Pregnancy Discussion

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Question Description

Here I have provided a simple article discussing the idea that there is communication from the fetus to the mom's brain and vice versa through the placenta. The idea that this results in changes in gene expression in both the mother's brain and the fetus's brain is introduced. I have also included the scientific article that this short news story is talking about for you to read (stick to the introduction, results and conclusions to make your life easier.

In several paragraphs, describe what you understand about these articles. What types of long-lasting effects does this cross-talk have on the mother and the newborn? Why is this news?

https://medicalxpress.com/news/2019-03-placenta-du...

When you are done, you must respond to 2 other posts (I will provide them after I submit my discussion since I can't see others posts before posting my own).

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THE JOURNAL • RESEARCH • www.fasebj.org Evidence for functional interactions between the placenta and brain in pregnant mice Susanta K. Behura,*,†,1 Andrew M. Kelleher,* and Thomas E. Spencer*,‡ *Division of Animal Sciences, †Informatics Institute, and ‡Department of Obstetrics, Gynecology, and Women’s Health, University of Missouri, Columbia, Missouri, USA ABSTRACT: The placenta plays a pivotal role in the development of the fetal brain and also influences maternal brain function, but our understanding of communication between the placenta and brain remains limited. Using a gene expression and network analysis approach, we provide evidence that the placenta transcriptome is tightly interconnected with the maternal brain and fetal brain in d 15 pregnant C57BL/6J mice. Activation of serotonergic synapse signaling and inhibition of neurotrophin signaling were identified as potential mediators of crosstalk between the placenta and maternal brain and fetal brain, respectively. Genes encoding specific receptors and ligands were predicted to affect functional interactions between the placenta and brain. Paralogous genes, such as sex comb on midleg homolog 1/scm-like with 4 mbt domains 2 and polycomb group ring finger (Pcgf) 2/Pcgf5, displayed antagonistic regulation between the placenta and brain. Additionally, conditional ablation of forkhead box a2 (Foxa2) in the glands of the uterus altered the transcriptome of the d 15 placenta, which provides novel evidence of crosstalk between the uterine glands and placenta. Furthermore, expression of cathepsin 6 and monocyte to macrophage differentiation associated 2 was significantly different in the fetal brain of Foxa2 conditional knockout mice compared with control mice. These findings provide a better understanding of the intricacies of uterus-placenta-brain interactions during pregnancy and provide a foundation and model system for their exploration.—Behura, S. K., Kelleher, A. M., Spencer, T. E. Evidence for functional interactions between the placenta and brain in pregnant mice. FASEB J. 33, 4261–4272 (2019). www.fasebj.org KEY WORDS: fetus • paralog • Foxa2 • regulation • uterine The establishment of pregnancy requires effective molecular crosstalk between the uterus and embryo, and the maintenance of pregnancy to term requires embryo implantation, stromal cell decidualization, and placental development and function. In mice, blastocysts enter the uterus early on gestational day (GD) 4 (GD 1 is observation of a postcoital vaginal plug), and implantation into the endometrium commences around midnight on GD4 (1, 2). Decidualization of stromal cells commences on the morning of GD5 near the attached and implanting blastocyst and eventually spreads toward the mesometrial area of the uterus (3). By GD6, the trophectoderm of the ABBREVIATIONS: BDNF, brain-derived neurotrophic factor; cKO, condi- tional knockout; Cts, cathepsin; DE, differentially expressed; FB, fetal brain; Foxa2, forkhead box a2; GD, gestational day; GO, gene ontology; LIF, leukemia inhibitory factor; MB, maternal brain; MI, mutual information; Mmd2, monocyte to macrophage differentiation associated 2; Pcgf, polycomb group ring finger; Prl, prolactin; Psg, pregnancy-specific glycoprotein; SPIA, signaling pathway impact analysis; WT, wild type 1 Correspondence: Division of Animal Sciences, 920 East Campus Drive, University of Missouri, Columbia, MO 65211, USA. E-mail: behuras@ missouri.edu doi: 10.1096/fj.201802037R This article includes supplemental data. Please visit http://www.fasebj.org to obtain this information. 