Increasing concern over endocrine disrupting chemicals (EDCs) in environmental and food samples has created the demand for rapid and high throughput screening methods to evaluate their estrogenic effects. In this study, a sensitive assay based on estrogen receptor α (ERα) and gold nanoparticles (AuNPs) was established to screen EDCs and confirm the binding affinities of EDCs with ERα. ERα protein can prevent the salt-induced aggregation of AuNPs by recruiting Na⁺ from AuNPs. When there are EDCs as targets in the sample, the specific binding of ERα and EDCs via hydrogen bonding results in a reduction in the binding between Na⁺ and ERα, and then most Na⁺ ions bind to the AuNPs and induce their aggregation. Nine kinds of estrogen-agonist compound, 17β-estradiol (17β-E2), diethylstilbestrol (DES), hexoestrolum (HES), 17α-estradiol (17α-E2), estrone (E1), 2,2-bis(4-hydroxyphenyl)-1,1,1-trichloroethane (HPTE), genistein, bisphenol A (BPA) and bisphenol B (BPB), were chosen as representative targets for the validation of this method. The ranking order of estrogenic potency determined by this method was DES > 17β-E2 > HES > 17α-E2 > E1 > HPTE > genistein > BPA > BPB, which was consistent with the published results. Moreover, the recoveries of the nine kinds of EDCs spiked in tap water and milk samples were all between 80.0% and 120.0%, which proved that this method can be used for the high throughput screening of these EDCs in environmental and food samples.

中文翻译：

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基于雌激素受体α和金纳米粒子的高通量筛选自来水和牛奶样品中内分泌干扰物的方法

对环境和食品样品中的内分泌干扰化学物质（EDC）的关注日益增加，因此对快速，高通量筛选方法以评估其雌激素作用的需求日益增加。在这项研究中，建立了一种基于雌激素受体α（ERα）和金纳米颗粒（AuNPs）的灵敏测定方法，以筛选EDC并确认EDC与ERα的结合亲和力。ERα蛋白可以通过从AuNPs中吸收Na ⁺来防止盐诱导的AuNPs聚集。当样品中有EDC作为目标时，ERα和EDC通过氢键的特异性结合会导致Na ⁺和ERα之间的结合减少，然后大多数Na ⁺离子与AuNPs结合并诱导其聚集。九种雌激素激动剂化合物，17β-雌二醇（17β-E2），己烯雌酚（DES），己雌激素（HES），17α-雌二醇（17α-E2），雌酮（E1），2,2-双（4-羟苯基） ）-1,1,1-三氯乙烷（HPTE），染料木黄酮，双酚A（BPA）和双酚B（BPB）被选为该方法验证的代表性目标。用这种方法确定的雌激素能力的排名顺序为：DES>17β-E2> HES>17α-E2> E1> HPTE>染料木黄酮> BPA> BPB，与已发表的结果一致。此外，自来水和牛奶样品中加标的9种EDC的回收率均在80.0％至120.0％之间，这证明该方法可用于环境和食品样品中这些EDC的高通量筛选。