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Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

ABSTRACT: 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.

SUBMITTER: Dean JL

PROVIDER: S-EPMC6106787 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

Dean Jeffry L JL Zhao Q Jay QJ Lambert Jason C JC Hawkins Belinda S BS Thomas Russell S RS Wesselkamper Scott C SC

Toxicological sciences : an official journal of the Society of Toxicology 20170501 1

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 cont ...[more]

PMID: 28123101

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Project description:We have collected computed barrier heights and reaction energies (and associated model structures) for five enzymes from studies published by Himo and co-workers. Using this data, obtained at the B3LYP/6- 311+G(2d,2p)[LANL2DZ]//B3LYP/6-31G(d,p) level of theory, we then benchmark PM6, PM7, PM7-TS, and DFTB3 and discuss the influence of system size, bulk solvation, and geometry re-optimization on the error. The mean absolute differences (MADs) observed for these five enzyme model systems are similar to those observed for PM6 and PM7 for smaller systems (10-15 kcal/mol), while DFTB results in a MAD that is significantly lower (6 kcal/mol). The MADs for PMx and DFTB3 are each dominated by large errors for a single system and if the system is disregarded the MADs fall to 4-5 kcal/mol. Overall, results for the condensed phase are neither more or less accurate relative to B3LYP than those in the gas phase. With the exception of PM7-TS, the MAD for small and large structural models are very similar, with a maximum deviation of 3 kcal/mol for PM6. Geometry optimization with PM6 shows that for one system this method predicts a different mechanism compared to B3LYP/6-31G(d,p). For the remaining systems, geometry optimization of the large structural model increases the MAD relative to single points, by 2.5 and 1.8 kcal/mol for barriers and reaction energies. For the small structural model, the corresponding MADs decrease by 0.4 and 1.2 kcal/mol, respectively. However, despite these small changes, significant changes in the structures are observed for some systems, such as proton transfer and hydrogen bonding rearrangements. The paper represents the first step in the process of creating a benchmark set of barriers computed for systems that are relatively large and representative of enzymatic reactions, a considerable challenge for any one research group but possible through a concerted effort by the community. We end by outlining steps needed to expand and improve the data set and how other researchers can contribute to the process.

Project description:BackgroundIn recent years, differentiation of human induced pluripotent stem cells (hiPSCs) into brain-specific microvascular endothelial cells (iBMECs) has frequently been used to model the blood-brain barrier (BBB). However, there are limitations in the use of iBMECs for in vitro studies, such as transendothelial electrical resistance (TEER) instability, weak junctional expression of VE-cadherin, and lack of proper fluid shear stress response. In vivo, the basement membrane (BM) composition of the BBB evolves throughout development, and laminins become the dominant component of the mature vascular BM. However, laminin isoforms of the endothelial BM have not been used for culture of differentiated iBMECs. The main goal of this study is to investigate the effect of different laminin isoforms of the endothelial BM on iBMEC functionality and to determine whether better recapitulation of the physiological BM in vitro can address the aforementioned limitations of iBMECs.MethodsUsing a previously reported method, hiPSCs were differentiated into iBMECs. The influence of main laminins of the endothelial BM, LN 411 and LN 511, on iBMEC functionality was studied and compared to a collagen IV and fibronectin mixture (CN IV-FN). Quantitative RT-PCR, immunocytochemistry, and TEER measurement were utilized to assess gene and protein expression and barrier properties of iBMECs on different extracellular matrices. Single-channel microfluidic devices were used to study the effect of shear stress on iBMECs.ResultsLN 511, but not LN 411, improved iBMEC barrier properties and resulted in more sustained TEER stability. Immunocytochemistry showed improved junctional protein expression compared to iBMECs cultured on CN IV-FN. iBMECs cultured on LN 511 showed a reduction of stress fibers, indicating resting endothelial phenotype, whereas gene expression analysis revealed upregulation of multiple genes involved in endothelial activation in iBMECs on CN IV-FN. Finally, culturing iBMECs on LN 511 enhanced physiological responses to shear stress, including morphological changes and enhanced junctional protein association.ConclusionLN 511 improves the functionality and long-term barrier stability of iBMECs. Our findings suggest that incorporation of physiologically relevant LN 511 in iBMEC culture would be beneficial for disease modeling applications and BBB-on-a-chip platforms that accommodate fluid flow.

Dataset Information

Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

Publications

Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

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