scholarly journals Regulation of Liver Regeneration by hepatocyte O-GlcNAcylation in mice

2021 ◽  
Author(s):  
Dakota R Robarts ◽  
Steven R McGreal ◽  
David S Umbaugh ◽  
Wendena S Parkes ◽  
Manasi Kotulkar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Regeneration ◽  
Posttranslational Modification ◽  
Target Genes ◽  
Critical Role ◽  
Rna Seq ◽  
Hepatocyte Differentiation ◽  
Hepatic Differentiation ◽  
Glcnac Transferase ◽  
Sustained Increase

The liver has a unique capacity to regenerate after injury in a highly orchestrated and regulated manner. Here we report that O-GlcNAcylation, an intracellular posttranslational modification (PTM) regulated by two enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), is a critical termination signal for liver regeneration (LR) following partial hepatectomy (PHX). We studied liver regeneration after PHX on hepatocyte specific OGT and OGA knockout mice (OGT-KO and OGA-KO), which caused a significant decrease (OGT-KO) and increase (OGA-KO) in hepatic O-GlcNAcylation, respectively. OGA-KO mice had normal regeneration, but the OGT-KO mice exhibited substantial defects in termination of liver regeneration with increased liver injury, sustained cell proliferation resulting in significant hepatomegaly, hepatic dysplasia and appearance of small nodules at 28 days after PHX. This was accompanied by a sustained increase in expression of cyclins along with significant induction in pro-inflammatory and pro-fibrotic gene expression in the OGT-KO livers. RNA-Seq studies revealed inactivation of hepatocyte nuclear 4 alpha (HNF4α), the master regulator of hepatic differentiation and a known termination signal, in OGT-KO mice at 28 days after PHX, which was confirmed by both Western blot and IHC analysis. Furthermore, a significant decrease in HNFα target genes was observed in OGT-KO mice, indicating a lack of hepatocyte differentiation following decreased hepatic O-GlcNAcylation. Immunoprecipitation experiments revealed HNF4α is O-GlcNAcylated in normal differentiated hepatocytes. These studies show that O-GlcNAcylation plays a critical role in the termination of LR via regulation of HNF4α in hepatocytes.

scholarly journals Hepatocyte-specific deletion of hepatocyte nuclear factor-4α in adult mice results in increased hepatocyte proliferation

2013 ◽  
Vol 304 (1) ◽  
pp. G26-G37 ◽  
Author(s):  
Chad Walesky ◽  
Sumedha Gunewardena ◽  
Ernest F. Terwilliger ◽  
Genea Edwards ◽  
Prachi Borude ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Viral Vector ◽  
Hepatocyte Proliferation ◽  
Nuclear Factor ◽  
Hepatocyte Nuclear Factor ◽  
Hepatocyte Differentiation ◽  
Hepatic Differentiation ◽  
Hepatocyte Nuclear Factor 4Α ◽  
Specific Deletion

Hepatocyte nuclear factor-4α (HNF4α) is known as the master regulator of hepatocyte differentiation. Recent studies indicate that HNF4α may inhibit hepatocyte proliferation via mechanisms that have yet to be identified. Using a HNF4α knockdown mouse model based on delivery of inducible Cre recombinase via an adeno-associated virus 8 viral vector, we investigated the role of HNF4α in the regulation of hepatocyte proliferation. Hepatocyte-specific deletion of HNF4α resulted in increased hepatocyte proliferation. Global gene expression analysis showed that a majority of the downregulated genes were previously known HNF4α target genes involved in hepatic differentiation. Interestingly, ≥500 upregulated genes were associated with cell proliferation and cancer. Furthermore, we identified potential negative target genes of HNF4α, many of which are involved in the stimulation of proliferation. Using chromatin immunoprecipitation analysis, we confirmed binding of HNF4α at three of these genes. Furthermore, overexpression of HNF4α in mouse hepatocellular carcinoma cells resulted in a decrease in promitogenic gene expression and cell cycle arrest. Taken together, these data indicate that, apart from its role in hepatocyte differentiation, HNF4α actively inhibits hepatocyte proliferation by repression of specific promitogenic genes.

