Dose-response assessment of dipentyl phthalate effects on testosterone production and morphogenesis of late-gestation fetal rat testis

Maansi V Gupta; Justin M Conley; Christy Lambright; Logan F Chin; Susan J Hall; L Earl Gray; Daniel J Spade

doi:10.1016/j.envint.2025.109551

. Author manuscript; available in PMC: 2025 Jun 13.

Published in final edited form as: Environ Int. 2025 May 23;200:109551. doi: 10.1016/j.envint.2025.109551

Dose-response assessment of dipentyl phthalate effects on testosterone production and morphogenesis of late-gestation fetal rat testis

Maansi V Gupta ^a, Justin M Conley ^b, Christy Lambright ^b, Logan F Chin ^a, Susan J Hall ^a, L Earl Gray ^b, Daniel J Spade ^a,^*

PMCID: PMC12163936 NIHMSID: NIHMS2087676 PMID: 40435860

Abstract

Dipentyl phthalate (DPeP) is a potent male reproductive toxicant that reduces fetal testicular testosterone production and induces abnormal fetal testis morphology, including multinucleated germ cells (MNGs). We aimed to test whether testosterone production, MNG density, or gene expression would be most sensitive to DPeP exposure and to determine which transcriptomic processes are initiated at the lowest DPeP dose. Timed pregnant Sprague Dawley rats were exposed to 0, 1, 11, 33, 100, or 300 mg DPeP/kg/d by oral gavage from GD 17–21. For comparison to DPeP, additional rats were exposed to vinclozolin, prochloraz, acetaminophen, mono-(2-ethylhexyl) tetrabromophthalate, and dexamethasone. Testosterone production was measured using an ex vivo culture assay, MNGs were quantified on testis sections, and fetal testes were used for RNA-seq, immunofluorescence, and in situ hybridization. Benchmark dose (BMD) analysis was used to compare apical endpoints and gene expression. DPeP dose-dependently reduced testosterone production and increased MNG density. ED₅₀ for MNG density was lower than for testosterone production, but BMD₁₀ values were similar. The lowest BMD estimates for apical toxicity (MNGs) and gene expression (R-RNO-210991: basigin interactions) were 2.675 mg/kg/d and 2.44 mg/kg/d, respectively. DPeP altered gene sets related to steroidogenesis, gonad development, epithelial cell differentiation, and vasculature development. We conclude that inhibition of testosterone production and induction of MNGs have similar utility for quantification of phthalate dose–response in the context of risk assessment. RNA-seq data suggest that cell differentiation and patterning processes were sensitive to DPeP and may contribute to phthalate toxicity mechanisms in the fetal rat testis.

Keywords: Phthalates, Testis, Testosterone, Germ cells, Development

1. Introduction

Phthalic acid esters (phthalates) are a class of chemicals used as plasticizers in polyvinyl chloride (PVC) polymers and in various industrial and consumer products, medical devices, and food packaging (Kavlock et al. 2006; Kavlock et al. 2002). Phthalates are not covalently bound to the products that they are used in, allowing them to leach into surrounding matrices, including foods. Following oral exposure, ortho-phthalic acid diesters are metabolized by esterases to produce monoesters that are toxicologically active and are excreted in the urine, sometimes following further oxidative metabolism (Albro 1986; Hoppin et al. 2002; Koch et al. 2012; Koch et al. 2006). During pregnancy, phthalates can cross the placenta, resulting in toxicity to the developing fetal testis and male reproductive system (Henriksen et al. 2023; Radke et al. 2018; Sathyanarayana et al. 2016; Swan et al. 2005).

The apical toxic effects of phthalates on the fetal male reproductive system have been well-characterized in rats. Gestational exposure to certain phthalates causes a suite of adverse male reproductive tract development outcomes, including cryptorchid testis, hypospadias, retained nipples, and shorter anogenital distance, collectively called phthalate syndrome (Foster 2006), which is attributable to diminished testosterone production in the fetal testis (Fisher 2004; Mylchreest et al. 1998; Parks et al. 2000). Rats are most sensitive to these effects when exposure occurs during the masculinization programming window (MPW), from gestational day 15.5 to 18.5 (van den Driesche et al. 2017). Phthalate syndrome in the rat mirrors testicular dysgenesis syndrome (TDS) in humans, which encompasses elevated risk of testicular cancer, poor fertility/sperm quality, cryptorchidism, hypospadias, and decreased anogenital distance (Fisher et al. 2003; Sharpe and Skakkebaek 2008). However, based on present evidence, phthalates also exert toxic effects on the fetal testis that are not directly attributable to suppression of testosterone production. In human fetal testis experiments, phthalate exposure has induced the production of multinucleated germ cells (MNGs), regardless of testosterone levels (Heger et al. 2012; Mitchell et al. 2012; Spade et al. 2014). Phthalates induced MNGs in both mice and rats, even though mice appeared insensitive to the antiandrogenic effects of phthalates (Gaido et al. 2007). The window of greatest sensitivity for induction of MNGs is in late gestation, after the MPW (Ferrara et al. 2006; Spade et al. 2015), and MNGs are part of an overall adverse effect of phthalates on the morphology of seminiferous cords (Kleymenova et al. 2005; Lara et al. 2017; Spade et al. 2015). Following gestational phthalate exposure in the rat, histopathological effects such as seminiferous tubule degeneration persisted into adulthood (Barlow et al. 2004; Mylchreest et al. 2000), and these effects may be attributable to disrupted development of Sertoli and/or germ cells, in addition to Leydig cell dysfunction. Although MNGs are degenerative and lead to loss of developing germ cells (Ferrara et al. 2006), the existing phthalate literature and risk assessments almost exclusively use testosterone production and downstream endpoints to quantify phthalate dose–response. There is relatively little dose–response data for morphogenic endpoints of phthalate toxicity such as MNGs or seminiferous cord diameter.

In this study, we aimed to address two questions about phthalate toxicity. First, we sought to determine whether testosterone production or morphological features of the fetal testis would respond more sensitively to a phthalate in the rat. Second, we aimed to use dose-dependent gene expression information and comparisons between a phthalate and other fetal testicular toxicants to make inferences about mechanisms underlying the adverse effects of phthalates on testis development. To address these goals, we chose to work with a potent phthalate, dipentyl phthalate (DPeP). In the Sprague-Dawley rat, DPeP is eight times more potent than di-(2-ethylhexyl) phthalate (DEHP) based on the dose–response for decreased testosterone production and two to three times more potent based on the dose–response for male reproductive tract maldevelopment outcomes, such as shorter anogenital distance and retained nipples (Hannas et al. 2011a). Because induction of MNGs by phthalates is relevant to humans (Li and Spade 2021), we previously tested several phthalates, including DPeP, at high doses and found that phthalates that cause antiandrogenic effects in the fetal rat also tend to induce MNGs (Spade et al. 2018). In the present study, we assessed the dose–response for testosterone production and MNG density in tissue sections over an approximately 2.5-log range of DPeP doses (1–300 mg/kg/d) in late gestation. We conducted benchmark dose modeling of testosterone, histological data, and gene expression data to identify endpoints and biological processes that respond to low-dose DPeP exposure and that may contribute to the mechanisms of phthalate-induced testicular dysgenesis.

2. Methods

2.1. Animals

Animal experiments were performed at the U.S. Environmental Protection Agency Center for Public Health and Environmental Assessment (US EPA CPHEA, hereafter referred to as EPA) and at Brown University. Procedures involving animals at EPA were approved by the US EPA CPHEA Institutional Animal Care and Use Committee. Procedures involving animals at Brown University were approved by the Brown University Institutional Animal Care and Use Committee, in accordance with the Guide for the Care and Use of Laboratory Animals. Timed pregnant Sprague-Dawley rats (Crl:CD(SD), strain code 001) were purchased from Charles River Laboratories (Shrewsbury, MA, or Raleigh, NC) and arrived at the facilities on gestation day (GD) 2 (EPA) or GD 4–11 (Brown). The day on which a copulatory plug was detected was considered GD 1. At both sites, animals were housed in Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC)-accredited animal care facilities. At EPA, animals were housed at 20–22 °C, 45–55 % humidity, and 12:12 photoperiod (lights on 06:00 EST) in clear polycarbonate cages (20 × 25 × 47 cm) with heat-treated, laboratory grade pine shavings (Northeast Products, Warrensburg, NY), and were provided ad libitum access to purified water and NIH07 rodent diet. At Brown, animals were housed at 20–22.2 °C, 30–70 % humidity (set point 50 %), 12:12 photoperiod (lights on at 07:00 ET) in polysulfone Optirat cages with 1181 cm² floor space (Animal Care Systems, Centennial, CO, USA) with autoclaved hardwood bedding (Sani-Chips) and had ad libitum access to RO water, chlorinated at 1–3 ppm, and LabDiet 5010 Rodent diet.

