AOP ID and Title:

Short Title: Aromatase inhibition leads to male-biased sex ratio via impacts on gonad differentiation

Authors

Kelvin J. Santana Rodriguez, Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Great Lakes Toxicology and Ecology Divison, Duluth, MN, USA

Daniel L. Villeneuve, Kathleen M. Jensen, Gerald T. Ankley, US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, MN, USA

David H. Miller, US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Ann Arbor, MI, USA

Status

Abstract

This adverse outcome pathway links inhibition of aromatase activity in teleost fish during gonadogenesis to increased differentiation to testis resulting in a male-biased sex ratio in the population, and ultimately, reduced population sustainability.  Most gonochoristic fish species develop either as males or females and do not change sex throughout their life span. However, in species where sexual differentiation is controlled at least to some degree by environmental factors, there can be a window of development during gonadal differentiation that is sensitive to a variety of exogenous conditions, including exposure to some chemicals. For example, treatment with sex steroids in conjunction with the period of sexual differentiation has been showed to favor ovary or testis development in fish exposed to estrogens or androgens, respectively. Altered synthesis and regulation of endogenous steroids can also affect sexual differentiation in fish. In most vertebrate taxa, aromatase (cytochrome P450 [CYP]19a1) is the rate-limiting enzyme for the conversion of 17β-estradiol (E2) from testosterone (T). Endocrine-active chemicals such as fadrozole, letrozole and exemestane (pharmaceuticals) or prochloraz and propiconazole (fungicides) inhibit aromatase activity. Exposure of some  fish species to aromatase inhibitors during sex differentiation can reduce endogenous E2 synthesis, thereby resulting in phenotypic males, the default sex in the absence of estrogen signaling during gonadal differentiation. Given the critical role of female fecundity in determining total numbers of offspring, the resultant male-biased sex ratio can reduce population size, especially if sustained over multiple generations.

Background

In fish sexual differentiation occurs post hatch and can be influenced by exogenous factors such as chemicals, temperature, pH, population density, social cues and more. As a result, the gonadal sex phenotype in oviparous fish can be altered by environmental conditions experienced during development, particularly in conjunction with sexual differentiation (Scholz and Klüver, 2009). At this stage, the bipotential gonad can differentiate to either testes or ovaries depending both on genetic and environmental factors (Strüssmann and Nakamura, 2002). Sex steroids are among the factors that influence sex differentiation in non-mammalian vertebrates; in many fish species exogenous androgens and estrogens act, respectively, to enhance the development of testes and ovaries in exposed animals (Nakamura 2010). In teleost fish, the relative balance between endogenous estrogens and androgens during sexual differentiation is critical to ensuring normal sex ratios and, ultimately, viable populations. Various homeostatic mechanisms ensure that steroid biosynthesis is appropriately controlled during development. A key biosynthetic enzyme is CYP19a1 (aromatase), which is responsible for the conversion of C19 androgens (e.g., T) to C18 estrogens (e.g., E2) in brain and gonadal tissues of vertebrates (Payne and Hales, 2004; Simpson et al. 1994).  In fish, there are two CYP19a1 isoforms, with CYP19a1a mostly expressed in the gonads and CYP19a1b largely expressed in the brain (Callard et al. 2001).

Since the mid-90s, there has been concern about the potential impacts of endocrine disrupting chemicals (EDCs) in fish and wildlife. Many  EDCs can exert effects in early life stages that can lead to potential impacts at the population level. For example, some chemicals have been shown to alter the sexual phenotype of fish by affecting steroidogenic enzymes such as aromatase. Inhibition of CYP19a1 expression or activity can alter the production  of estrogens in  developing gonads, affecting processes such as gonadal differentiation. In many fish species the “default” gonad type is testes, so when estrogen signaling is reduced there is a resultant bias toward male-biased sex ratios (Guiguen et al. 2010).   When male biased sex ratios occur, the number of breeding females can decrease over time and have negative impacts on population growth and sustainability. The present AOP provides the evidence framework of the negative impacts of aromatase inhibition at early developmental stages of teleost fish  during the critical period of sexual differentiation and how this could lead to  population-level effects.

 

Summary of the AOP

Events

Molecular Initiating Events (MIE), Key Events (KE), Adverse Outcomes (AO)

Key Event Relationships

Stressors

Stressor:292 Clotrimazole

Brown et al., 2015

Overall Assessment of the AOP

See details below.

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

Life Stage

 

The life stage to which this AOP applies is developing embryos/juveniles during gonadal differentiation. Since the sexually dimorphic expression of aromatase has been shown to play a crucial role in the differentiation to testis vs ovary of the undifferentiated bipotential gonad (Guiguen et al. 2010), the AOP is applicable to the stage of development during which aromatase might influence this process. The precise timing of the sensitive period relevant to this AOP will vary by species, but the AOP is not applicable to differentiated juveniles or to adults.

Studies with zebrafish (Danio rerio) have shown that both brain and gonadal aromatase expression can be observed at 20 days post-fertilization (dpf) with an increase in expression at 25 dpf in fish destined to become females, coinciding with the onset of gonadal differentiation period (Lau et al. 2016). In Nile tilapia (Oreochromis niloticus), aromatase expression can be observed as early as 3-4 dpf with an increase in expression starting at 11 dpf in genetic females (Kwon et al. 2001). Additionally, it has been shown that the period of 7-14 dpf is the most sensitive to chemical inhibition of CYP19a1 activity, and a continuous exposure of 2-3 weeks is sufficient for the masculinization of the majority of genetic female tilapia (Kwon et al. 2000). This clearly indicates alteration of differentiation from ovary to testis results during sex differentiation (OECD 2011). 

Sex

 

The molecular initiating event for this AOP occurs during gonad differentiation. Therefore, the AOP is only applicable to sexually undifferentiated individuals.  