0892-6638/19/0033-4261 © FASEB developing placenta begins to directly contact the decidualized stroma. The placenta is fully formed and functional by GD15 (4). Asynchronous embryo-uterine interactions and defective stromal cell decidualization can result in pregnancy loss and miscarriage as well as later pregnancy complications such as preeclampsia and fetal growth retardation (2, 5). Understanding the biologic and evolutionary links between the brain and reproductive system is important to obtain better insight into the molecular complexity of pregnancy (6, 7). The maternal brain (MB), uterus, and placenta interact during pregnancy and mediate maternal adaptations to support pregnancy and lactation after parturition (8, 9). The hormones estrogen, progesterone, prolactin (Prl), and oxytocin play key roles during pregnancy, and the brain robustly regulates their production via the hypothalamic-pituitary-gonadal axis (10). In mice, changes in the MB during pregnancy regulate maternal behaviors such as pup retrieval and nest building (11). In humans, pregnancy effects changes in the MB that last at least 2 yr after birth (12) and include enhancement of key hippocampal functions such as spatial memory (13, 14). In mice, changes in gene expression have been evaluated in specific regions of the MB during pregnancy (15, 16) as well as in virgin, pregnant, and postpartum periods (17). 4261 w.fasebj.org by California State Univ Northridge Univ Library (130.166.3.5) on March 30, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNum However, our understanding of how the placenta and brain communicate remains very limited. The placenta plays a major role in development of the fetus (18). Recent evidence supports the idea that placental metabolic pathways modulate fetal brain (FB) development and suggest an important role for maternal-placental-fetal interactions and serotonin (5hydroxytryptamine) in the fetal programming of adult mental disorders (19–21). Maternal stress factors during pregnancy, including body weight, nutrition, anemia, smoking, and substance abuse, can negatively affect and program fetal development with persistent life-long effects on offspring (22, 23). A primary regulator of placental development and function is the decidua of the uterus, which is formed by differentiation of stromal cells in the endometrium in response to progesterone and embryo implantation (24, 25). Recent studies suggest that stromal cell decidualization can be modulated by glands of the uterus (26, 27). Here, we first used a gene expression and network analysis approach to investigate global crosstalk of genes between the mouse placenta, FB, and MB on GD15. Next, we examined the effect of the conditional ablation of forkhead box a2 (Foxa2), a key transcription factor for uterine gland function during pregnancy establishment (26), on gene expression changes in the placenta and FB. The findings provide new evidence for and insights into how the brain, uterus, and placenta interact during pregnancy. (Thermo Fisher Scientific, Waltham, MA, USA) protocol. For placental RNA, 3 placentas were pooled from each of the 4 mice for RNA extraction. To eliminate genomic DNA contamination, extracted RNA was treated with DNase I and purified using Direct-zol MiniPrep Plus Kit according to the manufacturer’s instructions (Zymo Research, Irvine, CA, USA). RNA concentration was determined using a Qubit RNA Assay (Thermo Fisher Scientific), and quality was determined by a Fragment Analyzer instrument (Agilent, Santa Clara, CA, USA). Total RNA was submitted to the University of Missouri DNA Core Facility for RNA-Seq library construction using the Illumina TruSeq Stranded mRNA Sample Preparation Kit (Illumina, San Diego, CA, USA). Libraries were sequenced (paired-end, 75 bp) using a NextSeq500 instrument (Illumina). The mean read count generated from the RNA-Seq experiment was 27.4 million per sample. All the raw and processed data were deposited in the Gene Expression Omnibus database (GSE121799; https://www.ncbi.nlm. nih.gov/geo/). Differential gene expression analysis Raw sequences (FastQ files) were subjected to quality check by FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The program fqtrim (https://ccb.jhu.edu/software/fqtrim/) was used to remove adapters, perform