This article presents an optimized yeast estrogen screen for quantifying ligands in Personal Care Products (PCPs) that bind estrogen receptors alpha (ERα) and/or beta (ERβ). The method incorporates two colorimetric substrate options, a six-day refrigerated incubation for use in undergraduate courses, and statistical tools for data analysis.
The Yeast Estrogen Screen (YES) is used to detect estrogenic ligands in environmental samples and has been broadly applied in studies of endocrine disruption. Estrogenic ligands include both natural and manmade "Environmental Estrogens" (EEs) found in many consumer goods including Personal Care Products (PCPs), plastics, pesticides, and foods. EEs disrupt hormone signaling in humans and other animals, potentially reducing fertility and increasing disease risk. Despite the importance of EEs and other Endocrine Disrupting Chemicals (EDCs) to public health, endocrine disruption is not typically included in undergraduate curricula. This shortcoming is partly due to a lack of relevant laboratory activities that illustrate the principles involved while also being accessible to undergraduate students. This article presents an optimized YES for quantifying ligands in personal care products that bind estrogen receptors alpha (ERα) and/or beta (ERβ). The method incorporates one of the two colorimetric substrates (ortho-nitrophenyl-β-D-galactopyranoside (ONPG) or chlorophenol red-β-D-galactopyranoside (CPRG)) that are cleaved by β-galactosidase, a 6-day refrigerated incubation step to facilitate use in undergraduate laboratory courses, an automated application for LacZ calculations, and R code for the associated 4-parameter logistic regression analysis. The protocol has been designed to allow undergraduate students to develop and conduct experiments in which they screen products of their choosing for estrogen mimics. In the process, they learn about endocrine disruption, cell culture, receptor binding, enzyme activity, genetic engineering, statistics, and experimental design. Simultaneously, they also practice fundamental and broadly applicable laboratory skills, such as: calculating concentrations; making solutions; demonstrating sterile technique; serially diluting standards; constructing and interpolating standard curves; identifying variables and controls; collecting, organizing, and analyzing data; constructing and interpreting graphs; and using common laboratory equipment such as micropipettors and spectrophotometers. Thus, implementing this assay encourages students to engage in inquiry-based learning while exploring emerging issues in environmental science and health.
The Yeast Estrogen Screen (YES) is widely used to quantify ligands that mimic estradiol (E2 or 17β-estradiol) in a variety of matrices, including water, plant tissues, consumer products, and foods1,2,3,4. Collectively, such ligands are termed "Environmental Estrogens (EEs)." The YES was originally developed as a low cost, in vitro alternative to in vivo tests like the rodent uterotrophic assay5,6 and the rainbow trout feeding assay7. The aim of these tests is to determine if a product contains chemicals that stimulate or block estrogen-dependent mechanisms. Detection of EEs is critical, because they can interfere with normal endogenous estrogen signaling, particularly during fetal development. This interference compromises health by increasing risk of obesity, infertility, cancer, and cognitive loss8.
Despite the importance of EEs and other EDCs to public health, endocrine disruption is not commonly included in undergraduate curricula. This deficiency is partly due to a dearth of activities that illustrate the principles involved while also being accessible to undergraduate students. Additionally, several variations of the YES protocol exist9,10,11,12,13, and this diversity makes assay optimization time-consuming for laboratory coordinators not specifically trained in the relevant techniques. Finally, YES assays are usually completed over 1 long day or 2 consecutive days with an O/N incubation. This timing is not compatible with the format of undergraduate laboratory courses, which typically meet once/week for several h.
In response to these needs, this manuscript reports an optimized 96-well YES protocol that includes ethanolic extraction methods for Personal Care Products (PCPs)3 and a 6-day refrigeration step to accommodate weekly laboratory meetings. Absolute ethanol is a versatile organic solvent that can dissolve a variety of polar and nonpolar solutes. Moreover, it is suitable for undergraduate courses because it is readily available, relatively nontoxic, affordable, and miscible with water; it also evaporates easily without special equipment. However, ethanol is not ideal for extracting strongly hydrophobic endocrine disruptors or many oils and waxes, the latter two being common ingredients in PCPs. Poor extraction efficiency increases the risk of false negative findings. With this constraint in mind, investigators should choose extraction procedures (e.g., ethanolic extraction or solid phase extraction) that address sample characteristics and meet study objectives (research versus undergraduate instruction).