Taxonomic

 

Most evidence for the taxonomic applicability of this AOP comes from species in the class Osteichthyes. Aromatase itself is well conserved among vertebrates (e.g., Wilson et al. 2005; LaLone et al. 2018).  However, the degree to which aromatase and subsequent production of endogenous estrogens such as E2 are involved in sex determination or sexual differentiation varies with species. Many fish, amphibian, and reptile species have environmental sex determination, and regulation of aromatase expression and sex steroids profiles are closely tied to sex-determining environmental factors (Angelopoulou et al. 2012). Alternatively, vertebrates that largely rely on genetic sex determination (birds, mammals) would be anticipated to be less vulnerable to effects of aromatase inhibitors during gonad differentiation, although there remains compelling evidence for an important role of steroid signaling during the process (Angelopoulou et al. 2012).  Overall, regardless of differing roles for aromatase in sexual differentiation, expression appears universal among vertebrates during this life stage (Angelopoulou et al. 2012; Sarre et al. 2004; Uller and Helantera, 2011; Ramsey and Crews, 2009).  Thus, in principle, components of the present AOP may have some degree of applicability to all vertebrates. Given the substantial diversity of sex determination and differentiation strategies in fish, amphibians and reptiles (including those from closely related phylogenetic groups; Sarre et al. 2004; Angelopoulou et al. 2012), quantiative sensitivity, and taxonomic domain of appicability of the present AOP are hard to generalize, although there is reason to believe it should have broad applicability in bony fishes.

Essentiality of the Key Events

 

Weight of Evidence Summary

Biological Plausibility

Aromatase catalyzes the conversion of T to E2, so the biological plausibility of aromatase inhibition leading to reductions in available E2 is clear. Additionally, the role of E2 as a major regulator of normal female gonad development is well documented (Gorelick et al. 2011; Guiguen et al. 2010). The link between E2 reductions leading to increased differentiation of the bipotential gonad to testis is highly plausible. As E2 signaling is reduced, ER responsive genes required for ovarian differentiation will be downregulated in the bipotential gonad resulting in a default development of testes (Yin et al. 2017; Zhang et al. 2017). Therefore, it is plausible that E2 reduction in the undifferentiated gonad at the onset of sexual differentiation would promote testis formation. The direct link between increased differentiation to testis leading to a male biased sex ratio is also well supported by biological plausibility. If the conditions that favor a male producing phenotype (in this case, the aromatase inhibitor) overlap with the critical period of sex differentiation in a given population, it is reasonable that relatively more male offspring will be produced (D'Cotta et al., 2001, Kwon et al., 2000; Luzio et al. 2016). Therefore, exposure of sensitive species to aromatase inhibition for an extended period of time during reproducitve development plausibly would result in a male-biased population. Empirical evidence supporting the direct link between male biased cohorts and a reduced population sustainability in fish species is limited. However, biased sex ratios can definitely impact fish populations (Marty et al. 2017). For example, a male-biased sex ratio would logically lead to a reduction in the number of breeding females such that over time decreases in offspring would result in population declines (Brown et al. 2015; Grayson et al. 2014). Miller et al. (2022) recently developed a model specifically designed to capture the effects of male-biased sex ratios on population trajectories in fathead minnows (Pimephales promelas). 

Concordance of Dose Response Relationships

There have been a number of in vitro and in vivo studies, primarily in fish, that have examined the effects of known aromatase inhibitors on different key events in the AOP.  Most of these studies only measured one key event in the AOP so cannot be directly used to explore dose-response concordance between key events.

The differential sensitivity to inhibition of aromatase is most easily measured in vitro. Doering et al. (2019b) determined the effects of different concentrations of several known aromatase inhibitors (e.g., fadrozole, prochloraz) on brain aromatase activity in a taxonomically-diverse set of fish species, and found that while absolute potency of the chemicals varied across species, rank order potency of the test chemicals was generally similar. Importantly, relative potencies measured in vitro reflected those observed in in vivo studies such as those described below, thus providing indirect evidence of dose concordance between the MIE and downstream Key Events.

There have been several in vivo studies evaluating the effects of varying degrees of aromatase inhibition on different key events in the AOP. However, there are limitations to these studies in the context of determining dose-dependency across all key events in the AOP. For example, E2 levels typically have not been or measured or determined at a time relevant to gonadal differentiation. However, a few have measured multiple key events, although typically only at one time point. One study assessed dose-reponse relationships between different concentrations of the model aromatase inhibitor exemestane and expression of the enzyme. Immunohistochemical analyses revealed that gonad tissue of Nile tilapia (Oreochromis niloticus) exposed from 9-35 days post-hatch (dph) to 100, 500, 1000 and 2000 μg/g feed had no cross-reaction with P450arom at the three highest doses, but gonad tissue samples exhibited a strong immunopositive responses against P450arom at a lower dose of exemestane (100 μg/g feed), similar to the differentiating ovaries of the control fish (Ruksana et al. 2010). No ovarian development was noted in fish in the 500, 1000 and 2000 mg/kg treatments, and the 1000 and 2000 treatments resulted in 100% phenotypic males.

Uchida et al. (2004) evaluated two key events in the AOP in an experiment with fadrozole using zebrafish genetic females exposed from 15-40 dph via the diet. They observed ovarian transition to testis in all exposed animals, culminating in 62.5, 100 and 100% males in 10, 100 and 1000 mg/kg treatments, respectively.

Another study showed a dose-dependent rate of increased differentiation to testes in zebrafish exposed from 0-63 dph to different concentrations of fadrozole (10, 32, 100 ug/L) via the water (Muth-Köhne et al. 2016).