scholarly journals Elucidation of Regulatory Modes for Five Two-Component Systems in Escherichia coli Reveals Novel Relationships

mSystems ◽  
2020 ◽  
Vol 5 (6) ◽  
Author(s):  
Kumari Sonal Choudhary ◽  
Julia A. Kleinmanns ◽  
Katherine Decker ◽  
Anand V. Sastry ◽  
Ye Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Target Gene ◽  
Target Genes ◽  
Rna Seq ◽  
Content Type ◽  
E Coli ◽  
Component Systems ◽  
Two Component ◽  
Two Component Systems

ABSTRACT Escherichia coli uses two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress; KdpDE and PhoRB, induced by limiting potassium and phosphate, respectively; and ZraSR, stimulated by zinc. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data were used to validate condition-specific target gene binding sites. Based on these data, we do the following: (i) identify the target genes for each TCS; (ii) show how the target genes are transcribed in response to stimulus; and (iii) reveal novel relationships between TCSs, which indicate noncognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded. IMPORTANCE E. coli is a common commensal microbe found in the human gut microenvironment; however, some strains cause diseases like diarrhea, urinary tract infections, and meningitis. E. coli’s two-component systems (TCSs) modulate target gene expression, especially related to virulence, pathogenesis, and antimicrobial peptides, in response to environmental stimuli. Thus, it is of utmost importance to understand the transcriptional regulation of TCSs to infer bacterial environmental adaptation and disease pathogenicity. Utilizing a combinatorial approach integrating RNA sequencing (RNA-seq), independent component analysis, chromatin immunoprecipitation coupled with exonuclease treatment (ChIP-exo), and data mining, we suggest five different modes of TCS transcriptional regulation. Our data further highlight noncognate inducers of TCSs, which emphasizes the cross-regulatory nature of TCSs in E. coli and suggests that TCSs may have a role beyond their cognate functionalities. In summary, these results can lead to an understanding of the metabolic capabilities of bacteria and correctly predict complex phenotype under diverse conditions, especially when further incorporated with genome-scale metabolic models.

The characteristics of mesenteric adipose tissue attached to different intestinal segments and their roles in immune regulation

2022 ◽  
Author(s):  
Haowei Zhang ◽  
Yujin Ding ◽  
Qin Zeng ◽  
Dandan Wang ◽  
Ganglei Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adipose Tissue ◽  
Immune Regulation ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Mesenteric Adipose Tissue ◽  
Cell Components ◽  
Subsequent Effect

Background: Mesenteric adipose tissue (MAT) plays a critical role in the intestinal physiological ecosystems. Small and large intestines have evidently intrinsic and distinct characteristics. However, whether there exist any mesenteric differences adjacent to the small and large intestines (SMAT and LMAT) has not been properly characterized. We studied the important facets of these differences, such as morphology, gene expression, cell components and immune regulation of MATs, to characterize the mesenteric differences. Methods: The SMAT and LMAT of mice were utilized for comparison of tissue morphology. Paired mesenteric samples were analyzed by RNA-seq to clarify gene expression profiles. MAT partial excision models were constructed to illustrate the immune regulation roles of MATs, and 16S-seq was applied to detect the subsequent effect on microbiota. Results: Our data show that different segments of mesenteries have different morphological structures. SMAT not only has smaller adipocytes but also contains more fat-associated lymphoid clusters than LMAT. The gene expression profile is also discrepant between these two MATs in mice. B-cell markers were abundantly expressed in SMAT, while development-related genes were highly expressed in LMAT. Adipose-derived stem cells of LMAT exhibited higher adipogenic potential and lower proliferation rates than those of SMAT. In addition, SMAT and LMAT play different roles in immune regulation and subsequently affect microbiota components. Finally, our data clarified the described differences between SMAT and LMAT in humans. Conclusions: There were significant differences in cell morphology, gene expression profiles, cell components, biological characteristics, and immune and microbiota regulation roles between regional MATs.