The YES relies on recombinant Saccharomyces cerevisiae originally created by Dr. Charles Miller at Tulane University. Please see Miller et al. (2010) for a complete map of the engineered plasmid14. Yeast transformed with these plasmids constitutively express human nuclear ERα or ERβ (also called ESR1 and ESR2, respectively) when grown in media containing galactose (for ERα) or either glucose or galactose (for ERβ). If estrogenic chemicals are present in the media, they bind to the receptors, creating ligand-receptor complexes that activate β-galactosidase (lacZ) expression at a level proportional to the concentration of estrogenic chemicals. Yeast cells are then lysed to release the accumulated β-galactosidase. The lysis buffer contains either ONPG or CPRG, which are cleaved by β-galactosidase to yield yellow or red products, respectively. Colorimetric products can be quantified by measuring absorbance using a microwell plate spectrophotometer. The degree of color change is proportional to the concentration of estrogenic ligands to which the yeast was exposed.
The choice of substrate (CPRG or ONPG) depends on the potential for background absorbance arising from the samples being tested. For example, plant extracts will often add a yellow hue to the media that artificially inflates estrogenicity measures if ONPG (quantified at 405 nm) is used as the substrate for β-galactosidase. With plant extracts, CPRG (quantified at 574 nm) may be a more appropriate colorimetric substrate. CPRG is more expensive than ONPG but is used at one tenth the molarity. This article presents estrogenicities of PCP extracts quantified using both ONPG and CPRG.
Quantifying estrogenicity of environmental samples using both ERα and ERβ is a more comprehensive approach than using only one of these receptors. In animals, these receptors exhibit differential tissue distribution, regulatory activities, and binding affinities for estrogenic and anti-estrogenic ligands15. For example, plant-based phytoestrogens typically bind ERβ more strongly2, whereas synthetic chemicals can show preference for either ERα or ERβ or can bind both receptors equally well15. Therefore, binding to one estrogen receptor does not necessarily predict binding to the other.
Although EEs are found in many consumer products (e.g., pesticides, detergents, adhesives, lubricants, plastics, foods, and pharmaceuticals) as well as plants, the presented data were obtained using a selection of PCPs. PCPs are compelling, readily available, budget-friendly, and environmentally relevant for undergraduate students. Students can be invited to bring their favorite PCPs from home to test in the laboratory. They can also search the Skin Deep database developed by the Environmental Working Group16 to generate hypothesis-driven comparisons of PCPs with high and low toxicity scores. In this way, students can simultaneously develop advanced laboratory skills; engage in self-directed, inquiry-based learning; and explore emerging issues in environmental science and health.
1. Making Reagents
2. Preparing Samples and Extraction Controls
3. Culturing and Subculturing Yeast14
4. Preparing YES Plates (Day 1 of the Assay)
5. Processing YES Plates (Day 2 of the Assay)
6. Calculating LacZ Values
NOTE: LacZ values quantify the degree of color change for each sample and offer a normalized method of comparing values among separate assays by accounting for several variables (e.g., yeast optical density, media optical density, and incubation time if this differs among wells on the same plate)12.
7. Interpolating Sample Estradiol Equivalents (EEQs) Using 4-Parameter Logistic Regression
NOTE: EEQs relate sample LacZ values (color change) to the LacZ values of the standard curve created with E2. EEQs thus determine how much sample is required to elicit the same color change response as a known concentration of E2.
8. Standardizing EEQs (ng/mL) to PCP Sample Mass
The estrogenicities of triplicate samples of 15 PCPs were evaluated using this YES protocol. As noted by Miller et al. (2010), assays with yeast expressing ERβ were more than an order of magnitude more sensitive than assays with yeast expressing ERα (Figure 2)14. Therefore, estrogenic activity was more often detected with ERβ-expressing yeast (Table 2). Eight PCPs exhibited estrogenic activity with ERβ and 5 PCPs exhibited estrogenic activity with ERα. Hair cream, sunscreen, lotion, and lip balm samples were estrogenic with both receptors, whereas foundation, shaving cream, and nail polish were only estrogenic with ERβ at the tested concentrations. Seven other PCPs (4 shampoos, 2 soaps, and 1 lip balm) were not estrogenic with either receptor at the tested concentrations.
In addition to receptor sensitivity differences, EEQs for each sample differed depending on the colorimetric substrate (ONPG or CPRG) used in the assay (Table 2). In all but one sample, EEQs determined using ONPG were higher than those determined using CPRG. Moreover, variation among extraction replicates was lowest for EEQs measured with ERβ and CPRG and highest for EEQs determined with ERα and ONPG (Table 2).
In addition to comparing colorimetric substrates, 1 aim of the present study was to test incubation duration times that are compatible with the schedule of an undergraduate laboratory course. The typical YES assay requires a 17 h incubation followed immediately by incubation in LacZ buffer for 40 min – 4 h, a schedule that is impossible to implement in a teaching laboratory constrained by a single weekly session. To facilitate use of this assay in teaching, the assay was modified by introducing a 6 d refrigeration period (step 5.1.2) after the 17 h incubation. Standard curves from refrigerated plates were comparable to those from non-refrigerated plates (Figures 2 & 3), except that the standard errors of parameters estimated using four-parameter logistic regression models were all smaller for refrigerated plates than for nonrefrigerated plates (Table 3). Thus, refrigerating plates for 6 d reduces error and improves the accuracy of EEQ estimates.
