A systems biology approach for understanding the transcriptome wide modulation of cardiac gene expression under oxidative environment during early stage of cardiovascular remodeling in developing embryo
Ontology highlight
ABSTRACT:
ORGANISM(S): Gallus gallus
PROVIDER: GSE111840 | GEO | 2018/03/21
REPOSITORIES: GEO
Similar Datasets
Project description:A systems biology approach for understanding the transcriptome wide modulation of cardiac gene expression under oxidative environment during early stage of cardiovascular remodeling in developing embryo
| PRJNA439312 | ENA
Project description:Organotin compounds are highly persistent organic pollutants that bioaccumulate in marine biota, behaving as potent endocrine disruptors. Tributyltin (TBT) has been described as an environmental obesogen, as it contributes in mammals to lipid accumulation in a mechanism mediated by PPARγ and RXR. With the aim of studying the molecular mechanisms that elicit TBT-induced pathogenesis in fish, thicklip grey mullets Chelon labrosus were exposed to low (10 ng/L) and high (500 ng/L) TBT concentrations for 1, 7 and 21 days, and gene transcription and metabolome profiles were studied. With this purpose, the multitissue transcriptome of mullet was sequenced by 454 pyrosequencing obtaining 126 Mb of sequence information. Assembly and annotation allowed spotting 8330 gene signatures on an oligonucleotide microarray that was used to identify hepatic gene transcription profiles specific to each TBT exposure set-up. Functional pathway analysis revealed that early profiles were characterized by genes related to response to organic substances and to oxidative stress and glucose metabolic processes. After 21 days of exposure, enriched GO terms in both concentrations were related to lipid homeostasis with a significant regulation of steroid metabolic and cholesterol biosynthetic processes. Also, the androgen receptor signalling pathway was regulated while PPAR signalling appeared as the most significantly regulated KEGG pathway. Neutral lipid accumulation measured by Oil-Red-O histochemistry did not show any treatment-related effect but hepatic and plasma NMR and GC-MS metabolomic analysis revealed distinctive metabolites. Aqueous profiles were characterised by lactate, glucose and alanine while GC-MS revealed a whole set of discriminating polyunsaturated fatty acids. Thus, TBT pathogenesis involves alterations of lipid metabolism through a mechanism that could involve PPARγ-regulated processes confirming the obesogen hypothesis for TBT in fish. Thicklip grey mullets were exposed to tributyltin (TBT). 3 treatments: control, TBT low dose (10ng/L), TBT high dose (500ng/L); 3 sampling times: 1 day, 1 week, 3 weeks. 6 mullets were dissected in each sampling point and group.
2016-07-31 | E-GEOD-36811 | biostudies-arrayexpress
Project description:Traditional Chinese Medicine (TCM) involves a broad range of empirical testing and refinement and plays an important role in the health maintenance for people all over the world. However, due to the complexity of Chinese herbs, a full understanding of TCM's action mechanisms is still unavailable despite plenty of successful applications of TCM in the treatment of various diseases, including especially cardiovascular diseases (CVD), one of the leading causes of death. Thus in the present work, by incorporating the chemical predictors, target predictors and network construction approaches, an integrated system of TCM has been constructed to systematically uncover the underlying action mechanisms of TCM. From three representative Chinese herbs, i.e., Ligusticum chuanxiong Hort., Dalbergia odorifera T. Chen and Corydalis yanhusuo WT Wang which have been widely used in CVD treatment, by combinational use of drug absorption, distribution, metabolism and excretion (ADME) screening and network pharmacology techniques, we have generated 64 bioactive ingredients and identified 54 protein targets closely associated with CVD, of which 29 are common targets (52.7%) of the three herbs. The result provides new information on the efficiency of the Chinese herbs for the treatment of CVD and also explains one of the basic theories of TCM, i.e., "multiple herbal drugs can treat one disease". The predicted potential targets were then mapped to target-disease and target-signal pathway connections, which revealed the relationships of the active ingredients with their potential targets, diseases and signal systems. This means that for the first time, the action mechanism of these three important Chinese herbs for the treatment of CVD is uncovered, by generating and identifying both their active ingredients and novel targets specifically related to CVD, which clarifies some of the common conceptions in TCM, and thus provides clues to modernize such specific herbal medicines.
| S-EPMC3497338 | biostudies-literature
Project description:Organotin compounds are highly persistent organic pollutants that bioaccumulate in marine biota, behaving as potent endocrine disruptors. Tributyltin (TBT) has been described as an environmental obesogen, as it contributes in mammals to lipid accumulation in a mechanism mediated by PPARγ and RXR. With the aim of studying the molecular mechanisms that elicit TBT-induced pathogenesis in fish, thicklip grey mullets Chelon labrosus were exposed to low (10 ng/L) and high (500 ng/L) TBT concentrations for 1, 7 and 21 days, and gene transcription and metabolome profiles were studied. With this purpose, the multitissue transcriptome of mullet was sequenced by 454 pyrosequencing obtaining 126 Mb of sequence information. Assembly and annotation allowed spotting 8330 gene signatures on an oligonucleotide microarray that was used to identify hepatic gene transcription profiles specific to each TBT exposure set-up. Functional pathway analysis revealed that early profiles were characterized by genes related to response to organic substances and to oxidative stress and glucose metabolic processes. After 21 days of exposure, enriched GO terms in both concentrations were related to lipid homeostasis with a significant regulation of steroid metabolic and cholesterol biosynthetic processes. Also, the androgen receptor signalling pathway was regulated while PPAR signalling appeared as the most significantly regulated KEGG pathway. Neutral lipid accumulation measured by Oil-Red-O histochemistry did not show any treatment-related effect but hepatic and plasma NMR and GC-MS metabolomic analysis revealed distinctive metabolites. Aqueous profiles were characterised by lactate, glucose and alanine while GC-MS revealed a whole set of discriminating polyunsaturated fatty acids. Thus, TBT pathogenesis involves alterations of lipid metabolism through a mechanism that could involve PPARγ-regulated processes confirming the obesogen hypothesis for TBT in fish.