130 A CATALOG OF REFERENCE GENES WITH HIGH, MEDIUM, AND LOW LEVELS OF EXPRESSION DURING BOVINE IN VIVO PRE-IMPLANTATION DEVELOPMENT

2017 ◽  
Vol 29 (1) ◽  
pp. 173
Author(s):  
Z. Jiang ◽  
J. Sun ◽  
S. Marjani ◽  
H. Dong ◽  
X. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Genes ◽  
Target Genes ◽  
Stable Expression ◽  
Bovine Embryo ◽  
Rna Seq ◽  
Rt Pcr ◽  
Data Set ◽  
Low Expression

Appropriate reference genes for accurate normalization in RT-PCR are essential for the study of gene expression. Ideal reference genes should not only have stable expression across stages of embryo development, but also be expressed at comparable levels to the target genes. Using RNA-seq data from in vivo-produced bovine oocytes and embryos from the 2-cell to blastocyst stage (Jiang et al., 2014 BMC Genomics 15, 756), we tried to establish a catalogue of all reference genes for RT-PCR analysis. One-way ANOVA generated 4055 genes that did not differ across stages. To reduce this list, we used the entire RNA-seq data set and first removed genes with a FPKM (fragments per kilobase of transcript per million mapped reads) of <1, and then rescaled each gene’s expression values within a range of 0 to 1. We subsequently calculated the expression variance for each gene across all stages. By assuming that the calculated variances follow a Gaussian distribution and that the majority of the genes do not have a stable expression level, a gene was classified as a reference if its variance significantly deviated (P < 0.05) from these assumptions. We identified 346 potential reference genes, all of which were among the candidates from the ANOVA analysis. We arbitrarily assigned genes in this list to high (FPKM ≥ 100), medium (10 < FPKM < 100), and low expression levels (FPKM ≤ 10), and 37, 154, and 155 genes, respectively, fell into these groups. Surprisingly, none of the commonly used reference genes, such as GAPDH, PPIA, ACTB, PRL15, GUSB, and H3F2A, were identified as being stably expressed across in vivo development. This is consistent with findings of prior RT-PCR studies (Robert et al. 2002 Biol. Reprod. 67, 1465–1472; Ross et al. 2010 Cell Reprogram. 12, 709–717). The following gene ontology terms were significantly enriched for the 346 genes: cell cycle, translation, transport, chromatin, cell division, and metabolic process, indicating that the early embryos maintained constant levels of genes involved in fundamental biological functions. Finally, we performed RT-PCR to validate the RNA-seq results using different bovine in vivo-derived oocytes and embryos (n = 3/stage). We successfully validated 10 selected genes, including those in the high (CS, PGD, and ACTR3), medium (CCT5, MRPL47, COG2, CRT9, and HELLS), and low expression groups (CDC23 and TTF1). In conclusion, we recommend the use of reference genes that are expressed at comparable levels to target genes. This study offers a useful resource to aid in the appropriate selection of reference genes, which will improve the accuracy of quantitative gene expression analyses across bovine embryo pre-implantation development.

scholarly journals Structure and expression analysis of seven salt-related ERF genes of Populus

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10206
Author(s):  
Juanjuan Huang ◽  
Shengji Wang ◽  
Xingdou Wang ◽  
Yan Fan ◽  
Youzhi Han
Keyword(s):  
Abiotic Stress ◽  
Stress Tolerance ◽  
Expression Pattern ◽  
Target Genes ◽  
Abiotic Stress Tolerance ◽  
Critical Role ◽  
Plant Stress ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Go Annotation

Ethylene response factors (ERFs) are plant-specific transcription factors (TFs) that play important roles in plant growth and stress defense and have received a great amount of attention in recent years. In this study, seven ERF genes related to abiotic stress tolerance and response were identified in plants of the Populus genus. Systematic bioinformatics, including sequence phylogeny, genome organisation, gene structure, gene ontology (GO) annotation, etc. were detected. Expression-pattern of these seven ERF genes were analyzed using RT-qPCR and cross validated using RNA-Seq. Data from a phylogenetic tree and multiple alignment of protein sequences indicated that these seven ERF TFs belong to three subfamilies and contain AP2, YRG, and RAYD conserved domains, which may interact with downstream target genes to regulate the plant stress response. An analysis of the structure and promoter region of these seven ERF genes showed that they have multiple stress-related motifs and cis-elements, which may play roles in the plant stress-tolerance process through a transcriptional regulation mechanism; moreover, the cellular_component and molecular_function terms associated with these ERFs determined by GO annotation supported this hypothesis. In addition, the spatio-temporal expression pattern of these seven ERFs, as detected using RT-qPCR and RNA-seq, suggested that they play a critical role in mediating the salt response and tolerance in a dynamic and tissue-specific manner. The results of this study provide a solid basis to explore the functions of the stress-related ERF TFs in Populus abiotic stress tolerance and development process.