Figure 1. Microwell Plate Layout and Standard Dilution Curve Preparation for the YES Assay. E2 standards (light gray wells), samples and negative extraction controls (white wells), and vehicle (H1 – 3) and galactose media (H10 – 12) controls (dark gray wells) were all tested in triplicate. An E2 standard curve (light gray wells) was constructed by plating 320 µL of yeast into wells A1 through A3 and 120 µL of yeast into wells B1 through G3. Then, 5 µL of E2 (227.5 nM for yeast that express ERα; 9.75 nM for yeast that express ERβ) were added to the yeast in wells A1 through A3. The yeast + E2 suspension was serially diluted by transferring 205 µL from each well to the well below it, yielding the final E2 concentrations listed in Table 1. Note that, at the end of the serial dilution process, 205 µL must be discarded from wells G1 through G3 to achieve a final volume of 120 µL in each well. Sample and negative extraction control wells were prepared by adding 5 µL of each extract (dissolved in 50% ethanol) to 320 µL of yeast. Vehicle control wells (H1 – 3) were prepared by adding 5 µL of 50% ethanol to 320 µL of yeast. All sample and control wells were mixed by pipetting, and 205 µL were removed and discarded to adjust well volumes to 120 µL each. Lastly, media controls were prepared by plating 120 µL of galactose media into wells H10 – 12. To use the LacZ calculator in Appendix 1 and the R-based application described in Appendix 2, the E2 standard curve and vehicle and galactose media controls must be plated as shown. Samples and negative extraction controls can be plated in any of the white wells as long as the order of plating is noted. Please click here to view a larger version of this figure.
Figure 2. Standard Curves for the YES Plates Generated via 4-parameter Logistic Regression. Two substrates (ONPG & CPRG) were tested using yeast expressing one of two human estrogen receptors (ERα or ERβ) both without (A) and with (B) a 6 d refrigeration period after the 17 h incubation with 17β-estradiol and sample extracts. All E2 standards and media and vehicle controls were tested in triplicate. Points represent means of triplicate LacZ values, where LacZ values reflect the degree of color change induced by β-galactosidase. Logistic regression model parameters are listed in Table 3. ONPG = ortho-nitrophenyl-β-D-galactopyranoside; CPRG = chlorophenol red-β-D-galactopyranoside. Please click here to view a larger version of this figure.
Figure 3. Examples of Developed YES Plates. Two substrates (ONPG & CPRG) were tested using yeast expressing human estrogen receptors (ERα or ERβ), either without (left) or with (right) a six-day refrigeration period after the 17 h incubation with 17β-estradiol or sample extracts. All E2 standards, media and vehicle controls were tested in triplicates. Plates were arranged with the highest E2 concentration in the top row of each plate and controls (50% ethanol + yeast on the left and galactose media on the right) in the bottom row of each plate according to Figure 1. ONPG = ortho-nitrophenyl-β-D-galactopyranoside; CPRG = chlorophenol red-β-D-galactopyranoside. Please click here to view a larger version of this figure.
Standard Number | [E2] for ERα yeast (pM) | [E2] for ERβ yeast (pM) |
1 | 3500 | 150 |
2 | 2208 | 94.6 |
3 | 1393 | 59.7 |
4 | 878 | 37.6 |
5 | 554 | 23.7 |
6 | 349 | 15 |
7 | 220 | 9.45 |
Table 1. Final Concentrations of E2 Standards used in the YES.
Powdered E2 was dissolved in anhydrous ethanol and then diluted to working stock concentrations of 227.5 nM (for yeast that express ERα) and 9.75 nM (for yeast that express ERβ) in 50% ethanol. Working stocks were then added to microplate wells containing yeast in galactose media and serially diluted to the concentrations shown in the table.
