Interindividual variation in gut microbial formation of 8-prenylnaringenin results in increased, but sub-estrogenic, internal exposure

Interindividual variation in gut microbial formation of 8-prenylnaringenin results in increased, but sub-estrogenic, internal exposure | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Interindividual variation in gut microbial formation of 8-prenylnaringenin results in increased, but sub-estrogenic, internal exposure Maja Stevanoska, Michelle Cremona, Karsten Beekmann, Shana J. Sturla, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6511068/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The gut microbiome converts the prenylated polyphenol isoxanthohumol, a natural constituent of hops found in beer, to 8-prenylnaringenin (8-PN), a potent phytoestrogen, raising concerns about potential endocrine-disruption. Interindividual differences in microbiome composition may result in varying internal exposures to 8-PN and susceptibility to toxicity. To improve the understanding of 8-PN toxicokinetics, a human physiologically based kinetic (PBK) model was extended to include gut microbial 8-PN formation. Respective parameters were obtained from ex vivo fermentations using pooled and individual stool samples to predict average internal exposure while accounting for interindividual differences. This revealed twofold higher internal 8-PN exposure in high metabolizers compared to low metabolizers. Further, we measured estrogenicity of predicted uterus concentrations of 8-PN using alkaline phosphatase assays and found that even in high metabolizers, systemic 8-PN concentrations remain below estrogenicity thresholds. This study broadly demonstrates the applicability of microbiome-competent PBK modeling for quantifying health impacts of gut microbial metabolites. Health sciences/Endocrinology Health sciences/Gastroenterology/Gastrointestinal system/Microbiota Biological sciences/Drug discovery/Toxicology microbial metabolism pharmacokinetics PBK modeling biotransformation hop polyphenols estrogenicity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction The gut microbiome can modify xenobiotics, including dietary compounds, thereby producing metabolites that often exhibit different bioactivities and potentially induce toxicity to the consumer by interaction with various host physiological systems 1 , 2 . However, it is generally recognized that microbiome-mediated metabolism is often insufficiently addressed in current chemical safety assessment 3 . Traditional chemical safety assessment relies on animal testing, which raises ethical concerns, but also requires substantial resources and time, and introduces uncertainty due to species differences in response to chemical exposure, including differences related to microbiome composition. Consequently, there is a shift towards new approach methodologies (NAMs) that combine in vitro and in silico techniques 4 . For toxicokinetics, physiologically based kinetic (PBK) models have emerged as the key tool to predict the systemic fate of chemicals in humans. By integrating the gut microbiome as a metabolic compartment, systemic levels of microbial metabolites can be predicted, and enhance the prediction of bioactivity exerted by xenobiotics that are metabolized by the microbiome and respective gut microbial biotransformation products 5 . To this end, developing and harmonizing methods to assess gastrointestinal transformation kinetics and to incorporate such data in PBK models will ultimately advance our understanding of microbial biotransformation’s impact on human health 5 . Among the bioactivities of microbial metabolites, interactions with human hormone receptors may lead to endocrine disruption and related health effects 6 . For example, prenylated polyphenols naturally abundant in hops can be converted by the gut microbiome to the most potent phytoestrogen known, i.e., 8-prenylnaringenin (8-PN) 7 . Several studies have shown the dual nature of 8-PN, some showing beneficial effects such as alleviating menopausal symptoms or improving bone health, while others describe 8-PN as a potential endocrine disruptor 8 . The main route of exposure to hop polyphenols is through beer and hopped beverages. Additionally, hop supplements are used in alternative medicine practices by women to relieve post-menopausal symptoms 9 . In hops, the phytoestrogen 8-PN is present in low concentrations, while the major hop polyphenols are the chalcone xanthohumol (XN) and the flavonoid isoxanthohumol (iXN) 10 . During the brewing process and also by acidic cyclization in the stomach following ingestion, XN can be converted to iXN, which is the precursor of 8-PN 11 . iXN is further converted to 8-PN by CYP1A2-catalyzed O -demethylation in the liver 12 , but also by Eubacteria limosum and rammulus , resident bacteria in the human gut microbiome (Fig. 1 ) 13 , 14 . This bioactivation could be relevant for host toxicity; however, it remains unknown to what extent the gut microbiome contributes to this metabolic process. We previously predicted systemic levels of iXN and 8-PN in blood and tissues of toxicological concern by developing a PBK model for both compounds, however, not accounting for a potential gut microbial formation of 8-PN 15 . Therefore, in this study, we evaluated the potential role of gut microbial metabolism in endocrine-related toxicity of hop polyphenols by measuring the kinetics of microbial 8-PN formation and then extending the PBK model by integrating the gut microbiome. This included a consideration of interindividual differences in the microbiome’s metabolic capacities. The resulting microbiome-competent PBK model was used to predict uterus tissue concentrations of iXN and 8-PN after beer consumption. These were then compared with estrogenicity data from the in vitro alkaline phosphatase (ALP) assay to quantitatively predict in vivo endocrine disruption for chemical safety assessment. 2. Methods 2.1. Chemicals and reagents Isoxanthohumol (primary reference standard, purity ≥ 90.0%), 8-prenylnaringenin (analytical standard, purity ≥ 95.0%), glycerol, charcoal-stripped fetal bovine serum (FBS), fulvestrant (purity > 98%), 17β-estradiol (purity ≥ 98%), ethyl acetate, 4-nitrophenyl phosphate (purity ≥ 97%), diethanolamine, Triton-X, sodium dodecyl sulfate, dimethylformamide and MTT were purchased from Sigma–Aldrich (Buchs, Switzerland). DMSO was purchased from VWR (Dietikon, Switzerland), and MS-grade water was purchased from Merck-Millipore (Canada). Dulbecco’s Modified Eagle Medium (DMEM), phenol red-free DMEM, FBS, and penicillin/streptomycin were purchased from Gibco, Life Technologies Limited (Paisley, UK). Urolithin A (purity ≥ 95.0%) was purchased from abcr. Acetonitrile, methanol (MS-grade), and formic acid were purchased from Fisher Chemical. Glacial acetic acid and magnesium dichloride were purchased from Merck (Switzerland). MacFarlane media ingredients and corresponding vendors can be found in supplementary information. 2.2. PBK model development and parameterization A PBK model was adapted from a previously published PBK model for hop polyphenols 15 . Briefly, it contains separate compartments for blood, adipose, liver, gut, uterus, and kidney tissue, and the rest of the organs were grouped as slowly perfused tissues (bone, skin, and muscle) and quickly perfused tissues (heart, brain, and lungs). In this study, breast tissue was additionally added as a compartment. The partition coefficient for breast tissue was calculated based on the percentage of adipose tissue in breast tissue. Standard physiological metrics for an average female with a body weight of 60 kg, including relative tissue volumes, blood flow rates, gastrointestinal transit times, and glomerular filtration rate, were used to parameterize the model 16 . Compound-specific physicochemical parameters were also used, derived from LogP and pKa values for iXN and its metabolites, using the QIVIVE toolbox to calculate tissue partition coefficients and unbound plasma fractions 17 . Additionally, the kinetic parameters for the microbial formation of 8-PN were included as described below. Besides the microbial formation of 8-PN, the hepatic conversion of iXN to 8-PN by CYPA12 was included as previously described 15 . To account for variability and uncertainty in the most influential model parameters, Monte Carlo simulations (n = 1000) were performed. Parameter distributions were assigned as normal or log normal, based on physiological relevance. For normal distributions, SD was calculated as \(\:S=\mu\:\times\:CV\) , with CV set to 30% for physiological parameters, 20% for surface areas and patrician coefficients, and 70% for enzyme kinetic parameters based on Kang et al. 18 . For lognormal distributions, log-space variability was defined as \(\:{\sigma\:}_{ln}=\sqrt{\text{l}\text{n}(1+{CV}^{2})}\) , and the SD was computed as \(\:S=\mu\:\times\:\sqrt{{e}_{ln}^{\sigma\:2}-1}\) . Physiological constraints were applied to ensure parameters such as body weight, small intestine surface area, and large intestine surface area remained within biologically plausible ranges. The microbiome-competent PBK model was used to predict the tissue concentrations of iXN and 8-PN upon consuming one beer per day, each with varying iXN and 8-PN content, for seven days. The specific amounts of iXN and 8-PN in the beers used for modeling can be found in the supplementary information (Table 1). Additionally, a sensitivity analysis was performed to assess the physiological parameters influencing the predicted blood concentration of 8-PN. The analysis was performed using parameters either for pooled or individual microbial kinetics of 8-PN formation. To assess the sensitivity, each parameter was increased by 5%, and the normalized sensitivity coefficients (SC) were calculated using the formula by Evans and Andersen 19 : SC=(C′−C) ∕ (P′−P)×P ∕ C , where C and C’ refer to the unchanged or changed blood C max of 8-PN, respectively, P and P’ refer to the unchanged or increased parameter of interest. 2.2. Human stool sample collection and processing Stool samples from 12 individuals were collected following written informed consent and confirmation of inclusion criteria compliance. This study was exempted from review by the Cantonal Ethics Commission of Zurich. Donor criteria included having regular bowel movements ranging from once every three days to three times per day, no chronic inflammatory bowel conditions, no use of immunosuppressants, blood thinners, or medications affecting gut transit/digestion within the month before sample donation, absence of regular intestinal discomfort, and no history of operative intestinal interventions. The sample collection was anonymous, and the researchers were not able to link the sample number with its respective donors. Each donor provided a one-time donation in a container with an AnaeroGen™ bag for the generation of an anaerobic atmosphere. Following the collection, the samples were processed immediately in an anaerobic chamber (5% H 2 , 10% CO 2, and 85% N 2 ). A fecal slurry was prepared by diluting 25% w/v in 15% anaerobic glycerol in PBS. The samples were aliquoted and stored at -80°C until further use. 2.3. Determination of model parameters for microbial metabolism To determine the kinetic parameters V max and K m for the microbial biotransformation of iXN to 8-PN, incubations of fecal slurries with iXN (range: 1–55 µM) were performed in triplicate at 37°C under humified anaerobic conditions. Preliminary assays were performed to identify the correct time points to monitor 8-PN formation (0, 1, 3, 6, 24 h), where 8-PN was only detected at 24 h. Fecal slurries from all 12 donors were pooled and diluted in a 1:1,5 ratio with MacFarlane media, resulting in 10% pooled fecal slurry. The slurries were spiked with iXN dissolved in DMSO (final DMSO concentration was 0.1%) or DMSO as a solvent control. The 24-well plates were incubated for 24 h, and samples were removed at time points 0, 6, and 24 h. After the incubation, urolithin A as an internal standard was added to all wells to use as a control to account for material losses during sample preparation. Subsequently, the samples were extracted by adding ethyl acetate with 0.1% formic acid and centrifuged at 19,083 x g for 10 min at room temperature. Supernatants were collected and completely dried using a miVac SpeedVac and reconstituted in 70% methanol (MS-grade). The samples were stored at -20°C until further use and diluted at 1:10 before analysis. All analyses were performed using an Orbitrap iDX (Thermo Fisher Scientific) LC-MS/MS system. Briefly, analytes were separated on a Phenomenex Synergi™ 4 µm Polar-RP column (80 Å, 30×2 mm). The temperature of the column compartment was maintained at 40°C, while the samples in the autosampler were maintained at 4°C. An injection volume of 5 µL was used. The mobile phase consisted of LC-MS grade water (solvent A) and acetonitrile (solvent B), each containing 0.1% formic acid. The flow was adjusted to 0.4 mL/min with a gradient profile starting at 5% solvent B for the first 3 min, transitioning to 100% solvent B by 4 minutes, and returning to 5% solvent B from 4.1 to 5.5 minutes. The gut microbial metabolism of converting iXN to 8-PN in human stool samples followed Michaelis-Menten kinetics. The concentration-dependent metabolite formation was fitted using GraphPad Prism 10 to the Michaelis-Menten equation: $$\:v={V}_{max}*\left[S\right]t/({K}_{m}+[S\left]\right)$$ The V max was expressed in µmol/h/g of feces and scaled to the whole body based on the contents of the gastrointestinal tract 20 . 