The most commonly reported dose response relationship for this AOP was for the non-adjacent relationship between aromatase inhibition and an increased male biased sex ratio. For example, Nile tilapia, zebrafish, fathead minnow (Pimephales promelas), bluegill (Lepomis macrochirus), yellow catfish (Pelteobagrus fulvidraco) and Japanese flounder (Paralichthys olivaceus) exposed to different concentrations of known aromatase inhibitors (exemestane, fadrozole, letrozole, prochloraz) via the diet or water reported dose-dependent increases in the relative number of males (Kwon et al. 2000; Kitano et al. 2000; Thorpe et al. 2011;  Holbech et al. 2012; Gao et al. 2010; Shen et al. 2013).

Finally, there are models that demonstrate a dose-dependent decrease in population size corresponding with an increasing proportion of males in zebrafish and fathead minnows (Brown et al. 2015; Miller et al. 2022).

Temporal Concordance

Because this AOP involves actions during a specific development transition from an undifferentiated to differentiated gonad, the temporal concordance of the events is implicit. A male biased sex ratio cannot be observed until the population has undergone sexual differentiation. Likewise, reproduction and associated population growth rate cannot be assessed until the animals achieve sexual maturity.

Consistency

There have been a number of in vitro and in vivo studies, primarily in fish, that have examined the effects of known aromatase inhibitors on different key events in the AOP. Some of these studies measured only one key event in the AOP and/or employed just a single dose of a given stressor, so cannot be directly used to explore dose-response concordance. However, even with these limitations, they demonstrate that the overall AOP is consistent with expectations in a variety of species exposed to known chemical inhibitors of aromatase (see Dose Concordance table). For example, studies with chinook salmon (Oncorhynchus tshawytscha), Japanese fugu (Takifugu rubripes), Japanese medaka (Oryzias latipes), Nile tilapia, zebrafish, fathead minnow, bluegill, yellow catfish and Japanese flounder exposed to known aromatase inhibitors (exemestane, fadrozole, letrozole, prochloraz) via the diet or water during sexual differentiation have reported increases in differentiation to testis and/or the relative number of males (Piferrer et al. 1994; Kwon et al. 2000; Rashid et al. 2007; Kitano et al. 2000; Thorpe et al. 2011; Thresher et al. 2011; Holbech et al. 2012; Gao et al. 2010; Shen et al. 2013).

Male-biased sex ratios are not specific to this AOP. Many of the key events included overlap with another AOP (#376) linking activation of the androgen receptor to male biased sex ratios.

Uncertainties, inconsistencies, and data gaps

Currently the major uncertainty in this AOP is the biological linkage between E2 synthesis reduction by the undifferentiated gonad leading to an increased, differentiation to testis. Biological plausibility connections have been established, but experimental measurements of E2 during the particular period of differentiation are lacking. Also, as noted in the Domain of Applicability section, the taxonomic range of applicability of the AOP is uncertain.

Quantitative Consideration

There is not yet a sufficient quantitative understanding of this overall AOP to predict the degree to which aromatase inhibition would result in population-level impacts. That said, there are models available suitable for the quantitative prediction of changes in E2 levels caused by degree of aromatase inhibition in some small fish species (Conolly et al. 2018; Doering et al. 2019a), as well as the effects of different (male-biased) sex ratios on fathead minnow population size (Miller et al. 2022).  However, there currently are no quantitative data/models relating reductions in E2 to the degree of (increased) differentiation to male gonads and/or male-biased cohorts of fish.  

Considerations for Potential Applications of the AOP (optional)

Altered sex ratios in fish can be a useful diagnostic endpoint for identifying EDCs both in field and lab settings. For example, the Fish Sexual Development Test (FSDT) has formally been adopted by the Organisation of Economic Cooperation and Development (OECD) as a test guideline (No. 234) for the detecting EDCs (OECD, 2011b). The FDST is conducted in zebrafish during early development, including sexual differentiation, and uses gonadal differentiation and skewed sex ratios to detect estrogen, androgen and steroidogenesis activity of test chemicals (Dang & Kienzler 2019). This AOP directly supports the mechanistic basis for assays such as the FDST. The AOP also supports the use of in vitro assays that measure aromatase inhibition by test chemicals as a basis for predicting apical impacts on fish (e.g., Conolly et al. 2018; Doering et al. 2019a; 2019b). 

References

 

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Appendix 1

List of MIEs in this AOP

Event: 36: Inhibition, Aromatase

Short Name: Inhibition, Aromatase

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Cell term

Organ term

Evidence for Perturbation by Stressor

Overview for Molecular Initiating Event

Characterization of chemical properties: Chemicals are known to inhibit aromatase activity through two primary molecular mechanisms. Steroid-like structures can inhibit the enzyme at its active site, with structures having ∆4 positioned double bonds generally acting as stronger inhibitors than those with ∆5 positioned double bonds (Petkov et al. 2009). Non-steroidal aromatase inhibitors generally act by interfering with electron transfer via the cytochrome P450 heme group of the aromatase enzyme, with greater nucleophilicity of the heteroatom contributing to greater potency as an inhibitor (Petkov et al. 2009). Petkov et al. (Petkov et al. 2009) have provided a detailed analysis of structural categorization of chemicals as potential steroidal or non-steroidal aromatase inhibitors.

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Aromatase (CYP19) orthologs are known to be present among most of the vertebrate lineage, at least down to the cartilaginous fishes. Orthologs have generally not been found in invertebrates, however, CYP19 was detected in the invertebrate chordate, amphioxus and analysis of conservation of gene order and content suggests a possible origin among primitive chordates (Castro et al. 2005).

Fishes generally have two aromatase isoforms, cyp19a1a which is predominantly expressed in ovary and cyp19b, predominantly expressed in brain (Callard et al. 2001). Given that cyp19a1a is dominant isoform expressed in ovary and both isoforms appear to show similar sensitivity to aromatase inhibitors (Hinfray et al., 2006), for the purpose of this key event which focuses on gonadal aromatase activty, distinction of effects on one isoform versus the other are considered negligible. Total activity, without regard to isoform can be considered.

