefore, RNA-seq technology was applied to analyze transcriptome data comparatively between the yak and plain cattle estrous ovaries. Results After deep sequencing, 3,653,032 clean reads with a total of 4,828,772,880 base pairs were obtained from yak ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome, among which, 12,731 and 14,631 genes were assigned to Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, comparison of yak and cattle ovary transcriptome data revealed that 1307 genes were significantly and differentially expressed between the two libraries, wherein 661 genes were upregulated and 646 genes were downregulated in yak ovary. Functional analysis showed that the differentially expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. GO annotations indicated that the genes related to “cell adhesion,” “hormonal” biological processes, and “calcium ion binding,” “cation transmembrane transport” molecular events were significantly active. KEGG pathway analysis showed that the “complement and coagulation cascade” pathway was the most enriched in yak ovary transcriptome data, followed by the “cytochrome P450” related and “ECM–receptor interaction” pathways. Moreover, several novel pathways, such as “circadian rhythm,” were significantly enriched despite having no evident associations with the reproductive function. Conclusion Our findings provide a molecular resource for further investigation of the general molecular mechanism of yak ovary and offer new insights to understand comprehensively the specificity of yak reproduction. PMID:27044040
atBioNet--an integrated network analysis tool for genomics and biomarker discovery.
Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida
2012-07-20
Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.
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.
Precision control of recombinant gene transcription for CHO cell synthetic biology.
Brown, Adam J; James, David C
2016-01-01
The next generation of mammalian cell factories for biopharmaceutical production will be genetically engineered to possess both generic and product-specific manufacturing capabilities that may not exist naturally. Introduction of entirely new combinations of synthetic functions (e.g. novel metabolic or stress-response pathways), and retro-engineering of existing functional cell modules will drive disruptive change in cellular manufacturing performance. However, before we can apply the core concepts underpinning synthetic biology (design, build, test) to CHO cell engineering we must first develop practical and robust enabling technologies. Fundamentally, we will require the ability to precisely control the relative stoichiometry of numerous functional components we simultaneously introduce into the host cell factory. In this review we discuss how this can be achieved by design of engineered promoters that enable concerted control of recombinant gene transcription. We describe the specific mechanisms of transcriptional regulation that affect promoter function during bioproduction processes, and detail the highly-specific promoter design criteria that are required in the context of CHO cell engineering. The relative applicability of diverse promoter development strategies are discussed, including re-engineering of natural sequences, design of synthetic transcription factor-based systems, and construction of synthetic promoters. This review highlights the potential of promoter engineering to achieve precision transcriptional control for CHO cell synthetic biology. Copyright © 2015. Published by Elsevier Inc.
Komor, Alexis C.; Schneider, Curtis J.; Weidmann, Alyson G.; Barton, Jacqueline K.
2013-01-01
Deficiencies in the mismatch repair (MMR) pathway are associated with several types of cancers, as well as resistance to commonly used chemotherapeutics. Rhodium metalloinsertors have been found to bind DNA mismatches with high affinity and specificity in vitro, and also exhibit cell-selective cytotoxicity, targeting MMR-deficient cells over MMR-proficient cells. Ten distinct metalloinsertors with varying lipophilicities have been synthesized and their mismatch binding affinities and biological activities determined. Although DNA photocleavage experiments demonstrate that their binding affinities are quite similar, their cell-selective antiproliferative and cytotoxic activities vary significantly. Inductively coupled plasma mass spectrometry (ICP-MS) experiments have uncovered a relationship between the subcellular distribution of these metalloinsertors and their biological activities. Specifically, we find that all of our metalloinsertors localize in the nucleus at sufficient concentrations for binding to DNA mismatches. However, the metalloinsertors with high rhodium localization in the mitochondria show toxicity that is not selective for MMR-deficient cells, whereas metalloinsertors with less mitochondrial rhodium show activity that is highly selective for MMR-deficient versus proficient cells. This work supports the notion that specific targeting of the metalloinsertors to nuclear DNA gives rise to their cell-selective cytotoxic and antiproliferative activities. The selectivity in cellular targeting depends upon binding to mismatches in genomic DNA. PMID:23137296