2.2. Chemicals and study design

Dosing solutions were prepared using laboratory-grade corn oil (Sigma Aldrich, St. Louis, MO). DPeP used at EPA (CASRN: 131–18-0; Lot 1431420; RTI Log 040109-A-14) was gifted from National Toxicology Program (Research Triangle Park, NC) and independently verified for purity (>99 %) by Research Triangle Institute (Durham, NC) using gas chromatography with flame ionization detection. DPeP used at Brown (Lot MYZGF-BP; purity 99.4 %) was purchased from TCI America (Montgomeryville, PA). Vinclozolin (CASRN: 50471-44-8; Lot 2296X; purity > 99 %) was purchased from Riedel-de Haen (Seelze, Germany). Prochloraz (CASRN: 67747-09-5; Lot SZBA112XV), Acetaminophen (CASRN: 103-90-2; Lot SLBM5923v) and Dexamethasone (CASRN: 50-02-2; Lot BCBM4557V) were ≥98 % purity and purchased from Sigma-Aldrich (St. Louis, MO). Mono-(2-ethylhexyl) tetrabromophthalate (TBMEHP; CASRN 61776-60-1; custom synthesis; purity 95 %) was purchased from Asis Chem Inc. (Waltham, MA). Prochloraz and vinclozolin are well-characterized antiandrogenic chemicals (Conley et al. 2021), and acetaminophen has recently been reported as a possible antiandrogen (Kristensen et al. 2012; Navarro-Lafuente et al. 2021). These three known or potential antiandrogens were included in this study to test whether antiandrogenic treatments other than phthalates would induce phthalate-like testicular histopathology. Dexamethasone was included for comparison to DPeP because there is prior published evidence that dexamethasone and phthalates exerted additive antiandrogenic effects in the rat fetal testis (Drake et al. 2009). The brominated phthalate monoester, TBMEHP, was tested in this experiment because a previous study reported very mild elevation of MNGs in rats following exposure to 500 mg TBMEHP/kg/d on GD 17–18 (Springer et al. 2012). TBMEHP was used, rather than the parent compound, mono-(2-ethylhexyl) tetrabromophthalate (TBPH), because in vivo TBPH metabolism has, to our knowledge, never been studied.

Pregnant rats were treated with exposure compounds or corn oil vehicle from GD 17–21 by daily oral gavage in a volume of 2.5 mL/kg. DPeP exposures were conducted at both EPA (n = 3/group, 0, 1, 11, 33, and 100 mg/kg/d) and Brown (n = 3/group for 0, 1, 11, 33, and 100 mg/kg/d groups, n = 6 in 300 mg/kg/d group). All other treatments were conducted at EPA. Sample sizes were n = 6 vehicle and 3/treatment group for acetaminophen, prochloraz, and vinclozolin; n = 9 vehicle and 3–7/treatment group for dexamethasone; and n = 3/group for TBMEHP. Doses and sample size were selected based on effect levels from prior publications detailed in Table 1. Dams were euthanized on the final day of dosing, one hour after administration of the final dose, by decapitation (EPA), or by overdose of inhaled isoflurane, followed by bilateral thoracotomy (Brown). Fetuses were euthanized by decapitation. Fetal gonads were visualized under a stereomicroscope to determine sex, and testes were fixed for histological preparation, frozen in liquid nitrogen and stored at −80 °C for RNA isolation, or used immediately for ex vivo testosterone production assay, as described below.

Table 1.

Details of chemicals and doses used and published effect levels that informed dose selection.

Chemical	Abbrev.	CAS no.	Site	Doses (mg/kg/d)	TPROD ED50 (mg/kg/d)	T LOAEL (mg/kg/d)	MNG LOAEL(mg/kg/d)
dipentyl phthalate	DPeP	131–18-0	EPA	0, 1, 11, 33, 100	47 (Hannas et al. 2011a)	33 (Gray et al. 2016)	300 (Spade et al. 2018)
dipentyl phthalate	DPeP	131–18-0	Brown	0, 1, 11, 33, 100, 300	“	“	“
acetaminophen	APAP	103–90-2	EPA	0, 400	n.m.	150^## (Kristensen et al. 2011)	n.m.
prochloraz	PCZ	67747–09-5	EPA	0, 150	n.m.	62.5^** (Noriega et al. 2005)	n.m.
vinclozolin	VIN	50471–44-8	EPA	0, 200	n.m.	12^# (Hellwig et al. 2000)	n.m.
dexamethasone	DEX	50–02-2	EPA	0, 0.05, 0.1, 0.5, 5	n.m.	0.1^* (Drake et al. 2009)	n.m.
mono-(2-ethylhexyl) tetrabromophthalate	TBMEHP	61776–60-1	EPA	0, 62.5, 125, 250, 500	n.m.	n.m.	500 (Springer et al. 2012)

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Chemicals listed in order of first appearance of data in the manuscript. ED₅₀ = median effective dose; LOAEL = lowest observed adverse effect level; MNG = multinucleated germ cell(s); n.m. = not measured; TPROD = ex vivo testosterone production assay; “ = same as above; T LOAEL derived from TPROD data except as follows:

LOAEL of 0.1 mg/kg/d dexamethasone enhanced the antiandrogenic effect of dibutyl phthalate.

^**

LOAEL for any testicular histopathology;

LOAEL reported for retained nipples in male pups.

^##

LOAEL reported for shorter anogenital distance; in a separate study, T was lower in ex vivo rat testes cultured with 0.5 μM APAP (Kristensen et al. 2012).

2.3. Testosterone production assay

Testicular testosterone (T) production was determined in samples from Brown and EPA using an ex vivo culture method established at EPA (Furr et al. 2014). One freshly isolated testis from each of three males per litter was immersed in modified M-199 media without phenol red (Gibco/Life Technologies, Product #A31224DK), supplemented with 10 % dextran-coated charcoal-stripped fetal bovine serum (Hyclone Laboratories, Logan, UT) for 3 h in a humidified incubator at 37 °C on an orbital shaker, to allow testosterone to diffuse into media. Following incubation, media was removed and stored at −80 °C until measurement of T in media. For EPA samples, T in media was quantified in singlet (one media sample measurement for each of three fetuses per litter) using - radioimmunoassay (ALPCO, Cat. no. 72-TESTO-CT2) according to manufacturer specifications. The intra-assay coefficient of variation for this kit was 5.6 % (based on variability of the standard curve) and the inter-assay coefficient of variation was 8 %. Cross-reactivity of the T antibody with dihydrotestosterone (DHT) was 2.6 %. The limit of detection was 0.08 ng testosterone/mL. Media samples prepared at Brown were sent to the Ligand Assay and Analysis Core Laboratory at the University of Virginia (UVA), and total T was measured in duplicate (two media sample aliquots for each of three fetuses per litter) using a mouse/rat testosterone ELISA (IBL, Cat. no. IB79106). All samples were run at a 1:5 dilution, and all were within the reportable range of 10.0–1600.0 ng/dL. Intra-assay and inter-assay coefficient of variation for assays run at UVA in 2023 were 4.4 % and 9.4 %, respectively. Historical data from EPA Fetal Phthalate Screen (FPS) studies of DPeP (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a) were included in dose–response analyses and benchmark dose analyses for comparison to data measured in the present study.

2.4. Histology

For histology, one whole testis per fetus was collected from 2 to 4 different male fetuses per litter. Testes were fixed in modified Davidson’s solution (Electron Microscopy Sciences, Hatfield, PA) at room temperature with agitation for no more than two hours before being transferred to 70 % ethanol and stored at 4 °C. Testes were processed through graded ethanol solutions, cleared in three changes of xylenes, and embedded in histological paraffin. Samples prepared at EPA were shipped to Brown University as paraffin blocks. All samples were trimmed to the approximate center when possible, and sections were cut at a thickness of 5 μm. Sections were deparaffinized in three changes of xylenes and rehydrated in graded ethanol solutions (100 %, 95 %, 70 %), then stained with Gill’s hematoxylin and eosin Y (H&E) by standard protocols. H&E slides were scanned on an Aperio ScanScope CS at 40x magnification. Slide images were manually analyzed by a blinded scorer in ImageScope software v12.3 (Leica) to determine seminiferous cord diameter, cross-sectional testis area, and MNG number. Diameter was measured on the minor axis of each cord cross section. Area of each testis cross section was determined by manually annotating the boundary of the testis. MNGs were manually identified as cells with more than one nucleus visible in a single cell with a defined membrane and/or clearly continuous cytoplasm, and MNG annotations were checked by a second blinded scorer. The number of MNGs was divided by the area of the section to yield MNG density, reported as MNGs/mm² cross-sectional testis area.

2.5. Immunofluorescence

Paraffin sections were deparaffinized with three changes of xylene and rehydrated in graded ethanol solutions (100 %, 95 %, 70 %). Antigen retrieval was then conducted by immersing the sections in 10 mM citrate buffer, pH 6.0 (Vector Laboratories, Burlingame, CA), in a vegetable steamer for 20 min, followed by a 20-minute cooling period at room temperature. Permeabilization was then performed by incubating sections in a 0.1 % Triton X-100 (Sigma-Aldrich, St Louis, MO) solution for 5 min. Samples were incubated in a blocking buffer consisting of PBS with 5–8 % goat serum and 1 % bovine serum albumin for 1 h and then were incubated with primary antibodies (anti-DDX4/MVH, Abcam #ab13840, 1:1000 dilution; anti-SOX9, MilliporeSigma #AB5535, 1:500 dilution; anti-3BHSD, Santa Cruz #sc-51520, 1:150 dilution); in blocking buffer overnight in a humidified chamber at 4 °C. The next day, samples were incubated with secondary antibodies (goat anti-rabbit IgG Alexa Fluor 568,ThermoFisher A-11036, 1:500 dilution; goat anti-mouse IgG Alexa Fluor 488, ThermoFisher A-32723; 1:1000 dilution) in blocking buffer in a dark, humidified chamber for 2 h at room temperature, then counterstained with 10 μg/mL Hoechst 33,342 (Invitrogen) solution for 1 h in a dark, humidified chamber. Coverslips were mounted using Prolong Gold Antifade Reagent (Invitrogen), and allowed to cure at room temperature in the dark for 15 min. Sections were moved to 4 °C for long-term storage. Sections were imaged on an Olympus VS200 Fluorescent Slide Scanner. All sections were scanned using the DAPI filter set to detect Hoechst-labeled nuclear DNA, the mCherry or TRITC filter set for the fluorophore Alexa Fluor 568 (AF568), and the FITC filter set for AF488, as appropriate. Images were analyzed in QuPath v0.3.2 or v0.5.1.

