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Appendix G: Section 7 Supplemental, ERES TrSet Decision Criteria for Binder/Nonbinder 

and Data Collection and Processing Details 

G.1 Data Interpretation: Decision Criteria using Binding, Gene Activation and Associated 

Information to Determine Binders and Nonbinders. 

The following text and figures describe the types of information collected and how the 

information is used to classify test chemicals as Binders or Nonbinders in the ERES TrSet. This 

is meant to be a quick summary of the approach described more fully in the 2009 SAP to 

illustrate the decision process and the multiple lines of evidence collected and used in 

interpreting the data. The series of figures (Figures G-1 to G-8) illustrate various steps in the 

process and how the information is used together to provide a mechanistic understanding of the 

chemical’s activity in the assay as well as any effects assay components may have on the 

measured response. 

The empirical mechanistic evidence from rtER cytosolic binding assays and trout liver Vtg gene 

expression (GA) assays run in agonist and antagonist mode, along with recombinant rtERa 

binding assay data, and binding assay Ki determinations are all utilized together, as applicable 

(further described below) to assign a Binder or Nonbinder ‘hitcall’ for a parent chemical 

structure tested in the assays. These decisions are further supported by including measures of 

assay parameters such media pH stability over the incubation period, cytotoxicity in the Vtg 

(GA) assay, and solubility in binding and GA assays in the interpretation. Additionally, 

analytical chemistry is used when applicable to verify sustained presence of parent chemical in 

binding assays or investigate hypothesized bioactive metabolites. Information on compound 

chemistry is also used to assess the likelihood of charged chemical species presence under the 

assay conditions. Decision pathways also include a consideration of the activity of the other 

TrSet chemicals found within an ERES chemical group. Figure 1 provides an overview of the 

process, showing how rtER binding and GA assays are used in concert and iteratively in 

assigning Binder and NonBinder determinations. (Details for interpretations of binding curves 

and how the information is used to trigger GA assays are provided in Figures G-2 to G-6.) 

The decision process overview is as follows and shown in Figure G-1. It begins by asking if 

there is a reproducible ER binding result. If Yes, the type of result detected leads to further 

questions. Where there is no indication of binding in 2 reproducible replicate runs, each using 

different trout liver cytosol preparations (a flat line means no indication of binding 

displacement), and the chemical is in a ERES TrSet class where all members tested so far are 

Nonbinders (verified with GA confirmation for representative chemical(s) within the class), the 

chemical is added to the TrSet database as a Nonbinder. If there is reproducible binding 

displacement, an additional binding assay is run to obtain a third replicate for calculation of an 

RBA. The degree of displacement triggers a more detailed decision path (Figure G-2). If 

displacement is >80%, and the chemical is in a previous ERES class, and within the LogKow 

range of previously determined ER Binders (confirmed by Vtg GA), the chemical is added to the 

TrSet as an ER Binder. Where significant displacement is <80%, or the chemical is in a class 

new to ERES, the chemical proceeds to GA testing. (Again, more details are provided in 

additional figures and text below.) If GA is confirmed the chemical is added to TrSet as Binder, 
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and if not confirmed it’s added as a NonBinder. More detailed information on additional 

questions asked (information gathered) and decision within the boxes is provided in Figure G-2 

to G-8. 

If NO is the answer to the first question in Figure G-1, because replicate binding runs are outside 

of the typical tight assay variance, further investigation is done. Historically this occurs when the 

parent chemical is converted to a metabolite with higher affinity for the receptor, and because it 

occurs to different degrees in the 3 replicate cytosols the result is a higher CV. Thus, 

investigations to confirm or refute the possibility of metabolic transformation are conducted, 

including identification of the metabolite responsible for the binding. Figures G-7 to G-8 

illustrate how metabolism hypotheses are investigated in conjunction with binding, and GA data, 

respectively. 

Figure G-1. Overview of Decision Paths used to make final ER Binder or Nonbinder 

activity call for ERES TrSet chemicals. The figure illustrates the questions asked and 

resulting actions taken to gain sufficient confidence to assign chemical activity. Details of 

portions of the pathways are provided in Figures G-2 to G-8. 
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Figure G-2 shows 5 categories or ‘types’ of binding displacement curves that are found. 

Depending on whether a chemical yields a curve of type A through E determines whether a GA 

assay or other tests are done. Figures G-3 to G-6 show detailed flow charts for each binding 

Type. Type A & B are covered in Figure G-3; Type C in Figure G-4; Type D in Figure G-5, and 

Type E in Figure G-6. One common question is whether the chemical belongs to a “known 

inactive” class, for instance one that can yield assay results of ‘apparent’ but not real binding 

displacement (e.g., refer to detailed discussion on charged compound in SAP 2009). Thus, the 

questions asked and final interpretation build on previous knowledge and detailed investigations 

done to gain confidence in data interpretation. 

