Impaired LXRα Phosphorylation Attenuates Progression of Fatty Liver Disease

Bécares, Natalia; Gage, Matthew; Voisin, Maud; Shrestha, Elina; Martin-Gutierrez, Lucia; Liang, Ning; Louie, Rikah; Pourcet, Benoît; Pello, Óscar M.; Luong, Tu Vinh; Goñi, Saioa; Pichardo‐Almarza, César; Røberg-Larsen, Hanne; Díaz‐Zuccarini, Vanessa; Steffensen, Knut R.; O’Brien, Alastair; Garabedian, Michael J.; Rombouts, Krista; Treuter, Eckardt; Pineda-Torra, Inés

doi:10.1016/j.celrep.2018.12.094

Cited by 49 publications

(52 citation statements)

References 69 publications

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“…Alternatively, a CSV file from an online data repository can be used through a URL. To demonstrate the features of the app, example data is included of which the details can be found elsewhere (Becares et al, 2019;Gillingham et al, 2019).…”

Section: Data Input and Formatmentioning

confidence: 99%

“…Volcano plots typically show the data of hundreds to ten thousands of genes or proteins. Examples of such datasets are gene expression changes measured by RNA-seq (Becares et al, 2019), genome-wide loss-of-function CRISPR screens (Drainas et al, 2020), or mapping the interactome of proteins-of-interest by mass spectrometry (van der Weegen et al, 2020). Although volcano plots are based on rich datasets, only a handful of data points are usually labeled with a gene or protein name.…”

Section: Introductionmentioning

confidence: 99%

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VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

Goedhart

Luijsterburg

2020

Preprint

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Comparative genome-and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a userdefined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots (https://huygens.science.uva.nl/VolcaNoseR). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome-and proteome-wide datasets.

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Section: Data Input and Formatmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

Goedhart

Luijsterburg

2020

Preprint

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“…Liver X receptors (LXRs) are lipid‐activated TFs that form heterodimers with RXR to control enzymes and transporters involved in cholesterol and fatty acid homeostasis (Hong & Tontonoz, ), as well as inflammatory and immune responses (Tall & Yvan‐Charvet, ). Modulation of LRXα activity has been shown to affect broad hepatic enhancer landscapes and to retard NAFLD progression, by promoting anti‐inflammatory and anti‐fibrotic responses (Becares et al, ). The liver TF carbohydrate responsive element‐binding protein (ChREBP) is a core regulator of hepatic glycolytic and lipogenic genes (Dentin et al, ), which can be regulated by the histone acetyltransferase (HAT) p300, promoting its acetylation and activation.…”

Section: Liver Enhancer Dynamicsmentioning

confidence: 99%

Liver gene regulatory networks: Contributing factors to nonalcoholic fatty liver disease

Cebola

2020

WIREs Mechanisms of Disease

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Metabolic diseases such as nonalcoholic fatty liver disease (NAFLD) result from complex interactions between intrinsic and extrinsic factors, including genetics and exposure to obesogenic environments. These risk factors converge in aberrant gene expression patterns in the liver, which are underlined by altered cis‐regulatory networks. In homeostasis and in disease states, liver cis‐regulatory networks are established by coordinated action of liver‐enriched transcription factors (TFs), which define enhancer landscapes, activating broad gene programs with spatiotemporal resolution. Recent advances in DNA sequencing have dramatically expanded our ability to map active transcripts, enhancers and TF cistromes, and to define the 3D chromatin topology that contains these elements. Deployment of these technologies has allowed investigation of the molecular processes that regulate liver development and metabolic homeostasis. Moreover, genomic studies of NAFLD patients and NAFLD models have demonstrated that the liver undergoes pervasive regulatory rewiring in NAFLD, which is reflected by aberrant gene expression profiles. We have therefore achieved an unprecedented level of detail in the understanding of liver cis‐regulatory networks, particularly in physiological conditions. Future studies should aim to map active regulatory elements with added levels of resolution, addressing how the chromatin landscapes of different cell lineages contribute to and are altered in NAFLD and NAFLD‐associated metabolic states. Such efforts would provide additional clues into the molecular factors that trigger this disease. This article is categorized under: Biological Mechanisms > Metabolism Biological Mechanisms > Regulatory Biology Laboratory Methods and Technologies > Genetic/Genomic Methods

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“…Gene expression was measured by qPCR, as in 21,77 . Primers were used at a final concentration of 100 nM.…”

Section: Analysis Of Gene Expressionmentioning

confidence: 99%

“…To identify potential LXRE sequences we used NHR scan (RRID:SCR_016975) 82 to interrogate the UGCG gene ±20kb, as in 21,77 . Cistrome DB was used to identify LXR ChIP-seq experiments 83,84 .…”

Section: Chromatin Immunoprecipitationmentioning

confidence: 99%

LXR alters CD4⁺ T cell function through direct regulation of glycosphingolipid synthesis

Waddington

Robinson

Rubio-Cuesta

et al. 2019

Preprint

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Liver X Receptors (LXRs) are important transcriptional regulators of intracellular cholesterol, fatty acid, and phospholipid levels. LXRs can dampen inflammation in macrophages by promoting cholesterol efflux and altering plasma membrane lipid rafts; microdomains enriched for cholesterol and glycosphingolipids that regulate immune-cell signalling. However, little is known about the impact of LXR activators on T cell plasma membrane lipid rafts, which are critical for T-cell antigen receptor (TCR) signalling. Here we show that the LXR synthetic agonist GW3965 significantly increases glycosphingolipid levels and reduces cholesterol and lipid order (stability) in the plasma membrane of human CD4 + T cells. Moreover, the GSL biosynthesis enzyme UGCG was identified as a novel direct target of LXR activation. Importantly, LXR-mediated changes in T cell lipid composition were associated with altered spatiotemporal distribution of lipids and signalling molecules at the immune synapse. Crucially, LXR activation altered the kinetics of proximal TCR-signalling events in activated T cells, reduced T cell proliferation and enhanced the production of IL-2 and IL-4. Thus, LXR activation influences T cell function via alteration of the plasma membrane lipid profile. Finally, the expression of UGCG and other LXR-regulated genes and lipids was significantly dysregulated in T-cells isolated from people with multiple sclerosis. Overall, a novel action of LXR has been characterised that involves modulation of lipid raft-associated cholesterol and glycosphingolipids in CD4 + T-cells, which could be of therapeutic relevance in multiple sclerosis. Keywords liver X receptor -CD4 + T cell -lipid metabolismcholesterolglycosphingolipid-multiple sclerosis 3

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Impaired LXRα Phosphorylation Attenuates Progression of Fatty Liver Disease

Cited by 49 publications

References 69 publications

VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

Liver gene regulatory networks: Contributing factors to nonalcoholic fatty liver disease

LXR alters CD4⁺ T cell function through direct regulation of glycosphingolipid synthesis

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Impaired LXRα Phosphorylation Attenuates Progression of Fatty Liver Disease

Cited by 49 publications

References 69 publications

VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots

Liver gene regulatory networks: Contributing factors to nonalcoholic fatty liver disease

LXR alters CD4+ T cell function through direct regulation of glycosphingolipid synthesis

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LXR alters CD4⁺ T cell function through direct regulation of glycosphingolipid synthesis