2.6. In situ hybridization

In situ hybridization (ISH) was performed for selected genes, Amhr2, Gas6, Kdr, and Scarb1, using RNAscope 2.5 HD kits with DAB detection (Advanced Cell Diagnostics, Newark, CA, USA, catalog nos. 517791, 1250811-C1, 435711, and 1570161-C1, respectively), to qualitatively assess cell-type specific localization and gene expression intensity. The assays were performed according to the manufacturer’s instructions, as follows. Paraffin sections were deparaffinized with two changes of xylene and two changes of 100 % ethanol and dried completely, then treated with hydrogen peroxide for 10 min at room temperature. Slides were immersed in antigen retrieval reagents in a vegetable steamer for 15 min, then treated with protease K solution for 15 min at room temperature. Gene-specific probes were hybridized for 2 h in the ACD HybEZ hybridization oven at 40 °C, and subsequent amplification steps were followed according to the manufacturer’s protocol. Samples were developed with diaminobenzidine (DAB) and counterstained with hematoxylin, before dehydrating in two changes of isopropyl alcohol, followed by two changes of CitriSolv (Decon Labs, King of Prussia, PA, USA). Coverslips were mounted with Cytoseal-60. Sections were imaged at 40x on an Aperio CS slide scanner (Leica Biosystems).

2.7. RNA isolation and quality control

RNA was isolated from testes that were dissected and snap-frozen on GD 21, following exposure to 0–300 mg DPeP/kg/d at Brown. In some cases, only one frozen GD 21 testis sample was available per litter. In cases where multiple testes were collected for this analysis, two testes from the same litter were pooled to generate a single RNA sample. No tissue sample was available from one litter in the 300 mg/kg/d group, and only two samples were available in the 33 mg/kg/d group. Therefore, the 33 mg/kg/d group was omitted from this analysis. The sample size for RNA-seq analysis was n = 3/group for 0, 1, 11, and 100 mg/kg/d and n = 5 in the 300 mg/kg/d group. Total RNA was extracted from tissue samples using the Zymo Quick-RNA MicroPrep Kit (Zymo Research, Irvine, CA, USA). Samples were homogenized in 600 μL RNA Lysis Buffer in a RINO tube with zirconium oxide beads, by shaking in a Bullet Blender for 3 min on setting #8, and all subsequent steps were performed according to the manufacturer’s instructions, including the kit-supplied DNase digestion. Sample concentration and purity were assessed on a NanoDrop One spectrophotometer. All samples had A₂₆₀/A₂₈₀ ratios between 1.95 and 2.14, with a mean of 2.08, and A₂₆₀/A₂₃₀ ratios between 1.74 and 2.18, with a mean of 1.98. RIN values measured on an Agilent TapeStation ranged from 9.40 to 10, with a mean of 9.92, and DV200 ranged from 77.52 to 90.03, with a mean of 85.02. All samples met our quality thresholds (A₂₆₀/A₂₈₀ > 1.8, RIN > 8.0) and were included in the analysis.

2.8. Data analysis and Statistics

Histology, immunofluorescence, and testosterone data were summarized using Excel and analyzed using GraphPad Prism version 9 or 10 (GraphPad Software, San Diego, CA). The dam or litter was treated as the statistical unit. For any analysis in which multiple testes or fetuses were tested, the data were averaged at the level of the litter prior to statistical analysis. No data were excluded from the analysis. Ex vivo testosterone production data was converted to percent of control for analysis. MNG data were log-transformed to correct for unequal variance, defined as a greater than four-fold difference between the largest and smallest group SEM. Because DPeP treatments took place at both sites, data were compared between the two sites using a two-way ANOVA, followed by Sidak post-hoc test for MNGs counted on H&E-stained slides (Fig. S1A), MNGs counted on DDX4-stained slides (Fig. S1B), seminiferous cord diameter (Fig. S1C), and ex vivo testosterone production (Fig. S1D). The initial analysis found no significant differences between site within dose for MNG data from H&E slides or from ex vivo testosterone production data. For MNG counts on DDX4-stained slides, only the 33 mg/kg/d dose differed significantly between sites. There was a significant effect of site on seminiferous cord diameter across all doses. To address this, we applied a batch correction by subtracting 2x the average residual from each value in the EPA dataset. This is equivalent to mean centering, while maintaining the average of the Brown sample values. Following this batch correction, no significant site effect was detected by two-way ANOVA. Given that there were only minimal differences between sites in the DDX4 MNG dataset and no other differences between sites, we combined the DPeP data from both sites for subsequent statistical analysis.

To test differences between treatment groups, residuals were tested for normality using the D’Agostino-Pearson normality test. If residuals were normally distributed, differences between group means were tested using two-tailed t-test or one-way ANOVA, followed by Dunnett’s multiple comparison test. Datasets with non-normal residuals were analyzed by non-parametric Kruskall-Wallis test, followed by Dunn’s multiple comparison test. Prism was also used to perform correlation analysis (Spearman’s ρ) and linear regression analysis to compare the two MNG datasets. Dose-response assessment was performed in Prism using nonlinear regression. For the purposes of fitting and graphing dose–response curves in logarithmic space, the control dose was set to 0.1 mg/kg/d, instead of 0 mg/kg/d.

Benchmark dose (BMD) analysis was performed using U.S. EPA BMDS Online software (U.S. Environmental Protection Agency 2021). BMD analysis was performed for MNG datasets derived from both H&E and DDX4-stained slides, seminiferous cord diameter, T data obtained from the present study, and the historical T data from two FPS studies of DPeP (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a). All six datasets were analyzed using the exponential, Hill, linear, polynomial (maximum degree of 3), and power models. Benchmark response (BMR) type was set to relative deviation and benchmark response factor (BMRF) to 0.1. This corresponds to a benchmark response of 10 % difference from control in the adverse direction (BMD₁₀), and is consistent with the 2012 EPA BMD Guidance for non-nested datasets (U.S. Environmental Protection Agency 2012). Note that nested models for continuous data are not available in BMDS. MNG data and one of two historical T datasets were analyzed assuming normal distribution and non-constant variance. The remaining data were analyzed assuming normal distribution and constant variance. The best-fit model was selected based on the BMDS criteria, including a goodness-of-fit p-value > 0.1, lowest Akaike information criterion (AIC), and lowest lower-bound BMD estimate (BMDL). Results are reported as BMD with lower and upper bound estimates (BMDL, BMDU).

2.9. RNA-seq analysis and BMD estimation

RNA libraries were prepared and sequenced at Azenta Life Sciences (NJ, USA), as follows. Sequencing library preparation, including mRNA enrichment by polyA selection and first- and second-strand reverse transcription were performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina (New England Biolabs, Ipswich, MA, USA). A total of 36,91,11,125 sequence reads (1,10,734 Mb) were generated (18,358,869 – 24,922,898 reads/sample; mean = 2,17,12,419 reads), with 92.14 % of reads ≥ 30 bases. Reads were trimmed using Trim-momatic v.0.36 and mapped to the R. norvegicus reference genome build Rnor6.0 (ENSEMBL) using STAR aligner v.2.5.2b. Per-sample hit counts were quantified using featureCounts (Subread v.1.5.2). Total mapped reads/sample ranged from 1,78,83,074 – 25,145,382 (mean = 2,10,52,922, 97.67 %), and unique mapped reads/sample ranged from 1,72,25,683 – 23,962936 (mean = 2,02,05,762, 94.66 %). Differential expression (DE) analysis was performed for each treatment vs. vehicle control, using DESeq2 with the Wald test. For DE analysis, genes with average read count < 10 were filtered. Genes with adjusted p < 0.05 and absolute log₂(fold change) > 1, without fold change shrinkage, were considered significantly differentially expressed (DE). BMDExpress2 (Phillips et al. 2018) was used to identify DPeP-sensitive gene sets and to perform BMD analysis based on enriched gene sets. The full dataset of raw hit counts was normalized using the VoomNormalize module in GenePattern (Law et al. 2014) and imported into BMDExpress2. Data were prefiltered using the Williams trend test with 100 permutations and raw p < 0.05 This step is performed only to limit the genes used for model fitting to those with a dose-dependent trend, and the typical BMDExpress2 workflow uses the raw Williams Trend Test p-value (p < 0.05, no multiple test correction) (Johnson et al. 2020). The prefiltered dataset was then used for BMD analyses using the Hill, power, linear, polynomial 2, exponential 2, exponential 3, exponential 4, and exponential 5 models, with maximum iterations set to 250, a confidence level of 0.95, and an assumption of constant variance. BMR type was set to standard deviation, with the BMRF set to 1 standard deviation, and power was restricted to models with power ≥ 1. The best model was selected based on the lowest AIC, with p > 0.05. Hill models with k < 0.33 (one third of the lowest positive dose) were excluded, and the next best-fit model was selected. Following BMD analysis, Functional Classification was performed on the Gene Ontology (GO) Biological Process, Cellular Localization, and Molecular Function gene sets, as well as the Reactome gene sets, using the following settings: remove BMD with p < 0.1, remove genes with BMDU/BMDL > 40. Raw and normalized RNA-seq data are available at the NCBI GEO database (GSE255311). Volcano plots for data display were made with VolcaNoseR (Goedhart and Luijsterburg 2020). Finally, we reviewed published datasets to identify cell type-specific expression information for the genes that passed the Williams trend test prefilter in our BMDExpress2 analysis. Typical cellular localization for each gene was identified by searching gene ID in a single-cell RNA-seq dataset of fetal mouse testes (Stevant et al. 2018) and a microarray dataset derived from sorted mid-gestation mouse testis cells (embryonic day 11.5–13.5) (Jameson et al. 2012). Because our samples were late gestation testes, collected during a period when germ cells are differentiating into spermatogonia-like states, we also used a single-cell RNA-seq dataset of early postnatal mouse spermatogonia (Hermann et al. 2015) to identify additional germ cell-associated genes.