quality trimming (Phred score .30) by a sliding window scan (6 nt), and select read length of 30 nt or longer. The reads obtained from the quality control were mapped to the Mus musculus reference genome (GRCm38.p5) by the Hisat2 aligner (28). The program featureCounts (29) was then used to quantify read counts that mapped to the genes. The differentially expressed (DE) genes between sample groups were determined by edgeR-robust (30). The false discovery rate ,0.05 was used as a significance threshold. MATERIALS AND METHODS Animal breeding and sample collection Cluster and network analysis All animal procedures were approved by the Institutional Animal Care and Use Committee of the University of MissouriColumbia and conducted according to the Guide for the Care and Use of Laboratory Animals (National Institutes of Health, Bethesda, MD, USA) Adult (9 wk old) C57BL/6J wild-type (WT) female mice were mated with males of proven fertility to induce pregnancy. Pregnant WT mice (n = 4) were euthanized on GD15. The entire MB was quickly collected along with the FB and placenta from all implantation sites. Care was taken to isolate the placenta from the decidua by microdissection using a stereomicroscope. Each organ was washed in sterile PBS and snap frozen in liquid nitrogen. Adult female Foxa2 conditional knockout (cKO) mice were generated by breeding C57BL/6J lactotransferrin Cre (LtfiCre) knock-in mice with C57BL/6J floxed Foxa2 mice as described by our laboratory (26). Adult Foxa2 cKO (LtfiCre/+Foxa2f/f) mice are infertile because of defects in embryo implantation caused by an absence of leukemia inhibitory factor (LIF) expression by the glands of the uterus (27). To rescue implantation and pregnancy establishment, adult female Foxa2 cKO mice (n = 4) received intraperitoneal injections of 10 mg recombinant mouse LIF (BioLegend, San Diego, CA, USA) in sterile PBS at 10:00 AM and 6:00 PM on GD4 as previously described (27). The mice were necropsied on GD15, and the placenta and FB from each implantation site were isolated, washed, and frozen as previously described. A finite normal mixture model based on the Bayesian information criterion was employed to predict gene expression clusters from the RNA-Seq data using the R package mclust v.5 (31). To construct a gene expression network, an information theoretical approach (32) was adopted. In this method, mutual information (MI) of expression variation was calculated in pairwise manner between genes across the samples. The MI is the summation of log ratios of joint probability:marginal probability and measures the information content between 2 variables (genes in this case). It determines how much knowing 1 variable would predict variability of the other. The MI values were then used to generate a weighted adjacency matrix by the maximum relevance–minimum redundancy method (33) to construct gene expression networks. To compare gene expression patterns among MB, FB, and placenta samples, MI scores were generated between samples in a pairwise manner. The distance matrix of MI scores was then plotted using R (circlize package; https://CRAN.R-project.org/package=circlize) to infer links within and between the samples. RNA extraction and sequencing Total RNA was isolated from the MB, FB, and placenta (n = 4 biologic replicates for each organ) using a standard Trizol-based 4262 Vol. 33 March 2019 Analysis of paralogs and gene families Paralogous genes and gene families annotated from mouse genome annotation (GRCm38.p5) were downloaded from Ensembl using the BioMart (http://useast.ensembl.org/biomart/martview/ 667e0bf1998bb8e993e82e8517871448) tool. The information, along with the RNA-Seq data, was used to compare expression variation of genes that had one or more paralogs with expression variation of genes that had no paralog (single copy genes). As the number of genes expressed in the MB, FB, and placenta varied, The FASEB Journal x www.fasebj.org BEHURA ET AL. w.fasebj.org by California State Univ Northridge Univ Library (130.166.3.5) on March 30, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNum we normalized the variation of gene expression by sampling an equal number of genes (n = 1000 randomly) from the MB, FB, and placenta separately. The sampling was repeated 100 times, and the mean variance of expression was calculated for both gene types (with or without paralogs) separately for the MB, FB, and the placenta. Functional annotation