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. 2017 Jan;155(1):85-100.
doi: 10.1093/toxsci/kfw186. Epub 2016 Sep 23.

Editor's Highlight: Screening ToxCast Prioritized Chemicals for PPARG Function in a Human Adipose-Derived Stem Cell Model of Adipogenesis

Briana Foley  1 , Daniel L Doheny  1   2 , Michael B Black  1   2 , Salil N Pendse  1   2 , Barbara A Wetmore  1   2 , Rebecca A Clewell  1   2 , Melvin E Andersen  1   2 , Chad Deisenroth  3   2
Affiliations

Editor's Highlight: Screening ToxCast Prioritized Chemicals for PPARG Function in a Human Adipose-Derived Stem Cell Model of Adipogenesis

Briana Foley et al. Toxicol Sci. 2017 Jan.

Abstract

The developmental origins of obesity hypothesis posits a multifaceted contribution of factors to the fetal origins of obesity and metabolic disease. Adipocyte hyperplasia in gestation and early childhood may result in predisposition for obesity later in life. Rodent in vitro and in vivo studies indicate that some chemicals may directly affect adipose progenitor cell differentiation, but the human relevance of these findings is unclear. The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARG) is the master regulator of adipogenesis. Human adipose-derived stem cells (hASC) isolated from adipose tissue express endogenous isoforms of PPARG and represent a biologically relevant cell-type for evaluating activity of PPARG ligands. Here, a multi-endpoint approach based on a phenotypic adipogenesis assay was applied to screen a set of 60 chemical compounds identified in ToxCast Phase I as PPARG active (49) or inactive (11). Chemicals showing activity in the adipogenesis screen were further evaluated in a series of 4 orthogonal assays representing 7 different key events in PPARG-dependent adipogenesis, including gene transcription, protein expression, and adipokine secretion. An siRNA screen was also used to evaluate PPARG-dependence of the adipogenesis phenotype. A universal concentration-response design enabled inter-assay comparability and implementation of a weight-of-evidence approach for bioactivity classification. Collectively, a total of 14/49 (29%) prioritized chemicals were identified with moderate-to-strong activity for human adipogenesis. These results provide the first integrated screening approach of prioritized ToxCast chemicals in a human stem cell model of adipogenesis and provide insight into the capacity of PPARG-activating chemicals to modulate early life programming of adipose tissue.

Keywords: PPARG; ToxCast; adipogenesis; adipose-derived stem cell; endocrine disrupting chemicals; obesogens.