2.4. Assessment of 8-PN formation in individual fecal samples To assess the interindividual differences, each fecal sample used in the pooled fecal slurry was assessed individually for the capacity to transform iXN to 8-PN. Briefly, samples were diluted with MacFarlane media in a 1:1,5 ratio and incubated with 10 µM of iXN as a substrate and DMSO as a control for 24 h at 37°C. Thereafter, samples were treated in the same way as the pooled fecal slurry samples and analyzed by LC-MS/MS. Additionally, the results were scaled according to the average amount of 8-PN formed from the four independent anaerobic fermentations with 10 µM of iXN as a substrate. Subsequently, the pooled fecal slurry V max was used to estimate the individual V max of all samples. 2.5. Cell culture Ishikawa cells, a human endometrial adenocarcinoma cell line, were purchased from the European Collection of Authenticated Cell Cultures and cultured in DMEM 10% (v/v) fetal bovine serum and 1% (v/v) penicillin/streptomycin. The cells were incubated at 37°C in a humidified atmosphere (5% CO 2 ). Cells were sub-cultivated twice a week and used for experiments up to passage 32, which maintained logarithmic growth, and results were reproducible. 2.6. Alkaline phosphatase (ALP) assay ALP assays to measure the estrogenicity of iXN and 8-PN were performed as previously described 21 . Briefly, 15’000 Ishikawa cells per well were seeded in 96-well plates and allowed to attach for 24 h. Before exposing the cells to the compounds of interest, DMEM was replaced with phenol red-free DMEM supplemented with 10% (v/v) charcoal-stripped FBS and 1% (v/v) P/S (assay medium). iXN and 8-PN were dissolved in DMSO and further diluted in the assay medium to achieve the desired concentration, keeping the DMSO concentration below or at 0.1%. Cells were then exposed to various concentrations of 8-PN and iXN (or their combinations), the positive control estradiol (E2) at a concentration of 1 nM, or solvent control (DMSO, 0.1%), for 48 h. Additionally, co-incubation with the estrogen receptor antagonist, fulvestrant, was used to confirm that the observed effects were attributed to the test compounds interacting with ER. The cells were then washed three times with PBS and lysed by shock freezing at -80°C. After thawing at room temperature for 5 min, the detection buffer (5 mM 4-nitrophenyl phosphate, 1 M diethanolamine, 0.24 mM magnesium dichloride, pH 9.8) was added and the resulting mixture was allowed to incubate for 10 min. The increase in absorbance caused by the conversion of 4-nitrophenyl phosphate to 4-nitrophenol was measured at 405 nm for 1 h every 3 min using an Infinite Pro M200 Tecan plate reader. The ER-dependent induction of ALP expression was quantified by determining the slope of the dose-response curves obtained and scaling the values to the solvent control (0%) and positive control (100%). 2.7. MTT cell viability assay To confirm that effects observed in the ALP assays were not due to cytotoxicity, cell viability assays were performed. Ishikawa cells were seeded and exposed to the same compounds as was done for the ALP assay described above. As a negative control, 0.1% DMSO was used, and after 48 h, the cells were exposed to 0.1% Triton-X as a positive control. Following 1 h incubation with Triton-X, culture medium was removed, and 0.45 mg/mL MTT solution was added. After 2 h, formazan crystals were dissolved by adding 40% (vol/vol) dimethylformamide, 2% (vol/vol) glacial acetic acid, and 16% (wt/vol) sodium dodecyl sulfate. Absorbance values were then recorded at 570 nm and scaled to the negative control (100%) and the positive control (0%). 2.8. Combination index To assess potential interactions between 8-PN and iXN in estrogenicity, the combination index (CI) was calculated using the Chou-Talalay method 22 . In brief, this method uses the median-effect principle to test for synergistic, additive, or antagonistic interactions by integrating dose-response data from single compounds and their combinations. The normalized ALP activity described above was used to calculate the fraction affected ( \(\:{f}_{a}\) ) where the observed effect was divided by the maximum normalized ALP activity of the positive control. To account for the logarithmic dose-effect relationship, a logarithmic transformation of the dose-response equation was employed to determine the effective doses ( \(\:{D}_{x}\) ​) for each compound, calculated as: \(\:{D}_{x}=\:{10}^{\left(\frac{\text{log}\left(\frac{fa}{fu}\right)-b}{m}\right)}\) where \(\:{f}_{u\:}=1-\:{f}_{a},\:b=-m*\text{l}\text{o}\text{g}\:\left({D}_{m}\right)\) , and \(\:{D}_{m}\) is the median-effect dose. The CI for the fixed-ratio combinations was calculated as: \(\:CI=\frac{{D}_{1}}{{D}_{x}^{\left(1\right)}}+\frac{{D}_{2}}{{D}_{x}^{\left(2\right)}}\:\) where \(\:{D}_{1}\) and \(\:{D}_{2}\) are the doses of 8-PN and iXN in the combination. The \(\:CI\) values were interpreted as follows: \(\:CI1\) indicates antagonism. 2.9. Code availability The underlying PBK model code is available in the supplementary information. To execute the code, copy and paste it into Berkeley Madonna. 3. Results 3.1. Kinetic parameters of 8-PN formation in pooled human stool samples To determine kinetic parameters describing the average formation of 8-PN catalyzed by human gut microbiota, fecal slurries of 12 donors were pooled and incubated with iXN as a substrate. The formation of 8-PN was measured after 24 h of incubation and followed Michaelis-Menten kinetics with V max = 0.0005 µmol/h/g, K m = 30.59 µM, and a derived catalytic efficiency (k cat ) of 0.016 mL/h/g feces calculated as \(\:\text{V}\text{m}\text{a}\text{x}/\text{K}\text{m}\:\) (Fig. 2). 3.2. Inter-individual differences in the ex vivo microbial formation of 8-PN Inter-individual variability regarding the conversion of iXN to 8-PN by microbiota was examined for the 12 individual stool samples. Anaerobic incubations were conducted by diluting the fecal slurries and adding a single concentration of iXN or an equivalent volume of DMSO as the solvent control. Among the 12 donors, only one fecal microbiome failed to convert iXN to 8-PN (sample ID 30, Fig.3). Notably, the highest amount of 8-PN was formed in sample ID 17, followed by sample ID 26, with sample ID 17 producing around 600-fold more 8-PN than other samples. Control samples were also analyzed to confirm the absence of iXN and 8-PN, ensuring that the detected levels did not result from the consumption of beer or hopped beverages. The V max of each sample was extrapolated based on the V max calculated from the 8-PN formation rate in the pooled slurry. 3.3. PBK model-based predictions of 8-PN systemic and tissue levels We introduced gut microbial formation of 8-PN from iXN into a recently published PBK model 15 as a base for predicting systemic and tissue concentrations of iXN and 8-PN for use of a hop dietary supplement or consuming one beer per day for seven consecutive days. The beer consumption scenario was used to predict C max in blood and uterus as organs of toxicological relevance for xenoestrogen activity. Additionally, since iXN and 8-PN co-occur in beer, the PBK model was used to estimate their ratios in the uterus based on consuming high vs. low-hopped beer (supplementary information Table 1). The predicted uterine C max of iXN and 8-PN varied with the hop polyphenol levels present in the beers consumed, with concentrations ranging from 0.004 to 0.192 nM for iXN and from 0.0001 to 0.008 nM for 8-PN. The predicted 8-PN-to-iXN ratios varied depending on the beer type, with a mean ratio of 1:100 for highly hopped beers and 1:50 for low-hopped beers. These ratios were subsequently used to evaluate mixture effects on estrogenic activity in Ishikawa cells using the ALP assay. To investigate the role of inter-individual differences in 8-PN formation, the PBK model was used to predict blood levels of 8-PN resulting from the use of a hop supplement (3.6 mg of iXN and 1 mg of 8-PN) with individual formation rates for the 12 subjects and the rate measured in the pooled fecal slurry. The two highest metabolizers of 8-PN (sample IDs 17 and 26) exhibited elevated 8-PN concentrations in blood compared to all other samples (Fig. 4), with the concentration predicted for sample ID 17 more than doubling relative to the rest. To account for population variation in blood and uterus 8-PN concentration, Monte Carlo simulations of 1000 unique input sets were used to simulate varied outcomes for three different beers with different concentrations of hop polyphenols consumed once daily for 7 days. The simulations revealed substantial variability, with some simulations showing a twofold increase in 8-PN concentration (Fig. 5 ). To evaluate the sensitivity of all individual parameters of the model, sensitivity analysis was performed (Fig.6) using the Vmax derived from pooled fecal slurry fermentations and the individual Vmax for the highest 8-PN producer (sample ID 17). For both conditions, C max in blood was predominantly influenced by logP app values of iXN and 8-PN, body weight, and fraction of blood flow directed to the liver. The primary sensitivity difference between average and high 8-PN producers was observed in parameters related to metabolism. Unlike microbial kinetic parameters derived from the pooled slurry, those from the highest producer exhibited sensitivity, with the sensitivity coefficient being slightly above the threshold of 0.1. 3.5. Predicted 8-PN blood concentrations in the presence and absence of CYP1A2 catalyzed iXN to 8-PN formation To evaluate the contribution of hepatic CYP1A2-mediated conversion of iXN to 8-PN, the PBK model was simulated under conditions with and without CYP1A2 activity. This was performed using three different iXN doses as input, representing scenarios in which iXN was not hepatically converted to 8-PN. In the absence of CYP1A2 activity, the predicted 8-PN concentrations reflect only the microbial metabolism of iXN. The results indicate that hepatic CYP1A2 contributes to a 20-30% increase in 8-PN formation, depending on the iXN dose administered (Fig.7). 3.6. Estrogenicity of iXN and 8-PN as single compounds The estrogenic potential of 8-PN and iXN was evaluated across a concentration range using ALP activity as an indicator of estrogenic activity. Both compounds achieved comparable maximal ALP activity as treatment with 1 nM E2, albeit at higher concentrations, confirming their estrogenicity. While both compounds exhibited similar efficacy, their potencies differed. 