A Data-Driven Transcriptional Taxonomy of Adipogenic Chemicals to Identify White and Brite Adipogens,Environmental Health Perspectives

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A Data-Driven Transcriptional Taxonomy of Adipogenic Chemicals to Identify White and Brite Adipogens
Environmental Health Perspectives ( IF 10.1 ) Pub Date : 2021-7-29 , DOI: 10.1289/ehp6886
Stephanie Kim _{1,

2} , Eric Reed _{1,

3,

4} , Stefano Monti _{1,

3,

4} , Jennifer J Schlezinger _{1,

2}

Affiliation

Abstract

Background:

Chemicals in disparate structural classes activate specific subsets of the transcriptional programs of peroxisome proliferator-activated receptor- $γ$ ( $peroxisome proliferator-activated receptor lowercase gamma$ ) to generate adipocytes with distinct phenotypes.

Objectives:

Our objectives were to a) establish a novel classification method to predict $peroxisome proliferator-activated receptor lowercase gamma’s$ ligands and modifying chemicals; and b) create a taxonomy to group chemicals on the basis of their effects on $peroxisome proliferator-activated receptor lowercase gamma’s$ transcriptome and downstream metabolic functions. We tested the hypothesis that environmental adipogens highly ranked by the taxonomy, but segregated from therapeutic $peroxisome proliferator-activated receptor lowercase gamma$ ligands, would induce white but not brite adipogenesis.

Methods:

3T3-L1 cells were differentiated in the presence of 76 chemicals (negative controls, nuclear receptor ligands known to influence adipocyte biology, potential environmental $peroxisome proliferator-activated receptor lowercase gamma$ ligands). Differentiation was assessed by measuring lipid accumulation. mRNA expression was determined by RNA-sequencing (RNA-Seq) and validated by reverse transcription–quantitative polymerase chain reaction. A novel classification model was developed using an amended random forest procedure. A subset of environmental contaminants identified as strong $peroxisome proliferator-activated receptor lowercase gamma$ agonists were analyzed by their effects on lipid handling, mitochondrial biogenesis, and cellular respiration in 3T3-L1 cells and human preadipocytes.

Results:

We used lipid accumulation and RNA-Seq data to develop a classification system that a) identified $peroxisome proliferator-activated receptor lowercase gamma$ agonists; and b) sorted chemicals into likely white or brite adipogens. Expression of Cidec was the most efficacious indicator of strong $peroxisome proliferator-activated receptor lowercase gamma$ activation. 3T3-L1 cells treated with two known environmental $peroxisome proliferator-activated receptor lowercase gamma$ ligands, tetrabromobisphenol A and triphenyl phosphate, which sorted distinctly from therapeutic ligands, had higher expression of white adipocyte genes but no difference in Pgc1a and Ucp1 expression, and higher fatty acid uptake but not mitochondrial biogenesis. Moreover, cells treated with two chemicals identified as highly ranked $peroxisome proliferator-activated receptor lowercase gamma$ agonists, tonalide and quinoxyfen, induced white adipogenesis without the concomitant health-promoting characteristics of brite adipocytes in mouse and human preadipocytes.

Discussion:

A novel classification procedure accurately identified environmental chemicals as $peroxisome proliferator-activated receptor lowercase gamma$ ligands distinct from known $peroxisome proliferator-activated receptor lowercase gamma$ -activating therapeutics.

Conclusion:

The computational and experimental framework has general applicability to the classification of as-yet uncharacterized chemicals. https://doi.org/10.1289/EHP6886

中文翻译：

用于识别白色和 Brite 脂肪原的脂肪生成化学物质的数据驱动转录分类法

摘要

背景：

不同结构类别的化学物质激活过氧化物酶体增殖物激活受体转录程序的特定子集- $γ$ ( $peroxisome proliferator-activated receptor lowercase gamma$ ) 以产生具有不同表型的脂肪细胞。

目标：

我们的目标是a ) 建立一种新的分类方法来预测 $peroxisome proliferator-activated receptor lowercase gamma’s$ 配体和改性化学品；b ) 创建一个分类法，根据化学物质对化学物质的影响对它们进行分组 $peroxisome proliferator-activated receptor lowercase gamma’s$ 转录组和下游代谢功能。我们检验了环境脂肪原在分类学中排名很高但与治疗性分离的假设 $peroxisome proliferator-activated receptor lowercase gamma$ 配体，会诱导白色但不诱导脂肪生成。

方法：

3T3-L1 细胞在 76 种化学物质（阴性对照、已知影响脂肪细胞生物学的核受体配体、潜在环境 $peroxisome proliferator-activated receptor lowercase gamma$ 配体）。通过测量脂质积累来评估分化。通过 RNA 测序 (RNA-Seq) 确定 mRNA 表达，并通过逆转录-定量聚合酶链反应进行验证。使用修正的随机森林程序开发了一种新的分类模型。被确定为强的环境污染物子集 $peroxisome proliferator-activated receptor lowercase gamma$ 通过对 3T3-L1 细胞和人类前脂肪细胞中脂质处理、线粒体生物发生和细胞呼吸的影响来分析激动剂。

结果：

我们使用脂质积累和 RNA-Seq 数据开发了一个分类系统，该系统a ) 确定 $peroxisome proliferator-activated receptor lowercase gamma$ 激动剂；b ) 将化学品分类为可能的白色或新式脂肪原。Cidec的表达是最强的最有效的指标 $peroxisome proliferator-activated receptor lowercase gamma$ 激活。用两种已知环境处理的 3T3-L1 细胞 $peroxisome proliferator-activated receptor lowercase gamma$ 与治疗性配体明显不同的配体四溴双酚 A 和磷酸三苯酯具有较高的白色脂肪细胞基因表达，但Pgc1a和Ucp1表达无差异，脂肪酸摄取较高，但线粒体生物发生无差异。此外，用两种化学物质处理的细胞被确定为高等级 $peroxisome proliferator-activated receptor lowercase gamma$ 激动剂 Tonalide 和 quinoxyfen 可诱导白色脂肪生成，但没有伴随小鼠和人类前脂肪细胞中 brite 脂肪细胞的健康促进特性。

讨论：

一种新的分类程序准确地将环境化学品识别为 $peroxisome proliferator-activated receptor lowercase gamma$ 不同于已知的配体 $peroxisome proliferator-activated receptor lowercase gamma$ -激活疗法。