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk
2014-10-09
To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less
Doran, Anthony G; Berry, Donagh P; Creevey, Christopher J
2014-10-01
Four traits related to carcass performance have been identified as economically important in beef production: carcass weight, carcass fat, carcass conformation of progeny and cull cow carcass weight. Although Holstein-Friesian cattle are primarily utilized for milk production, they are also an important source of meat for beef production and export. Because of this, there is great interest in understanding the underlying genomic structure influencing these traits. Several genome-wide association studies have identified regions of the bovine genome associated with growth or carcass traits, however, little is known about the mechanisms or underlying biological pathways involved. This study aims to detect regions of the bovine genome associated with carcass performance traits (employing a panel of 54,001 SNPs) using measures of genetic merit (as predicted transmitting abilities) for 5,705 Irish Holstein-Friesian animals. Candidate genes and biological pathways were then identified for each trait under investigation. Following adjustment for false discovery (q-value < 0.05), 479 quantitative trait loci (QTL) were associated with at least one of the four carcass traits using a single SNP regression approach. Using a Bayesian approach, 46 QTL were associated (posterior probability > 0.5) with at least one of the four traits. In total, 557 unique bovine genes, which mapped to 426 human orthologs, were within 500kbs of QTL found associated with a trait using the Bayesian approach. Using this information, 24 significantly over-represented pathways were identified across all traits. The most significantly over-represented biological pathway was the peroxisome proliferator-activated receptor (PPAR) signaling pathway. A large number of genomic regions putatively associated with bovine carcass traits were detected using two different statistical approaches. Notably, several significant associations were detected in close proximity to genes with a known role in animal growth 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.
Vrahatis, Aristidis G; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios
2017-01-01
In the era of Systems Biology and growing flow of omics experimental data from high throughput techniques, experimentalists are in need of more precise pathway-based tools to unravel the inherent complexity of diseases and biological processes. Subpathway-based approaches are the emerging generation of pathway-based analysis elucidating the biological mechanisms under the perspective of local topologies onto a complex pathway network. Towards this orientation, we developed PerSub, a graph-based algorithm which detects subpathways perturbed by a complex disease. The perturbations are imprinted through differentially expressed and co-expressed subpathways as recorded by RNA-seq experiments. Our novel algorithm is applied on data obtained from a real experimental study and the identified subpathways provide biological evidence for the brain aging.
BioCore Guide: A Tool for Interpreting the Core Concepts of Vision and Change for Biology Majors
Freeman, Scott; Wenderoth, Mary Pat; Crowe, Alison J.
2014-01-01
Vision and Change in Undergraduate Biology Education outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and created a Vision and Change BioCore Guide—a set of general principles and specific statements that expand upon the core concepts, creating a framework that biology departments can use to align with the goals of Vision and Change. We used a grassroots approach to generate the BioCore Guide, beginning with faculty ideas as the basis for an iterative process that incorporated feedback from more than 240 biologists and biology educators at a diverse range of academic institutions throughout the United States. The final validation step in this process demonstrated strong national consensus, with more than 90% of respondents agreeing with the importance and scientific accuracy of the statements. It is our hope that the BioCore Guide will serve as an agent of change for biology departments as we move toward transforming undergraduate biology education. PMID:26086653
Mirror mechanism and dedicated circuits are the scaffold for mirroring processes.
Fogassi, Leonardo
2014-04-01
In the past decade many studies have demonstrated the existence of a mirror mechanism that matches the sensory representation of a biological stimulus with its somatomotor and visceromotor representation. This mechanism, likely phylogenetically very old, explains several types of mirroring behaviours, at different levels of complexity. The presence in primates of dedicated neuroanatomical pathways for specific sensorimotor integrations processes implies, at least in the primate lineage, a hard-wired mirror mechanism for social cognitive functions.
Future biologic therapies in asthma.
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.