scholarly journals Hepatocyte Nuclear Factor 4 alpha (HNF4α) Activation is Essential for Termination of Liver Regeneration

2018 ◽  
Author(s):  
Ian Huck ◽  
Sumedha Gunewardena ◽  
Regina Espanol-Suner ◽  
Holger Willenbring ◽  
Udayan Apte
Keyword(s):  
Gene Expression ◽  
Liver Regeneration ◽  
Target Gene ◽  
Nuclear Factor ◽  
Hepatocyte Nuclear Factor ◽  
Hepatic Differentiation ◽  
Target Gene Expression ◽  
Protein Levels ◽  
Hepatocyte Nuclear Factor 4

AbstractHepatocyte Nuclear Factor 4 alpha (HNF4α) is critical for hepatic differentiation. Recent studies have highlighted its role in inhibition of hepatocyte proliferation and tumor suppression. However, the role of HNF4α in liver regeneration is not known. We hypothesized that hepatocytes modulate HNF4α activity when navigating between differentiated and proliferative states during liver regeneration. Western blot analysis revealed a rapid decline in nuclear and cytoplasmic HNF4α protein levels accompanied with decreased target gene expression within 1 hour after 2/3 partial hepatectomy (post-PH) in C57BL/6J mice. HNF4α protein expression did not recover to the pre-PH levels until day 3. Hepatocyte-specific deletion of HNF4α (HNF4α-KO) in mice resulted in 100% mortality post-PH despite increased proliferative marker expression throughout regeneration. Sustained loss of HNF4α target gene expression throughout regeneration indicated HNF4α-KO mice were unable to compensate for loss of HNF4α transcriptional activity. Deletion of HNF4α resulted in sustained proliferation accompanied by c-myc and cyclin D1 over expression and a complete deficiency of hepatocyte function after PH. Interestingly, overexpression of degradation-resistant HNF4α in hepatocytes did not prevent initiation of regeneration after PH. Finally, AAV8-mediated reexpression of HNF4α in hepatocytes of HNF4α-KO mice post-PH restored HNF4α protein levels, induced target gene expression and improved survival of HNF4α-KO mice post-PH. In conclusion, these data indicate that HNF4α reexpression following initial decrease is critical for hepatocytes to exit from cell cycle and resume function during the termination phase of liver regeneration. These results reveal the role of HNF4α in liver regeneration and have implications for therapy of liver failure.

scholarly journals The role of KMT2D and KDM6A in cardiac development: A cross-species analysis in humans, mice, and zebrafish

2020 ◽  
Author(s):  
Rwik Sen ◽  
Ezra Lencer ◽  
Elizabeth A. Geiger ◽  
Kenneth L. Jones ◽  
Tamim H. Shaikh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Development ◽  
Target Genes ◽  
Cardiac Development ◽  
Heart Defects ◽  
Neural Crest Cell ◽  
Kabuki Syndrome ◽  
Rna Seq ◽  
Wide Range

AbstractCongenital Heart Defects (CHDs) are the most common form of birth defects, observed in 4-10/1000 live births. CHDs result in a wide range of structural and functional abnormalities of the heart which significantly affect quality of life and mortality. CHDs are often seen in patients with mutations in epigenetic regulators of gene expression, like the genes implicated in Kabuki syndrome – KMT2D and KDM6A, which play important roles in normal heart development and function. Here, we examined the role of two epigenetic histone modifying enzymes, KMT2D and KDM6A, in the expression of genes associated with early heart and neural crest cell (NCC) development. Using CRISPR/Cas9 mediated mutagenesis of kmt2d, kdm6a and kdm6al in zebrafish, we show cardiac and NCC gene expression is reduced, which correspond to affected cardiac morphology and reduced heart rates. To translate our results to a human pathophysiological context and compare transcriptomic targets of KMT2D and KDM6A across species, we performed RNA sequencing (seq) of lymphoblastoid cells from Kabuki Syndrome patients carrying mutations in KMT2D and KDM6A. We compared the human RNA-seq datasets with RNA-seq datasets obtained from mouse and zebrafish. Our comparative interspecies analysis revealed common targets of KMT2D and KDM6A, which are shared between species, and these target genes are reduced in expression in the zebrafish mutants. Taken together, our results show that KMT2D and KDM6A regulate common and unique genes across humans, mice, and zebrafish for early cardiac and overall development that can contribute to the understanding of epigenetic dysregulation in CHDs.

