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      Adipocytes fail to maintain cellular identity during obesity due to reduced PPAR γ activity and elevated TGFβ-SMAD signaling

      research-article
      1 , 2 , 3 , , 1 , 4 , 3 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , ∗∗
      Molecular Metabolism
      Elsevier
      Adipose tissue, Obesity, Cellular identity, NuTRAP, PPARγ, TGFβ-SMAD, T2D, Type 2 diabetes, HFD, high-fat diet, TZDs, thiazolidinediones, Rosi, rosiglitazone, PPARγ, peroxisome proliferator-activated receptor γ, TGFβ, Transforming growth factor beta, eWAT, epididymal white adipose tissue, iWAT, inguinal white adipose tissue, BAT, brown adipose tissue, NuTRAP, nuclear tagging and translating ribosome affinity purification, ChIP-seq, chromatin immunoprecipitation sequencing.

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          Abstract

          Objective

          Obesity due to overnutrition causes adipose tissue dysfunction, which is a critical pathological step on the road to type 2 diabetes (T2D) and other metabolic disorders. In this study, we conducted an unbiased investigation into the fundamental molecular mechanisms by which adipocytes transition to an unhealthy state during obesity.

          Methods

          We used nuclear tagging and translating ribosome affinity purification (NuTRAP) reporter mice crossed with Adipoq-Cre mice to determine adipocyte-specific 1) transcriptional profiles (RNA-seq), 2) promoter and enhancer activity (H3K27ac ChIP-seq), 3) and PPAR γ cistrome (ChIP-seq) profiles in mice fed chow or a high-fat diet (HFD) for 10 weeks. We also assessed the impact of the PPAR γ agonist rosiglitazone (Rosi) on gene expression and cellular state of adipocytes from the HFD-fed mice. We integrated these data to determine the transcription factors underlying adipocyte responses to HFD and conducted functional studies using shRNA-mediated loss-of-function approaches in 3T3-L1 adipocytes.

          Results

          Adipocytes from the HFD-fed mice exhibited reduced expression of adipocyte markers and metabolic genes and enhanced expression of myofibroblast marker genes involved in cytoskeletal organization, accompanied by the formation of actin filament structures within the cell. PPAR γ binding was globally reduced in adipocytes after HFD feeding, and Rosi restored the molecular and cellular phenotypes of adipocytes associated with HFD feeding. We identified the TGFβ1 effector protein SMAD to be enriched at HFD-induced promoters and enhancers and associated with myofibroblast signature genes. TGFβ1 treatment of mature 3T3-L1 adipocytes induced gene expression and cellular changes similar to those seen after HFD in vivo, and knockdown of Smad3 blunted the effects of TGFβ1.

          Conclusions

          Our data demonstrate that adipocytes fail to maintain cellular identity after HFD feeding, acquiring characteristics of a myofibroblast-like cell type through reduced PPAR γ activity and elevated TGFβ-SMAD signaling. This cellular identity crisis may be a fundamental mechanism that drives functional decline of adipose tissues during obesity.

          Highlights

          • Adipocytes after HFD intake exhibit defects in cellular identity maintenance.

          • Adipocytes develop actin filament networks in obesity.

          • Altered PPAR γ activity mediates defective adipocyte identity phenotypes.

          • TGFβ-SMAD pathways promote HFD-induced aberrant phenotype of adipocytes.

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          Most cited references77

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              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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                Author and article information

                Contributors
                Journal
                Mol Metab
                Mol Metab
                Molecular Metabolism
                Elsevier
                2212-8778
                28 September 2020
                December 2020
                28 September 2020
                : 42
                : 101086
                Affiliations
                [1 ]Division of Endocrinology, Diabetes and Obesity, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA
                [2 ]Broad Institute, Cambridge, MA, 02142, USA
                [3 ]Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
                Author notes
                []Corresponding author. Division of Endocrinology, Diabetes and Obesity, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA. hyunroh@ 123456iu.edu
                [∗∗ ]Corresponding author. Broad Institute, Cambridge, MA, 02142, USA. erosen@ 123456bidmc.harvard.edu
                [4]

                Present address: Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany.

                Article
                S2212-8778(20)30160-5 101086
                10.1016/j.molmet.2020.101086
                7559520
                32992037
                1dae6f00-c94d-48b2-a152-3d6b5e4ab841
                © 2020 Published by Elsevier GmbH.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 15 July 2020
                : 9 September 2020
                : 17 September 2020
                Categories
                Original Article

                adipose tissue,obesity,cellular identity,nutrap,pparγ,tgfβ-smad,t2d, type 2 diabetes,hfd, high-fat diet,tzds, thiazolidinediones,rosi, rosiglitazone,pparγ, peroxisome proliferator-activated receptor γ,tgfβ, transforming growth factor beta,ewat, epididymal white adipose tissue,iwat, inguinal white adipose tissue,bat, brown adipose tissue,nutrap, nuclear tagging and translating ribosome affinity purification,chip-seq, chromatin immunoprecipitation sequencing.

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