8-PN caused a significant increase in ALP activity at much lower concentrations, with an EC 50 of 1.77 nM and a lowest observed effect level (LOEL) of 1 nM (Fig. 7 ). In contrast, both the EC 50 (1045 nM) and the LOEL (500 nM) of iXN were comparably higher, confirming that 8-PN is over 100 times more potent than iXN. 3.7. Estrogenicity of iXN and 8-PN mixtures The microbiome-competent PBK model was utilized to predict 8-PN to iXN concentration ratios in the uterus under high and low-hopped beer dosing scenarios. These ratios (1:50 and 1:100, respectively) were used to assess mixture effects in estrogenicity in ALP assays. Concentration-dependent ER activation was measured for individual compounds (Fig. 8 ) and for combinations of iXN and 8-PN (Fig. 9 ). As thresholds of estrogenicity, in vitro point of departure concentrations were observed at 500 nM for iXN, 1 nM for 8-PN and 1 nM 8-PN within both 1:50 and 1:100 mixtures. To assess combinatory effects that potentially deviate from additive bioactivity, the Chou-Talalay method was used to calculate the combination index, allowing quantitative evaluation of their interactions 22 . For the 1:50 8-PN/iXN mixture, we observed varying interaction patterns across different ALP activity levels. Moderate synergism was observed at a concentration of 1 nM 8-PN with 39.2% ALP activity (CI = 0.751), indicating enhanced efficacy at these concentrations. At concentrations stimulating moderate ALP activity levels (e.g., 47.6–81.2%), the combination exhibited additivity or slight antagonism (1.165 ≤ CI ≤ 1.314). At higher activity levels (e.g., 89.7%), corresponding to 10 nM 8-PN and 500 nM iXN, the interaction shifted to antagonism (CI = 1.509). The highest concentrations of 8-PN and iXN lead to reduced estrogenicity as compared to the maximal effects. Similarly, CI values ranging from 0.7 to 1.4 were calculated for the estrogenicity of the 1:100 iXN/8-PN mixture. At moderate ALP induction levels, a slight synergism was observed, while for the mixture at a concentration of 4 nM 8-PN (65.6% ALP induction), slight antagonism was indicated. The observed antagonism at the lowest dose of the 1:50 mixture is likely due to variability at the lower detection limit of the assay. Across all activity levels and for both 8-PN to iXN ratios, the CI was relatively stable, indicating cumulative to slightly antagonistic effects. While the 1:50 ratio exhibited stronger antagonism at higher activity levels, the 1:100 ratio demonstrated more consistent additivity or mild synergism across the effect range. 4. Discussion In this study, the influence of the gut microbial bioactivation of iXN to 8-PN was characterized. Using microbiome-competent PBK modeling, we predicted blood and tissue concentrations of 8-PN under different dosing scenarios. Subsequently, the estrogenicity of these corresponding levels was evaluated in a cell-based test system. This approach allowed quantitative extrapolation of in vitro estrogenicity to assess the potential for endocrine disruption in humans. Anaerobic ex vivo fermentations are a common means to obtain kinetic parameters for microbiome-competent PBK models 23 , 24 . In this study, 12 fecal slurries were obtained from healthy human donors. Aliquots of each slurry were pooled and then incubated with increasing iXN concentrations to determine the average kinetics of ex vivo 8-PN formation. Using LC-MS/MS analysis, we monitored both the degradation of the parent chemical and the formation of 8-PN over 24 h, resembling average colonic transit times 25 . The efficiency of gastrointestinal 8-PN formation was relatively low in the pooled fecal samples with a k cat of 0.016 mL/h/g, which is far lower compared to the described microbial biotransformation reactions of other polyphenols. For example, the microbial formation of daidzein to S-equol is more efficient with a k cat of 1.24 mL/h/g 20 . Consistent with the low rate of 8-PN formation, it was detected only after 24 h of incubation in the fecal slurry. This further suggests that under the experimental conditions, the transformation could be delayed due to bacterial adaptation time. Due to the highly individual nature of the gut microbiome, it is important to consider interindividual differences in biotransformation capacity 5 . Therefore, we incubated individual stool samples with a single concentration of iXN and found considerable inter-individual variability in 8-PN formation (Fig. 3 ). Among the 12 individual fecal slurries, only one did not yield 8-PN, while two produced very high 8-PN levels reaching up to 3.9 µM within 24 h (Fig. 3 ). In comparison, the pooled fecal samples across replicates yielded 298 nM under the same conditions, indicating a 13-fold variation above average. The sample set represents the expected range of metabolic capacities, consistent with previous classifications of microbiomes into poor, moderate, and strong 8-PN producers 26 , 27 . As recently reviewed by Cortés-Martín et al. , the classification of different metabotypes can be useful to better understand whether dietary polyphenols and their metabolites can have a beneficial effect on the host 28 . However, this concept is difficult to establish for 8-PN since the compound is not only produced by gut bacteria, but also in the human liver, and is already present in dietary products. The microbial composition of the stool samples used in this study was characterized by 16s rRNA amplicon sequencing. The relative abundance of bacterial communities at the phylum level and the Shannon diversity index were assessed in relation to 8-PN production levels, and a PCoA plot was generated to visualize the variance among samples (available in the supplementary information). While Eubacteria limosum and rammulus have been associated with the microbial conversion of 8-PN 13 , 14 , additional unidentified bacteria might play a role in the 8-PN formation. Although the 16s rRNA analysis gives an insight into the microbial composition, the current sequencing resolution limits the precise identification of other involved strains. Metagenomic approaches could potentially be used to identify the specific enzyme and corresponding gene responsible for 8-PN formation. Finally, it remains unclear whether external factors such as lifestyle or age influence microbial metabolism of 8-PN, and analyses addressing these aspects could facilitate personalized risk assessment and targeted intervention strategies. A previously developed PBK model was extended to predict the microbial formation of 8-PN based on metabolic kinetic parameters that were obtained from incubations with pooled fecal slurry. The V max was scaled to gastrointestinal tract contents based on a fecal fraction of human body weight. The model predicted blood and uterus concentrations of 8-PN in the low picomolar range, and therefore, several magnitudes of order lower than concentrations for which estrogenic effects were previously reported 21 , 29 . To account for population variability resulting from model parameters, Monte Carlo simulations were performed, demonstrating that the human variability should be expected to cause interindividual differences of internal concentrations in the range of approximately +/- 100%. To take the inter-individual differences in microbial 8-PN formation into consideration when predicting its concentrations that are achieved systematically and in potential target tissue, the PBK model was individualized by using the apparent V max obtained from the pooled fecal slurry to extrapolate the V max of 8-PN formation in the individual stool samples. Applying these values to the gut compartment, the PBK model was amended to predict the formation of 8-PN in each individual (Fig. 3 ). As expected, the predicted blood concentrations of 8-PN were significantly higher in strong producers, with sample ID 17 virtually exhibiting more than twice the levels compared to the predictions of the PBK model that uses pooled fecal slurry kinetics. Besides the gut microbiome, hepatic CYP1A2 enzymes also convert iXN to 8-PN 12 , 15 . To evaluate the role of the liver, the systemic fate of iXN and 8-PN was simulated with and without CYP1A2-catalyzed conversion (Fig. 7 ). The model predicted a 30% increase in 8-PN blood concentration with CYP1A2, indicating a substantial hepatic contribution to systemic 8-PN levels for moderate microbial 8-PN producers. CYP1A2 activity is modulated by genetic polymorphisms, such as the − 163C > A variant, a single-nucleotide mutation in the promoter region of the gene 30 . This polymorphism increases the inducibility of enzyme expression, particularly in response to stressors such as cigarette smoke, resulting in higher metabolic activity compared to individuals with the wild-type allele 30 . Consequently, individuals carrying this variant may produce elevated levels of 8-PN in combination with certain lifestyle factors. Moreover, the microbial 8-PN high metabolizers who also possess genetic polymorphisms associated with increased CYP1A2 activity may have even higher systemic levels of 8-PN. 8-PN is a potent xenoestrogen, raising concerns about its endocrine activity, particularly in individuals with enhanced microbial and hepatic metabolism. A previous study suggested that dietary beer consumption could induce estrogenic effects in Ishikawa cells 21 . However, the concentrations tested of iXN and 8-PN were not determined based on their toxicokinetics in humans but estimated based on dietary exposure. In this study, we used the microbiome-competent PBK model to quantitatively predict internal exposure to 8-PN. For the selection of concentrations to be tested for in vitro estrogenicity, we focused on the uterus as an organ of toxicological concern due to its high expression of estrogen receptors that can be activated upon xenoestrogen exposure 31 . Under high and low-hopped beer intake scenarios, blood and uterine levels of 8-PN were predicted to be in the low nanomolar range, with tissue partitioning resulting in slightly higher concentrations in the uterus than in blood. A Monte Carlo simulation was performed to account for population variability (Fig. 5 ), demonstrating that predicted maximal exposure levels were twice as high when population variability was considered. These results underscore the substantial influence of interindividual differences on the pharmacokinetics of 8-PN and highlight the need to incorporate population variability in PBK modeling. As iXN and 8-PN co-occur in hopped beverages, the PBK model was used to determine their concentration ratios (8-PN/iXN) of 1:50 and 1:100, reflecting relative exposure in the uterus under high- and low-hopped beer intake scenarios. These ratios were selected to represent physiologically relevant conditions and assess potential combinatory effects on estrogenicity in Ishikawa cells using the ALP assay, a well-established and license-free assay that utilizes the ER-dependent expression of ALP as a natural reporter gene for estrogenicity 32 . Although the low concentrations of iXN that were used with the 1:50 mixture only stimulated none to moderate estrogenicity when applied individually, they were still included to capture potential interactions between the compounds. For single compounds, point of departure (POD) concentrations of 1 nM for 8-PN and 500 nM for iXN were determined. Applying the 1:50 mixture showed synergism at mid-range ALP activity (39.2%, CI = 0.75) but was additive or antagonistic at higher levels (89.7%, CI = 1.51). The 1:100 ratio exhibited consistent additivity with mild synergism (43.9%, CI = 0.74) and reduced antagonism (93.6%, CI = 0.87) (Fig. 9 ). Similar effects were reported at a 1:500 ratio 21 , indicating dose-dependent interactions in ER transactivation. Additionally, the POD for both mixtures is not lower than the POD for 8-PN alone, indicating that the combinatory mixture effects of both compounds are negligible for hazard assessment and the estrogenicity is attributable to 8-PN rather than iXN. The analysis of individual fecal samples suggested the potential for large interindividual differences, on the order of 600-fold, in 8-PN formation from iXN. Significant estrogenic activity of 8-PN and iXN in Ishikawa cells was observed starting from 1 nM and 500 nM, respectively. Even for high microbial producers, the predicted uterus exposure to 8-PN remains below these POD concentrations. Based on this, dietary exposure to iXN and 8-PN associated with typical consumption is unlikely to pose a risk to human health via estrogenic effects. This illustrates the magnitude of variability that can arise from gut microbial bioactivation. Although such variability may be of limited consequence for 8-PN toxicity, it could be highly relevant in causing individual bioactivity of other gut microbial metabolites, especially pharmaceuticals known to undergo microbial metabolism, and thus warrants further investigation. Furthermore, in this study, we observed large interindividual differences in microbial metabolism, demonstrating the importance of PBK models to integrate microbial metabolism to improve the safety assessment of chemicals. Declarations Author contributions Conceptualization: M.S. and G.A., Methodology: M.S. and M.C., Writing original draft: M.S., Reviewing and editing: M.S., M.C., K.B., S.J.S., G.A., Supervision: G.A., K.B., S.J.S. All authors read and approved the final manuscript. Acknowledgments This research was funded by the Swiss Center for Applied Human Toxicology (SCAHT). Open access funding was provided by ETH Zurich. GA was also supported with a fellowship from the Future Food Initiative, a program run by the World Food System Center of ETH Zurich, the Integrative Food and Nutrition Center of EPFL and their industrial partners. The Dutch Ministry of Agriculture, Fisheries, Food Security and Nature (Ministerie van Landbouw, Visserij, Voedselzekerheid en Natuur) is gratefully acknowledged for providing financial support (KB37-002-023). The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript. The authors are grateful to Amrei Rolof for helping with the ex vivo experiments. Data availability The datasets generated and/or analysed during the current study are available from the corresponding author on request. Competing interests The authors declare no competing interests. References Koppel, N., Maini Rekdal, V. & Balskus, E. P. Chemical transformation of xenobiotics by the human gut microbiota. Science 356 , doi:10.1126/science.aag2770 (2017). Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570 , 462-467, doi:10.1038/s41586-019-1291-3 (2019). Ampatzoglou, A., Gruszecka-Kosowska, A. & Aguilera-Gomez, M. Microbiota analysis for risk assessment of xenobiotics: toxicomicrobiomics, incorporating the gut microbiome in the risk assessment of xenobiotics and identifying beneficial components for One Health. EFSA J 20 , e200915, doi:10.2903/j.efsa.2022.e200915 (2022). 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J Agr Food Chem 70 , 343-352, doi:10.1021/acs.jafc.1c03950 (2022). Aichinger, G., Bliem, G. & Marko, D. Systemically achievable doses of beer flavonoids induce estrogenicity in human endometrial cells and cause synergistic effects with selected pesticides. Front Nutr 8 , 691872, doi:10.3389/fnut.2021.691872 (2021). Chou, T. C. Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol Rev 58 , 621-681, doi:10.1124/pr.58.3.10 (2006). Mendez-Catala, D. M., Wang, Q. & Rietjens, I. PBK model-based prediction of intestinal microbial and host metabolism of zearalenone and consequences for its estrogenicity. Mol Nutr Food Res 65 , 2100443, doi:10.1002/mnfr.202100443 (2021). Liu, C., van Mil, J., Noorlander, A. & Rietjens, I. Use of Physiologically Based Kinetic Modeling-Based Reverse Dosimetry to Predict In Vivo Nrf2 Activation by EGCG and Its Colonic Metabolites in Humans. J Agric Food Chem 70 , 14015-14031, doi:10.1021/acs.jafc.2c04811 (2022). Wang, Y. T. et al. Regional gastrointestinal transit and pH studied in 215 healthy volunteers using the wireless motility capsule: influence of age, gender, study country and testing protocol. Aliment Pharmacol Ther 42 , 761-772, doi:10.1111/apt.13329 (2015). Possemiers, S. et al. The prenylflavonoid isoxanthohumol from hops (Humulus lupulus L.) is activated into the potent phytoestrogen 8-prenylnaringenin in vitro and in the human intestine. J Nutr 136 , 1862-1867, doi:10.1093/jn/136.7.1862 (2006). Bolca, S. et al. Microbial and dietary factors associated with the 8-prenylnaringenin producer phenotype: a dietary intervention trial with fifty healthy post-menopausal Caucasian women. Br J Nutr 98 , 950-959, doi:10.1017/S0007114507749243 (2007). Cortes-Martin, A., Selma, M. V., Tomas-Barberan, F. A., Gonzalez-Sarrias, A. & Espin, J. C. Where to Look into the Puzzle of Polyphenols and Health? The Postbiotics and Gut Microbiota Associated with Human Metabotypes. Mol Nutr Food Res 64 , e1900952, doi:10.1002/mnfr.201900952 (2020). Milligan S, K. J., Pocock V, Heyerick A, De Cooman L, Rong H, De Keukeleire D. . Oestrogenic activity of the hop phyto-oestrogen, 8-prenylnaringenin. Reproduction-cambridge 123 , 235-242, doi:10.1530/rep.0.1230235 (2002). Koonrungsesomboon, N., Khatsri, R., Wongchompoo, P. & Teekachunhatean, S. The impact of genetic polymorphisms on CYP1A2 activity in humans: a systematic review and meta-analysis. Pharmacogenomics J 18 , 760-768, doi:10.1038/s41397-017-0011-3 (2018). Mylonas, I. et al. Immunohistochemical analysis of estrogen receptor alpha, estrogen receptor beta and progesterone receptor in normal human endometrium. Acta Histochem 106 , 245-252, doi:10.1016/j.acthis.2004.02.005 (2004). Holinka CF, H. M., Finch CE. The Response to a Single Dose of Estradiol in the Uterus of Ovariectomized C57BL/6J Mice During Aging Biol Reprod 17 , 262-264, doi:10.1095/biolreprod17.2.262 (1977). Additional Declarations No competing interests reported. Supplementary Files SupplementaryPBKmodelcoderefastext.docx Supplementary.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6511068","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":446833617,"identity":"b35ea5cd-a5f6-473d-8a89-d03b44e67b5d","order_by":0,"name":"Maja Stevanoska","email":"","orcid":"","institution":"ETH Zurich","correspondingAuthor":false,"prefix":"","firstName":"Maja","middleName":"","lastName":"Stevanoska","suffix":""},{"id":446833618,"identity":"76802294-da2b-416a-ace1-86de859eb1d7","order_by":1,"name":"Michelle Cremona","email":"","orcid":"","institution":"ETH Zurich","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"","lastName":"Cremona","suffix":""},{"id":446833619,"identity":"679cae24-813d-4465-a57e-e126f1877c80","order_by":2,"name":"Karsten Beekmann","email":"","orcid":"","institution":"Wageningen Food Safety Research (WFSR)","correspondingAuthor":false,"prefix":"","firstName":"Karsten","middleName":"","lastName":"Beekmann","suffix":""},{"id":446833620,"identity":"4a6c7c4a-6cd4-4203-94ab-f324d5f7d2e8","order_by":3,"name":"Shana J. Sturla","email":"","orcid":"","institution":"ETH Zurich","correspondingAuthor":false,"prefix":"","firstName":"Shana","middleName":"J.","lastName":"Sturla","suffix":""},{"id":446833621,"identity":"d07387c4-3683-4229-9ae7-12375996e3ed","order_by":4,"name":"Georg Aichinger","email":"data:image/png;base64,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","orcid":"","institution":"ETH Zurich","correspondingAuthor":true,"prefix":"","firstName":"Georg","middleName":"","lastName":"Aichinger","suffix":""}],"badges":[],"createdAt":"2025-04-23 09:23:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6511068/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6511068/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81624314,"identity":"ea80ccf0-3c8b-494f-a8a3-07b46ddd5084","added_by":"auto","created_at":"2025-04-29 09:55:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":230921,"visible":true,"origin":"","legend":"\u003cp\u003eIsoxanthohumol (iXN) is biotransformed into 8-prenylnaringenin (8-PN) via the hepatic CYP1A2 enzyme and by the gut microbial strains Eubacteria limosum and rammulus.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/2be199b29966b7f47d0884d3.png"},{"id":81623342,"identity":"3d614ef5-9c98-4074-b139-885769e94f3f","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63006,"visible":true,"origin":"","legend":"\u003cp\u003eKinetic analysis of microbial 8-PN formation from iXN as a substrate in pooled fecal slurries under anaerobic conditions. The relationship of iXN concentration (x-axis) with 8-PN formation rate (y-axis) is depicted with Michaelis-Menten curve fitting. Data are represented as mean±SD of at least three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/84fd18fe673e15c272ab8011.png"},{"id":81623347,"identity":"aaef3f08-c9f8-4886-9c0f-033249d46bd1","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103885,"visible":true,"origin":"","legend":"\u003cp\u003eInterindividual differences in the formation of 8-PN after anaerobic incubations of individual human stool samples with 10 µM iXN for 24 h, shown for 12 individuals. Data is represented as mean±SD of three replicates.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/a17c6a0d4433f781b10f3612.png"},{"id":81625742,"identity":"c655f656-2321-4367-97d6-2acad5c1c6af","added_by":"auto","created_at":"2025-04-29 10:11:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":59029,"visible":true,"origin":"","legend":"\u003cp\u003eCurves representing predicted blood concentrations of 8-PN after supplementation with a hop supplement containing 3.2 mg iXN and 1 mg 8-PN. The model was run with different V\u003csub\u003emax\u003c/sub\u003e values based either on pooled fecal slurry incubations or on estimated individual V\u003csub\u003emax \u003c/sub\u003ebased on the fecal slurry prediction. The various color lines represent the formation rate of 8-PN in different individuals, and the black line represents the formation rate of 8-PN in the pooled fecal slurry.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/4ebfdbd4405f1db10b4bf351.png"},{"id":81623349,"identity":"a18a1e70-3615-4837-b387-2ab3cfe389c3","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110296,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted levels of 8-PN in blood and uterus after administering three different beers, once daily for 7 days. The solid lines represent the model predictions, while the shaded grey area represents the Monte Carlo simulation outcomes (n=1000) as mean± SD.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/a2b303b2dcf3b7f1a53fcd05.png"},{"id":81623355,"identity":"c6407277-4e85-4e7f-a176-28453d3fcd70","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":212075,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity of model parameters (A. based on pooled V\u003csub\u003emax\u003c/sub\u003e, B. based on the V\u003csub\u003emax\u003c/sub\u003e of the highest 8-PN producer), shown as normalized sensitivity coefficients that were calculated in changes of blood Cmax caused by a 5% increase of the respective parameters. Paratmeters with an absolute SC\u0026gt;0.1 are shown and they are abbreviated as : BW, bodyweight; VLc, relative liver tissue volume; VSc, relative slowly perfused tissues volume; VSI, volume of the small intestinal lumen; VLI, volume of the large intestinal lumen; QC, cardiac output; QGc, fraction of blood flow to gut; QPc fraction of blood flow to portal vein perfused tissues; QLAc, fraction of blood flow to liver via artery; QLc, total fraction of blood to liver; QFc, fraction of blood flow to fat;\u0026nbsp; areaSI, surface area of the small intestinal lumen; areaLI surface area of large intestinal lumen; logPappIXN, logarithm of the permeability coefficient across the intestinal barrier of iXN; logPapp8PN, logarithm of the permeability coefficient across the intestinal barrier of 8-PN; VLS9, scaling factor for S9 protein to liver tissue; VmaxL8PN, maximal velocity of hepatic 8-PN glucuronidation; KmL8PN, affinity constant for hepatic 8-PN glucuronidation VmaxM8PN, maximal velocity of microbial 8-PN formation; KmM8PN, affinity constant for microbial 8-PN formation; VMB, scaling to gastrointestinal tract contents.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/e0410c4c81c958dffe6d64ba.png"},{"id":81623352,"identity":"3fc6fb59-23be-413e-b42d-396cbb9efa15","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110650,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted blood levels of 8-PN upon three administered doses of iXN. The solid lines represent the hepatic CYP1A2-catalyzed and microbial conversion of iXN to 8-PN, while the dashed lines depict simulations in which CYP1A2-mediated conversion of iXN to 8-PN was not considered.