Gαq-Stimulated Gene Expression Is Insensitive to Bromo Extra Terminal Domain Inhibitors in HEK 293 Cells

Abstract

Bromodomain and extraterminal domain (BET) family proteins are ubiquitous transcriptional co-activators that function broadly in cellular differentiation, proliferation, and stress responses. Pharmacological inhibition of BET proteins with small molecules that disrupt bromodomain engagement with acetyllysine residues (such as JQ1) or drive their degradation through the ubiquitin-proteasome system (such as dBET6) ameliorates pathological gene expression in a range of systems and shows promise as a potential therapeutic strategy. Understanding the cell-type and signaling pathway requirements that dictate BET dependence in a particular cellular context remains incomplete. We previously demonstrated that, in neonatal rat cardiomyocytes, GPCR-induced hypertrophy responses depended strongly on the BET protein Brd4 when signaling was coupled to Gαs, but not Gαq. Here, we tested whether Brd4 was differentially responsive to G protein isoforms in HEK 293 cells by expressing Gαs- or Gαq-coupled Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). Gαq induced the expression of a group of early response genes and inflammatory genes in a manner largely insensitive to pharmacological BET inhibition, consistent with our previous data in cardiomyocytes. Gαs activated a small subset of the Gαq-induced genes, but this effect was largely reversed by dBET6. Our data further suggest that there may be general signaling requirements to activate Brd4 across cell types.

Keywords: DREADDs; G proteins; bromodomain and extraterminal domain (BET) family proteins; cellular signaling; transcriptional regulation.

Figure 1

Functional validation of Gαq- and Gαs-coupled DREADDs using BRET biosensors. (A) DBRET was measured in HEK 293 cells transfected with the PKC biosensor and either Gαq-DREADD or a vector control. Measurements were taken at the indicated doses of DCZ at the indicated times (n = 3 independent experiments; error bars indicate SEM). “Veh” indicates vehicle control for DCZ (ddH₂O). (B) As in (A) for the EPAC biosensor and either Gαs-DREADD or vector control. (C) DBRET was measured in HEK 293 cells transfected with either DREADD/biosensor combination after 1 μM DCZ treatment for the indicated times (n = 3 independent experiments; error bars indicate SEM). “Veh” indicates 1 h vehicle control for DCZ (ddH₂O) treatment.

Figure 2

Functional validation of BET inhibitors. (A) Plot of ImageJ quantification of anti-Brd4 immunoblots (normalized to GAPDH loading control, n = 3; means ± SEM). The 3 h vehicle (DMSO) treatment is used as the “0” control. * indicates significant difference from 0 (two-tailed t-test; p < 0.05). (B) RT-qPCR to quantify relative c-myc transcript levels after treatment of HEK 293 cells with either 1 μM JQ1 or 100 nM dBET6 for the indicated times (n = 3 independent experiments). Values for 3 h vehicle (DMSO) treatment were set to 1.

Figure 3

Gene expression changes triggered by DREADDs in HEK 293 cells. (A) Volcano plots of differentially expressed genes identified comparing cells expressing Gαq-DREADD (right) or Gαs-DREADD (left) ± DCZ treatment (fold change ≥ 1.5, p ≤ 0.1). (B) Venn diagram showing overlap of genes induced by Gαq-DREADD/DCZ and ERK primary response genes identified in [47]. (C) KEGG pathway analysis of 55 Gαq-DREADD/DCZ upregulated genes. “GeneRatio” indicates ratio of number of genes enriched in the indicated category to total number of differentially expressed genes.

Figure 4

Gene expression changes triggered by BET inhibitors in HEK 293 cells. (A) Volcano plot of differentially expressed genes identified comparing cells expressing Gαq-DREADD ± dBET6 (fold change ≥ 1.5, p ≤ 0.1). (B) KEGG pathway analysis of significantly downregulated genes from (A). (C) Volcano plot of differentially expressed genes identified comparing cells expressing Gαq-DREADD ± JQ1 (fold change ≥ 1.5, p ≤ 0.1). (D) Venn diagrams comparing the significantly downregulated (top) and upregulated (bottom) genes identified upon dBET6 or JQ1 treatment. (E) KEGG pathway analysis of significantly upregulated (left) and downregulated (right) genes from (C).

Figure 5

Most gene regulatory effects of Gαq-DREADD activation are maintained in the presence of BET inhibitors. (A) Volcano plot of differentially expressed genes identified comparing cells expressing Gαq-DREADD with combined DCZ/dBET6 treatment to those expressing Gαq-DREADD and treated with dBET6 alone (fold change ≥ 1.5, p ≤ 0.1). (B) Venn diagrams comparing the significantly upregulated genes identified upon DCZ treatment of cells expressing Gαq-DREADD in the presence or absence of dBET6. (C) Volcano plot of differentially expressed genes identified comparing cells expressing Gαq-DREADD with combined DCZ/JQ1 treatment to those expressing Gαq-DREADD and treated with JQ1 alone (fold change ≥ 1.5, p ≤ 0.1). (D) Venn diagrams comparing the significantly upregulated genes identified upon DCZ treatment of cells expressing Gαq-DREADD in the presence or absence of JQ1.