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      Multi- and Transgenerational Outcomes of an Exposure to a Mixture of Endocrine-Disrupting Chemicals (EDCs) on Puberty and Maternal Behavior in the Female Rat

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          Abstract

          Background:

          The effects of endocrine-disrupting chemicals (EDCs) on fertility and reproductive development represent a rising concern in modern societies. Although the neuroendocrine control of sexual maturation is a major target of EDCs, little is known about the potential role of the hypothalamus in puberty and ovulation disruption transmitted across generations.

          Objectives:

          We hypothesized that developmental exposure to an environmentally relevant dose of EDC mixture could induce multi- and/or transgenerational alterations of sexual maturation and maternal care in female rats through epigenetic reprograming of the hypothalamus. We investigated the transmission of a disrupted reproductive phenotype via the maternal germline or via nongenomic mechanisms involving maternal care.

          Methods:

          Adult female Wistar rats were exposed prior to and during gestation and until the end of lactation to a mixture of the following 13 EDCs: di- n-butyl phthalate (DnBP), di(2-ethylhexyl) phthalate (DEHP), bisphenol A (BPA), vinclozolin, prochloraz, procymidone, linuron, epoxynaxole, dichlorodiphenyldichloroethylene, octyl methoxynimmate, 4-methylbenzylidene camphor (4-MBC), butylparaben, and acetaminophen. Perinatally exposed offspring (F1) were mated with unexposed males to generate germ cell (F2) and transgenerationally exposed (F3 and F4) females. Sexual maturation, maternal behavior, and hypothalamic targets of exposure were studied across generations.

          Results:

          Germ cell (F2) and transgenerationally (F3) EDC-exposed females, but not F1, displayed delayed pubertal onset and altered folliculogenesis. We reported a transgenerational alteration of key hypothalamic genes controlling puberty and ovulation ( Kiss1, Esr1, and Oxt), and we identified the hypothalamic polycomb group of epigenetic repressors as actors of this mechanism. Furthermore, we found a multigenerational reduction of maternal behavior (F1–F3) induced by a loss in hypothalamic dopaminergic signaling. Using a cross-fostering paradigm, we identified that the reduction in maternal phenotype was normalized in EDC-exposed pups raised by unexposed dams, but no reversal of the pubertal phenotype was achieved.

          Discussion:

          Rats developmentally exposed to an EDC mixture exhibited multi- and transgenerational disruption of sexual maturation and maternal care via hypothalamic epigenetic reprogramming. These results raise concerns about the impact of EDC mixtures on future generations. https://doi.org/10.1289/EHP8795

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          Most cited references168

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          Is Open Access

          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            A new mathematical model for relative quantification in real-time RT-PCR.

            M. Pfaffl (2001)
            Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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              A Threshold Selection Method from Gray-Level Histograms

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                Author and article information

                Journal
                Environ Health Perspect
                Environ Health Perspect
                EHP
                Environmental Health Perspectives
                Environmental Health Perspectives
                0091-6765
                1552-9924
                12 August 2021
                August 2021
                : 129
                : 8
                : 087003
                Affiliations
                [ 1 ]GIGA Neurosciences, Neuroendocrinology Unit, University of Liège , Liège, Belgium
                [ 2 ]Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University (OHSU) , Portland, Oregon, USA
                [ 3 ]Lille Neuroscience & Cognition (LilNCog), Institut national de la santé et de la recherche médicale (Inserm), CHU Lille , Lille, France
                [ 4 ]Tumor and Development Biology, GIGA-Cancer, University of Liège , Liège, Belgium
                [ 5 ]Department of Psychology: Cognition and Behavior, University of Liège , Liège, Belgium
                [ 6 ]Department of Pediatrics, University Hospital Liège , Liège, Belgium
                Author notes
                Address correspondence to David López-Rodríguez, Neuroendocrinology Unit, GIGA Neurosciences, University of Liège, Sart Tilman, B-4000 Liège, Belgium. Telephone: +3243662539. Email: dlopez@ 123456uliege.be
                Article
                EHP8795
                10.1289/EHP8795
                8360047
                34383603
                ffab63e1-4dc7-40ab-bd1a-c4eec243ce7b

                EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.

                History
                : 09 December 2020
                : 28 June 2021
                : 13 July 2021
                Categories
                Research

                Public health
                Public health

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