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/07b82b37c07738e2fdb4471e.png"},{"id":81624692,"identity":"b3410ba4-354c-4c07-aae1-e84d4bb707e7","added_by":"auto","created_at":"2025-04-29 10:03:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":51153,"visible":true,"origin":"","legend":"\u003cp\u003eInduction of ALP expression by the hop polyphenols 8-PN and iXN. Values were scaled to the solvent control (0%; 0.1 % DMSO) and the positive control (100%; 1 nM E2) and are expressed as means ± SD of at least 4 independent experiments. Significant differences from the no-effect level were calculated by one-way ANOVA using Dunnett’s multiple comparisons and are labeled with * (p\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/77f78099ba0e50f5e1abf70a.png"},{"id":81624694,"identity":"1a6c2207-556c-47fa-aa58-770c2c1ef9c9","added_by":"auto","created_at":"2025-04-29 10:03:28","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":121359,"visible":true,"origin":"","legend":"\u003cp\u003eEstrogen receptor-dependent induction of ALP expression by iXN, 8-PN or a mix of both at 1:50 (A) and 1:100 (C), showing the ALP activity scaled to the positive (1 nM E2) and negative (0.1% DMSO) control. The data is expressed as mean ± SD of four independent experiments. Graphs (B) and (D) show the calculated CI values based on the measured data points. Significant differences from the no-effect level were calculated by one-way ANOVA using Dunnett’s multiple comparisons and are labeled with * (p\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/6367f29b2c314dc95b828c62.png"},{"id":84892561,"identity":"e4595c1b-3fd3-48ef-9be7-02e9c6d9c65c","added_by":"auto","created_at":"2025-06-18 13:08:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1930712,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/e053e93a-8e9a-4115-82d8-c49d6e009d60.pdf"},{"id":81624309,"identity":"1cb62c24-c0ae-4bf6-a7c3-ffed30ee6a27","added_by":"auto","created_at":"2025-04-29 09:55:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":37264,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryPBKmodelcoderefastext.docx","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/507b1ea732029158a41c8d32.docx"},{"id":81623350,"identity":"957ca6ee-9401-4170-8fa9-66fd08bf5981","added_by":"auto","created_at":"2025-04-29 09:47:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":204786,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6511068/v1/5960766c9949eaa0b029695a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Interindividual variation in gut microbial formation of 8-prenylnaringenin results in increased, but sub-estrogenic, internal exposure","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe gut microbiome can modify xenobiotics, including dietary compounds, thereby producing metabolites that often exhibit different bioactivities and potentially induce toxicity to the consumer by interaction with various host physiological systems \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. However, it is generally recognized that microbiome-mediated metabolism is often insufficiently addressed in current chemical safety assessment \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Traditional chemical safety assessment relies on animal testing, which raises ethical concerns, but also requires substantial resources and time, and introduces uncertainty due to species differences in response to chemical exposure, including differences related to microbiome composition. Consequently, there is a shift towards new approach methodologies (NAMs) that combine \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein silico\u003c/em\u003e techniques \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. For toxicokinetics, physiologically based kinetic (PBK) models have emerged as the key tool to predict the systemic fate of chemicals in humans. By integrating the gut microbiome as a metabolic compartment, systemic levels of microbial metabolites can be predicted, and enhance the prediction of bioactivity exerted by xenobiotics that are metabolized by the microbiome and respective gut microbial biotransformation products\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. To this end, developing and harmonizing methods to assess gastrointestinal transformation kinetics and to incorporate such data in PBK models will ultimately advance our understanding of microbial biotransformation\u0026rsquo;s impact on human health \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the bioactivities of microbial metabolites, interactions with human hormone receptors may lead to endocrine disruption and related health effects \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. For example, prenylated polyphenols naturally abundant in hops can be converted by the gut microbiome to the most potent phytoestrogen known, i.e., 8-prenylnaringenin (8-PN)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Several studies have shown the dual nature of 8-PN, some showing beneficial effects such as alleviating menopausal symptoms or improving bone health, while others describe 8-PN as a potential endocrine disruptor \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The main route of exposure to hop polyphenols is through beer and hopped beverages. Additionally, hop supplements are used in alternative medicine practices by women to relieve post-menopausal symptoms \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In hops, the phytoestrogen 8-PN is present in low concentrations, while the major hop polyphenols are the chalcone xanthohumol (XN) and the flavonoid isoxanthohumol (iXN) \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. During the brewing process and also by acidic cyclization in the stomach following ingestion, XN can be converted to iXN, which is the precursor of 8-PN \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. iXN is further converted to 8-PN by CYP1A2-catalyzed \u003cem\u003eO\u003c/em\u003e-demethylation in the liver \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, but also by Eubacteria \u003cem\u003elimosum\u003c/em\u003e and \u003cem\u003erammulus\u003c/em\u003e, resident bacteria in the human gut microbiome (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. This bioactivation could be relevant for host toxicity; however, it remains unknown to what extent the gut microbiome contributes to this metabolic process.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe previously predicted systemic levels of iXN and 8-PN in blood and tissues of toxicological concern by developing a PBK model for both compounds, however, not accounting for a potential gut microbial formation of 8-PN \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Therefore, in this study, we evaluated the potential role of gut microbial metabolism in endocrine-related toxicity of hop polyphenols by measuring the kinetics of microbial 8-PN formation and then extending the PBK model by integrating the gut microbiome. This included a consideration of interindividual differences in the microbiome\u0026rsquo;s metabolic capacities. The resulting microbiome-competent PBK model was used to predict uterus tissue concentrations of iXN and 8-PN after beer consumption. These were then compared with estrogenicity data from the \u003cem\u003ein vitro\u003c/em\u003e alkaline phosphatase (ALP) assay to quantitatively predict \u003cem\u003ein vivo\u003c/em\u003e endocrine disruption for chemical safety assessment.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemicals and reagents\u003c/h2\u003e \u003cp\u003eIsoxanthohumol (primary reference standard, purity\u0026thinsp;\u0026ge;\u0026thinsp;90.0%), 8-prenylnaringenin (analytical standard, purity\u0026thinsp;\u0026ge;\u0026thinsp;95.0%), glycerol, charcoal-stripped fetal bovine serum (FBS), fulvestrant (purity\u0026thinsp;\u0026gt;\u0026thinsp;98%), 17β-estradiol (purity\u0026thinsp;\u0026ge;\u0026thinsp;98%), ethyl acetate, 4-nitrophenyl phosphate (purity\u0026thinsp;\u0026ge;\u0026thinsp;97%), diethanolamine, Triton-X, sodium dodecyl sulfate, dimethylformamide and MTT were purchased from Sigma\u0026ndash;Aldrich (Buchs, Switzerland). DMSO was purchased from VWR (Dietikon, Switzerland), and MS-grade water was purchased from Merck-Millipore (Canada). Dulbecco\u0026rsquo;s Modified Eagle Medium (DMEM), phenol red-free DMEM, FBS, and penicillin/streptomycin were purchased from Gibco, Life Technologies Limited (Paisley, UK). Urolithin A (purity\u0026thinsp;\u0026ge;\u0026thinsp;95.0%) was purchased from abcr. Acetonitrile, methanol (MS-grade), and formic acid were purchased from Fisher Chemical. Glacial acetic acid and magnesium dichloride were purchased from Merck (Switzerland). MacFarlane media ingredients and corresponding vendors can be found in supplementary information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. PBK model development and parameterization\u003c/h2\u003e \u003cp\u003eA PBK model was adapted from a previously published PBK model for hop polyphenols \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Briefly, it contains separate compartments for blood, adipose, liver, gut, uterus, and kidney tissue, and the rest of the organs were grouped as slowly perfused tissues (bone, skin, and muscle) and quickly perfused tissues (heart, brain, and lungs). In this study, breast tissue was additionally added as a compartment. The partition coefficient for breast tissue was calculated based on the percentage of adipose tissue in breast tissue. Standard physiological metrics for an average female with a body weight of 60 kg, including relative tissue volumes, blood flow rates, gastrointestinal transit times, and glomerular filtration rate, were used to parameterize the model \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Compound-specific physicochemical parameters were also used, derived from LogP and pKa values for iXN and its metabolites, using the QIVIVE toolbox to calculate tissue partition coefficients and unbound plasma fractions \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Additionally, the kinetic parameters for the microbial formation of 8-PN were included as described below. Besides the microbial formation of 8-PN, the hepatic conversion of iXN to 8-PN by CYPA12 was included as previously described \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. To account for variability and uncertainty in the most influential model parameters, Monte Carlo simulations (n\u0026thinsp;=\u0026thinsp;1000) were performed. Parameter distributions were assigned as normal or log normal, based on physiological relevance. For normal distributions, SD was calculated as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:S=\\mu\\:\\times\\:CV\\)\u003c/span\u003e\u003c/span\u003e, with CV set to 30% for physiological parameters, 20% for surface areas and patrician coefficients, and 70% for enzyme kinetic parameters based on Kang \u003cem\u003eet al.