2016-07-31 | GSE36811 | GEO
Project description:BACKGROUND: The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. RESULTS: With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. CONCLUSIONS: This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.
| S-EPMC4331812 | biostudies-literature
Project description:Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium as a significant factor in development of cancer, showing that understanding lithium action is of high importance. In this paper we undertake first steps toward a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with cancer. This work integrates information from two important databases, STRING, and KEGG pathways. We find that for the majority of cancer pathways the mutual enrichment is statistically highly significant, reinforcing previous lines of evidence that lithium is an important influence on cancer.
| S-EPMC6503094 | biostudies-literature
Project description:E. coli frequently encounters oxidative stress both in its natural environment or in industrial biotechnology. Elucidating the mechanisms behind tolerance to oxidative stress would be beneficial for understanding pathogenesis as well as improving production strain fitness. We make use of adaptive laboratory evolution to develop two strains of E. coli which exhibit 500% increased tolerance to paraquat stress compared to wild type. Evolved strains tolerate oxidative stress by reduction of flux through TCA, dyregulation of iron-uptake genes, and up-regulation of cell motility or iron-sulfur cluster repair genes.
2022-07-07 | GSE134256 | GEO
Project description:The considerable difficulty encountered in reproducing the results of published dynamical models limits validation, exploration and reuse of this increasingly large biomedical research resource. To address this problem, we have developed Tellurium Notebook, a software system for model authoring, simulation, and teaching that facilitates building reproducible dynamical models and reusing models by 1) providing a notebook environment which allows models, Python code, and narrative to be intermixed, 2) supporting the COMBINE archive format during model development for capturing model information in an exchangeable format and 3) enabling users to easily simulate and edit public COMBINE-compliant models from public repositories to facilitate studying model dynamics, variants and test cases. Tellurium Notebook, a Python-based Jupyter-like environment, is designed to seamlessly inter-operate with these community standards by automating conversion between COMBINE standards formulations and corresponding in-line, human-readable representations. Thus, Tellurium brings to systems biology the strategy used by other literate notebook systems such as Mathematica. These capabilities allow users to edit every aspect of the standards-compliant models and simulations, run the simulations in-line, and re-export to standard formats. We provide several use cases illustrating the advantages of our approach and how it allows development and reuse of models without requiring technical knowledge of standards. Adoption of Tellurium should accelerate model development, reproducibility and reuse.
| S-EPMC6021116 | biostudies-literature
Project description:Salinity is one of the most common abiotic stresses in agriculture production. Salt tolerance of rice (Oryza sativa) is an important trait controlled by various genes. The mechanism of rice salt tolerance, currently with limited understanding, is of great interest to molecular breeding in improving grain yield. In this study, a gene regulatory network of rice salt tolerance is constructed using a systems biology approach with a number of novel computational methods. We developed an improved volcano plot method in conjunction with a new machine-learning method for gene selection based on gene expression data and applied the method to choose genes related to salt tolerance in rice. The results were then assessed by quantitative trait loci (QTL), co-expression and regulatory binding motif analysis. The selected genes were constructed into a number of network modules based on predicted protein interactions including modules of phosphorylation activity, ubiquity activity, and several proteinase activities such as peroxidase, aspartic proteinase, glucosyltransferase, and flavonol synthase. All of these discovered modules are related to the salt tolerance mechanism of signal transduction, ion pump, abscisic acid mediation, reactive oxygen species scavenging and ion sequestration. We also predicted the three-dimensional structures of some crucial proteins related to the salt tolerance QTL for understanding the roles of these proteins in the network. Our computational study sheds some new light on the mechanism of salt tolerance and provides a systems biology pipeline for studying plant traits in general.
| S-EPMC3676415 | biostudies-literature
Project description:Here we present Tellurium, a Python-based environment for model building, simulation, and analysis that facilitates reproducibility of models in systems and synthetic biology. Tellurium is a modular, cross-platform, and open-source simulation environment composed of multiple libraries, plugins, and specialized modules and methods. Tellurium is a self-contained modeling platform which comes with a fully configured Python distribution. Two interfaces are provided, one based on the Spyder IDE which has an accessible user interface akin to MATLAB and a second based on the Jupyter Notebook, which is a format that contains live code, equations, visualizations, and narrative text. Tellurium uses libRoadRunner as the default SBML simulation engine which supports deterministic simulations, stochastic simulations, and steady-state analyses. Tellurium also includes Antimony, a human-readable model definition language which can be converted to and from SBML. Other standard Python scientific libraries such as NumPy, SciPy, and matplotlib are included by default. Additionally, we include several user-friendly plugins and advanced modules for a wide-variety of applications, ranging from complex algorithms for bifurcation analysis to multidimensional parameter scanning. By combining multiple libraries, plugins, and modules into a single package, Tellurium provides a unified but extensible solution for biological modeling and analysis for both novices and experts. AVAILABILITY:tellurium.analogmachine.org.
| S-EPMC6108935 | biostudies-literature