Samples Tested | Assay Conditions | Estrogenic Equivalents (EEQs) of PCPs | |||||
PCP # | Sample Type | Receptor | Substrate | EEQ 1 (ng/g) | EEQ 2 (ng/g) | EEQ 3 (ng/g) | Mean EEQ (ng/g) |
1 | Hair cream | ERα | ONPG | ND | 0.379 | ND | <0.379 |
1 | Hair cream | ERα | CPRG | ND | ND | ND | ND |
1 | Hair cream | ERβ | ONPG | 0.528 | 0.338 | 0.363 | 0.410 |
1 | Hair cream | ERβ | CPRG | ND | 0.215 | ND | <0.215 |
4 | Sunscreen | ERα | ONPG | 6.803 | 1.390 | ND | <4.097 |
4 | Sunscreen | ERα | CPRG | ND | ND | ND | ND |
4 | Sunscreen | ERβ | ONPG | 1.321 | 0.838 | 0.818 | 0.992 |
4 | Sunscreen | ERβ | CPRG | 0.651 | 0.591 | 0.725 | 0.656 |
7 | Foundation | ERα | ONPG | ND | ND | ND | ND |
7 | Foundation | ERα | CPRG | ND | ND | ND | ND |
7 | Foundation | ERβ | ONPG | ND | 0.158 | ND | <0.158 |
7 | Foundation | ERβ | CPRG | ND | ND | ND | ND |
9 | Shave cream | ERα | ONPG | ND | ND | ND | ND |
9 | Shave cream | ERα | CPRG | ND | ND | ND | ND |
9 | Shave cream | ERβ | ONPG | ND | 0.256 | 0.295 | <0.276 |
9 | Shave cream | ERβ | CPRG | 0.507 | 0.392 | 0.560 | 0.486 |
10 | Nail Polish | ERα | ONPG | ND | ND | ND | ND |
10 | Nail Polish | ERα | CPRG | ND | ND | ND | ND |
10 | Nail Polish | ERβ | ONPG | 0.916 | 0.503 | 0.554 | 0.658 |
10 | Nail Polish | ERβ | CPRG | 0.532 | 0.628 | 0.594 | 0.585 |
11 | Lotion | ERα | ONPG | ND | ND | 2.327 | <2.327 |
11 | Lotion | ERα | CPRG | ND | ND | ND | ND |
11 | Lotion | ERβ | ONPG | Exceeds range | 2.599 | 1.845 | >2.222 |
11 | Lotion | ERβ | CPRG | — | 1.986 | 1.236 | 1.611 |
13 | Sunscreen | ERα | ONPG | 14.069 | 11.494 | 10.189 | 11.917 |
13 | Sunscreen | ERα | CPRG | 4.773 | 5.790 | 5.850 | 5.471 |
13 | Sunscreen | ERβ | ONPG | Exceeds range | 2.580 | Exceeds Range | >2.580 |
13 | Sunscreen | ERβ | CPRG | 0.292 | 0.240 | ND | <0.266 |
15 | Lip balm | ERα | ONPG | ND | ND | 0.431 | <0.431 |
15 | Lip balm | ERα | CPRG | ND | ND | ND | ND |
15 | Lip balm | ERβ | ONPG | 1.202 | 1.060 | 0.887 | 1.050 |
15 | Lip balm | ERβ | CPRG | 0.820 | 0.871 | 0.851 | 0.847 |
Table 2. EEQs of PCPs with non-zero EEQs. Three aliquots of 15 PCPs and three extraction controls were homogenized in anhydrous ethanol, evaporated, and reconstituted in 50% ethanol for a total of 48 samples, each of which was analyzed in triplicate using the YES assay. Eight PCPs had at least 1 non-zero EEQ, while 7 PCPs were not found to be estrogenic at the tested concentrations. EEQ 1, EEQ 2, and EEQ 3 refer to the three aliquots of each PCP, each tested in triplicate on a separate plate. Values for EEQ 1, EEQ 2, and EEQ 3 are the means of the triplicates for each aliquot. Yeast used in the assay expressed 1 of 2 isoforms of human estrogen receptors (ERα or ERβ). Two colorimetric substrates, ONPG and CPRG, were tested using the non-refrigerated protocol. EEQs were determined using four-parameter logistic regressions (with R2 values ≥ 0.98) of LacZ values at each of 7 concentrations of E2. ND = below detection limit of the assay. — = lost replicate.
Assay Conditions | Model Parameters | ||||||
Receptor | Substrate | Arrest at 4 °C for 6 d | Model R2 | Growth Rate (LacZ units/ng/ml) | Inflection Point (ng/mL) | Lower Asymptote (LacZ units) | Upper Asymptote (LacZ units) |
ERα | ONPG | NO | >0.99 | 8.548 ±1.633 | -0.512 ±0.025 | -1.623 ±4.408 | 128.11 ±6.31 |
ERα | ONPG | YES | >0.99 | 7.618 ±0.758 | -0.587 ±0.014 | -8.378 ±2.223 | 99.53 ±2.528 |
ERα | CPRG | NO | >0.99 | 8.256 ±2.182 | -0.610 ±0.033 | 0.853 ±3.333 | 62.52 ±3.473 |
ERα | CPRG | YES | >0.99 | 5.068 ±0.616 | -0.523 ±0.022 | -3.147 ±1.946 | 68.06 ±3.069 |
ERβ | ONPG | NO | >0.99 | 1.041 ±2.004 | -0.898 ±4.410 | -32.98 ±86.62 | 248.6 ±778.9 |
ERβ | ONPG | YES | >0.99 | 4.327 ±1.289 | -1.736 ±0.087 | 4.654 ±3.087 | 66.37 ±10.75 |
ERβ | CPRG | NO | = 0.99 | 5.673 ±1.764 | -1.914 ±0.052 | 3.925 ±1.679 | 28.05 ±2.334 |
ERβ | CPRG | YES | >0.99 | 4.412 ±1.142 | -1.894 ±0.051 | 2.052 ±1.303 | 22.64 ±2.047 |
Table 3. Model Parameters of 4-parameter Logistic Regressions for the Standard Curves in Figure 2. Two substrates, ONPG and CPRG, were tested using yeast expressing 1 of 2 human estrogen receptors (ERα or ERβ) both without and with a six-day refrigeration period after the 17 h incubation. Parameters are reported as estimates ±standard errors.
