Toxicogenomics for transcription factor-governed molecular pathways: moving on to roles beyond classification and prediction

Andersen, Melvin E.; McMullen, Patrick D.; Bhattacharya, Sudin

doi:10.1007/s00204-012-0980-6

Cited by 17 publications

(9 citation statements)

References 26 publications

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“…With analytical tools, toxicogenomic data can be used to inform gene groupings or pathways that are modulated by chemical exposure. Analysis of dose-response changes in grouped genes can infer dose-dependent transitions in MoA (Andersen et al, 2013). the Hamner Institutes for Health Sciences is developing a series of pathway-based case studies with the objective being the simultaneous development of assays along with interpretation and extrapolation tools that can be applied to MoA-specific risk and safety estimations, as proof of principle for the approach (Andersen et al, 2012).…”

Section: Hamner Institutes For Health Sciences: Pathway-targeted Casementioning

confidence: 99%

Pathway-based toxicity: history, current approaches and liver fibrosis and steatosis as prototypes

Willett

Rae

Goyak

et al. 2014

ALTEX

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Section: Hamner Institutes For Health Sciences: Pathway-targeted Casementioning

confidence: 99%

Pathway-based toxicity: history, current approaches and liver fibrosis and steatosis as prototypes

Willett

Rae

Goyak

et al. 2014

ALTEX

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“…These TFs, including the nuclear receptors, p53, nuclear factor erythroid 2-related factor (NRF2), nuclear factor-κB (NF-κB), the STAT (signal transducers and activators of transcription) family, and the aryl hydrocarbon receptor (AHR), typically coordinate a broad range of physiological processes like metabolism, oxidative stress response, differentiation, tumor suppression, reproduction, development, and homeostasis (Audet-Walsh and Giguére 2015; Evans and Mangelsdorf 2014;Ma 2013;Tyagi et al 2011;Wright et al 2017). They thus act as sentinels of normal biological activity, but their inappropriate activation or inhibition can lead to adverse outcomes at the cellular or tissue level (Andersen et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Gene co-regulation and co-expression in the aryl hydrocarbon receptor-mediated transcriptional regulatory network in the mouse liver

Josyula

Andersen²,

Kaminski

et al. 2019

Arch Toxicol

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Four decades after its discovery, the aryl hydrocarbon receptor (AHR), a ligand-inducible transcription factor (TF) activated by the persistent environmental contaminant 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), remains an enigmatic molecule with a controversial endogenous role. Here, we have assembled a global map of the AHR gene regulatory network in female C57BL/6 mice orally gavaged with 30 µg/kg of TCDD from a combination of previously published gene expression and genome-wide TF-binding data sets. Using Kohonen self-organizing maps and subspace clustering, we show that genes co-regulated by common upstream TFs in the AHR network exhibit a pattern of co-expression. Directly bound, indirectly bound, and non-genomic AHR target genes exhibit distinct expression patterns, with the directly bound targets associated with highest median expression. Interestingly, among the directly bound AHR target genes, the expression level increases with the number of AHR-binding sites in the proximal promoter regions. Finally, we show that co-regulated genes in the AHR network activate distinct groups of downstream biological processes. Although the specific findings described here are restricted to hepatic effects under short-term TCDD exposure, this work describes a generalizable approach to the reconstruction and analysis of transcriptional regulatory cascades underlying cellular stress response, revealing network hierarchy and the nature of information flow from the initial signaling events to phenotypic outcomes. Such reconstructed networks can form the basis of a new generation of quantitative adverse outcome pathways. Keywords Ligand-activated transcription factors • DNA binding • Dioxin response element • Signaling • Co-regulation • Co-expression • Phenotypic outcomes Abbreviations AHR Aryl hydrocarbon receptor ARNT Aryl hydrocarbon nuclear translocator bHLH Basic helix-loop-helix ChEA2 ChIP-X enrichment analysis Electronic supplementary material The online version of this article (

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“…Transcription factors regulate stress-induced biological processes and determine the landscape of toxicological response [50][51][52]. Characterization of the gene regulatory programs activated in response to nanoparticle treatment can improve risk assessment and potentially aid to build predictive toxicity models.…”

Section: Discussionmentioning

confidence: 99%

Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes

Zhernovkov

Santra

Cassidy

et al. 2018

Preprint

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BackgroundCarbon nanotubes (CNTs) usage has rapidly increased in the last few decades due to their unique properties, exploited in various industrial and commercial products. Certain types of CNTs cause adverse health effects, including chronic inflammation and fibrosis. Despite the large number of in vitro and in vivo studies evaluating these effects, many important questions remain unanswered due to a lack of mechanistic understanding of how CNTs induce cellular stress responses. In order to predict CNT toxicity, it is important to understand which transcriptional programs are specifically activated in response to CNTs, and what similarities and differences exist in relation to other toxic inducers exerting similar adverse effects. ResultsA systems biology approach was applied to reveal complex interactions at the molecular level in mouse lung tissue in response to different fibrosis inducers: two types of multiwalled CNTs, NM-401 and NRCWE-26, and bleomycin (BLM). Based on mRNA gene expression profiles, we inferred gene regulatory networks (GRNs) to capture functional hierarchical regulatory structures between genes and their regulators. We found that activities of the transcription factors (TFs) Myc, Arid5a and Mxd1 were associated with the regulation of cytokine transcription in response to CNTs, while in response to BLM treatment, Myc was associated with p53 signaling. TF Litaf was identified as the essential regulator for noncanonical signaling of TLR2/4 driven by CNTs. Despite the different nature of the lung injury caused by CNTs and BLM, we identified common stress response modules, that included DNA damage (TFs : E2f8, E2f1, Foxm1), M1/M2 macrophage polarization (TF: Mafb), Interferon response (TFs: Irf7, Stat2 and Irf9) for all agents. ConclusionsThese results suggest that the reconstruction and analysis of TF-centric gene interaction networks can reveal key targets and regulators of cellular stress responses to toxic agents.2

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Toxicogenomics for transcription factor-governed molecular pathways: moving on to roles beyond classification and prediction

Cited by 17 publications

References 26 publications

Pathway-based toxicity: history, current approaches and liver fibrosis and steatosis as prototypes

Pathway-based toxicity: history, current approaches and liver fibrosis and steatosis as prototypes

Gene co-regulation and co-expression in the aryl hydrocarbon receptor-mediated transcriptional regulatory network in the mouse liver

Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes

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