scholarly journals An Arabidopsis gene expression predictor enables inference of transcriptional regulators

2020 ◽  
Author(s):  
Haiying Geng ◽  
Meng Wang ◽  
Jiazhen Gong ◽  
Yupu Xu ◽  
Shisong Ma
Keyword(s):  
Gene Expression ◽  
Lateral Root ◽  
Secondary Cell Wall ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Transcriptional Regulators ◽  
Endoplasmic Reticulum Stress Response ◽  
Rna Seq ◽  
Average Correlation ◽  
Cell Wall Development

ABSTRACTGene expression regulation by transcription factors (TF) has long been studied, but no model exists yet that can accurately predict transcriptome profiles based on TF activities. We have constructed a universal predictor for Arabidopsis to predict the expression of 28192 non-TF genes using 1678 TFs. Applied to bulk RNA-Seq samples from diverse tissues, the predictor produced accurate predicted transcriptomes correlating well with actual expression, with average correlation coefficient of 0.986. Having recapitulated the quantitative relationships between TFs and target genes, the predictor further enabled downstream inference of TF regulators for genes and pathways, i.e. those involved in suberin, flavonoid, glucosinolate metabolism, lateral root, xylem, secondary cell wall development, and endoplasmic reticulum stress response. Our predictor provides an innovative approach to study transcriptional regulation.

scholarly journals Raw sequence to target gene prediction: An integrated inference pipeline for ChIP-seq and RNA-seq datasets

2017 ◽  
Author(s):  
Nisar Wani ◽  
Khalid Raza
Keyword(s):  
Gene Expression ◽  
Target Gene ◽  
Target Genes ◽  
Gene Prediction ◽  
Expression Patterns ◽  
Dna Binding Proteins ◽  
Gene Expression Patterns ◽  
Rna Seq ◽  
Cellular Processes ◽  
Regulatory Effects

AbstractGene expression patterns determine the manner whereby organisms regulate various cellular processes and therefore their organ functions.These patterns do not emerge on their own, but as a result of diverse regulatory factors such as, DNA binding proteins known as transcription factors (TF), chromatin structure and various other environmental factors. TFs play a pivotal role in gene regulation by binding to different locations on the genome and influencing the expression of their target genes. Therefore, predicting target genes and their regulation becomes an important task for understanding mechanisms that control cellular processes governing both healthy and diseased cells.In this paper, we propose an integrated inference pipeline for predicting target genes and their regulatory effects for a specific TF using next-generation data analysis tools.

scholarly journals ISMARA: Completely automated inference of gene regulatory networks from high-throughput data

2017 ◽  
Author(s):  
Mikhail Pachkov ◽  
Piotr J Balwierz ◽  
Phil Arnold ◽  
Andreas J Gruber ◽  
Mihaela Zavolan ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Regulatory Networks ◽  
Target Genes ◽  
Chromatin State ◽  
Response Analysis ◽  
Rna Seq ◽  
High Throughput Data ◽  
Micro Rnas ◽  
Gene Regulatory

As the costs of high-throughput measurement technologies continue to fall, experimental approaches in biomedicine are increasingly data intensive and the advent of big data is justifiably seen as holding the promise to transform medicine. However, as data volumes mount, researchers increasingly realize that extracting concrete, reliable, and actionable biological predictions from high-throughput data can be very challenging. Our laboratory has pioneered a number of methods for inferring key gene regulatory interactions from high-throughput data. For example, we developed motif activity response analysis (MARA)[, which models genome-wide gene expression (RNA-Seq, or microarray) and chromatin state (ChIP-Seq) data in terms of comprehensive predictions of regulatory sites for hundreds of mammalian regulators (TFs and micro-RNAs). Using these models, MARA identifies the key regulators driving gene expression and chromatin state changes, the activities of these regulators across the input samples, their target genes, and the sites on the genome through which these regulators act. We recently completely automated MARA in an integrated web-server (ismara.unibas.ch) that allows researchers to analyze their own data by simply uploading RNA-Seq or ChIP-Seq datasets, and provides results in an integrated web interface as well as in downloadable flat form.

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