Appendix 1. Application for Calculating LacZ Values. To use the application, first download free Java software (as noted in Table of Materials). Then open the LacZ application. The plate layout used with the application must be identical to the plate layout presented in Figure 1. If some sample wells were not used, retain absorbance readings from the empty wells as place holders in the absorbance dataset being pasted into the LacZ application. This preserves the spatial layout of the plate in the application and ensures that media control wells are in their required location. Additionally, the application will not execute if there are empty cells. Paste in OD405 readings (for ONPG) or OD574 readings (for CPRG) of all wells using keyboard command “control (ctrl) + v” or “command + v,” depending on the computer platform being used. Enter the amount of incubation time in hours for the assay to produce color (from step 5.4; for example, 0.66667 h for 40 min). Click next. Paste in OD610 readings from step 5.3. Click submit. LacZ results will be displayed and can be copied by pressing “control (ctrl) + c” or “command + c,” depending on the computer platform being used. Please click here to download this file.
Appendix 2. Statistical Software Options for Calculating EEQs. EEQs can be calculated using one of three presented options. Directions for using 1. JMP software or 2. R code are provided in Appendix 2. The R code has also been converted to 3. an application format available at https://furmanbiology.shinyapps.io/YESapp/. Please click here to download this file.
Appendix 3. Sample Data Collected using Yeast that Express ERα and CPRG as the Substrate. Measurements of OD610 and OD574 for each of seven E2 standards, vehicle and media controls, and a single representative PCP sample are included, along with calculated LacZ values. LacZ values of standards were used to construct a four-parameter logistic regression model of the standard curve as described in steps 7A & B above. The model was used to interpolate triplicate estimates of EEQs of the representative sample in ng/mL in the microplate wells. These values were then converted to EEQs expressed as ng/g of sample (step 8.1). Please click here to download this file.
The YES is a low cost method used to detect estrogenic ligands in environmental samples, such as water, food, plant tissues, or personal care products. Data presented here compare 2 estrogen receptors (ERα and ERβ), 2 substrates (ONPG and CPRG), and 2 timelines (2 d protocol without refrigeration and seven-day protocol with refrigeration) for measuring estrogenicity in personal care products via the YES assay. The 7 d, refrigerated protocol using CPRG and yeast expressing ERα and/or ERβ best quantifies EEQs while also being compatible with the time constraints imposed by undergraduate laboratory courses that meet only once/week for several h. In fact, compared to the 2 d assay without refrigeration, the seven-day refrigerated assay was associated with reduced variance across plate replicates. In addition, the linear part of the standard curve was slightly expanded for data collected using the refrigerated assay. The linear portion of the standard curve defines the assay detection range and is the only portion of the standard curve that can be used to interpolate sample EEQs.
In all but one of the tested samples, EEQs measured using CPRG were lower than those quantified with ONPG. With a higher extinction coefficient and lower Km and Vmax, CPRG is ten times more sensitive than ONPG17. Thus, CPRG can be used at lower concentrations and can be used to detect lower amounts of β-galactosidase. For these reasons, CPRG is generally preferred over ONPG18,19. However, greater substrate sensitivity does not explain the lower EEQ values detected with CPRG. The higher EEQ values detected with ONPG could be due to matrix interference with the assay, as noted by other authors2,18. Yellow pigments from personal care product extracts could inflate EEQ values detected with ONPG. Others have circumvented this problem by including pigment controls in their experimental design2, an approach that doubles the number of plates in an experiment. When matrix interference may be problematic, CPRG may be a preferable substrate for the YES assay, although it is more expensive and requires longer incubation times than ONPG. Furthermore, the color change induced by the cleavage of substrate by β-galactosidase is more dramatic with CPRG, making it easier for students to visualize results.
Miller et al. (2010), who engineered the yeast used in this protocol, noted that yeast expressing ERβ were 30x more sensitive to 17β-estradiol than yeast expressing ERα, a finding substantiated by our data14. Apart from potential nuances in plasmid construction, Miller et al. (2010) could not explain this difference in sensitivity14. One difference between the two plasmid constructs is that ERα expression is regulated by galactose, whereas ERβ expression is regulated by either glucose or galactose. The yeast used in the YES assay are cultured in glucose media and only given galactose when they are diluted at the start of the assay. Therefore, yeast expressing ERβ might accumulate higher copy numbers of receptor proteins prior to the start of the assay, thereby conferring higher sensitivity to estrogenic ligands.