3. Results

3.1. Dam and pup weights after DPeP exposure

DPeP treatment did not result in significant differences in dam body weight at GD 21 (p = 0.1225, Fig. 1A). From GD 17 to GD 21, dams exposed to 300 mg/kg/d DPeP gained less weight relative to the vehicle control group (Fig. 1B; p = 0.0259). However, when the difference in dam body weight was normalized to the number of pups per litter, dam body weight gain per pup was not significantly different from control at any dose level (Fig. 1C; p = 0.2563). There was a significant difference in GD 21 dam body weight (Fig. S2A, p = 0.0017), but not dam body weight gain (Fig. S2B), between the EPA and Brown animals. This may have resulted from smaller litter sizes at Brown, compared to EPA (Fig. S2C, p = 0.0092), though litter sizes at both sites were within historical control ranges of 8.50–17.04 (mean = 14.59) reported by Charles River for all GD 21 Sprague Dawley rat studies (Middle Atlantic Reproduction and Teratology Association 1993). There was no significant difference in dam body weight gain per pup (Fig. S2D). Because of a difference between sites in collection protocol, GD 21 fetal body weights were recorded during necropsy at Brown only. For those animals treated at Brown, DPeP treatment did not result in significant differences in fetal body weight on GD 21 (Fig. S3, p = 0.1225), in male, female, or all pups. There was one litter in the 11 mg/kg/d group that had a mean pup body weight well above average. This may have been in part because of the smaller than average litter size for that litter (9 total pups, relative to the study average of 12.7 pups/litter). There was no evidence of fetotoxicity at any dosage level at either site. All pups were alive at termination of the study, and no post-implantation losses, resorptions, or indications of gross pathology or poor condition were noted at either site.

3.2. Fetal testis morphometrics after DPeP exposure

MNGs were quantified in H&E-stained sections and immunofluorescent DDX4-stained sections of GD 21 testes. In the H&E-stained sections (Fig. 2A–B), the density of MNGs (MNGs/mm² cross-sectional testis area) was significantly higher than vehicle control at 11, 33, 100, and 300 mg/kg/d DPeP (Fig. 2C; p = 0.0049, p < 0.0001, p < 0.0001 and p < 0.0001, respectively). Seminiferous cord diameter was also measured on H&E stained slides. Diameter was significantly greater than vehicle control in the 100 mg/kg/d and 300 mg/kg/d DPeP doses (Fig. 2D; p = 0.0024 and < 0.0001, respectively).

In DDX4-stained sections (Fig. 3A), significantly higher MNG density (p < 0.0001) was observed at the 33, 100, and 300 mg/kg/d DPeP dosage levels (Fig. 3B). DPeP did not alter the density of DDX4-positive germ cells at any treatment level (Fig. 3C). MNG density values determined by analysis of H&E- and DDX4-stained sections were significantly correlated (Fig. 3D, ρ = 0.8421, p < 0.0001), and simple linear regression of H&E versus DDX4 MNG densities gave a significant regression (p < 0.0001) with a best fit equation of y = 0.4217x + 1.194 (Fig. 3D). In SOX9/3BHSD-immunolabeled testis sections, (Fig. 3E), there were no treatment-related significant differences in the density of SOX9-positive Sertoli cells (Fig. 3F) or 3BHSD-positive Leydig cells (Fig. 3G) or the ratio of Sertoli cells to Leydig cells (Fig. 3H) at any dose.

3.3. Testosterone production after DPeP exposure

Following in utero exposure to DPeP, testes were explanted and cultured for measurement of ex vivo testosterone production. These experiments were conducted at both Brown University and EPA. As detailed in the methods section, when data from each site were converted to percent of concurrent control average and analyzed to test for differences between the two sites, no individual comparison between sites within dose was significant by the Sidak post hoc test (Fig. S1C). In the combined dataset, rats exposed to 100 and 300 mg/kg/d DPeP had significantly lower testosterone production (Fig. 4; p = 0.0006 and p < 0.0001, respectively).

Fig. 4. — *Ex vivo* testosterone production following dipentyl phthalate (DPeP) exposure. *Ex vivo* testosterone (T) production (one-way ANOVA with Dunnett’s *post hoc* test). Data normalized to % of concurrent control mean. Charts show individual replicate values with mean ± SEM. Data from Brown and EPA were analyzed as a single combined dataset (n = 6 litters/group). Brackets are labeled with p-value. Summary data in Table S5.

3.4. Dose-Response comparison and benchmark dose analysis

To test the relative potency of DPeP for different toxic endpoints, we modeled dose–response curves for four endpoints studied in this experiment (GD 17–21 exposure window): ex vivo testosterone production, MNG density measured via H&E staining, MNG density measured via immunofluorescent DDX4 staining, and seminiferous cord diameter. To enable a comparison between our testosterone production data (GD 17–21) and testosterone production following exposure to DPeP during the most sensitive window for phthalate effects on testosterone, we also modeled dose–response for ex vivo testosterone production at GD 18 following DPeP exposure from GD 14–18 in all prior EPA FPS studies (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a) (Fig. 5 and Table 2). Non-linear (sigmoid) regression models were fit for each of the five endpoints in Prism. The fit of each dose–response curve was strong (R² > 0.61) except for the MNG density on DDX4-stained slides (R² = 0.4953), likely because of a decline in MNG density between 100 and 300 mg/kg/d DPeP in that dataset (Fig. 3B). We found that the ED₅₀ values were different between the five endpoints (p < 0.0001). The lowest calculated ED₅₀ value was 18.95 mg/kg/d for MNGs on DDX4-stained slides. MNG density on H&E-stained and DDX4-stained sections produced similar ED₅₀ estimates with overlapping 95 % CI. However, the ED₅₀ 95 % CI for MNGs did not overlap with the ED₅₀ 95 % CI for testosterone production or seminiferous cord diameter, suggesting that the mean effect level for MNGs was slightly but significantly lower than the mean effect dose for testosterone production or cord diameter. Notably, our analysis of historical T production data derived from EPA FPS studies that used the earlier exposure window of GD 14–18 (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a) gave an ED₅₀ of 109.8 mg/kg/d, while the new data presented in this paper, obtained from the later GD 17–21 window of exposure, had an ED₅₀ of 134.1 mg/kg/d; however, these values had overlapping 95 % CI. This comparison should be interpreted with caution because of the overlapping confidence intervals and because the studies were conducted separately.

Fig. 5. — Comparison of dose–response for different dipentyl phthalate (DPeP) effects. Dose-response analysis was performed for four parameters reported in this paper, following DPeP exposure from GD 17–21: ex vivo testosterone (T), multinucleated germ cells (MNGs)/mm² on H&E sections, MNGs/mm² on DDX4-stained sections, and seminiferous cord diameter. Data from Brown and EPA were analyzed as a single combined dataset (n = 6 litters/group). Ex vivo T data from all prior blocks in the EPA Fetal Phthalate Screen with DPeP exposure from GD 14–18 were included for comparison (0, 11, 33, 50, 100, and 300 mg/kg/d in CR SD rats, n = 9–29/group; and 0, 11, 33, 50, 100, 300, 325, and 750 mg/kg/d in Harlan SD rats, n = 3–24/group) (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a); CR = Charles River; SD = Sprague Dawley. T data are plotted as % of control. MNGs are presented as % of maximum, calculated as the % of the mean MNG density in the dose group with the highest MNG density. Seminiferous cord diameter fluctuates over a small absolute range, so the average value of the vehicle group was subtracted from all data points, and that value was converted to % of maximum using the same approach that was used for MNGs. Dose-response analysis was performed in Prism using nonlinear regression. Vehicle control value was set to 0.1 mg/kg/d to enable log transformation of dose on the x-axis. Model constraints: bottom = 0, top = 100. LogED₅₀ values differed between data sets (p < 0.0001). ED₅₀ for MNGs was slightly lower than ED₅₀ for either measure of T or for Δ SC diameter, with non-overlapping 95 % CIs. ED₅₀ values are provided in Table 2. Summary Data in Table S5.

Table 2.

Comparison of best-fit dose–response values for DPeP responses.

				Non-linear Regression		BMDS Analysis
Measurement	Time Point (GD)	Strain	Method	ED50 DPeP mg/kg/d (95 % CI)	Model R²	Best Fit Model	BMD(BMDL, BMDU)	Data Source
ex vivo T	18	CR SD	RIA (ALPCO)	109.8 (90.49–135.4)	0.7559	Hill	14.609 (10.959, 22.546)	(Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a)
ex vivo T	18	Harlan SD	RIA (ALPCO)	42.28 (34.75–51.55)	0.8157	Hill^*^#	9.811 (8.583, 11.137)	(Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a)
ex vivo T	21	CR SD	RIA (ALPCO), ELISA (IBL)	134.1 (80.88–270.8)	0.6152	Hill	14.014 (4.756, 33.303)	this paper (Fig. 4)
MNGs	21	CR SD	H&E	27.20 (16.11–42.80)	0.6650	Hill ^*	2.675 (0.79, 6.695)	this paper (Fig. 2C)
MNGs	21	CR SD	DDX4	18.95 (11.48–37.28)	0.4953	Hill ^*^##	8.958 (8.634, 9.237)	this paper (Fig. 3B)
Δ SC diameter	21	CR SD	H&E	85.54 (64.73–108.2)	0.8051	Exponential (M5)	68.656 (46.122, 96.716)	this paper (Fig. 2D)

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Dose-response analyses performed on data reported in this paper for GD 21 time points, following treatment with 0, 1, 11, 33, 100, or 300 mg/kg/d DPeP (n = 6/group). Comparative dose–response analysis performed on previously reported ex vivo testosterone production data from EPA Fetal Phthalate Screen studies with 0, 11, 33, 50, 100, and 300 mg/kg/d in CR SD rats (n = 9–29/group) and 0, 11, 33, 50, 100, 300, 325, and 750 mg/kg/d in Harlan SD rats (n = 3–24/group). Non-linear (sigmoid) regression analysis performed in Prism. BMDS Analysis refers to benchmark dose analysis performed using U.S. EPA BMDS Online software. ALPCO = APLCO Life Science; BMD = benchmark dose; BMDL = BMD lower limit; BMDU = BMD upper limit; ED = effective dose; CR = Charles River; DPeP = dipentyl phthalate; RIA= radioimmunoassay; SC = seminiferous cord; SD = Sprague Dawley

assumed unequal variance;

questionable model fit with nonconstant variance test failed (Test 3p < 0.05), but data also failed constant variance test;

^##

questionable model fit with goodness of fit p < 0.1. Summary data in Table S5.