\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. For lognormal distributions, log-space variability was defined as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{ln}=\\sqrt{\\text{l}\\text{n}(1+{CV}^{2})}\\)\u003c/span\u003e\u003c/span\u003e, and the SD was computed as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:S=\\mu\\:\\times\\:\\sqrt{{e}_{ln}^{\\sigma\\:2}-1}\\)\u003c/span\u003e\u003c/span\u003e. Physiological constraints were applied to ensure parameters such as body weight, small intestine surface area, and large intestine surface area remained within biologically plausible ranges. The microbiome-competent PBK model was used to predict the tissue concentrations of iXN and 8-PN upon consuming one beer per day, each with varying iXN and 8-PN content, for seven days. The specific amounts of iXN and 8-PN in the beers used for modeling can be found in the supplementary information (Table\u0026nbsp;1). Additionally, a sensitivity analysis was performed to assess the physiological parameters influencing the predicted blood concentration of 8-PN. The analysis was performed using parameters either for pooled or individual microbial kinetics of 8-PN formation. To assess the sensitivity, each parameter was increased by 5%, and the normalized sensitivity coefficients (SC) were calculated using the formula by Evans and Andersen \u003csup\u003e19\u003c/sup\u003e: \u003cem\u003eSC=(C\u0026prime;\u0026minus;C) ∕ (P\u0026prime;\u0026minus;P)\u0026times;P ∕ C\u003c/em\u003e, where C and C\u0026rsquo; refer to the unchanged or changed blood C\u003csub\u003emax\u003c/sub\u003e of 8-PN, respectively, P and P\u0026rsquo; refer to the unchanged or increased parameter of interest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Human stool sample collection and processing\u003c/h2\u003e \u003cp\u003eStool samples from 12 individuals were collected following written informed consent and confirmation of inclusion criteria compliance. This study was exempted from review by the Cantonal Ethics Commission of Zurich. Donor criteria included having regular bowel movements ranging from once every three days to three times per day, no chronic inflammatory bowel conditions, no use of immunosuppressants, blood thinners, or medications affecting gut transit/digestion within the month before sample donation, absence of regular intestinal discomfort, and no history of operative intestinal interventions. The sample collection was anonymous, and the researchers were not able to link the sample number with its respective donors. Each donor provided a one-time donation in a container with an AnaeroGen\u0026trade; bag for the generation of an anaerobic atmosphere. Following the collection, the samples were processed immediately in an anaerobic chamber (5% H\u003csub\u003e2\u003c/sub\u003e, 10% CO\u003csub\u003e2,\u003c/sub\u003e and 85% N\u003csub\u003e2\u003c/sub\u003e). A fecal slurry was prepared by diluting 25% w/v in 15% anaerobic glycerol in PBS. The samples were aliquoted and stored at -80\u0026deg;C until further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Determination of model parameters for microbial metabolism\u003c/h2\u003e \u003cp\u003eTo determine the kinetic parameters V\u003csub\u003emax\u003c/sub\u003e and K\u003csub\u003em\u003c/sub\u003e for the microbial biotransformation of iXN to 8-PN, incubations of fecal slurries with iXN (range: 1\u0026ndash;55 \u0026micro;M) were performed in triplicate at 37\u0026deg;C under humified anaerobic conditions. Preliminary assays were performed to identify the correct time points to monitor 8-PN formation (0, 1, 3, 6, 24 h), where 8-PN was only detected at 24 h. Fecal slurries from all 12 donors were pooled and diluted in a 1:1,5 ratio with MacFarlane media, resulting in 10% pooled fecal slurry. The slurries were spiked with iXN dissolved in DMSO (final DMSO concentration was 0.1%) or DMSO as a solvent control. The 24-well plates were incubated for 24 h, and samples were removed at time points 0, 6, and 24 h. After the incubation, urolithin A as an internal standard was added to all wells to use as a control to account for material losses during sample preparation. Subsequently, the samples were extracted by adding ethyl acetate with 0.1% formic acid and centrifuged at 19,083 x g for 10 min at room temperature. Supernatants were collected and completely dried using a miVac SpeedVac and reconstituted in 70% methanol (MS-grade). The samples were stored at -20\u0026deg;C until further use and diluted at 1:10 before analysis. All analyses were performed using an Orbitrap iDX (Thermo Fisher Scientific) LC-MS/MS system. Briefly, analytes were separated on a Phenomenex Synergi\u0026trade; 4 \u0026micro;m Polar-RP column (80 \u0026Aring;, 30\u0026times;2 mm). The temperature of the column compartment was maintained at 40\u0026deg;C, while the samples in the autosampler were maintained at 4\u0026deg;C. An injection volume of 5 \u0026micro;L was used. The mobile phase consisted of LC-MS grade water (solvent A) and acetonitrile (solvent B), each containing 0.1% formic acid. The flow was adjusted to 0.4 mL/min with a gradient profile starting at 5% solvent B for the first 3 min, transitioning to 100% solvent B by 4 minutes, and returning to 5% solvent B from 4.1 to 5.5 minutes. The gut microbial metabolism of converting iXN to 8-PN in human stool samples followed Michaelis-Menten kinetics. The concentration-dependent metabolite formation was fitted using GraphPad Prism 10 to the Michaelis-Menten equation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:v={V}_{max}*\\left[S\\right]t/({K}_{m}+[S\\left]\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe V\u003csub\u003emax\u003c/sub\u003e was expressed in \u0026micro;mol/h/g of feces and scaled to the whole body based on the contents of the gastrointestinal tract \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Assessment of 8-PN formation in individual fecal samples\u003c/h2\u003e \u003cp\u003eTo assess the interindividual differences, each fecal sample used in the pooled fecal slurry was assessed individually for the capacity to transform iXN to 8-PN. Briefly, samples were diluted with MacFarlane media in a 1:1,5 ratio and incubated with 10 \u0026micro;M of iXN as a substrate and DMSO as a control for 24 h at 37\u0026deg;C. Thereafter, samples were treated in the same way as the pooled fecal slurry samples and analyzed by LC-MS/MS. Additionally, the results were scaled according to the average amount of 8-PN formed from the four independent anaerobic fermentations with 10 \u0026micro;M of iXN as a substrate. Subsequently, the pooled fecal slurry V\u003csub\u003emax\u003c/sub\u003e was used to estimate the individual V\u003csub\u003emax\u003c/sub\u003e of all samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Cell culture\u003c/h2\u003e \u003cp\u003eIshikawa cells, a human endometrial adenocarcinoma cell line, were purchased from the European Collection of Authenticated Cell Cultures and cultured in DMEM 10% (v/v) fetal bovine serum and 1% (v/v) penicillin/streptomycin. The cells were incubated at 37\u0026deg;C in a humidified atmosphere (5% CO\u003csub\u003e2\u003c/sub\u003e). Cells were sub-cultivated twice a week and used for experiments up to passage 32, which maintained logarithmic growth, and results were reproducible.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Alkaline phosphatase (ALP) assay\u003c/h2\u003e \u003cp\u003eALP assays to measure the estrogenicity of iXN and 8-PN were performed as previously described \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Briefly, 15\u0026rsquo;000 Ishikawa cells per well were seeded in 96-well plates and allowed to attach for 24 h. Before exposing the cells to the compounds of interest, DMEM was replaced with phenol red-free DMEM supplemented with 10% (v/v) charcoal-stripped FBS and 1% (v/v) P/S (assay medium). iXN and 8-PN were dissolved in DMSO and further diluted in the assay medium to achieve the desired concentration, keeping the DMSO concentration below or at 0.1%. Cells were then exposed to various concentrations of 8-PN and iXN (or their combinations), the positive control estradiol (E2) at a concentration of 1 nM, or solvent control (DMSO, 0.1%), for 48 h. Additionally, co-incubation with the estrogen receptor antagonist, fulvestrant, was used to confirm that the observed effects were attributed to the test compounds interacting with ER. The cells were then washed three times with PBS and lysed by shock freezing at -80\u0026deg;C. After thawing at room temperature for 5 min, the detection buffer (5 mM 4-nitrophenyl phosphate, 1 M diethanolamine, 0.24 mM magnesium dichloride, pH 9.8) was added and the resulting mixture was allowed to incubate for 10 min. The increase in absorbance caused by the conversion of 4-nitrophenyl phosphate to 4-nitrophenol was measured at 405 nm for 1 h every 3 min using an Infinite Pro M200 Tecan plate reader. The ER-dependent induction of ALP expression was quantified by determining the slope of the dose-response curves obtained and scaling the values to the solvent control (0%) and positive control (100%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.7. MTT cell viability assay\u003c/h2\u003e \u003cp\u003eTo confirm that effects observed in the ALP assays were not due to cytotoxicity, cell viability assays were performed. Ishikawa cells were seeded and exposed to the same compounds as was done for the ALP assay described above. As a negative control, 0.1% DMSO was used, and after 48 h, the cells were exposed to 0.1% Triton-X as a positive control. Following 1 h incubation with Triton-X, culture medium was removed, and 0.45 mg/mL MTT solution was added. After 2 h, formazan crystals were dissolved by adding 40% (vol/vol) dimethylformamide, 2% (vol/vol) glacial acetic acid, and 16% (wt/vol) sodium dodecyl sulfate. Absorbance values were then recorded at 570 nm and scaled to the negative control (100%) and the positive control (0%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Combination index\u003c/h2\u003e \u003cp\u003eTo assess potential interactions between 8-PN and iXN in estrogenicity, the combination index (CI) was calculated using the Chou-Talalay method \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In brief, this method uses the median-effect principle to test for synergistic, additive, or antagonistic interactions by integrating dose-response data from single compounds and their combinations. The normalized ALP activity described above was used to calculate the fraction affected (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{a}\\)\u003c/span\u003e\u003c/span\u003e) where the observed effect was divided by the maximum normalized ALP activity of the positive control. To account for the logarithmic dose-effect relationship, a logarithmic transformation of the dose-response equation was employed to determine the effective doses (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{x}\\)\u003c/span\u003e\u003c/span\u003e​) for each compound, calculated as: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{x}=\\:{10}^{\\left(\\frac{\\text{log}\\left(\\frac{fa}{fu}\\right)-b}{m}\\right)}\\)\u003c/span\u003e\u003c/span\u003e where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{u\\:}=1-\\:{f}_{a},\\:b=-m*\\text{l}\\text{o}\\text{g}\\:\\left({D}_{m}\\right)\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{m}\\)\u003c/span\u003e\u003c/span\u003e is the median-effect dose. The CI for the fixed-ratio combinations was calculated as: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CI=\\frac{{D}_{1}}{{D}_{x}^{\\left(1\\right)}}+\\frac{{D}_{2}}{{D}_{x}^{\\left(2\\right)}}\\:\\)\u003c/span\u003e\u003c/span\u003e where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{1}\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{2}\\)\u003c/span\u003e\u003c/span\u003e are the doses of 8-PN and iXN in the combination. The \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CI\\)\u003c/span\u003e\u003c/span\u003e values were interpreted as follows: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CI\u0026lt;1\\)\u003c/span\u003e\u003c/span\u003e indicates synergism, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CI=1\\)\u003c/span\u003e\u003c/span\u003e indicates additivity and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CI\u0026gt;1\\)\u003c/span\u003e\u003c/span\u003e indicates antagonism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Code availability\u003c/h2\u003e \u003cp\u003eThe underlying PBK model code is available in the supplementary information. To execute the code, copy and paste it into Berkeley Madonna.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Kinetic parameters of 8-PN formation in pooled human stool samples\u003c/h2\u003e\n \u003cp\u003eTo determine kinetic parameters describing the average formation of 8-PN catalyzed by human gut microbiota, fecal slurries of 12 donors were pooled and incubated with iXN as a substrate. The formation of 8-PN was measured after 24 h of incubation and followed Michaelis-Menten kinetics with V\u003csub\u003emax\u003c/sub\u003e = 0.0005 \u0026micro;mol/h/g, K\u003csub\u003em\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;30.59 \u0026micro;M, and a derived catalytic efficiency (k\u003csub\u003ecat\u003c/sub\u003e) of 0.016 mL/h/g feces calculated as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{V}\\text{m}\\text{a}\\text{x}/\\text{K}\\text{m}\\:\\)\u003c/span\u003e\u003c/span\u003e(Fig. 2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Inter-individual differences in the \u003cem\u003eex vivo\u003c/em\u003e microbial formation of 8-PN\u003c/h2\u003e\n \u003cp\u003eInter-individual variability regarding the conversion of iXN to 8-PN by microbiota was examined for the 12 individual stool samples. Anaerobic incubations were conducted by diluting the fecal slurries and adding a single concentration of iXN or an equivalent volume of DMSO as the solvent control. Among the 12 donors, only one fecal microbiome failed to convert iXN to 8-PN (sample ID 30, Fig.3). Notably, the highest amount of 8-PN was formed in sample ID 17, followed by sample ID 26, with sample ID 17 producing around 600-fold more 8-PN than other samples. Control samples were also analyzed to confirm the absence of iXN and 8-PN, ensuring that the detected levels did not result from the consumption of beer or hopped beverages. The V\u003csub\u003emax\u0026nbsp;\u003c/sub\u003eof each sample was extrapolated based on the V\u003csub\u003emax\u0026nbsp;\u003c/sub\u003ecalculated from the 8-PN formation rate in the pooled slurry.