The lower sensitivity of ERα-expressing yeast may explain the higher rates of non-detection of estrogenicity in samples measured with ERα compared with ERβ. To increase the likelihood that sample EEQs will be detected, users could employ different extraction solvents and methods or add higher volumes of sample to the yeast. If higher sample volumes are used, the concentrations of E2 standards should be adjusted such that the same volume of standards and samples can be used in the assay. One limitation of adding more sample is that yeast can tolerate only 6 – 10% ethanol, with better tolerance at incubation temperatures of 30 Vs. 35 °C20. To control for effects of ethanol on yeast, investigators should add triplicate "yeast only" wells to the plate layout and confirm that the OD610 of these "yeast only" wells is comparable to the OD610 of vehicle control wells immediately after the addition of LacZ buffer. Alternatively, samples dissolved in ethanol can be added to dry microwell plates and the ethanol evaporated off before yeast are added. Dimethylsulfoxide (DMSO) is also used as a sample solvent in YES assays, but the final working concentration of DMSO with yeast should be limited to 1%12.
The YES assay is a powerful screening tool for detecting estrogenicity in environmental samples. Specifically, the YES detects ligands that bind nuclear estrogen receptors that interact with estrogen response elements to direct gene expression14. However, the YES also has important limitations. The YES does not detect EEs that work through non-nuclear mechanisms such as membrane estrogen receptors or mechanisms that involve additional elements such as Activator Protein 1 (AP-1) transcription factors. Moreover, because yeast do not have the same metabolic capacity as mammalian cells, the YES cannot detect ligands that require metabolic activation to be estrogenic.
In addition, the YES assay cannot readily differentiate between estrogenic and anti-estrogenic ligands in complex samples. Instead, it measures net estrogenicity, which is the sum effect of estrogenic and anti-estrogenic ligands. To quantify the concentration of ER antagonists or evaluate the inhibitory activity of mixtures, the assay can be modified by incubating yeast with both the standard agonist (17β-estradiol) and a range of test sample concentrations12. This process determines if antagonists in the samples can diminish agonist-induced reporter activity and provides a useful screen for identifying the presence of ER antagonists in samples.
The protocol presented here can accommodate a variety of sample types, although some samples may require modifications to the extraction and sample preparation steps. For example, EEQs varied widely among replicates of some personal care products. The more variable samples tended to contain oil droplets or were otherwise not entirely homogeneous, indicating that a more lipophilic solvent such as diethyl ether would be helpful. Alternatively, oils and wax in personal care products could be excluded by extracting samples with 50% ethanol instead of 100% ethanol. A 50% ethanol extraction will also capture more water soluble estrogenic ligands (e.g., some pigments). However, 50% ethanol evaporates more slowly than 100% ethanol and thus may extend extraction time. Additionally, some samples (such as soaps) were cytotoxic to yeast, resulting in reduced cell density measurements (OD610). Fox et al. (2008) suggest that such samples should be diluted and retested if cell density differences exceed 30% compared to vehicle control wells12.
If the YES assay is used for analytical research purposes, dilution curves of sample pools can be tested to preemptively determine appropriate volumes of extract to be added to yeast in step 4.5. Alternatively, extracts can be simultaneously tested at multiple volumes (e.g., 5 µL and 20 µL extract added to yeast in step 4.5) or dilutions that span orders of magnitude (e.g., 0.2 µL, 2 µL, and 20 µL). "Appropriate" volumes of extract are those that identify estrogenicity by matching LacZ values along the linear part of the standard curve. Optimization prevents problems caused by adding too much or too little sample to the yeast, such as cytotoxicity, false negatives, or estrogenicity that exceeds the standard curve. As mentioned above, the volumes of samples and E2 standards should be adjusted when different amounts of ligand are used such that yeast are exposed to a consistent volume and concentration of ethanol or other vehicle across the plate.
Despite the potential for false negatives, the YES assay has been identified as a Tier 3 testing tool for endocrine disruptors by Schug et al. (2013), who developed a comprehensive Tiered Protocol for Endocrine Disruption (TiPED)21. For undergraduate education, the assay is valuable for teaching concepts related to endocrine disruption, cell culture, receptor binding, enzyme activity, genetic engineering, statistics, and experimental design. Students who use the assay also practice fundamental and broadly applicable laboratory skills such as serially diluting standards; extracting samples; making solutions; constructing and interpolating standard curves; calculating concentrations; making solutions; demonstrating sterile technique; culturing cells; identifying variables and controls; collecting, organizing, and analyzing data; constructing and interpreting graphs; and using common laboratory equipment such as micropipettors and spectrophotometers.