Next, we used BMDS to obtain BMD₁₀ estimates for all six datasets (Table 2). There was a large degree of overlap in the BMD₁₀ estimate bounds (BMDL – BMDU). However, MNGs counted on H&E-stained slides had the lowest BMD₁₀ estimate (2.68 mg/kg/d), overlapping with only the bounds of the GD 21 ex vivo T data from this paper. All of the remaining datasets had similar BMD₁₀ estimates with overlapping bounds, except for the seminiferous cord diameter, which had a BMD₁₀ of 68.656 mg/kg/d. Excluding the low BMD₁₀ for MNGs (H&E) and the high BMD₁₀ for seminiferous cord diameter, the remaining four analyses gave BMD₁₀ estimates in a narrow window ranging from 8.96–14.6 mg/kg/d.

3.5. RNA-seq analysis of rat fetal testis following DPeP exposure

Using DEseq2, at the individual gene level, we identified 5, 18, 95, and 212 differentially expressed genes (DEGs) between the vehicle control and the 1, 11, 100, and 300 mg/kg/d DPeP treatments, respectively (Fig. 6A, Table S1). Several genes showed apparent dose-dependence across the 11, 100, and 300 mg/kg/d group, while the five DEGs at 1 mg/kg/d were not seen in any other treatment group. Notable categories of DEGs included upregulated testis injury markers (Clu, Testin); downregulated genes coding for cholesterol metabolism, steroidogenesis, or hormone signaling proteins (Aldh1b1, Aldh1l1, Cyp11a1, Cyp17a1, Hsd17b1, Hsd3b3, Inha, Insl3, Nr4a1, Scarb1, Star); two down-regulated glutathione S-transferase genes (Gsta1, Gsta2); genes coding for cellular and extracellular structural molecules that were both up- and down-regulated (Cdh1, Col22a1, Col2a1, Col8a1, Col9a2, Col9a3, Dync1i1); and development and spatial patterning genes that were mostly upregulated (Lefty2, Nanos2, Ptgds, Sox10, Sox6, Sox8). Many genes met the significance criteria at only one dose, but 61 DEGs were shared between 100 and 300 mg/kg/d and 10 DEGs were shared between 11, 100, and 300 mg/kg/d (Fig. 6B).

We identified 753 nominally dose-dependent genes using the Williams trend test in BMDExpress2, 457 of which were annotated to a known gene (Fig. 6C, Table S2, p < 0.05, no multiple test correction). The most common best-fit model was poly 2, followed by linear, exp 4, exp 2, Hill, and only few genes that best fit the power, exp 5, and exp 3 models. Unsurprisingly, given the different shape of the best fit curves, the median best fit BMD for poly 2, exp 4, Hill, and exp 5 was lower than the median for the linear and exp 2 models, and much lower than the power and exp 3 models. Using previously published datasets (Hermann et al. 2015; Jameson et al. 2012; Stevant et al. 2018), we identified 66 of the 457 annotated BMDExpress2 genes as being Sertoli cell-expressed, as well as 11 expressed in progenitor cells (“early progenitor” cluster in Stevant et al. (2018)), 33 in Leydig cells and their progenitors, 20 in interstitial cells, 33 in germ cells, and 29 in endothelial cells (Fig. 6D). Using Fisher’s exact test, we identified 26 Reactome gene sets and 566 Gene Ontology (GO) Biological Process, Molecular Function, and Cellular Compartment terms that were enriched among the prefiltered genes (p < 0.05) and included at least 3 genes and at least 2 % of the genes in the gene set (Fig. 6E, Table 3, Table S3). The enriched gene set with the lowest BMD median was the Reactome gene set, basigin interactions (R-RNO-210991), with a BMD median value of 2.44 mg/kg/d. The enriched gene sets included canonically phthalate-associated terms, such as GO:0006694, steroid biosynthetic process, as well as genes related to categories plausibly involved in testicular morphogenesis, with multiple enriched terms related to gonad development, vasculature development, and epithelial cell differentiation (Fig. 7A, Table S4). Steroid metabolism genes, epithelial development genes, and vasculature development genes were largely downregulated with increasing DPeP dose, while genes that fall under gonad development terms were both up- and downregulated. Some genes, such as Scarb1, belonged to multiple enriched terms. Four DEGs were selected for in situ hybridization to investigate the changes in cell type-specific expression patterns resulting from DPeP exposure: Scarb1, Gas6, Amhr2, and Kdr. Scarb1 was chosen to confirm the known effect of phthalates on steroid biosynthesis in the Leydig cell. Gas6 and Amhr2 were selected as novel phthalate response genes expressed in the Sertoli cell, with roles in gonad development. Kdr was chosen as a known vascular development gene that responded to DPeP in bulk RNA-seq. In situ hybridization showed a strong association of Scarb1 with Leydig cells. Scarb1 expression was variable but less intense in DPeP-treated sections than vehicle control (Fig. 7B–C). Gas6 and Amhr2 were expressed in Sertoli cells, and subjectively appeared to be expressed more strongly in Sertoli cells of DPeP-treated rats (Fig. 7D–F). Gas6 was particularly associated with the developing rete testis. Kdr was strongly expressed in endothelial cells in all treatment groups. Some interstitial areas of DPeP-treated sections had fewer Kdr-positive blood vessels than control samples (Fig. 7G).

Table 3.

Benchmark dose modeling of DPeP RNA-seq data.

GO/Reactome Gene Set ID	GO/Reactome Gene Set	BMD Median	n	Genes up	Genes down	%	p-value	Best Fit Model (n)
R-RNO-210991	Basigin interactions	2.44 (1.38, 7.17)	16		Slc7a8, Slc3a2, Mag	18.75	0.017	Exp4 (3)
GO:0015180	L-alanine transmembrane transporter activity	5.28 (2.92, 10.82)	8		Slc36a1, Slc7a8, Slc3a2	37.5	0.001	Exp4 (2), Poly2 (1)
GO:0031528	microvillus membrane	5.94 (2.92, 25.10)	23		Slc7a8, Slc6a6, Scarb1	13.04	0.030	Exp4 (1), Hill (1), Poly2 (1)
GO:0120178	steroid hormone biosynthetic process	5.94 (2.89, 20.19)	21		Cyp11a1, Hsd17b1, Scarb1	14.29	0.024	Hill (3)
R-RNO-8964043	Plasma lipoprotein clearance	5.94 (2.89, 25.10)	21	Pcsk9	Nceh1, Scarb1	14.29	0.036	Exp4 (1), Hill (1), Poly2 (1)
GO:0089718	amino acid import across plasma membrane	6.10 (2.92, 27.53)	29		Slc36a1, Slc7a8, Slc3a2, Slc6a6, Gfap	17.24	0.002	Exp4 (3), Poly2 (2)
GO:0001541	ovarian follicle development	7.06 (2.27, 32.72)	53	Bmp4	Kdr, Lhcgr, Inha, Cebpb	9.43	0.021	Hill (3), Linear (1), Poly2 (1)
GO:0006694	steroid biosynthetic process	7.33 (3.24, 25.10)	82		Tm7sf2, Tecr, Cyp11a1, Sqle, Cyp7b1, Hsd17b1, Scarb1	8.54	0.011	Exp2 (2), Exp4 (1), Hill (3), Linear (1)
GO:0030247	polysaccharide binding	8.45 (3.16, 33.57)	20	Endou, Ppp1r3a	Vtn	15	0.021	Exp4 (2), Hill (1)
GO:0051580	regulation of neurotransmitter uptake	9.21 (3.01, 68.88)	14	Rab3b, Drd2	Gfap	21.43	0.008	Exp4 (2), Poly2 (1)

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Benchmark dose (BMD) analysis of RNA-seq data performed in EPA BMDExpress2 software. RNA-seq was used to analyze fetal testis RNA following exposure to 0, 1, 11, 100, or 300 mg/kg/d DPeP from GD 17–21 (n = 3/group for all groups except 300 mg/kg/d, where n = 5). Genes were analyzed for trend using Williams trend test, then for enriched Reactome (R-RNO) or Gene Ontology (GO) gene sets by Fisher’s exact test. BMD Median is the median gene BMD for the gene set, shown with the median BMD lower bound and upper bound (BMDL Median, BMDU Median); DE: differentially expressed; n: number of genes in the gene set; p-value: 2-tailed Fisher’s exact test p-value; Genes up, Genes down, and % refer to all genes that passed all BMDExpress filters; Best Fit Model shows the number of best fit genes in parentheses for each DE gene in the gene set.

Fig. 7. — Enriched biological processes in DPeP benchmark dose analysis. A. Heat maps highlighting details of the RNA-seq analysis performed on testes treated with DPeP at Brown (n = 3 litters/group for 0, 1, 11, and 100 mg/kg/d DPeP, n = 5 for 300 mg/kg/d DPeP). Heat maps display genes from each of several significantly enriched gene sets corresponding to selected testis development processes: steroid metabolism includes GO:0008202, GO:0006694, GO:0120178, and R-RNO-211976. Gonad development includes GO:0001541, GO:0008584, and GO:0008406. Vasculature development is GO:0001944, which was redundant with 8 additional GO terms. Epithelial cell differentiation is GO:0030855. Heat maps were made with Morpheus (https://software.broadinstitute.org/morpheus). Darker red color represents row maximum, while white represents row minimum. Cell type of highest known expression based on review of prior literature (Hermann et al. 2015; Jameson et al. 2012; Stevant et al. 2018) is listed to the right of each gene name. Heat map data in Table S4. B-G. Localization of select transcripts by RNAscope *in situ* hybridization of testis sections from both Brown and EPA sites treated with 0, 100, and 300 mg/kg/d DPeP (3–6 sections/treatment group). B-C. Scarb1 expression. D-E Gas6 expression Rete testis is visible in D, while E is a higher-magnification view of punctate stain predominantly in Sertoli cells. F. Amhr2 expression. G. Kdr expression. Scale bars = 300 μm in B, 200 μm in D and G, 60 μm in C, E, and F.

