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Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation

SCOPE: To predict gut microbial metabolism of xenobiotics and the resulting plasma concentrations of metabolites formed, an in vitro–in silico‐based testing strategy is developed using the isoflavone daidzein and its gut microbial metabolite S‐equol as model compounds. METHODS AND RESULTS: Anaerobic...

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Autores principales: Wang, Qianrui, Spenkelink, Bert, Boonpawa, Rungnapa, Rietjens, Ivonne M. C. M., Beekmann, Karsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154660/
https://www.ncbi.nlm.nih.gov/pubmed/32027771
http://dx.doi.org/10.1002/mnfr.201900912
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author Wang, Qianrui
Spenkelink, Bert
Boonpawa, Rungnapa
Rietjens, Ivonne M. C. M.
Beekmann, Karsten
author_facet Wang, Qianrui
Spenkelink, Bert
Boonpawa, Rungnapa
Rietjens, Ivonne M. C. M.
Beekmann, Karsten
author_sort Wang, Qianrui
collection PubMed
description SCOPE: To predict gut microbial metabolism of xenobiotics and the resulting plasma concentrations of metabolites formed, an in vitro–in silico‐based testing strategy is developed using the isoflavone daidzein and its gut microbial metabolite S‐equol as model compounds. METHODS AND RESULTS: Anaerobic rat fecal incubations are optimized and performed to derive the apparent maximum velocities (V (max)) and Michaelis–Menten constants (K (m)) for gut microbial conversion of daidzein to dihydrodaidzein, S‐equol, and O‐desmethylangolensin, which are input as parameters for a physiologically based kinetic (PBK) model. The inclusion of gut microbiota in the PBK model allows prediction of S‐equol concentrations and slightly reduced predicted maximal daidzein concentrations from 2.19 to 2.16 µm. The resulting predicted concentrations of daidzein and S‐equol are comparable to in vivo concentrations reported. CONCLUSION: The optimized in vitro approach to quantify kinetics for gut microbial conversions, and the newly developed PBK model for rats that includes gut microbial metabolism, provide a unique tool to predict the in vivo consequences of daidzein microbial metabolism for systemic exposure of the host to daidzein and its metabolite S‐equol. The predictions reveal a dominant role for daidzein in ERα‐mediated estrogenicity despite the higher estrogenic potency of its microbial metabolite S‐equol.
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spelling pubmed-71546602020-04-14 Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation Wang, Qianrui Spenkelink, Bert Boonpawa, Rungnapa Rietjens, Ivonne M. C. M. Beekmann, Karsten Mol Nutr Food Res Research Articles SCOPE: To predict gut microbial metabolism of xenobiotics and the resulting plasma concentrations of metabolites formed, an in vitro–in silico‐based testing strategy is developed using the isoflavone daidzein and its gut microbial metabolite S‐equol as model compounds. METHODS AND RESULTS: Anaerobic rat fecal incubations are optimized and performed to derive the apparent maximum velocities (V (max)) and Michaelis–Menten constants (K (m)) for gut microbial conversion of daidzein to dihydrodaidzein, S‐equol, and O‐desmethylangolensin, which are input as parameters for a physiologically based kinetic (PBK) model. The inclusion of gut microbiota in the PBK model allows prediction of S‐equol concentrations and slightly reduced predicted maximal daidzein concentrations from 2.19 to 2.16 µm. The resulting predicted concentrations of daidzein and S‐equol are comparable to in vivo concentrations reported. CONCLUSION: The optimized in vitro approach to quantify kinetics for gut microbial conversions, and the newly developed PBK model for rats that includes gut microbial metabolism, provide a unique tool to predict the in vivo consequences of daidzein microbial metabolism for systemic exposure of the host to daidzein and its metabolite S‐equol. The predictions reveal a dominant role for daidzein in ERα‐mediated estrogenicity despite the higher estrogenic potency of its microbial metabolite S‐equol. John Wiley and Sons Inc. 2020-02-25 2020-03 /pmc/articles/PMC7154660/ /pubmed/32027771 http://dx.doi.org/10.1002/mnfr.201900912 Text en © 2020 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Wang, Qianrui
Spenkelink, Bert
Boonpawa, Rungnapa
Rietjens, Ivonne M. C. M.
Beekmann, Karsten
Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title_full Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title_fullStr Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title_full_unstemmed Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title_short Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S‐Equol and Its Consequences for ERα Activation
title_sort use of physiologically based kinetic modeling to predict rat gut microbial metabolism of the isoflavone daidzein to s‐equol and its consequences for erα activation
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154660/
https://www.ncbi.nlm.nih.gov/pubmed/32027771
http://dx.doi.org/10.1002/mnfr.201900912
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