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. PBK model-based predictions of 8-PN systemic and tissue levels\u003c/h2\u003e\n \u003cp\u003eWe introduced gut microbial formation of 8-PN from iXN into a recently published PBK model \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e as a base for predicting systemic and tissue concentrations of iXN and 8-PN for use of a hop dietary supplement or consuming one beer per day for seven consecutive days. The beer consumption scenario was used to predict C\u003csub\u003emax\u003c/sub\u003e in blood and uterus as organs of toxicological relevance for xenoestrogen activity. Additionally, since iXN and 8-PN co-occur in beer, the PBK model was used to estimate their ratios in the uterus based on consuming high vs. low-hopped beer (supplementary information Table 1). The predicted uterine C\u003csub\u003emax\u003c/sub\u003e of iXN and 8-PN varied with the hop polyphenol levels present in the beers consumed, with concentrations ranging from 0.004 to 0.192 nM for iXN and from 0.0001 to 0.008 nM for 8-PN. The predicted 8-PN-to-iXN ratios varied depending on the beer type, with a mean ratio of 1:100 for highly hopped beers and 1:50 for low-hopped beers. These ratios were subsequently used to evaluate mixture effects on estrogenic activity in Ishikawa cells using the ALP assay.\u003c/p\u003e\n \u003cp\u003eTo investigate the role of inter-individual differences in 8-PN formation, the PBK model was used to predict blood levels of 8-PN resulting from the use of a hop supplement (3.6 mg of iXN and 1 mg of 8-PN) with individual formation rates for the 12 subjects and the rate measured in the pooled fecal slurry. The two highest metabolizers of 8-PN (sample IDs 17 and 26) exhibited elevated 8-PN concentrations in blood compared to all other samples (Fig. 4), with the concentration predicted for sample ID 17 more than doubling relative to the rest.\u003c/p\u003e\n \u003cp\u003eTo account for population variation in blood and uterus 8-PN concentration, Monte Carlo simulations of 1000 unique input sets were used to simulate varied outcomes for three different beers with different concentrations of hop polyphenols consumed once daily for 7 days. The simulations revealed substantial variability, with some simulations showing a twofold increase in 8-PN concentration (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eTo evaluate the sensitivity of all individual parameters of the model, sensitivity analysis was performed (Fig.6) using the Vmax derived from pooled fecal slurry fermentations and the individual Vmax for the highest 8-PN producer (sample ID 17).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFor both conditions, C\u003csub\u003emax\u003c/sub\u003e in blood was predominantly influenced by logP\u003csub\u003eapp\u003c/sub\u003e values of iXN and 8-PN, body weight, and fraction of blood flow directed to the liver. The primary sensitivity difference between average and high 8-PN producers was observed in parameters related to metabolism. Unlike microbial kinetic parameters derived from the pooled slurry, those from the highest producer exhibited sensitivity, with the sensitivity coefficient being slightly above the threshold of 0.1.\u003c/p\u003e\n \u003cp\u003e3.5. Predicted 8-PN blood concentrations in the presence and absence of CYP1A2 catalyzed iXN to 8-PN formation\u003c/p\u003e\n \u003cp\u003eTo evaluate the contribution of hepatic CYP1A2-mediated conversion of iXN to 8-PN, the PBK model was simulated under conditions with and without CYP1A2 activity. This was performed using three different iXN doses as input, representing scenarios in which iXN was not hepatically converted to 8-PN. In the absence of CYP1A2 activity, the predicted 8-PN concentrations reflect only the microbial metabolism of iXN. The results indicate that hepatic CYP1A2 contributes to a 20-30% increase in 8-PN formation, depending on the iXN dose administered (Fig.7).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6. Estrogenicity of iXN and 8-PN as single compounds\u003c/h2\u003e\n \u003cp\u003eThe estrogenic potential of 8-PN and iXN was evaluated across a concentration range using ALP activity as an indicator of estrogenic activity. Both compounds achieved comparable maximal ALP activity as treatment with 1 nM E2, albeit at higher concentrations, confirming their estrogenicity. While both compounds exhibited similar efficacy, their potencies differed. 8-PN caused a significant increase in ALP activity at much lower concentrations, with an EC\u003csub\u003e50\u003c/sub\u003e of 1.77 nM and a lowest observed effect level (LOEL) of 1 nM (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). In contrast, both the EC\u003csub\u003e50\u003c/sub\u003e (1045 nM) and the LOEL (500 nM) of iXN were comparably higher, confirming that 8-PN is over 100 times more potent than iXN.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.7. Estrogenicity of iXN and 8-PN mixtures\u003c/h2\u003e\n \u003cp\u003eThe microbiome-competent PBK model was utilized to predict 8-PN to iXN concentration ratios in the uterus under high and low-hopped beer dosing scenarios. These ratios (1:50 and 1:100, respectively) were used to assess mixture effects in estrogenicity in ALP assays. Concentration-dependent ER activation was measured for individual compounds (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e) and for combinations of iXN and 8-PN (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e). As thresholds of estrogenicity, \u003cem\u003ein vitro\u003c/em\u003e point of departure concentrations were observed at 500 nM for iXN, 1 nM for 8-PN and 1 nM 8-PN within both 1:50 and 1:100 mixtures. To assess combinatory effects that potentially deviate from additive bioactivity, the Chou-Talalay method was used to calculate the combination index, allowing quantitative evaluation of their interactions \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. For the 1:50 8-PN/iXN mixture, we observed varying interaction patterns across different ALP activity levels. Moderate synergism was observed at a concentration of 1 nM 8-PN with 39.2% ALP activity (CI\u0026thinsp;=\u0026thinsp;0.751), indicating enhanced efficacy at these concentrations. At concentrations stimulating moderate ALP activity levels (e.g., 47.6\u0026ndash;81.2%), the combination exhibited additivity or slight antagonism (1.165\u0026thinsp;\u0026le;\u0026thinsp;CI\u0026thinsp;\u0026le;\u0026thinsp;1.314). At higher activity levels (e.g., 89.7%), corresponding to 10 nM 8-PN and 500 nM iXN, the interaction shifted to antagonism (CI\u0026thinsp;=\u0026thinsp;1.509). The highest concentrations of 8-PN and iXN lead to reduced estrogenicity as compared to the maximal effects. Similarly, CI values ranging from 0.7 to 1.4 were calculated for the estrogenicity of the 1:100 iXN/8-PN mixture. At moderate ALP induction levels, a slight synergism was observed, while for the mixture at a concentration of 4 nM 8-PN (65.6% ALP induction), slight antagonism was indicated. The observed antagonism at the lowest dose of the 1:50 mixture is likely due to variability at the lower detection limit of the assay. Across all activity levels and for both 8-PN to iXN ratios, the CI was relatively stable, indicating cumulative to slightly antagonistic effects. While the 1:50 ratio exhibited stronger antagonism at higher activity levels, the 1:100 ratio demonstrated more consistent additivity or mild synergism across the effect range.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, the influence of the gut microbial bioactivation of iXN to 8-PN was characterized. Using microbiome-competent PBK modeling, we predicted blood and tissue concentrations of 8-PN under different dosing scenarios. Subsequently, the estrogenicity of these corresponding levels was evaluated in a cell-based test system. This approach allowed quantitative extrapolation of \u003cem\u003ein vitro\u003c/em\u003e estrogenicity to assess the potential for endocrine disruption in humans. Anaerobic \u003cem\u003eex vivo\u003c/em\u003e fermentations are a common means to obtain kinetic parameters for microbiome-competent PBK models \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this study, 12 fecal slurries were obtained from healthy human donors. Aliquots of each slurry were pooled and then incubated with increasing iXN concentrations to determine the average kinetics of \u003cem\u003eex vivo\u003c/em\u003e 8-PN formation. Using LC-MS/MS analysis, we monitored both the degradation of the parent chemical and the formation of 8-PN over 24 h, resembling average colonic transit times \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe efficiency of gastrointestinal 8-PN formation was relatively low in the pooled fecal samples with a k\u003csub\u003ecat\u003c/sub\u003e of 0.016 mL/h/g, which is far lower compared to the described microbial biotransformation reactions of other polyphenols. For example, the microbial formation of daidzein to S-equol is more efficient with a k\u003csub\u003ecat\u003c/sub\u003e of 1.24 mL/h/g \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Consistent with the low rate of 8-PN formation, it was detected only after 24 h of incubation in the fecal slurry. This further suggests that under the experimental conditions, the transformation could be delayed due to bacterial adaptation time. Due to the highly individual nature of the gut microbiome, it is important to consider interindividual differences in biotransformation capacity \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Therefore, we incubated individual stool samples with a single concentration of iXN and found considerable inter-individual variability in 8-PN formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the 12 individual fecal slurries, only one did not yield 8-PN, while two produced very high 8-PN levels reaching up to 3.9 \u0026micro;M within 24 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In comparison, the pooled fecal samples across replicates yielded 298 nM under the same conditions, indicating a 13-fold variation above average. The sample set represents the expected range of metabolic capacities, consistent with previous classifications of microbiomes into poor, moderate, and strong 8-PN producers \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. As recently reviewed by Cort\u0026eacute;s-Mart\u0026iacute;n \u003cem\u003eet al.\u003c/em\u003e, the classification of different metabotypes can be useful to better understand whether dietary polyphenols and their metabolites can have a beneficial effect on the host \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, this concept is difficult to establish for 8-PN since the compound is not only produced by gut bacteria, but also in the human liver, and is already present in dietary products. The microbial composition of the stool samples used in this study was characterized by 16s rRNA amplicon sequencing. The relative abundance of bacterial communities at the phylum level and the Shannon diversity index were assessed in relation to 8-PN production levels, and a PCoA plot was generated to visualize the variance among samples (available in the supplementary information). While Eubacteria \u003cem\u003elimosum\u003c/em\u003e and \u003cem\u003erammulus\u003c/em\u003e have been associated with the microbial conversion of 8-PN \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, additional unidentified bacteria might play a role in the 8-PN formation. Although the 16s rRNA analysis gives an insight into the microbial composition, the current sequencing resolution limits the precise identification of other involved strains. Metagenomic approaches could potentially be used to identify the specific enzyme and corresponding gene responsible for 8-PN formation. Finally, it remains unclear whether external factors such as lifestyle or age influence microbial metabolism of 8-PN, and analyses addressing these aspects could facilitate personalized risk assessment and targeted intervention strategies.