3.6. Analysis of rat fetal testis histology and testosterone production following dexamethasone exposure

To test whether dexamethasone produces phthalate-like toxicity, we measured ex vivo testosterone production, MNG density, and seminiferous cord diameter in rats exposed to dexamethasone from GD 17–21 (Fig. 8). No significant difference in MNG density was observed after exposure to 0.05–0.5 mg/kg/d dexamethasone; 5 mg/kg/d dexamethasone slightly increased MNG density (Fig. 8A). No difference in seminiferous cord diameter was observed upon dexamethasone exposure (Fig. 8B). In contrast to the histopathological findings, a significant, dose-dependent decrease in testosterone production was observed at 0.5 and 5 mg/kg/d dexamethasone (Fig. 8C). A non-linear (sigmoid) regression model (Fig. 8D) gave an estimated ED₅₀ of 0.3960 mg dexamethasone/kg/d (95 % CI: 0.08826 – 2.536). However, these results occurred at doses that resulted in maternal toxicity. Dam body weight was significantly lower at 0.5 and 5 mg/kg/d dexamethasone (Fig. 8E). Moreover, body weight gain was lower at 0.1–5 mg/kg/d dexamethasone doses, with dams losing weight from GD 17–21 following 5 mg/kg/d dexamethasone exposure (Fig. 8F).

Fig. 8. — Fetal rat testis testosterone production and histology following treatment with dexamethasone. Rats were exposed to 0–5 mg/kg/d dexamethasone from GD 17–21. A. Multinucleated germ cells (MNGs)/mm² testis counted on H&E-stained slides (one-way ANOVA with Dunnett’s *post hoc* test). B. seminiferous cord diameter (one-way ANOVA with Dunnett’s *post hoc* test). C. *ex vivo* testosterone production (one-way ANOVA with Dunnett’s *post hoc* test). D. Nonlinear regression of *ex vivo* testosterone production data. Dose-response analysis was performed in Prism using nonlinear regression. Vehicle control value was set to 0.01 mg/kg/d to enable log transformation. Model constraints: bottom ≥ 0, top = 100. Model-derived ED₅₀ was 0.3960 mg/kg/d (95 % CI: 0.08826 – 2.536). Solid line is the regression line, and dotted lines show the 95 % CI. E. dam body weights on the final day of the (ANOVA with Dunnett’s multiple comparison test). F. Maternal body weight gain from gestational day (GD) 17–21 (Kruskall-Wallis test with Dunn’s multiple comparison test). All treatments were performed at EPA (n = 3–9 litters/group). Data are shown as individual values with group mean ± SEM. Brackets are labeled with p-values. Data shown as mean ± SEM for each dose. Summary data in Table S5.

3.7. Analysis of rat fetal testis histology and testosterone production following exposure to other antiandrogenic compounds

To test whether impaired androgen signaling would result in phthalate-like induction of MNGs, we measured ex vivo T production, MNGs on H&E slides, and seminiferous cord diameter on H&E slides for rats that were exposed to three known or reported antiandrogens from GD 17–21: 150 mg/kg/d prochloraz, 400 mg/kg/d acetaminophen, and 200 mg/kg/d vinclozolin (Fig. S4). Among these, only vinclozolin exposure resulted in significantly lower ex vivo testosterone production (Fig. S4A, p = 0.0104), despite past results indicating that vinclozolin primarily works through AR inhibition and that the other three compounds have the potential to impair testosterone production. No significant difference in MNG density (Fig. S4B) or seminiferous cord diameter (Fig. S4C) was detected following any exposure.

3.8. Analysis of rat fetal testis histology and testosterone production following TBMEHP exposure

We performed a dose–response experiment to compare the effects of the highly potent toxic phthalate, DPeP, against a phthalate with low toxic potency, TBMEHP. TBMEHP exposure did not yield significant differences in MNG density on H&E-stained slides, seminiferous cord diameter, or ex vivo testosterone production following exposure to 0–500 mg/kg/d TBMEHP from GD 17–21 (Fig. S5).

4. Discussion

Phthalates cause a decrease in masculinization of the male reproductive tract in rats (Fisher et al. 2003), disrupt the morphogenesis of the fetal testis in rats (Andrade et al. 2006; Kleymenova et al. 2005; Lara et al. 2017), and cause adverse fetal germ cell outcomes in mice (Gaido et al. 2007), rats (Spade et al. 2018), and human testis explants (Heger et al. 2012; Spade et al. 2014). One of the goals of this experiment was to test whether there is a difference in sensitivity to DPeP for different phthalate toxicity endpoints in the fetal rat testis. We performed a quantitative dose–response assessment of phthalate-induced multinucleated germ cells (MNGs), covering an approximately 2.5-log dose range. We found that 11 mg DPeP/kg/d was sufficient to produce significantly higher MNG density than vehicle-treated control testes. This is, to our knowledge, the lowest reported apical response LOAEL, on a mg/kg basis, for fetal testis toxicity of a phthalate. It is well established that phthalate exposure in fetal rats results in a significant decrease in testosterone production (Furr et al. 2014). Phthalates are strongly antiandrogenic in the fetal rat, but the effects of phthalates on testicular morphogenesis and seminiferous cord/germ cell development are not dependent on inhibition of testosterone production (Gaido et al. 2007; Habert et al. 2014; Heger et al. 2012; Johnson et al. 2012; Lambrot et al. 2009; Mitchell et al. 2012; Spade et al. 2014). This indicates that phthalates exert these two toxic effects in the fetal testis through distinct downstream modes of action, although they may be caused by a single upstream molecular initiating event that is presently unknown. Based on our benchmark dose analyses, DPeP disrupted testis morphogenesis and lowered testosterone with similar potency. This has important implications for extrapolation of phthalate dose–response data in the rat to humans, because phthalates are known to induce MNGs in the human fetal testis, even when testosterone production is not altered (Heger et al. 2012; Mitchell et al. 2012; Spade et al. 2014; van den Driesche et al. 2015).

We estimated the ED₅₀ for MNG density as 18.95 (11.48–37.28) mg/kg/d or 27.20 (16.11–42.80) mg/kg/d DPeP, depending on the method used to quantify MNGs – H&E sections and DDX4 immunolabeled sections, respectively. This was approximately 1.5- to 7-fold lower than the ED₅₀ for ex vivo testosterone production in previous studies that used the GD 14–18 exposure window or the present study, which used the GD 17–21 exposure window, but with some overlapping 95 % CIs (Table 2). It is reasonable that MNGs would be a very sensitive phthalate response because of the apparent mechanism, which involves rapid cellular responses to Sertoli cell stress and may only require a loss of germ cell-Sertoli cell contact and a collapse of germ cell intercellular bridges, rather than induction of a program of gene expression, protein synthesis, or mitosis (Kleymenova et al. 2005; Spade et al. 2015). It should be noted, however, that justification for the use of MNGs to measure phthalate dose–response is strongest when the exposure window includes the late gestational germ cell quiescent period, beginning on approximately GD 18 in the rat (Culty 2009). A single-dose or short-term phthalate exposure within the quiescent period can induce MNGs. However, past experiments in which animals were exposed prior to the quiescent period and euthanized prior to the quiescent period have not reported an effect on MNG density (Ferrara et al. 2006; Spade et al. 2015). It is possible that an exposure prior to the quiescent period could have the latent effect of inducing MNGs in late gestation, as was reported in one study, albeit with relatively low MNG counts (Shirota et al. 2005). However, the bulk of the evidence suggests that the window of greatest sensitivity for MNG induction is from GD 18 to parturition. Conversely, with respect to ex vivo T, prior studies have indicated that antiandrogenic treatments have the greatest effect on testosterone biosynthesis and masculinization of the male reproductive tract when the exposure occurs in the masculinization programming window (MPW), approximately GD 14–18 (Scott et al. 2009). We found that the ED₅₀ for testosterone production in the present study was higher than ED₅₀ reported in prior studies in which the exposure was conducted during the MPW (Furr et al. 2014; Gray et al. 2016; Hannas et al. 2011a). Although this is not a direct comparison, the potency of DPeP to impair testosterone production may be greatest during the MPW due to the well-characterized sensitivity of the fetal testis to antiandrogens during that period of development.

To determine whether selection of the different endpoints that we tested would lead to widely different points of departure for risk assessment, we performed benchmark dose (BMD) analysis using BMDS (Table 2). The BMD₁₀ values were more similar across the endpoints that we measured than the ED₅₀ values. The BMD₁₀ CIs overlapped for all endpoints except for seminiferous cord diameter. The lowest BMD₁₀ estimate was for MNGs on H&E-stained slides (2.68 mg/kg/d). The remaining endpoints had nearly indistinguishable BMD₁₀ values ranging from 8.96 to 14.6 mg/kg/d, suggesting that MNGs and T are similarly appropriate endpoints to estimate BMD in dose–response assessment of phthalates. The seminiferous cord diameter had a higher BMD₁₀, 68.23 mg/kg/d, with a CI that only slightly overlapped with GD 21 ex vivo T, suggesting that it would be less useful for dose–response analysis in the context of risk assessment. U.S. EPA guidance for setting benchmark response (BMR) levels to determine BMD for risk assessment says that “for continuous data, the preferred approach is to define a BMR based on the level of change in the endpoint at which the effect is considered to become biologically significant” (U.S. Environmental Protection Agency 2012). Given that MNGs are an aberrant, degenerative germ cell phenotype, a 10 % change in MNGs is an appropriate, biologically significant phthalate response in the fetal testis. Similarly, 10 % lower ex vivo T production is biologically significant (Gray et al. 2016). Overall, because MNGs and testosterone production are approximately equally sensitive phthalate response endpoints, and because MNGs are known to be human-relevant, it would be reasonable to incorporate MNG data into phthalate risk assessment when available.