The authors have nothing to disclose.
This project was funded by start-up funding to TME and AMR from Louisiana Tech University and Furman University, respectively. Additional funding was provided by a 2015 Faculty Advancement Grant to AMR and TME from The Associated Colleges of the South, a Louisiana EPSCoR Pfund grant to TME from the National Science Foundation and the Louisiana Board of Regents, and a travel award to TME from the University of the South. We thank Dr. David Eubanks (Furman) for assistance with statistical analyses and Mr. Christopher Moore for “giving us a hand” during filming.
Equipment | |||
Vortex Mixer (for single or multiple tubes) | Fisher Scientific (www.fishersci.com) | 02-215-365 | Any mixer will suffice. |
Bucket centrifuge | Fisher Scientific (www.fishersci.com) | 75-063-839 | Any bucket centrifuge will suffice if it is capable of centrifuging conical tubes at 4000 rpm. |
Bunsen burner | Fisher Scientific (www.fishersci.com) | 17-012-823 | Any Bunsen burner will suffice, or an alcohol burner (Fisher Scientific 04-245-1) can be used instead. |
Incubator | Fisher Scientific (www.fishersci.com) | 50125590H | Any incubator will suffice if it is capable of maintaining 30 °C. |
Microplate reader | BioTek (www.biotek.com) | EPOCH2 | A different brand of plate reader will suffice if it can measure absorbance at wavelengths of 405, 574, and 610 nm. |
Gen5 microplate reader and imager software | BioTek (www.biotek.com) | GEN5 | Software required depends on make and model of plate reader; GEN5 software is intended for use with BioTek plate reader. |
Refrigerator | Fisher Scientific (www.fishersci.com) | 05LREEFSA | Any refrigerator will suffice if it is capable of maintaining 4 °C. |
Pipettor or PipetAid compatible with 1-10 ml serological pipets | Fisher Scientific (www.fishersci.com) | 13-681-15E | Any pipettors will suffice if they are compatible with 1- and 10-ml serological pipets. |
P10 micropipettor | Fisher Scientific (www.fishersci.com) | F144562G | Any micropipettor will suffice if it is capable of dispensing 5 µl. |
P200 micropipettor | Fisher Scientific (www.fishersci.com) | F144565G | Any micropipettor will suffice if it is capable of dispensing up to 200 µl. |
P300 multichannel pipettor | Fisher Scientific (www.fishersci.com) | FBE1200300 | Any multichannel pipettor will suffice if it is capable of dispensing 50 to 205 µl. |
Repeating pipettor | Fisher Scientific (www.fishersci.com) | F164001G | Must be able to deliver 100-320 µl; this pipettor is optional because a multichannel pipettor can be used instead. |
Name | Company | Catalog Number | Comments |
Supplies | |||
Sterile 15-ml conical tubes with caps | Fisher Scientific (www.fishersci.com) | 05-539-801 | |
Glass scintillation vials | Fisher Scientific (www.fishersci.com) | 03-337-4 | |
Polystyrene 96-well, flat-bottom microplates with lid (non-sterile) | Fisher Scientific (www.fishersci.com) | 12565501 | |
Polypropylene 96-well, flat-bottom microplates without lid | Cole-Parmer (www.coleparmer.com) | EW-01728-81 | |
100 ml glass beakers | Fisher Scientific (www.fishersci.com) | 02-539H | Any glass beakers will suffice if they are autoclavable. |
250 ml glass Erlenmeyer flasks | Fisher Scientific (www.fishersci.com) | FB500250 | Any glass Erlenmeyer flasks will suffice if they are autoclavable. |
Sterile, adhesive, porous film | VWR (www.vwr.com) | 60941-086 | |
Metal forceps | Fisher Scientific (www.fishersci.com) | 12-000-157 | Any metal forceps will suffice. |
Reagent reservoir | Fisher Scientific (www.fishersci.com) | 07-200-127 | |
Filtration units (0.2 µm) | Fisher Scientific (www.fishersci.com) | 09-761-52 | |
Squirt bottle (for ethanol) | Fisher Scientific (www.fishersci.com) | 02-897-10 | Any laboratory squirt bottles will suffice. |
Autoclavable storage bottles | Fisher Scientific (www.fishersci.com) | 06-414-1D | Any autoclavable glass storage bottles will suffice. |
10 ml glass serological pipets (sterile) | Fisher Scientific (www.fishersci.com) | 13-678-27F | Any glass serological pipets will suffice. |
1 ml glass serological pipets (sterile) | Fisher Scientific (www.fishersci.com) | 13-678-27C | Any glass serological pipets will suffice. |
