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Genome-Scale Characterization of Toxicity-Induced Metabolic Alterations in Primary Hepatocytes

ABSTRACT: Context-specific Genome-scale Metabolic Network Reconstructions (GENREs) provide a means to understand cellular metabolism at a deeper level of physiological detail. Here, we use transcriptomics data from chemically exposed rat hepatocytes to constrain a GENRE of rat hepatocyte metabolism and predict biomarkers of liver toxicity using the Transcriptionally Inferred Metabolic Biomarker Response (TIMBR) algorithm. We profiled alterations in cellular hepatocyte metabolism following in vitro exposure to three toxicants (acetaminophen, 2,3,7,8-tetrachlorodibenzodioxin, and trichloroethylene) for six hours. TIMBR predictions were compared with paired metabolomics data from the same exposure conditions. Agreement between computational model predictions and experimental data led to the identification of specific metabolites and thus metabolic pathways associated with toxicant exposure; where predictions and experimental data disagreed, we identified testable hypotheses to reconcile differences between the model predictions and experimental data. The presented pipeline for using paired transcriptomics and metabolomics data provides a framework for interrogating multiple omics datasets to generate mechanistic insight of metabolic changes associated with toxicological responses.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE129814 | GEO | 2019/08/27

REPOSITORIES: GEO

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Project description:Background: Arachidonic acid (AA) metabolism pathway is dominant in metabolic programming after hypoxia exposure, but its biological function is disputed and require in-depth studies. In this research, we aimed at integrating plasma metabolomics and transcriptomics approaches to systematically explore its roles in response to acute hypoxia based on model of acute high-altitude exposure. Methods: Blood samples were taken from 53 enrolled subjects before and after their exposure to high altitude. Ultra-performance liquid chromatography- quadrupole time-of-flight mass spectrometry and RNA sequencing were performed to acquire corresponding metabolomic and transcriptomic profiling along with hypoxia exposure, separately. Influential modules comprising essential metabolites and genes were identified by weighted gene co-expression network analysis (WGCNA) after integrating metabolic information with phenotypic and transcriptomic datasets, respectively. Results: Enrolled individuals showed significant alterations in heart rate, SpO2, hemoglobin and Lake Louise Score (LLS) in response to hypoxia. Metabolomics profiling demonstrated that AA metabolism pathway was remarkable in these metabolic alterations. Integrated analysis of metabolomic and transcriptomic data revealed that increasing AA metabolism pathway might count for gas transport incapacitation and disorders in hemoglobin metabolism under hypoxia stimuli. Moreover, identified in further analysis and another cohort, excessively elevated AA metabolism pathway was involved in poor response to hypoxia. Conclusion: Our study, for the first time, constructed the maps of AA metabolism pathway in response to hypoxia; and revealed the crosstalk between phenotypic variation to hypoxia and AA metabolism pathway. These findings will not only advanced pathophysiological mechanisms for acute hypoxic diseases, but provided new insights into critical roles of AA metabolism pathway in development and prevention of these diseases.

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Genome-Scale Characterization of Toxicity-Induced Metabolic Alterations in Primary Hepatocytes

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