Finally, we calculated BMD estimates for DPeP based on RNA-seq data, using BMDExpress2 (Figs. 6–7, Table 3). The lowest gene set BMD median was 2.44 (1.38, 7.17) mg/kg/d for the Reactome gene set, basigin interactions (R-RNO-210991), which is almost identical to the lowest apical endpoint BMD of 2.68 mg/kg/d for MNG density. For determination of transcriptome benchmark dose using BMDExpress2, selection of gene sets with a higher number of genes passing all of the filters may make the estimate more robust (Johnson et al. 2020). The lowest gene set BMD median with at least 7 genes that passed all filters was 7.33 (3.24, 25.10) mg/kg/d for the Gene Ontology term, steroid biosynthetic process (GO:0006694). While the gene set point of departure modeling approach is relatively new (Phillips et al. 2018; Thomas et al. 2011), it is well-supported by papers reporting similar apical and gene expression BMD estimates for several compounds targeting different organs, including myclobutanil (LaRocca et al. 2020), ketoconazole (Johnson et al. 2022), triclopyr, pronamide, sulfoxaflor, and fenpicoxamid (Bianchi et al. 2021). The concordance between apical toxicity outcomes and gene expression data in the present study provides confidence that a BMD in the range of 2–3 mg/kg/d would be an appropriate point of departure for modeling the risk of in utero DPeP exposure to fetal testis development. Notably, there is recent evidence that the effects of phthalates and other antiandrogens on male reproductive tract development are dose-additive, such that mixtures can produce significant reductions of T production at doses below the NOAEL for each individual compound (Conley et al. 2018; Conley et al. 2021; Hannas et al. 2011b; Hotchkiss et al. 2010; Howdeshell et al. 2015; Rider et al. 2008). With DPeP BMD₁₀ values as low as 9.81 (8.58–11.14) mg/kg/d for ex vivo T production and 2.68 (0.79–6.70) mg/kg/d for MNG density, DPeP could contribute significantly to the toxicity of a phthalate mixture. Accordingly, human exposure to DPeP should be assessed when possible. Phthalate biomonitoring data from different geographic regions show differences in exposure to specific phthalates (Wang et al. 2019). These regional differences may be unpredictable, as seen in one report of high exposure to diisopentyl phthalate in a cohort of pregnant women in Brazil (Bertoncello Souza et al. 2018).

The other major goal of the present study was to investigate potential mechanisms of phthalate toxicity, as there remains a lack of certainty about the molecular initiating events and underlying biological processes that precede cell- and tissue-level effects of phthalates (Conley et al. 2018; Li and Spade 2021). In the seminiferous cord, phthalates adversely affect Sertoli cell function, resulting in germ cell clustering, multinucleated germ cells (MNGs), dysgenic cords, and/or dilated cords, depending on the window of exposure (Ferrara et al. 2006; Lara et al. 2017; Spade et al. 2015). MNGs are degenerative and undergo apoptosis before the onset of spermatogenesis (Saffarini et al. 2012), but fetal and lactational exposure to phthalates leads to persistent adverse effects including degeneration of the seminiferous epithelium and male reproductive tract malformations in adult rats (Andrade et al. 2006; Barlow and Foster 2003; Barlow et al. 2004; Mylchreest et al. 2000; Saillenfait et al. 2008). This suggests that phthalate toxicity to germ cells and/or testicular morphogenesis is persistent, although it occurs through unknown mechanisms. We approached this problem in two ways: first, by assessing the dose-dependent gene expression signature of DPeP in the rat fetal testis, and second, by comparing the effects of DPeP to those of antiandrogens and a glucocorticoid. It is often assumed that toxicant-induced changes in gene and protein expression precede and form the basis for changes at the tissue level. This assumption is illustrated by the original papers on adverse outcome pathways (AOPs), in which “cellular responses,” including changes in gene and protein expression precede “organ responses,” such as altered tissue development or function (Ankley et al. 2010). This is consistent with many core toxicology mechanisms and provides rationale for efforts to use gene expression as a basis for identification of sensitive points of departure for risk assessment (Dean et al. 2017). As noted above, the results of our gene expression BMD analysis indicated that, in addition to the known effects of phthalates on expression of steroid biosynthesis genes, DPeP altered expression of genes in categories related to basic cell structure and function, such as basigin interactions and alanine transport, with very low benchmark doses. Basigin is a cell membrane-anchored receptor that functions in cell–cell contact through basigin-integrin interactions (Curtin et al. 2005). Additional membrane function and cell–cell contact and communication mechanisms, including amino acid transport, plasma lipoprotein clearance, neurotransmitter uptake, and microvillous membrane proteins were among the gene sets with the lowest BMD median values in our analysis.

More holistically, DPeP differential expression data were enriched for a number of developmentally important biological processes that we aggregated into four categories: steroid metabolism, gonad development, epithelial cell differentiation, and vasculature development, with some of the enriched gene sets having median BMDs in the 5–25 mg/kg/d range (Fig. 7 and Table S3). These results reinforce some existing knowledge about phthalates and also generate some hypotheses about phthalate toxicity mechanisms that would be candidates for further testing. As expected based on prior phthalate studies, many genes involved in steroid metabolism and signaling were largely downregulated across the DPeP dose–response, including the cholesterol metabolism and transport genes, Sqle and Scarb1. Changes in cholesterol metabolism or transport are plausible upstream events that could explain the effect of phthalates on steroid biosynthesis. Similarly, upregulation of Cyp26b1 suggests that DPeP treatment may alter retinoid metabolism or signaling in the testis, as CYP26 enzymes metabolize retinoic acid. This would be consistent with prior findings in mouse and rat DEHP/MEHP studies from the Spade lab (Alhasnani et al. 2022; Spade et al. 2019) and with a recent study from Martino-Andrade and colleagues (Curi et al. 2023). However, significantly higher Cyp26b1 expression was not observed following exposure to an 8-phthalate mixutre in a study by Gray et al. (2021).

We also identified several enriched gene sets related to gonad development with low gene set BMDs. Approximately half of the genes in these gene sets were upregulated and half downregulated. Most of the upregulated genes, such as Bmp4, are typically associated with ovary determination, while testis-associated genes, such as Nr0b1, were downregulated, suggesting that DPeP exposure may antagonize signaling processes required to maintain normal Sertoli cell function (Brennan and Capel 2004; Ross et al. 2003). Important testis development genes, Inha and Lhcgr, were down-regulated in DPeP-exposed animals. Inha is a part of the TGFβ family inhibin A and B complexes, which negatively regulate FSH production (Woodruff et al. 1996). Lhcgr codes for the luteinizing hormone (LH) and chorionic gonadotropin receptor. Both FSH and LH signaling are typically active in late gestation (Warren et al. 1984). Although it is not a member of the enriched gene categories, Testin was upregulated, consistent with a prior phthalate experiment (Liu et al. 2005). Testin encodes a cell surface protein that is upregulated when Sertoli-germ cell junctions are disrupted (Grima et al. 1998). Upregulation of Testin following phthalate exposure is consistent with the hypothesis that phthalate-induced MNGs and germ cell clusters form because of a loss of germ cell-Sertoli cell contact.

Especially novel gene clusters among the enriched gene sets pertain to epithelial cell differentiation and vasculature development. The large number of genes related to epithelial cell differentiation were largely downregulated, and they included some structural genes, for example Myo7a, and spatial patterning genes, such as Sox18. Other DE genes that are known to contribute to structural and spatial development included Lefty2, Cdh1, Nanos2, Dync1i1, and Sox10 (Fig. 6A). The vasculature development category is interesting because there have been multiple prior observations of vascular abnormalities in the testes of phthalate-treated rats, including damaged interstitial blood vessels and hemorrhage (Gray et al. 2000; Klinefelter et al. 2012; Veeramachaneni and Klinefelter 2014). Approximately two thirds of the vasculature-related genes in the enriched gene sets in our analysis were downregulated, including Vcam1, Cdh5, Sox18, and Kdr. We confirmed expression of Kdr in endothelial cells by ISH. Density of Kdr-positive blood vessels was possibly lower following DPeP exposure, but was variable (Fig. 7G), and quantification of this effect would require further study. It is well-known that in early testis development, the vasculature guides cord morphogenesis (Cool et al. 2011; Coveney et al. 2008; DeFalco et al. 2014). The extent to which the vasculature continues to guide cord development in late gestation is unknown, but we hypothesize that disruption of these vascular development processes could mediate some of the adverse effects of phthalates on fetal testis cord morphogenesis. Among the vasculature development-related DE genes were several genes typically expressed in interstitial and Leydig cells, that were downregulated with very low gene BMDs (Fig. 7A), including Igf1 (26.6307), Vcam1 (5.72 mg/kg/d), and Scarb1 (5.94 mg/kg/d). Our ISH analysis qualitatively showed that Scarb1 expression decreased variably on a per-cell basis (Fig. 7B–C). Because Scarb1 is highly expressed in normal Leydig cells, downregulated following phthalate exposure, and involved in signaling for angiogenesis, it may be a key contributor to the effects of phthalates on testis development. The pattern of ISH staining of our selected Sertoli cell-expressed DEGs was more difficult to interpret. Although Amhr2 and Gas6 were both clearly expressed in Sertoli cells, their expression was low (Fig. 7D–F). However, the higher bulk gene expression of both of these genes is consistent with the hypothesis that impaired Sertoli cell development and function leads to altered testis morphogenesis. Gas6 is particularly interesting, as its signal appeared much stronger in the developing rete testis than in typical Sertoli cells, suggesting that it is plausible that a change in bulk expression of Gas6 could be driven by changes in rete testis development. Hypothetically, improper development of the rete testis or adjacent Sertoli valves could explain some persistent effects of phthalates on testis function (Uchida et al. 2022). To our knowledge, phthalate effects on rete testis development have not been tested in prior studies, but they should be assessed in the future.