P10 micropipettor tips | USA Scientific (www.usascientific.com) | 1120-3810 | Any tips will suffice if they are compatible with the micropipettor above. |
P200 micropipettor tips | USA Scientific (www.usascientific.com) | 1120-8810 | Any tips will suffice if they are compatible with the micropipettor above. |
P300 micropipettor tips | USA Scientific (www.usascientific.com) | 1120-9810 | Any tips will suffice if they are compatible with the micropipettor above. |
Syringe tips for repeating pipettor | Fisher Scientific (www.fishersci.com) | F164150G | Only required if a repeating pipettor is used. |
Sterile petri dishes | Fisher Scientific (www.fishersci.com) | FB0875712 | Any sterile petri dishes will suffice. |
Parafilm | Fisher Scientific (www.fishersci.com) | S37440 | |
Name | Company | Catalog Number | Comments |
Yeast | |||
Saccharomyces cerevisiae strains that lack the TRP1 gene product (e.g. W303a) | American Type Culture Company (ATCC) (www.ATCC.org) | MYA-151 | Recombinant yeast are also available upon request from the authors. |
Receptor/reporter plasmid for ERα | Addgene (www.addgene.org) | pRR-ERalpha-5Z (Plasmid #23061) | |
Receptor/reporter plasmid for ERβ | Addgene (www.addgene.org) | pRR-ERbeta-5Z (Plasmid #23062) | |
Name | Company | Catalog Number | Comments |
Chemicals | |||
Difco agar | BD (www.bd.com) | 214530 | |
Dithiothreitol | Sigma (www.sigmaaldrich.com) | D0632 | CAUTION: Dithiothreitol is an acute skin and eye irritant. Use appropriate personal protection equipment (gloves, fume hood, dust mask) to avoid skin and eye contact, inhalation and ingestion. |
Ortho-nitrophenyl-β-D-galactopyranoside | Sigma (www.sigmaaldrich.com) | N1127 | |
Chlorophenol red-β-D-galactopyranoside | Sigma (www.sigmaaldrich.com) | 10884308001 | |
Yeast nitrogen base | Sigma (www.sigmaaldrich.com) | Y0626 | |
Glucose | Sigma (www.sigmaaldrich.com) | G8270 | |
Galactose | Sigma (www.sigmaaldrich.com) | G5388 | |
Adenine sulfate | Sigma (www.sigmaaldrich.com) | A9126 | |
Uracil | Sigma (www.sigmaaldrich.com) | U0750 | |
Leucine | Sigma (www.sigmaaldrich.com) | L8000 | |
Histidine | Sigma (www.sigmaaldrich.com) | H8000 | |
17 β-Estradiol | Sigma (www.sigmaaldrich.com) MP Biomedicals | E8875-250 mg 0219456401 – 1 mg | CAUTION: Estradiol is a suspected carcinogen and reproductive toxicant. It is harmful if inhaled, swallowed, or absorbed through skin. Estradiol may cause harm to breast-fed children and fetuses. Estradiol is very toxic to aquatic life. Use appropriate personal protection (gloves, fume hood, dust mask) and avoid exposure during pregnancy and lactation. Estradiol should be disposed of as hazardous waste and not released to the environment. |
100% ethanol | Pharmco-Aaper (www.pharmcoaaper.com) | 111000200 | |
Sodium phosphate monobasic monohydrate | Sigma (www.sigmaaldrich.com) | S9638 | |
Sodium phosphate dibasic (anhydrous) | Sigma (www.sigmaaldrich.com) | S0876 | |
Magnesium chloride | Sigma (www.sigmaaldrich.com) | M8266 | |
Potassium chloride | Sigma (www.sigmaaldrich.com) | P9333 | |
Sarkosyl (N-lauroylsarcosine sodium salt) | Sigma (www.sigmaaldrich.com) | L5125 | |
Sodium carbonate | Sigma (www.sigmaaldrich.com) | S7795 | |
Name | Company | Catalog Number | Comments |
Software | |||
Excel spreadsheet software | Microsoft | Excel is convenient spreadsheet software for managing data outputs and generating .csv files for R analysis. | |
Java software (required for Appendix 1 application) | Oracle Corporation | To calculate LacZ values using the application in Appendix 1, first download free Java software (https://www.java.com/en/download/), then open the LacZ application in Appendix 1. LacZ results created by the application can be copied by pressing "control (ctrl) + c" on PC keyboards, or "command + c" on Mac keyboards. | |
JMP statistical software version 13.0.0 | SAS Institute | Appendix 2 includes directions on using JMP to fit LacZ data to a four-parameter logistic regression curve. The curve is used to interpolate test sample estradiol equivalents (EEQs), relative to the estradiol standard curve. | |
R statistical computing and graphics software | R Foundation | Free R software can be downloaded from https://www.r-project.org/. Directions and code for using R to fit LacZ data to a four-parameter logistic regression curve are given in Appendix 2. |