Dynamic DNA methylation landscape defines brown and white cell specificity during adipogenesis

Objective: DNA methylation may be a stable epigenetic contributor to defining fat cell lineage. Methods: We performed reduced representation bisulfite sequencing (RRBS) and RNA-seq to depict a genome-wide integrative view of the DNA methylome and transcriptome during brown and white adipogenesis. Results: Our analysis demonstrated that DNA methylation is a stable epigenetic signature for brown and white cell lineage before, during, and after differentiation. We identified 31 genes whose promoters were significantly differentially methylated between white and brown adipogenesis at all three time points of differentiation. Among them, five genes belong to the Hox family; their expression levels were anti-correlated with promoter methylation, suggesting a regulatory role of DNA methylation in transcription. Blocking DNA methylation with 5-Aza-cytidine increased the expression of these genes, with the most prominent effect on Hoxc10, a repressor of BAT marker expression. Conclusions: Our data suggest that DNA methylation may play an important role in lineage-specific development in adipocytes.ASTAR (Agency for Sci., Tech. and Research, S’pore)NMRC (Natl Medical Research Council, S’pore)Published versio

Increased expression of pathological markers in Parkinson's disease dementia post-mortem brains compared to dementia with Lewy bodies

Background: Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) are common age-related neurodegenerative diseases comprising Lewy body spectrum disorders associated with cortical and subcortical Lewy body pathology. Over 30% of PD patients develop PD dementia (PDD), which describes dementia arising in the context of established idiopathic PD. Furthermore, Lewy bodies frequently accompany the amyloid plaque and neurofibrillary tangle pathology of Alzheimer’s disease (AD), where they are observed in the amygdala of approximately 60% of sporadic and familial AD. While PDD and DLB share similar pathological substrates, they differ in the temporal onset of motor and cognitive symptoms; however, protein markers to distinguish them are still lacking. Methods: Here, we systematically studied a series of AD and PD pathogenesis markers, as well as mitochondria, mitophagy, and neuroinflammation-related indicators, in the substantia nigra (SN), temporal cortex (TC), and caudate and putamen (CP) regions of human post-mortem brain samples from individuals with PDD and DLB and condition-matched controls. Results: We found that p-APPT668 (TC), α-synuclein (CP), and LC3II (CP) are all increased while the tyrosine hydroxy lase (TH) (CP) is decreased in both PDD and DLB compared to control. Also, the levels of Aβ42 and DD2R, IBA1, and p-LRRK2S935 are all elevated in PDD compared to control. Interestingly, protein levels of p-TauS199/202 in CP and DD2R, DRP1, and VPS35 in TC are all increased in PDD compared to DLB. Conclusions: Together, our comprehensive and systematic study identified a set of signature proteins that will help to understand the pathology and etiology of PDD and DLB at the molecular level.Ministry of Health (MOH)National Medical Research Council (NMRC)Published versionThis research was supported by Open Fund-Large Collaborative Grant (LCG002–SPARK II) and Open Fund-Individual Research Grant (No. NMRC/ OFIRG/0074/2018), administered by the Singapore Ministry of Health’s National Medical Research Council

De novo reconstruction of human adipose transcriptome reveals conserved lncRNAs as regulators of brown adipogenesis

Obesity has emerged as an alarming health crisis due to its association with metabolic risk factors such as diabetes, dyslipidemia, and hypertension. Recent work has demonstrated the multifaceted roles of lncRNAs in regulating mouse adipose development, but their implication in human adipocytes remains largely unknown. Here we present a catalog of 3149 adipose active lncRNAs, of which 909 are specifically detected in brown adipose tissue (BAT) by performing deep RNA-seq on adult subcutaneous, omental white adipose tissue and fetal BATs. A total of 169 conserved human lncRNAs show positive correlation with their nearby mRNAs, and knockdown assay supports a role of lncRNAs in regulating their nearby mRNAs. The knockdown of one of those, lnc-dPrdm16, impairs brown adipocyte differentiation in vitro and a significant reduction of BAT-selective markers in in vivo. Together, our work provides a comprehensive human adipose catalog built from diverse fat depots and establishes a roadmap to facilitate the discovery of functional lncRNAs in adipocyte development.NRF (Natl Research Foundation, S’pore)MOE (Min. of Education, S’pore)NMRC (Natl Medical Research Council, S’pore)Published versio

