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In vitro gene regulatory networks predict in vivo function of liver.

ABSTRACT: BACKGROUND: Evolution of toxicity testing is predicated upon using in vitro cell based systems to rapidly screen and predict how a chemical might cause toxicity to an organ in vivo. However, the degree to which we can extend in vitro results to in vivo activity and possible mechanisms of action remains to be fully addressed. RESULTS: Here we use the nitroaromatic 2,4,6-trinitrotoluene (TNT) as a model chemical to compare and determine how we might extrapolate from in vitro data to in vivo effects. We found 341 transcripts differentially expressed in common among in vitro and in vivo assays in response to TNT. The major functional term corresponding to these transcripts was cell cycle. Similarly modulated common pathways were identified between in vitro and in vivo. Furthermore, we uncovered the conserved common transcriptional gene regulatory networks between in vitro and in vivo cellular liver systems that responded to TNT exposure, which mainly contain 2 subnetwork modules: PTTG1 and PIR centered networks. Interestingly, all 7 genes in the PTTG1 module were involved in cell cycle and downregulated by TNT both in vitro and in vivo. CONCLUSIONS: The results of our investigation of TNT effects on gene expression in liver suggest that gene regulatory networks obtained from an in vitro system can predict in vivo function and mechanisms. Inhibiting PTTG1 and its targeted cell cycle related genes could be key mechanism for TNT induced liver toxicity.

SUBMITTER: Deng Y

PROVIDER: S-EPMC2998496 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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In vitro gene regulatory networks predict in vivo function of liver.

Deng Youping Y Johnson David R DR Guan Xin X Ang Choo Y CY Ai Junmei J Perkins Edward J EJ

BMC systems biology 20101112

<h4>Background</h4>Evolution of toxicity testing is predicated upon using in vitro cell based systems to rapidly screen and predict how a chemical might cause toxicity to an organ in vivo. However, the degree to which we can extend in vitro results to in vivo activity and possible mechanisms of action remains to be fully addressed.<h4>Results</h4>Here we use the nitroaromatic 2,4,6-trinitrotoluene (TNT) as a model chemical to compare and determine how we might extrapolate from in vitro data to i ...[more]

PMID: 21073692

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Project description:BackgroundLiver cirrhosis is one of the leading causes of death worldwide. MicroRNAs (miRNAs) can regulate liver fibrosis, but the underlying mechanisms are not fully understood, and the interactions between miRNAs and mRNAs are not clearly elucidated.MethodsmiRNA and mRNA expression arrays of cirrhotic samples and control samples were acquired from the Gene Expression Omnibus database. miRNA-mRNA integrated analysis, functional enrichment analysis and protein-protein interaction (PPI) network construction were performed to identify differentially expressed miRNAs (DEMs) and mRNAs (DEGs), miRNA-mRNA interaction networks, enriched pathways and hub genes. Finally, the results were validated with in vitro cell models.ResultsBy bioinformatics analysis, we identified 13 DEMs between cirrhotic samples and control samples. Among these DEMs, six upregulated (hsa-miR-146b-5p, hsa-miR-150-5p, hsa-miR-224-3p, hsa-miR-3135b, hsa-miR-3195, and hsa-miR-4725-3p) and seven downregulated (hsa-miR-1234-3p, hsa-miR-30b-3p, hsa-miR-3162-3p, hsa-miR-548aj-3p, hsa-miR-548x-3p, hsa-miR-548z, and hsa-miR-890) miRNAs were further validated in activated LX2 cells. miRNA-mRNA interaction networks revealed a total of 361 miRNA-mRNA pairs between 13 miRNAs and 245 corresponding target genes. Moreover, PPI network analysis revealed the top 20 hub genes, including COL1A1, FBN1 and TIMP3, which were involved in extracellular matrix (ECM) organization; CCL5, CXCL9, CXCL12, LCK and CD24, which participated in the immune response; and CDH1, PECAM1, SELL and CAV1, which regulated cell adhesion. Functional enrichment analysis of all DEGs as well as hub genes showed similar results, as ECM-associated pathways, cell surface interaction and adhesion, and immune response were significantly enriched in both analyses.ConclusionsWe identified 13 differentially expressed miRNAs as potential biomarkers of liver cirrhosis. Moreover, we identified 361 regulatory pairs of miRNA-mRNA and 20 hub genes in liver cirrhosis, most of which were involved in collagen and ECM components, immune response, and cell adhesion. These results would provide novel mechanistic insights into the pathogenesis of liver cirrhosis and identify candidate targets for its treatment.

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In vitro gene regulatory networks predict in vivo function of liver.

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In vitro gene regulatory networks predict in vivo function of liver.

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