Cyto rtER binding 

displacement results

Type A 

Displacement : 

80% or greater

Decision Path Step 1:

Analyze Binding Displacement Curve to Trigger Next Step 

Type B 

Displacement:

50 to 80%

Type C 

Displacement:

20 to 50%

Type D

Displacement: 

5 to 20%

Type E:

Displacement: 

Flatline/skijump

Figure G-2. TrSet Decision Path Step 1: Characterize the Type of Reproducible Binding 

Displacement Curve Produced for the Chemical Under Study. The figure illustrates 

categories of binding assays results that are analyzed to determine if a confirmatory slice 

Vtg GA assay is needed. See Figures 3 to 6 for detailed decision paths for each binding 

type. 
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Figure G-3 shows the decision path when a chemical yields a Type A and B binding 

displacement curve. If there is a lot of previous information for chemicals in this ERES chemical 

group then the confidence is high in assigning a Binder determination to the newly tested 

chemical in the group yielding at least a 50% displacement curve (Type B) or > 80% 

displacement (Type A), if its within a known active class. Or if it’s in a class known to give 

false positives with a good mechanistic understanding, then the chemical is classes as a 

Nonbinder. There is the option of using the in-depth determination of nature of the binding 

displacement referred to as Ki investigations where needed to gain more mechanistic 

understanding. When previously done these experiments have confirmed the GA results, that is, 

that the apparent binding was not due to ER-ligand interaction but other effects (e.g., charged 

species denaturing proteins resulting in labeled ligand release but not true competitive binding). 

Figure G-3. Decision Path Step 2 to determine if a Vtg gene activation (GA) assay needs to 

be run, and the final activity assignment given to the chemical based on results of the GA 

assay are shown. This decision path is used for: A) chemicals yielding a Type A ER 

Binding displacement curve of >80% and also in a previously untested ERES chemical 

class; and B) chemicals with 50% to 80% binding displacement. In each case the assay 

result must be reproducible. 
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A similar analysis is done in Figure G-4 when Type C binding curves are noted. Notice the 

additional use of recombinant (rec) rtER assays also appears in this figure. The higher total 

protein concentration in cyto rtER preparations can result in lowering chemical bioavailability so 

only partial curves are obtained, while the same chemical tested in the rec rtER preparation (with 

lower total protein) may yield a more complete curve. Thus, this assay can help to confirm 

parent chemical ER binding is responsible for the GA result and not a metabolite. However, if 

no displacement is seen in this assay, but GA was seen, the chemical is put in a ‘hold for further 

investigation’ box which can include looking for a possible metabolite to which GA might be 

attributable. 

Figure G-4. Decision Path Step 2 for Type C chemicals yielding 20 to 50% displacement in 

cyto rtER binding assays. The questions asked to determine if a Vtg gene activation (GA) 

assay needs to be run and the final activity assignment given to the chemical to add it to the 

TrSet are shown. 
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In Figure G-5 the information is used to gain confidence in the Binder or NonBinder decision 

when Type D curves are noted, where there may be some slight indication of binding and thus 

more uncertainty exists than for members of “known inactive” classes. The additional 

information may include some evidence of binding from literature references, and/or that the 

ERES class the chemical is in raises the likelihood that it may be a binder, or there is little 

evidence either way for a chemical from a new ERES chemical group. 

Figure G-5. Decision Path Step 2 for Type D chemicals yielding 5 to 20% displacement in 

cyto rtER binding assays. The questions asked in determining if Vtg gene activation (GA) 

assays need to be run, and the final activity assignment given to the chemical to add it to 

the TrSet are shown. 

The next figure (Figure G-6) largely pertains to investigations into a new ERES chemical group, 

or for a chemical with evidence in the literature that it may be an ER Binder. In instances with 

some TrSet knowledge within the class and no TrSet evidence of binding, but uncertainty due to 

literature reports, the metabolism hypothesis warrants investigation. Further investigations to 

determine if the activity noted is due to a metabolite and not the parent chemical are shown in 

Figures G-7 (utilizing binding assays along with analytical chemistry) and in Figure G-8 (for 

investigating metabolism hypotheses in GA assays with chemical analyses). 

Taken together, the decision pathways in Figures G-1 to G-8 illustrate that many different lines 

of information are used to gain mechanistic insights into whether a chemical is interacting at the 
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ER ligand domain and capable of producing GA apart from possible artifacts, and to gain 

confidence that the binding is due to the parent chemical form and not a metabolite. The figures 

also demonstrate the process of combining this information to derive a final “hit call” for a 

chemical that reduces the level of uncertainty and providing more confidence in both Binder and 

NonBinder TrSet determinations. 