Life stage applicability:  Aromatase activity can be measured at any life stage after the onset of endogenous steroid biosynthesis, generally shortly after birth or hatch.

Sex applicability:  Although expression and activity tends to be greater in females, aromatase activity can be measured in both male and female vertebrates. 

Key Event Description

Inhibition of cytochrome P450 aromatase (CYP19; specifically cyp19a1a in fish).

Site of action: The site of action for the molecular initiating event is the ovarian granulosa cells.

While many vertebrates have a single isoform of aromatase, fish are known to have two isoforms. CYP19a1a is predominantly expressed in ovary while cyp19a1b is predominantly expressed in brain (Callard et al. 2001; Cheshenko et al. 2008). For the purposes of this MIE, when applied to fish, the assumed effect is on cyp19a1a. However, given that both isoforms show similar sensitivity to aromatase inhibitors (Hinfray et al. 2006) and catalyze the same reaction, discrimination of specific isoforms is not viewed as critical in relative to determining downstream key events resulting from aromatase inhibition in ovarian granulosa cells.

Responses at the macromolecular level: Aromatase catalyzes three sequential oxidation steps (i.e., KEGG reactions R02501, R04761, R03087 or R01840, R04759, R02351; http://www.genome.jp/kegg/pathway.html) involved in the conversion of C-19 androgens (e.g., testosterone, androstenedione) to C-18 estrogens (e.g., 17β-estradiol, estrone). Aromatase inhibitors interfere with one or more of these reactions, leading to reduced efficiency in converting C-19 androgens into C-18 estrogens. Therefore, inhibition of aromatase activity results in decreased rate of 17β-estradiol (and presumably estrone) production by the ovary.

How it is Measured or Detected

Measurement/detection: Aromatase activity is typically measured by evaluating the production of tritiated water released upon the aromatase catalyzed conversion of radio-labeled androstenedione to estrone (Lephart and Simpson 1991). Aromatase activity can be measured in cell lines exposed in vitro (e.g., human placental JEG-3 cells and JAR choriocarcinoma cells, (Letcher et al. 1999); H295R human adrenocortical carcinoma cells (Sanderson et al. 2000)). Aromatase activity can also be quantified in tissue (i.e., ovary or brain) from vertebrates exposed in vivo (e.g., (Villeneuve et al. 2006; Ankley et al. 2002). In vitro aromatase assays are amenable to high throughput and have been included in nascent high throughput screening programs like the US EPA ToxcastTM program. Specific ToxCast assays indicative of potential aromatase inhibition include:

NVS_ADME_hCYP19A1

ERF_ENZ_hCYP19A1_dn

TOX21_Aromatase_Inhibition

References

• Petkov PI, Temelkov S, Villeneuve DL, Ankley GT, Mekenyan OG. 2009. Mechanism-based categorization of aromatase inhibitors: a potential discovery and screening tool. SAR QSAR Environ Res 20(7-8): 657-678.

• Lephart ED, Simpson ER. 1991. Assay of aromatase activity. Methods Enzymol 206: 477-483.

• Letcher RJ, van Holsteijn I, Drenth H-J, Norstrom RJ, Bergman A, Safe S, et al. 1999. Cytotoxicity and aromatase (CYP19) activity modulation by organochlorines in human placental JEG-3 and JAR choriocarcinoma cells. Toxico App Pharm 160: 10-20.

• Sanderson J, Seinen W, Giesy J, van den Berg M. 2000. 2-chloro-triazine herbicides induce aromatase (CYP19) activity in H295R human adrenocortical carcinoma cells: a novel mechanism for estrogenicity. Toxicol Sci 54: 121-127.

• Villeneuve DL, Knoebl I, Kahl MD, Jensen KM, Hammermeister DE, Greene KJ, et al. 2006. Relationship between brain and ovary aromatase activity and isoform-specific aromatase mRNA expression in the fathead minnow (Pimephales promelas). Aquat Toxicol 76(3-4): 353-368.

• Ankley GT, Kahl MD, Jensen KM, Hornung MW, Korte JJ, Makynen EA, et al. 2002. Evaluation of the aromatase inhibitor fadrozole in a short-term reproduction assay with the fathead minnow (Pimephales promelas). Toxicol Sci 67: 121-130.

• Castro LF, Santos MM, Reis-Henriques MA. 2005. The genomic environment around the Aromatase gene: evolutionary insights. BMC Evol Biol 5: 43.

• Callard GV, Tchoudakova AV, Kishida M, Wood E. 2001. Differential tissue distribution, developmental programming, estrogen regulation and promoter characteristics of cyp19 genes in teleost fish. J Ster Biochem Mol Biol 79: 305-314.

• Cheshenko K, Pakdel F, Segner H, Kah O, Eggen RI. Interference of endocrine disrupting chemicals with aromatase CYP19 expression or activity, and consequences for reproduction of teleost fish. Gen Comp Endocrinol. 2008 Jan 1;155(1):31-62.

• Hinfray N, Porcher JM, Brion F. Inhibition of rainbow trout (Oncorhynchus mykiss) P450 aromatase activities in brain and ovarian microsomes by various environmental substances. Comp Biochem Physiol C Toxicol Pharmacol. 2006 Nov;144(3):252-62

List of Key Events in the AOP

Event: 1789: Reduction, 17beta-estradiol synthesis by the undifferentiated gonad

Short Name: Reduction, E2 Synthesis by the undifferentiated gonad

Key Event Component

AOPs Including This Key Event

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability:  Most of the key enzymes involved in the process of E2 biosynthesis are well conserved among vertebrates (Callard et al. 2001; Thornton et al. 2001; Eick et al. 2011; Coumailleau et al. 2015). Estrogens play a key role in embryonic development particularly during gonadogenesis for most vertebrates (Coumailleauet al., 2015; Callard et al., 2015). Therefore, it is possible that this key event is applicable to most vertebrate taxa. In contrast, this key event is not applicable to organisms that lack the necessary enzymes for estrogen synthesis such as invertebrates and plants (Jones et al. 2017). 