\u003c/p\u003e \u003cp\u003eA previously developed PBK model was extended to predict the microbial formation of 8-PN based on metabolic kinetic parameters that were obtained from incubations with pooled fecal slurry. The V\u003csub\u003emax\u003c/sub\u003e was scaled to gastrointestinal tract contents based on a fecal fraction of human body weight. The model predicted blood and uterus concentrations of 8-PN in the low picomolar range, and therefore, several magnitudes of order lower than concentrations for which estrogenic effects were previously reported \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. To account for population variability resulting from model parameters, Monte Carlo simulations were performed, demonstrating that the human variability should be expected to cause interindividual differences of internal concentrations in the range of approximately +/- 100%.\u003c/p\u003e \u003cp\u003eTo take the inter-individual differences in microbial 8-PN formation into consideration when predicting its concentrations that are achieved systematically and in potential target tissue, the PBK model was individualized by using the apparent V\u003csub\u003emax\u003c/sub\u003e obtained from the pooled fecal slurry to extrapolate the V\u003csub\u003emax\u003c/sub\u003e of 8-PN formation in the individual stool samples. Applying these values to the gut compartment, the PBK model was amended to predict the formation of 8-PN in each individual (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As expected, the predicted blood concentrations of 8-PN were significantly higher in strong producers, with sample ID 17 virtually exhibiting more than twice the levels compared to the predictions of the PBK model that uses pooled fecal slurry kinetics. Besides the gut microbiome, hepatic CYP1A2 enzymes also convert iXN to 8-PN \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. To evaluate the role of the liver, the systemic fate of iXN and 8-PN was simulated with and without CYP1A2-catalyzed conversion (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The model predicted a 30% increase in 8-PN blood concentration with CYP1A2, indicating a substantial hepatic contribution to systemic 8-PN levels for moderate microbial 8-PN producers. CYP1A2 activity is modulated by genetic polymorphisms, such as the \u0026minus;\u0026thinsp;163C\u0026thinsp;\u0026gt;\u0026thinsp;A variant, a single-nucleotide mutation in the promoter region of the gene\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. This polymorphism increases the inducibility of enzyme expression, particularly in response to stressors such as cigarette smoke, resulting in higher metabolic activity compared to individuals with the wild-type allele \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Consequently, individuals carrying this variant may produce elevated levels of 8-PN in combination with certain lifestyle factors. Moreover, the microbial 8-PN high metabolizers who also possess genetic polymorphisms associated with increased CYP1A2 activity may have even higher systemic levels of 8-PN.\u003c/p\u003e \u003cp\u003e8-PN is a potent xenoestrogen, raising concerns about its endocrine activity, particularly in individuals with enhanced microbial and hepatic metabolism. A previous study suggested that dietary beer consumption could induce estrogenic effects in Ishikawa cells \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, the concentrations tested of iXN and 8-PN were not determined based on their toxicokinetics in humans but estimated based on dietary exposure. In this study, we used the microbiome-competent PBK model to quantitatively predict internal exposure to 8-PN. For the selection of concentrations to be tested for \u003cem\u003ein vitro\u003c/em\u003e estrogenicity, we focused on the uterus as an organ of toxicological concern due to its high expression of estrogen receptors that can be activated upon xenoestrogen exposure \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Under high and low-hopped beer intake scenarios, blood and uterine levels of 8-PN were predicted to be in the low nanomolar range, with tissue partitioning resulting in slightly higher concentrations in the uterus than in blood. A Monte Carlo simulation was performed to account for population variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e), demonstrating that predicted maximal exposure levels were twice as high when population variability was considered. These results underscore the substantial influence of interindividual differences on the pharmacokinetics of 8-PN and highlight the need to incorporate population variability in PBK modeling.\u003c/p\u003e \u003cp\u003eAs iXN and 8-PN co-occur in hopped beverages, the PBK model was used to determine their concentration ratios (8-PN/iXN) of 1:50 and 1:100, reflecting relative exposure in the uterus under high- and low-hopped beer intake scenarios. These ratios were selected to represent physiologically relevant conditions and assess potential combinatory effects on estrogenicity in Ishikawa cells using the ALP assay, a well-established and license-free assay that utilizes the ER-dependent expression of ALP as a natural reporter gene for estrogenicity \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Although the low concentrations of iXN that were used with the 1:50 mixture only stimulated none to moderate estrogenicity when applied individually, they were still included to capture potential interactions between the compounds. For single compounds, point of departure (POD) concentrations of 1 nM for 8-PN and 500 nM for iXN were determined.\u003c/p\u003e \u003cp\u003eApplying the 1:50 mixture showed synergism at mid-range ALP activity (39.2%, CI\u0026thinsp;=\u0026thinsp;0.75) but was additive or antagonistic at higher levels (89.7%, CI\u0026thinsp;=\u0026thinsp;1.51). The 1:100 ratio exhibited consistent additivity with mild synergism (43.9%, CI\u0026thinsp;=\u0026thinsp;0.74) and reduced antagonism (93.6%, CI\u0026thinsp;=\u0026thinsp;0.87) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Similar effects were reported at a 1:500 ratio \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, indicating dose-dependent interactions in ER transactivation. Additionally, the POD for both mixtures is not lower than the POD for 8-PN alone, indicating that the combinatory mixture effects of both compounds are negligible for hazard assessment and the estrogenicity is attributable to 8-PN rather than iXN.\u003c/p\u003e \u003cp\u003eThe analysis of individual fecal samples suggested the potential for large interindividual differences, on the order of 600-fold, in 8-PN formation from iXN. Significant estrogenic activity of 8-PN and iXN in Ishikawa cells was observed starting from 1 nM and 500 nM, respectively. Even for high microbial producers, the predicted uterus exposure to 8-PN remains below these POD concentrations. Based on this, dietary exposure to iXN and 8-PN associated with typical consumption is unlikely to pose a risk to human health via estrogenic effects.\u003c/p\u003e \u003cp\u003eThis illustrates the magnitude of variability that can arise from gut microbial bioactivation. Although such variability may be of limited consequence for 8-PN toxicity, it could be highly relevant in causing individual bioactivity of other gut microbial metabolites, especially pharmaceuticals known to undergo microbial metabolism, and thus warrants further investigation. Furthermore, in this study, we observed large interindividual differences in microbial metabolism, demonstrating the importance of PBK models to integrate microbial metabolism to improve the safety assessment of chemicals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: M.S. and G.A., Methodology: M.S. and M.C., Writing original draft: M.S., Reviewing and editing: M.S., M.C., K.B., S.J.S., G.A., Supervision: G.A., K.B., S.J.S. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Swiss Center for Applied Human Toxicology (SCAHT). Open access funding was provided by ETH Zurich. GA was also supported with a fellowship from the Future Food Initiative, a program run by the World Food System Center of ETH Zurich, the Integrative Food and Nutrition Center of EPFL and their industrial partners. The Dutch Ministry of Agriculture, Fisheries, Food Security and Nature (Ministerie van Landbouw, Visserij, Voedselzekerheid en Natuur) is gratefully acknowledged for providing financial support (KB37-002-023). The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript. The authors are grateful to Amrei Rolof for helping with the ex vivo experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKoppel, N., Maini Rekdal, V. \u0026amp; Balskus, E. P. Chemical transformation of xenobiotics by the human gut microbiota. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e356\u003c/strong\u003e, doi:10.1126/science.aag2770 (2017).\u003c/li\u003e\n\u003cli\u003eZimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. \u0026amp; Goodman, A. L. 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The Response to a Single Dose of Estradiol in the Uterus of Ovariectomized C57BL/6J Mice During Aging \u003cem\u003eBiol Reprod\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 262-264, doi:10.1095/biolreprod17.2.262 (1977).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"microbial metabolism, pharmacokinetics, PBK modeling, biotransformation, hop polyphenols, estrogenicity","lastPublishedDoi":"10.21203/rs.3.rs-6511068/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6511068/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe gut microbiome converts the prenylated polyphenol isoxanthohumol, a natural constituent of hops found in beer, to 8-prenylnaringenin (8-PN), a potent phytoestrogen, raising concerns about potential endocrine-disruption. Interindividual differences in microbiome composition may result in varying internal exposures to 8-PN and susceptibility to toxicity. To improve the understanding of 8-PN toxicokinetics, a human physiologically based kinetic (PBK) model was extended to include gut microbial 8-PN formation. Respective parameters were obtained from \u003cem\u003eex vivo\u003c/em\u003e fermentations using pooled and individual stool samples to predict average internal exposure while accounting for interindividual differences. This revealed twofold higher internal 8-PN exposure in high metabolizers compared to low metabolizers. Further, we measured estrogenicity of predicted uterus concentrations of 8-PN using alkaline phosphatase assays and found that even in high metabolizers, systemic 8-PN concentrations remain below estrogenicity thresholds. This study broadly demonstrates the applicability of microbiome-competent PBK modeling for quantifying health impacts of gut microbial metabolites.\u003c/p\u003e","manuscriptTitle":"Interindividual variation in gut microbial formation of 8-prenylnaringenin results in increased, but sub-estrogenic, internal exposure","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-29 09:47:23","doi":"10.21203/rs.3.rs-6511068/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f63aa22b-729b-4d40-9183-27cc46821b43","owner":[],"postedDate":"April 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47559542,"name":"Health sciences/Endocrinology"},{"id":47559543,"name":"Health sciences/Gastroenterology/Gastrointestinal system/Microbiota"},{"id":47559544,"name":"Biological sciences/Drug discovery/Toxicology"}],"tags":[],"updatedAt":"2025-06-18T13:08:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-29 09:47:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6511068","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6511068","identity":"rs-6511068","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}