Figure G-6. Decision Path Step 2 for chemicals yielding no indication of binding (Type E) 

but there is greater uncertainty, e.g., the chemical class has not been previously 

investigated, or there is literature evidence of apparent ER Binding. The questions asked to 

determine if Vtg gene activation (GA) assays need to be run, and the final activity 

assignment given to the chemical to add it to the TrSet are shown. 
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Figure G-7. Decision Path used when an ER active metabolite is suspected. The questions 

asked using a combination of analytical chemistry and metabolite confirmation in binding 

assays is shown. 

Figure G-8. Decision Path to investigate metabolic activation hypotheses in slice Vtg GA 

assays. The questions asked using a combination of analytical chemistry and metabolite 

confirmation in slice assays is shown. 
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G.2. Data Collection and Processing

Cytosolic rtER Binding Assay

Trout liver cytosol containing endogenous ERs was prepared from individual fish using a 

method modified from Laws et al. (1996) as reported in Schmieder et al. (2004). Competitive 

binding assays modified from Laws et al. (1996) were performed to measure rtER affinity for 

test chemicals as described in Schmieder et al., (2004). The competitive binding assays used 

displacement of [3H]-E2 from the rtER as the binding endpoint. Data were analyzed to 

determine relative binding affinity (RBA) for Binders with respect to the IC50 for E2 conducted 

in that experiment. Ligand binding characterizations (Ki binding assay) were performed when 

necessary on a case by case basis to assess whether binding was true competitive binding assays 

or not (Schmieder et al. 2004). 

Rainbow Trout Liver Slice Vitellogenin mRNA Assay

Slices were prepared from the livers of immature male rainbow trout and incubated at one slice 

per well in a multi-well plate system as previously described Schmieder et al. (2000). Slices 

were incubated with ethanol (0.2%) controls, E2 (10-10 to 10-5 M, in duplicate) as positive 

controls, and six concentrations of test chemical. After 48h incubation slices were analyzed for 

VTG mRNA by real time reverse transcriptase polymerase chain reaction (Q-PCR) as described 

in Schmieder et al. 2004. 

Slice viability was assessed three ways: 1) through visual observation, 2) observed decrease in 

total extractable slice RNA as a crude indicator of viability, and 3) by monitoring lactate 

dehydrogenase (LDH) leakage into slice media as previously described (Schmieder et al. 2000). 

Each chemical was tested in at least two agonist tests and if no agonist activity was apparent, was 

further tested in at least one antagonist test. 

Chemical Analyses

A subset of the chemicals tested in the slice and binding assays assay underwent chemical 

analysis for behavior over time in the assay system. Chemicals were chosen for chemical 

analysis based on their activity in the slice assay and analytical knowledge of other chemicals in 

the same chemical class. A variety of analytical chemistry techniques were employed to

measure test chemical concentration in binding and gene assays where necessary (Schmieder et 

al. 2004). Techniques of analysis included HPLC, GC-MS and LC-MS. 

Analysis of Binding and Vtg mRNA Data: GraphPad Prism (GraphPad Software, San Diego, 

CA; www.graphpad.com) was used for curve generation and statistical analysis. Competitive 

binding curves and IC50s for the full E2 response curve and test chemicals were generated as 

described in Schmieder et al. 2004. The Vtg mRNA data for test chemical was analyzed using 

the nonparametric Kruskal-Wallis Rank Sum test with a Dunn’s post hoc test comparing test 

chemical results to negative control results (p-value 0.05) to identify test chemical concentrations 

which significantly induced Vtg mRNA expression above the level in the control slices in that 

same run. The Vtg mRNA induction curve for the concentration response of E2 run in parallel 

were not compared to the test chemical in an assay. The response of these positive controls was

used as a QC verification that the assay was responding as expected. For an acceptable slice 

assay the maximum E2 response needed to be greater than 1E+06 Vtg mRNA copies/400 ng 
10

total RNA and the LOEC for E2 should be equal to or less than -8 log M. If this response level 

and potency was not achieved the slice data was not used. 

References

Laws, S.; Carey, S.; Kelce, W.; Cooper, R.; Gray, L. E. 1996, Vinclozolin does not alter 

progesterone receptor (PR) function in vivo despite inhibition of PR binding by its metabolites in 

vitro, Toxicology, 112:173-182. 

Schmieder, P.; Tapper, M.; Linnum, A.; Denny, J.; Kolanczyk, R.; Johnson, R.. 2000, 

Optimization of a precision-cut trout liver tissue slice assay as a screen for vitellogenin 

induction: comparison of slice incubation techniques. Aquat. Toxicol., 49:251-268.

Schmieder, P. K.; Tapper, M. A.; Denny, J. S.; Kolanczyk, R. C.; Sheedy, B. R.; Henry, 

T. R.; Veith, G. D. 2004. Use of trout liver slices to enhance mechanistic interpretation 

of estrogen receptor binding for cost-effective prioritization of chemicals within large 

inventories. Environ. Sci. Technol. 38:6333-6342.