Life stage applicability:  Endogenous steroid biosynthesis generally begins shortly after birth or hatch.

Sex applicability:  This key event applies to the undifferentiated gonad. Therefore, sex is non-specific. 

Key Event Description

Estrogens are essential for normal ovarian differentiation, growth and maintenance. When estrogens bind to estrogen receptors (ER), these then regulate the transcription of downstream estrogen-responsive genes necessary for proper gonad development (Guiguen et al. 2010; Gorelick et al. 2011). Among the different forms of estrogens, 17β-estradiol (E2) is considered the most fundamental in gonad differentiation in most vertebrates, as it is responsible for inducing and maintaining ovarian development (Bondesson et al. 2015; Li et al. 2019). Consequently, disruption of the E2 synthesis by the undifferentiated gonad has been linked to altered gonad differentiation and development in many vertebrates. 

How it is Measured or Detected

Estrogen concentrations can be measured via radioimmunoassay (e.g., US EPA 2002) or by analytical methods such as LC/MS/MS (e.g., Gravitte et al. 2021; Jalabert et al. 2021; Nouri et al. 2020).  Measurement in the undifferentiated gonad would generally require extraction of tissue homogenates. This tissue mass can be very limited during primordial stages.

References

Bondesson, M., Hao, R., Lin, C. Y., Williams, C., & Gustafsson, J. Å. (2015). Estrogen receptor signaling during vertebrate development. Biochimica et biophysica acta, 1849(2), 142–151. 

Callard, G. V., Tarrant, A. M., Novillo, A., Yacci, P., Ciaccia, L., Vajda, S., Chuang, G. Y., Kozakov, D., Greytak, S. R., Sawyer, S., Hoover, C., & Cotter, K. A. (2011). Evolutionary origins of the estrogen signaling system: insights from amphioxus. The Journal of steroid biochemistry and molecular biology, 127(3-5), 176–188. 

Cheshenko, K., Pakdel, F., Segner, H., Kah, O., & Eggen, R. I. (2008). Interference of endocrine disrupting chemicals with aromatase CYP19 expression or activity, and consequences for reproduction of teleost fish. General and comparative endocrinology, 155(1), 31–62. 

Coumailleau, P., Pellegrini, E., Adrio, F., Diotel, N., Cano-Nicolau, J., Nasri, A., Vaillant, C., & Kah, O. (2015). Aromatase, estrogen receptors and brain development in fish and amphibians. Biochimica et biophysica acta, 1849(2), 152–162. 

Eick, G. N., & Thornton, J. W. (2011). Evolution of steroid receptors from an estrogen-sensitive ancestral receptor. Molecular and cellular endocrinology, 334(1-2), 31–38. 

Gorelick, D. A., & Halpern, M. E. (2011). Visualization of estrogen receptor transcriptional activation in zebrafish. Endocrinology, 152(7), 2690–2703. https://doi.org/10.1210/en.2010-1257

Gravitte A, Archibald T, Cobble A, Kennard B, Brown S. Liquid chromatography-mass spectrometry applications for quantification of endogenous sex hormones. Biomed Chromatogr. 2021 Jan;35(1):e5036. doi: 10.1002/bmc.5036.

Guiguen, Y., Fostier, A., Piferrer, F., & Chang, C. F. (2010). Ovarian aromatase and estrogens: a pivotal role for gonadal sex differentiation and sex change in fish. General and comparative endocrinology, 165(3), 352–366. 

Jalabert C, Ma C, Soma KK. Profiling of systemic and brain steroids in male songbirds: Seasonal changes in neurosteroids. J Neuroendocrinol. 2021 Jan;33(1):e12922. doi: 10.1111/jne.12922.

Jones, B. L., Walker, C., Azizi, B., Tolbert, L., Williams, L. D., & Snell, T. W. (2017). Conservation of estrogen receptor function in invertebrate reproduction. BMC evolutionary biology, 17(1), 65. 

Li, M., Sun, L., & Wang, D. (2019). Roles of estrogens in fish sexual plasticity and sex differentiation. General and comparative endocrinology, 277, 9–16. https://doi.org/10.1016/j.ygcen.2018.11.015

Nouri MZ, Kroll KJ, Webb M, Denslow ND. Quantification of steroid hormones in low volume plasma and tissue homogenates of fish using LC-MS/MS. Gen Comp Endocrinol. 2020 Sep 15;296:113543. doi: 10.1016/j.ygcen.2020.113543.

Ruksana, S., Pandit, N. P., & Nakamura, M. (2010). Efficacy of exemestane, a new generation of aromatase inhibitor, on sex differentiation in a gonochoristic fish. Comparative biochemistry and physiology. Toxicology & pharmacology : CBP, 152(1), 69–74. 

Schroeder, A. L., Ankley, G. T., Habib, T., Garcia-Reyero, N., Escalon, B. L., Jensen, K. M., Kahl, M. D., Durhan, E. J., Makynen, E. A., Cavallin, J. E., Martinovic-Weigelt, D., Perkins, E. J., & Villeneuve, D. L. (2017). Rapid effects of the aromatase inhibitor fadrozole on steroid production and gene expression in the ovary of female fathead minnows (Pimephales promelas). General and comparative endocrinology, 252, 79–87. 

Thornton J. W. (2001). Evolution of vertebrate steroid receptors from an ancestral estrogen receptor by ligand exploitation and serial genome expansions. Proceedings of the National Academy of Sciences of the United States of America, 98(10), 5671–5676. 

US EPA. 2002. A Short-term test method for assessing the reproductive toxicity of endocrine-disrupting chemicals using the Fathead Minnow (Pimephales promelas). EPA/600/R-01/067. Appendix C.