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Figures

FIG. 1
FIG. 1
Overview of the human adipogenesis study design. Chemical selection from ToxCast Phase 1 screening consisted of 49 chemicals identified in 3 independent PPARG binding and transactivation assays. 11 “low active” chemicals were selected as experimental negatives based on hit ratios across all ToxCast assays. A primary screen with 60 chemicals was run in a functional adipogenesis assay to identify viability ranges for each chemical, as well as activity for the differentiation endpoint. Assay hits were then evaluated across 4 additional orthologous assays spanning 7 endpoints that are specific for molecular and phenotypic features of human adipocytes. All data was analyzed in concentration-response format using a universal assay platform. Chemical hits identified in each assay were scored and classified according to hit frequency, efficacy, and potency.
FIG. 2
FIG. 2
Optimization of a PPARG-dependent human adipogenesis assay. A donor pool of non-differentiated adipose-derived stem cells was tested for adipogenic capacity and expression of endogenous PPARG isoforms at the end of the 8 day assay protocol. A Western blot of non-differentiated (Neg Con) and differentiated (Rosi 1 µM) cells was probed for PPARG, FABP4, and GAPDH expression (A). A modified medium formulation illustrates concentration-responsive differentiation of rosiglitazone (B) and tributyltin (C) treated cells, multiplexed with acute (LDH release) and chronic (cell counts) cytotoxicity endpoints. Concentrations are mean ± SEM of 3 experimental replicates. Micrographs taken with a 20× objective demonstrate brightfield (BF), nuclear (Hoechst), neutral lipid (AdipoRed), and composite images of the 4 control samples used in the adipogenesis screen (D). Neg Con = non-differentiated hASC, DMSO= vehicle, Rosi= rosiglitazone, TBT= tributyltin.
FIG. 3
FIG. 3
Primary adipogenesis screening results. Sixty chemicals screened in the adipogenesis assay were scored for significance and plotted as rank-ordered (left-to-right) maximum fold-change observed for any concentration point in the viable range of each chemical (A). The corresponding AC50 values and cytotoxicity derived TCC are plotted for each hit identified (B). Red circles are PPARG candidate chemical hits, black circles are non-significant PPARG candidate chemical hits, and blue triangles are negative controls. Pos Con = rosiglitazone positive control, Veh Con = DMSO vehicle control, 5*BMAD = significance threshold cutoff, TCC = toxicity concentration cutoff.
FIG. 4
FIG. 4
Loss-of-function evaluation in the PPARG siRNA assay. Plate sets of non-_targeting and PPARG siRNA were evaluated in concentration-response format for loss of RLA. ΔRLA fold-change plotted for rosiglitazone (A) and tributyltin (B) demonstrate a reduction in lipid accumulation. Concentrations are mean ± SEM of 3 experimental replicates. The performance of control values from all plate sets run in the assay (n = 16) are shown (C). Each box and whisker plot displays the median, first and third quartiles (boxes), and the 2.5–97.5 percentile (whiskers). Results from the chemicals screened in the ΔRLA assay were scored for significance and plotted as rank-ordered (left-to-right) maximum fold-change observed for any concentration point in the viable range determined for each chemical (D). The corresponding AC50 values and TCC are plotted for each hit identified (E).
FIG. 5
FIG. 5
Multiplexed gene expression results. CEBPA, PPARG, PLIN1, and FABP4 mRNA expression are plotted as Log2 ratios of treated versus DMSO vehicle controls for rosiglitazone (A) and tributyltin (B). Each gene endpoint was scored independently and comprehensive AC50 and TCC values plotted for each chemical (C). Dashed lines separate regions of hit frequency (0–4), with activity of negative control (asulam) shown.
FIG. 6
FIG. 6
FABP4 protein expression results. Qualitative and quantitative FABP4 and GAPDH protein expression levels are shown in concentration-response format for rosiglitazone (A) and tributyltin (B). Values are representative of 3 experimental replicates. N = non-differentiated controls, P = rosiglitazone positive control, V = DMSO vehicle control. The performance of control values from all plates run in the assay (n = 16) are shown (C). Each box and whisker plot displays the median, first and third quartiles (boxes), and the 2.5–97.5 percentile (whiskers). Results from the chemicals screened in the FABP4 assay were scored for significance and plotted as rank-ordered (left-to-right) maximum percentage of positive control observed for any concentration point in the viable range of each chemical (D). The corresponding AC50 values and TCC are plotted for each hit identified (E).
FIG. 7
FIG. 7
Adiponectin secretion results. Secretion of adiponectin into the assay medium was assessed in concentration-response format for rosiglitazone (A) and tributyltin (B). Values are mean ± SEM of 3 independent replicates. The performance of control values from all plates run in the assay (n = 22) demonstrate concentration (C) and dynamic range (D) of the assay. Each box and whisker plot displays the median, first and third quartiles (boxes), and the 2.5–97.5 percentile (whiskers). Results from the chemicals screened in the adiponectin assay were scored for significance and plotted as rank-ordered (left-to-right) maximum fold-change observed for any concentration point in the viable range of each chemical (D). The corresponding AC50 values and TCC are plotted for each hit identified (E).
FIG. 8
FIG. 8
Efficacy, hit frequency, and potency summary values for adipogenesis hits. The total peak area under the curve (AUC) of significant hits across 8 assay endpoints was calculated and plotted on a heat map for each of the 26 chemical hits identified in the primary adipogenesis screen. Rosiglitazone and tributyltin positive controls (PC) and asulam negative control (NC) are included for context. Compounds were rank-ordered (top-to-bottom) by total AUC and include CASRN and hit frequency (A). The range of AC50 values for each endpoint hit is displayed for each compound as in part A (B). Each box and whisker plot displays the median, first and third quartiles (boxes), and the min–max (whiskers).
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