Our approach to studying the gene expression effects of DPeP had some notable limitations. One such limitation is the heterogeneity of cell types in samples used for bulk RNA-seq. This heterogeneity can lead to failure to identify gene expression changes in numerically minor cell types; misinterpretation of expression changes that differ in different cell types; or conflation of changes in cell number with changes in per-cell gene expression regulation. Our ISH data indicated that some changes in bulk gene levels detected by RNA-seq may have resulted from changes in both cell number/distribution and per-cell expression levels, as in the cases of the endothelial cell gene, Kdr (Fig. 7). However, given the variable and punctate staining patterns, we felt that ISH data for some of our targets would be difficult to quantify accurately. Therefore, to test whether DPeP exposure caused changes in relative densities of several major testicular cell types, which could influence interpretation of bulk RNA-seq data, we quantified the density of germ cells, Sertoli cells, and Leydig cells in tissue sections, using immunofluorescence (Fig. 3). We found that the density of each of these three cell types was unchanged by DPeP treatment. By inference, this is evidence that changes in measured gene expression were not caused primarily by changes in relative density of these cell types, but by differences in cell type-specific gene expression, at least for germ cells, Sertoli cells, and Leydig cells. This interpretation is limited by our ability to detect what might be subtle changes in relative cell densities that do not meet statistical significance. It also does not account for the several numerically minor cell types that are critical to testis development and function, including endothelial cells, macrophages, and undifferentiated pre-cursors. Although single-cell RNA-seq is beyond the scope of the present manuscript, future studies could use single-cell methods to overcome these limitations and test the effect of phthalates on cell type-specific gene expression in the fetal testis, including numerically minor cell types, in an unbiased manner. Among other advantages, such an approach would enable more precise testing of the hypotheses generated by our BMDExpress analysis, such as phthalate-induced changes in vasculature and rete testis development. There is recent progress in development of methods to analyze single-cell RNA-seq data in the context of large dose–response experiments (Gavriilidis et al. 2024), including a study of TCDD hepatotoxicity in which the effect of dose on cellular function was modeled in a manner similar to pseudotime analysis of development (Kana et al. 2023). These approaches should be employed in future phthalate toxicity studies.

Finally, for comparison to DPeP, we tested non-phthalate compounds with two known modes of action related to phthalate toxicity. It is notable for our understanding of phthalate toxicity that these compounds did not cause phthalate-like effects on fetal testis morphogenesis. Of the antiandrogens that we tested, only vinclozolin, which is typically thought of as an AR antagonist (Monosson et al. 1999), resulted in significantly lower testosterone production. In contrast to prior results, simvastatin, prochloraz, and acetaminophen did not affect testosterone production, but this could be due to the relatively late window of exposure used in our study (GD 17–21). Not surprisingly, despite reducing testosterone, vinclozolin did not alter MNG density. This reinforces prior findings that lower testosterone levels or impaired androgen signaling were not sufficient to induce MNGs in the fetal testis, making MNG induction an essentially phthalate-specific outcome. In addition to testing antiandrogenic chemicals, we tested the glucocorticoid, dexamethasone, which has previously been reported to enhance the antiandrogenic effects of DBP (Drake et al. 2009). Docking studies and in vitro studies suggest that some phthalate diesters may be GR ligands themselves (Leng et al. 2020; 2021). In the present study, dexamethasone treatment resulted in significantly, dose-dependently lower testosterone production in the rat fetal testis, but it only significantly increased MNG density in the highest dose group (Fig. 8), a finding that should be interpreted cautiously because of the significant maternal toxicity caused by dexamethasone. Dam body weight gain was reduced at all tested doses, and at 5 mg/kg/d, the pregnant dams lost weight during the exposure window. This is evidence that, despite a reported significant interaction between dexamethasone and DBP, GR binding and/or transactivation does not duplicate the effects of phthalates on the fetal testis.

In conclusion, with respect to DPeP dose–response, we found that in the context of late gestation DPeP exposure, MNG density may be a slightly more sensitive response metric than testosterone production, when potency is defined by ED₅₀ (Fig. 5, Table 2). However, all the endpoints tested in this project, except for seminiferous cord diameter, produced very similar potency estimates when using the benchmark dose modeling approach (Tables 2–3). Therefore, testosterone and MNGs are likely to be equally useful for the purpose of assessing phthalate dose–response for risk assessment. This conclusion is strengthened by multi-site validation, in which we found that response data were reproducible between the EPA and Brown sites. With respect to phthalate mechanisms, the results of this study reinforce prior findings that phthalates cause maldevelopment of the testis and diminish testosterone production. Although there is no known molecular initiating event(s) for phthalate testicular toxicity (Li and Spade 2021), in our analysis, DPeP disrupted expression of genes required for steroid metabolism, gonad development, epithelial cell differentiation, and vascular development. Very sensitive genes in these categories, including Scarb1, may be key to understanding the mechanisms by which phthalates disrupt testis morphogenesis.

Disclosures

The research described in this article has been reviewed by the U.S. Environmental Protection Agency and approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the Agency nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

Supplementary Material

NIHMS2087676-supplement-1.docx^{(962.9KB, docx)}

NIHMS2087676-supplement-2.xlsx^{(298.2KB, xlsx)}

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.envint.2025.109551.

Acknowledgements

This work was supported by the National Institutes of Health [grant number R00ES025231]; Brown University; and the U.S. Environmental Protection Agency Chemical Safety for Sustainability Research Action Plan. The University of Virginia Center for Research in Reproduction Ligand Assay and Analysis Core is supported by the National Institutes of Health [grant number R24HD102061].

The authors would like to acknowledge David Silverberg for processing and cutting histological samples, Joceline Helmbreck for assistance with immunofluorescent staining and image analysis, and Drs. Colette Miller (U.S. EPA) and Thomas Jackson (U.S. EPA) for reviewing prior drafts of the manuscript.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Daniel J. Spade reports financial support was provided by National Institutes of Health. L. Earl Gray and Justin M. Conley report financial support was provided by United States Environmental Protection Agency. Justin M. Conley, L. Earl Gray, and Christy Lambright are employees of the U.S. Environmental Protection Agency. Daniel J. Spade served as an ad hoc reviewer for U.S. EPA Science Advisory Committee on Chemicals for hazard/risk assessments of diisononyl phthalate and diisodecyl phthalate. No known competing financial interests or personal relationships influenced the work reported in this paper or the decision to publish.

Nomenclature

Glossary

BMD: benchmark dose
BMDExpress2: gene expression benchmark dose software
BMDL: BMD lower limit
BMDS: U.S. EPA BMDS Online software
BMDU: BMD upper limit
DPeP: dipentyl phthalate
ED: effective dose
ED₅₀: median effective dose
GD: gestational day
GO: Gene Ontology
LOAEL: lowest observed adverse effect level
MNG: multinucleated germ cell(s)
SD: Sprague Dawley rat
TPROD: ex vivo testosterone production assay

Footnotes

CRediT authorship contribution statement

Maansi V. Gupta: Conceptualization, Formal analysis, Investigation, Writing – original draft, Writing – review & editing, Methodology. Justin M. Conley: Conceptualization, Formal analysis, Investigation, Writing – original draft, Writing – review & editing, Methodology. Christy Lambright: Conceptualization, Investigation, Writing – review & editing, Methodology. Logan F. Chin: Investigation, Writing – review & editing. Susan J. Hall: Conceptualization, Data curation, Investigation, Project administration, Writing – review & editing. L. Earl Gray: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing. Daniel J. Spade: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing.

Data availability

Data will be made available on request.

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Associated Data

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Supplementary Materials

NIHMS2087676-supplement-1.docx^{(962.9KB, docx)}

NIHMS2087676-supplement-2.xlsx^{(298.2KB, xlsx)}

Data Availability Statement

Data will be made available on request.

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PERMALINK

Dose-response assessment of dipentyl phthalate effects on testosterone production and morphogenesis of late-gestation fetal rat testis

Maansi V Gupta

Justin M Conley

Christy Lambright

Logan F Chin

Susan J Hall

L Earl Gray

Daniel J Spade

Abstract

1. Introduction

2. Methods

2.1. Animals

2.2. Chemicals and study design

Table 1.

2.3. Testosterone production assay

2.4. Histology

2.5. Immunofluorescence

2.6. In situ hybridization

2.7. RNA isolation and quality control

2.8. Data analysis and Statistics

2.9. RNA-seq analysis and BMD estimation

3. Results

3.1. Dam and pup weights after DPeP exposure

Fig. 1.

3.2. Fetal testis morphometrics after DPeP exposure

Fig. 2.

Fig. 3.

3.3. Testosterone production after DPeP exposure

Fig. 4.

3.4. Dose-Response comparison and benchmark dose analysis

Fig. 5.

Table 2.

3.5. RNA-seq analysis of rat fetal testis following DPeP exposure

Fig. 6.

Table 3.

Fig. 7.

3.6. Analysis of rat fetal testis histology and testosterone production following dexamethasone exposure

Fig. 8.

3.7. Analysis of rat fetal testis histology and testosterone production following exposure to other antiandrogenic compounds

3.8. Analysis of rat fetal testis histology and testosterone production following TBMEHP exposure

4. Discussion

Disclosures

Supplementary Material

Acknowledgements

Declaration of competing interest

Nomenclature

Footnotes

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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