Warner, D. A., Addis, E., Du, W. G., Wibbels, T., & Janzen, F. J. (2014). Exogenous application of estradiol to eggs unexpectedly induces male development in two turtle species with temperature-dependent sex determination. General and comparative endocrinology, 206, 16–23. 

Yin, Y., Tang, H., Liu, Y., Chen, Y., Li, G., Liu, X., & Lin, H. (2017). Targeted Disruption of Aromatase Reveals Dual Functions of cyp19a1a During Sex Differentiation in Zebrafish. Endocrinology, 158(9), 3030–3041. 

Event: 1790: Increased, Differentiation to Testis

Short Name: Increased, Differentiation to Testis

Key Event Component

AOPs Including This Key Event

Biological Context

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

 

Key Event Description

Prior to gonadal sex determination in vertebrates, the developing organism has a primordial bipotential gonad that can be fated to either sex depending on the genetic makeup of the embryo (genetic sex determination) or environmental conditions (environmental sex determination) or a combination of both factors.

During male development, the embryonic stem cells can differentiate to primordial germ cells, which in turn proliferate and differentiate into precursor spermatogonia stem cells. Sertoli cells are the first to differentiate into the different fetal gonad seminiferous cords surrounded by peritubular myoid cells enclosing fetal germ cells. Sertoli cells can also differentiate into Leydig cells. Successively, the interstitial Leydig cells differentiate and produce sex steroids such as testosterone to maintain the testis and control aspects of masculinization including secondary sex characteristics (McLaren 1998; DeFalco and Capel 2009; Trukina et al. 2013).  

Although the timing and location of gene expression leading to the morphological development of the testis may differ among vertebrate taxa, the basic molecular machinery and pathways involved are well conserved (Cutting et al. 2013). Similarly, the cell types and basic morphological structure of the testis across vertebrates are well-conserved (McLaren 1998; DeFalco and Capel 2009).

How it is Measured or Detected

Depending upon the size of the test organism and life stage it may be possible to identify the presence of developed testes versus ovaries visually or with low-power magnification without a need for gonad removal, fixation and processing. This would require, of course, experienced personnel well-versed in the biology of the species of interest. 

In instances where organisms are small, at early life-stages and/or have poorly differentiated gonads, it will be necessary to employ histological examination by light microscopy to identify nature of the gonad.  In all vertebrates, the gonads of phenotypic males in early development have three main differentiating cell types; the gamete forming germ cells (spermatogonia), support cells (Sertoli cells), and hormone-secreting Leydig or interstitial cells (DeFalco and Capel 2009; McLaren 1998).

There are many standardized techniques available for fixation, processing and staining of tissues of concern, including gonads (e.g., Carson and Cappellano 2014). There also are species-specific resources available to aid interpretation of histological images; for example, the National Toxicology Program maintains an on-line Atlas of Non-Neoplastic lesions for a variety of organs, including gonads, in rodents (https://ntp.niehs.nih.gov/nnl/index.htm).

Although there are fewer publicly-accessible resources available for interpretation of histological images in other vertebrate classes, there is often published reference material suitable for this purpose (e.g., Spitsbergen et al. 2009).

References

Carson, F. and C.H. Cappellano. 2014. Histotechnology: A Self-Instructional Text. 4^th Ed., ASCP.

Cutting, A., Chue, J., & Smith, C. A. (2013). Just how conserved is vertebrate sex determination?. Developmental dynamics : an official publication of the American Association of Anatomists, 242(4), 380–387. 

 DeFalco T, Capel B. Gonad morphogenesis in vertebrates: divergent means to a convergent end. Annu Rev Cell Dev Biol. 2009;25:457-482. doi:10.1146/annurev.cellbio.042308.13350

McLaren A. (1998). Gonad development: assembling the mammalian testis. Current biology : CB, 8(5), R175–R177. https://doi.org/10.1016/s0960-9822(98)70104-6

Spitsbergen JM, Blazer VS, Bowser PR, Cheng KC, Cooper KR, Cooper TK, Frasca Jr S,  Groman DB, Harper CM, Lawk JM, Marty GD,
Smolowitz RM, Leger J, Wolf DC, Wolf JC. 2009. Finfish and aquatic invertebrate pathology resources for now and the future. Comparative Biochemistry and Physiology 149C, 249-257.

Trukhina, A. V., Lukina, N. A., Wackerow-Kouzova, N. D., & Smirnov, A. F. (2013). The variety of vertebrate mechanisms of sex determination. BioMed research international, 2013, 587460. https://doi.org/10.1155/2013/587460

Event: 1791: Increased, Male Biased Sex Ratio

Short Name: Increased, Male Biased Sex Ratio

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Life Stage Applicability Sex Applicability

Any sexually reproducing organism can theoretically experience a male-biased population, although the phenomenon certainly has not been demonstrated empirically in all species of potential concern.

Key Event Description

Sex ratio is the ratio of males to females in a population. A male-biased sex ratio for a given species is defined as a significant increase in the number of males, relative to the average ratio found in most populations of that species.

While simple in concept, the “normal” sex ratio for a given species can be challenging to define.

• In organisms with genetic sex determination (GSD) such as mammals and birds, as well as many poikilothermic vertebrates, the male to female ratio often is 1:1. In these instances it is easy to define a deviation from normal in terms of either a relatively greater number of males or females.
• When considering organisms with environmental sex determination (ESD), such as many reptiles and some amphibians and fish, deviations from a 1:1 relationship can and do occur that nonetheless may be normal in the context of the organism’s life history. For example, some reptile species have temperature-dependent sex determination where differentiation of developing organisms to males versus females predominates at different temperatures (Norris and Carr 2020).
• Further complicating a generalized definition of normal sex ratios are situations where sexual differentiation is determined by a combination of genetic and environmental variables, such is the case in many fish species.