of differentially regulated genes Gene ontology (GO) analysis was conducted by Panther tools (http://www.pantherdb.org) using Fisher’s exact test. The cluster analysis of fold enrichment of the GO terms was performed by mclust v.5 (31). The signaling pathway impact analysis (SPIA) method (34) was used to perform topology-based pathway analysis using the R and Bioconductor package ToPASeq (35). The DE genes were used as a query to predict receptor and corresponding ligands from the FANTOM5 database of receptors and ligands (Riken, Tokyo, Japan) (36). Transcription factors as regulators of correlated expression changes of genes among the MB, FB, and placenta were predicted by iRegulon (37). iRegulon is a gene set analysis tool to infer gene regulatory networks based on mapping incidences of transcription factors binding to motifs. Quantitative RT-PCR For quantitative RT-PCR assays, total RNA (1 mg) from the FB of GD 15 WT and Foxa2 cKO mice was reverse transcribed in a 20 ml reaction volume using iScript RT Supermix (Bio-Rad, Hercules, CA, USA) using methods previously described (38). PCR assays were performed using Bio-Rad Universal SYBR Green Supermix on a Bio-Rad CFX384 Touch Real-Time System with glyceraldehyde-3-phosphate dehydrogenase as a reference gene. All genes were assayed using predesigned and validated Bio-Rad PrimePCR primers specific to the desired mouse gene. RESULTS Gene expression patterns in the brain and placenta The transcriptome of the MB, FB, and placenta from C57BL/6J mice was determined on GD15, which was selected because the placenta is fully mature and functional at this timepoint of pregnancy (4). The pattern of gene expression correlations among MB, FB, and placenta samples is shown in Fig. 1. This represents a generalized pattern, inclusive of positive, negative, and nonlinear correlations, inferred by calculating the MI of gene expression variation between samples in pairwise manner. The links connecting 1 sample to another, shown as colored curves of varying width, represent quantitative measurement for correlated expression changes of genes between samples. As expected, samples within group (MB, FB, or placenta) are well connected with each other. In contrast, the links connecting samples between groups (placenta vs. FB, placenta vs. MB, or MB vs. FB) are quantitatively much less than within-group links. Thus, gene expression patterns of the MB, FB, and placenta are highly distinct. The DE gene analysis revealed thousands of genes whose expression was altered in MB and/or FB in a coordinate manner relative to the placenta (Fig. 2). Three PLACENTA-BRAIN INTERACTIONS Figure 1. Chord diagram showing MI of gene expression among the MB, FB, and placenta (PL) of WT d 15 pregnant mice. The links by color-matched curves represent extent of correlated gene expression between the color-coded samples. The MI scale is shown on the circumference of each sample. patterns of differential gene expression were observed. One of the patterns is related to the expression changes due to tissue differences (placenta and brain). A total of 5258 genes were up-regulated in both the MB and FB compared with the placenta, and a comparable number of genes (5405) were down-regulated in both MB and FB relative to the placenta. The second pattern of gene expression was related to differences in developed MB as compared with the developing FB. Many genes were DE in the MB compared with the placenta (1491 increased and 1182 decreased), but such a difference in expression was not evident in the FB. Genes were also identified with different expression in the FB compared with the placenta (1034 increased and 920 decreased), but such differences in expression were not evident in MB. The third pattern represented gene expression changes that are neither tissue related nor development (brain) related; rather, they are related to differential regulation among the MB, FB, and the placenta. This pattern included genes that are either increased in the MB but decreased in the FB (927) or increased in the FB but decreased in the MB (n = 1037) relative to the placenta (Fig. 2). To identify genes associated with the correlated expression changes among the MB, FB, and placenta, we performed a model-based cluster analysis of gene expression using the Bayesian information criterion method (31). The analysis identified a small group of 57 genes associated with a single cluster of differential expression