Even in species potentially requiring fewer males than females to maintain a viable population, at some point a female-biased population could become problematic in terms of having an adequate number of males to fertilize eggs produced by females or, in the longer term, ensure a robust level of genetic diversity in a population. Further, in situations where a population is male-biased relative to conditions considered normal for a given species, overall productivity may be negatively impacted due to fewer females being available to produce eggs.

A variety of external factors can produce populations that would be characterized as abnormally male-biased based on analysis of phenotypic sex ratios (examples, not comprehensive):

• Differential mortality can occur in males versus females. This might include situations where predation or harvest techniques geared toward larger individuals, which could be either males or females depending upon species may effectively skew the apparent male to female ratio higher.
• Endocrine disruption during early development, most prominently, during gonadal differentiation. For example, in some fish species, exposure during gonadal differentiation to androgen receptor agonists or inhibitors of cytochrome P450 19a1 (aromatase), an enzyme involved in the synthesis of 17β-estradiol, can caused male-biased populations (Delbes et al. 2022).  

 

 

How it is Measured or Detected

Fundamentally, determination of sex ratio (and consequently male-biased sex ratio) is based on counts of the number of males and/or non males in a population, or some statistically representative sub-sample of a population.

• For mature animals that are sexually dimorphic, direct observation of phenotypic secondary sex characteristics is a common method for assessing sex ratios.
• In animals that are not sexually dimorphic or those in pubertal/juvenile stages examination of the gonad, either via gross observation or histological examination is required to determine phenotypic sex.
• There can be instances where gonads cannot be clearly identified histologically as either testis or ovary because cell types indicative of both are simultaneously present. This type of intersex condition has been observed in some amphibians and fish, and may require a third classification category (Abdul-moneim et al. 2015).
• For animals with GSD, genotyping or the use of genetic markers can also be employed to determine genotypic sex ratio.  However, it is noted that there are cases where genotypic sex ratio and phenotypic sex ratio may not be equivalent.

Considerations when evaluating measurements of sex ratio:

• Care needs to be taken to collect an adequate number of animals to ensure that statistical power of the sex ratio point estimates is sufficient to address whether true deviations from normal conditions exist. It is not uncommon for published papers to report skewed sex ratios based on sample sizes far too small to result in environmentally meaningful conclusions.
• Determination of sex ratios is generally straight-forward in a laboratory environment where all (or a defined proportion of) animals from a particular experimental treatment of interest can be collected and examined. Under such conditions, determination of a male bias relative to normal is a simple matter of a statistical comparison between the treated and control groups.
• Determination of sex ratios in the field/wild can often be quite challenging as variables such as sampling gear used, or time and location of collection could bias samples toward one sex versus another. Additionally, often more difficult than ascertaining phenotypic male to female ratio is determining whether observations deviate from what would be considered normal for a particular species of interest. As discussed above (Key Event Description), the relative number of males normally expected will be taxa-dependent, and in some cases may also vary by region and/or environmental conditions. In cases where a male bias is being proposed for a population in the field, compelling scientific support for the “normal” sex ratio expected in the field and for the unbiased nature of the sampling should be made.

References

Abul-moneim, A, DP Coulter, CT Mahapatra and MS Sepulveda. 2015. Intersex in fishes and amphibians: Population implications, prevalance, mechanisms and molecular biomarkers. J Appl Toxicol 35:1228-1240.

Delbes, G, M Blázquez, JI Fernandino, P Grigorova, BF Hales, C Metcalfe, L. Navarro-Martín, L Parent, B Robairee, A Rwigemera, G Van Der Kraak, M Wade and V Marlatt. 2022. Effects of endocrine-disrupting chemicals on gonad development: Mechanistic insights from fish and mammals. Environ Res 204B,  https://doi.org/10.1016/j.envres.2021.112040

Norris, DO and JA. Carr. 2020. Vertebrate Endocrinology, 6^th Edition. Elsevier.

List of Adverse Outcomes in this AOP

Event: 360: Decrease, Population growth rate

Short Name: Decrease, Population growth rate

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Consideration of population size and changes in population size over time is potentially relevant to all living organisms.

Key Event Description

A population can be defined as a group of interbreeding organisms, all of the same species, occupying a specific space during a specific time (Vandermeer and Goldberg 2003, Gotelli 2008).  As the population is the biological level of organization that is often the focus of ecological risk assessments, population growth rate (and hence population size over time) is important to consider within the context of applied conservation practices.

If N is the size of the population and t is time, then the population growth rate (dN/dt) is proportional to the instantaneous rate of increase, r, which measures the per capita rate of population increase over a short time interval. Therefore, r, is a difference between the instantaneous birth rate (number of births per individual per unit of time; b) and the instantaneous death rate (number of deaths per individual per unit of time; d) [Equation 1]. Because  r is an instantaneous rate, its units can be changed via division.  For example, as there are 24 hours in a day, an r of 24 individuals/(individual x day) is equal to an r of 1 individual/(individual/hour) (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). 

Equation 1:  r = b - d

This key event refers to scenarios where r < 0 (instantaneous death rate exceeds instantaneous birth rate).

Examining r in the context of population growth rate:

● A population will decrease to extinction when the instantaneous death rate exceeds the instantaneous birth rate (r < 0).  

           ● The smaller the value of r below 1, the faster the population will decrease to zero.  

● A population will increase when resources are available and the instantaneous birth rate exceeds the instantaneous death rate (r > 0)

           ● The larger the value that r exceeds 1, the faster the population can increase over time      

● A population will neither increase or decrease when the population growth rate equals 0 (either due to N = 0, or if the per capita birth and death rates are exactly balanced).  For example, the per capita birth and death rates could become exactly balanced due to density dependence and/or to the effect of a stressor that reduces survival and/or reproduction (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020).     

Effects incurred on a population from a chemical or non-chemical stressor could have an impact directly upon birth rate (reproduction) and/or death rate (survival), thereby causing a decline in population growth rate.  

● Example of direct effect on r:  Exposure to 17b-trenbolone reduced reproduction (i.e., reduced b) in the fathead minnow over 21 days at water concentrations ranging from 0.0015 to about 41 mg/L (Ankley et al. 2001; Miller and Ankley 2004).             

Alternatively, a stressor could indirectly impact survival and/or reproduction.  

● Example of indirect effect on r:  Exposure of non-sexually differentiated early life stage fathead minnow to the fungicide prochloraz has been shown to produce male-biased sex ratios based on gonad differentiation, and resulted in projected change in population growth rate (decrease in reproduction due to a decrease in females and thus recruitment) using a population model. (Holbech et al., 2012; Miller et al. 2022)

Density dependence can be an important consideration:

● The effect of density dependence depends upon the quantity of resources present within a landscape.  A change in available resources could increase or decrease the effect of density dependence and therefore cause a change in population growth rate via indirectly impacting survival and/or reproduction.  

● This concept could be thought of in terms of community level interactions whereby one species is not impacted but a competitor species is impacted by a chemical stressor resulting in a greater availability of resources for the unimpacted species.  In this scenario, the impacted species would experience a decline in population growth rate. The unimpacted species would experience an increase in population growth rate (due to a smaller density dependent effect upon population growth rate for that species).       

Closed versus open systems:

● The above discussion relates to closed systems (there is no movement of individuals between population sites) and thus a declining population growth rate cannot be augmented by immigration.  

● When individuals depart (emigrate out of a population) the loss will diminish population growth rate.  

Population growth rate applies to all organisms, both sexes, and all life stages.

 

How it is Measured or Detected

Population growth rate (instantaneous growth rate) can be measured by sampling a population over an interval of time (i.e. from time t = 0 to time t = 1).  The interval of time should be selected to correspond to the life history of the species of interest (i.e. will be different for rapidly growing versus slow growing populations). The population growth rate, r, can be determined by taking the difference (subtracting) between the initial population size, N_t=0 (population size at time t=0), and the population size at the end of the interval, N_t=1 (population size at time t = 1), and then subsequently dividing by the initial population size. 

Equation 2:  r = (N_t=1 - N_t=0) / N_t=0

The diversity of forms, sizes, and life histories among species has led to the development of a vast number of field techniques for estimation of population size and thus population growth over time (Bookhout 1994, McComb et al. 2021).  

● For stationary species an observational strategy may involve dividing a habitat into units. After setting up the units, samples are performed throughout the habitat at a select number of units (determined using a statistical sampling design) over a time interval (at time t = 0 and again at time t = 1), and the total number of organisms within each unit are counted. The numbers recorded are assumed to be representative for the habitat overall, and can be used to estimate the population growth rate within the entire habitat over the time interval.  

● For species that are mobile throughout a large range, a strategy such as using a mark-recapture method may be employed (i.e. tags, bands, transmitters) to determine a count over a time interval (at time = 0 and again at time =1).   

Population growth rate can also be estimated using mathematical model constructs (for example, ranging from simple differential equations to complex age or stage structured matrix projection models and individual based modeling approaches), and may assume a linear or nonlinear population increase over time (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). The AOP framework can be used to support the translation of pathway-specific mechanistic data into responses relevant to population models and output from the population models, such as changing (declining) population growth rate, can be used to assess and manage risks of chemicals (Kramer et al. 2011). As such, this translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures (Kramer et al. 2011).  

Some examples of modeling constructs used to investigate population growth rate:

● A modeling construct could be based upon laboratory toxicity tests to determine effect(s) that are then linked to the population model and used to estimate decline in population growth rate.  Miller et al. (2007) used concentration–response data from short term reproductive assays with fathead minnow (Pimephales promelas) exposed to endocrine disrupting chemicals in combination with a population model to examine projected alterations in population growth rate.  

● A model construct could be based upon a combination of effects-based monitoring at field sites (informed by an AOP) and a population model.  Miller et al. (2015) applied a population model informed by an AOP to project declines in population growth rate for white suckers (Catostomus commersoni) using observed changes in sex steroid synthesis in fish exposed to a complex pulp and paper mill effluent in Jackfish Bay, Ontario, Canada. Furthermore, a model construct could be comprised of a series of quantitative models using KERs that culminates in the estimation of change (decline) in population growth rate.  

● A quantitative adverse outcome pathway (qAOP) has been defined as a mathematical construct that models the dose–response or response–response relationships of all KERs described in an AOP (Conolly et al. 2017, Perkins et al. 2019). Conolly et al. (2017) developed a qAOP using data generated with the aromatase inhibitor fadrozole as a stressor and then used it to predict potential population‐level impacts (including decline in population growth rate). The qAOP modeled aromatase inhibition (the molecular initiating event) leading to reproductive dysfunction in fathead minnow (Pimephales promelas) using 3 computational models: a hypothalamus–pituitary–gonadal axis model (based on ordinary differential equations) of aromatase inhibition leading to decreased vitellogenin production (Cheng et al. 2016), a stochastic model of oocyte growth dynamics relating vitellogenin levels to clutch size and spawning intervals (Watanabe et al. 2016), and a population model (Miller et al. 2007).

● Dynamic energy budget (DEB) models offer a methodology that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources (Nisbet et al. 2000, Nisbet et al. 2011).  Murphy et al. (2018) developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates.

● Endogenous Lifecycle Models (ELMs), capture the endogenous lifecycle processes of growth, development, survival, and reproduction and integrate these to estimate and predict expected fitness (Etterson and Ankley, 2021).  AOPs can be used to inform ELMs of effects of chemical stressors on the vital rates that determine fitness, and to decide what hierarchical models of endogenous systems should be included within an ELM (Etterson and Ankley, 2021).

 

Regulatory Significance of the AO

Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is a widely accepted regulatory goal upon which risk assessments and risk management decisions are based.

References

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Appendix 2

List of Key Event Relationships in the AOP