among the MB, FB, and placenta (Fig. 3). In this cluster, 33 genes were expressed in the FB as well as the placenta, but they were either not expressed or not very abundant in the MB (Supplemental Table S1). The other 24 genes were 4263 w.fasebj.org by California State Univ Northridge Univ Library (130.166.3.5) on March 30, 2019. The FASEB Journal Vol. ${article.issue.getVolume()}, No. ${article.issue.getIssueNum Figure 2. Number and direction of DE genes. A) The numbers of increased and decreased genes (shown within rectangles) between the brain and placenta are shown. The DE gene sets are color coded according to the samples (dark green for MB, light green for FB, and pink for PL). The black arrows designate the direction of expression changes. Two-sided arrows indicate commonly regulated genes. The 1-sided arrows indicate genes that are increased between 1 group pair but decreased in the other group pair. B) The plots of log fold-changes illustrate nearly equal distribution of genes that are either increased or decreased in the MB or FB compared with the placenta. PL, placenta. expressed together in the MB and placenta but either not expressed or poorly expressed in the FB. Network analysis further predicted that these genes are likely to interact with each other (Fig. 3). The property of these genes to crosstalk suggests their role in functional interaction between the placenta and brain during pregnancy. In addition, we found differential expression of specific paralogous genes in the placenta and brain during pregnancy. In the MB as well as the FB, single copy genes displayed more than a 2-fold higher variation in expression compared with gene families or genes with one or more paralogs. However, this pattern is apparently absent in the placenta (Supplemental Fig. S1). We identified several paralogs within gene families, such as Ceacam, Prl, cathepsin (Cts), Serpin, and pregnancy-specific glycoprotein (Psg), which are coordinately activated in the placenta relative to the MB and FB. Specific paralog gene pairs (n = 340) were identified when both the genes were abundantly expressed in the placenta but were either absent or poorly expressed in the brain (Supplemental Table S2). On the other hand, our data also showed paralog gene pairs (n = 8) in which both the genes were highly expression in both the MB and FB but were either absent or poorly expressed in the placenta (Supplemental Table S2). Moreover, we observed 2 genes whose paralogs seem to be differentially regulated between brain and placenta. Sex comb on midleg homolog 1 was activated in both MB and FB more than 8-fold relative to the placenta, but its paralog, scm-like with four mbt domains 2, was activated in the placenta more than 60-fold relative to both the MB and FB. Similarly, polycomb group ring finger (Pcgf) 5 was increased in the placenta more than 10-fold relative to both the MB and FB, but its paralog Pcgf2 increased more than 6-fold in the MB and FB relative to the ...
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Pregnancy Discussion Outline
Comprehension of the Articles
The placenta is a small organ that plays out the elements of a few grown-up organs for the
developing embryo.
Long-Term Effects on mother and New-conceived
Such tragedy provides us with helpful exercises on the impacts of caloric confinement/lack of
healthy sustenance on fetal advancement and infection pervasiveness in adulthood.
Why it is News
Records of the long-term sequelae of these people are not as clear as those in Holland. Critically,
the components of these in utero "programming" impacts are obscure.


Running head: PREGNANCY DISCUSSION

Pregnancy Discussion
Author’s Name
Institutional Affiliation

1

PREGNANCY DISCUSSION

2
Comprehension of the Articles

The placenta is a small organ that plays out the elements of a few grown-up organs for
the developing embryo. The placenta is structured extraordinarily for exchange of air
(oxygen), supplements, antibodies, hormones, and waste items between the mother and baby
and may convey essential data about the pregnancy. Although a placenta after conveyance is
among the most active open human tissues, it is generally disposed of after a careless
assessment. A few pregnancy issues including preeclampsia (PE) and preterm work are
related t...

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Anonymous
Thanks, good work

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