Altered striatal dopamine levels in Parkinson's disease VPS35 D620N mutant transgenic aged mice

Vacuolar protein sorting 35 (VPS35) is a major component of the retromer complex that mediates the retrograde transport of cargo proteins from endosomes to the trans-Golgi network. Mutations such as D620N in the VPS35 gene have been identified in patients with autosomal dominant Parkinson's disease (PD). However, it remains poorly understood whether and how VPS35 deficiency or mutation contributes to PD pathogenesis; specifically, the studies that have examined VPS35 thus far have differed in results and methodologies. We generated a VPS35 D620N mouse model using a Rosa26-based transgene expression platform to allow expression in a spatial manner, so as to better address these discrepancies. Here, aged (20-months-old) mice were first subjected to behavioral tests. Subsequently, DAB staining analysis of substantia nigra (SN) dopaminergic neurons with the marker for tyrosine hydroxylase (TH) was performed. Next, HPLC was used to determine dopamine levels, along with levels of its two metabolites, 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA), in the striatum. Western blotting was also performed to study the levels of key proteins associated with PD. Lastly, autoradiography (ARG) evaluation of [3H]FE-PE2I binding to the striatal dopamine transporter DAT was carried out. We found that VPS35 D620N Tg mice displayed a significantly higher dopamine level than NTg counterparts. All results were then compared with that of current VPS35 studies to shed light on the disease pathogenesis. Our model allows future studies to explicitly control spatial expression of the transgene which would generate a more reliable PD phenotype.National Medical Research Council (NMRC)Published versionThis research was supported by the Open Fund-Large Collaborative Grant [OFLCG18May-0026]; and Open Fund-Individual Research Grant [NMRC/OFIRG/0074/2018] administered by the Singapore Ministry of Health’s National Medical Research Council

Dynamic transcriptome changes during adipose tissue energy expenditure reveal critical roles for long noncoding RNA regulators

<div><p>Enhancing brown fat activity and promoting white fat browning are attractive therapeutic strategies for treating obesity and associated metabolic disorders. To provide a comprehensive picture of the gene regulatory network in these processes, we conducted a series of transcriptome studies by RNA sequencing (RNA-seq) and quantified the mRNA and long noncoding RNA (lncRNA) changes during white fat browning (chronic cold exposure, beta-adrenergic agonist treatment, and intense exercise) and brown fat activation or inactivation (acute cold exposure or thermoneutrality, respectively). mRNA–lncRNA coexpression networks revealed dynamically regulated lncRNAs to be largely embedded in nutrient and energy metabolism pathways. We identified a brown adipose tissue–enriched lncRNA, lncBATE10, that was governed by the cAMP-cAMP response element-binding protein (Creb) axis and required for a full brown fat differentiation and white fat browning program. Mechanistically, lncBATE10 can decoy Celf1 from Pgc1α, thereby protecting Pgc1α mRNA from repression by Celf1. Together, these studies provide a comprehensive data framework to interrogate the transcriptomic changes accompanying energy homeostasis transition in adipose tissue.</p></div

Transcriptome landscape associated with browning of white adipose tissue (WAT).

<p><b>(A)</b> Schematic representation of the 3 treatments (chronic cold exposure at 4°C, treatment with β3-adrenoceptor agonist, CL316243, or swimming exercise) used to induce browning of WAT in mice. <b>(B,C)</b> Hierarchical clustering (Ward’s method, spearman correlation) of treatments based on RNA sequencing–derived gene expression profiles (mRNA and long noncoding RNA [lncRNA]) of adipose tissue undergoing browning. <b>(D-G)</b> Venn analysis of overlap between significantly differentially expressed mRNA and lncRNA (false discovery rate [FDR] ≤ 0.05, absolute log2FC ≥ 1) during adipose tissue browning induced by the 3 treatments. <b>(H,I)</b> Scatterplot depicting the significance of overlap between differentially expressed browning-related mRNAs (<b>H</b>) and lncRNAs (<b>I</b>) and their tissue-specific expression patterns. Significance of overlap between tissue-specific and browning-related gene expression was estimated via FDR based on the hypergeometric test. <b>(J)</b> Scatterplot depicting significance of overlap (FDR) between transcription factor binding sites (from chromatin immunoprecipitation sequencing [ChIP-seq] data) and the promoters of browning-induced genes under the 3 treatments. The dash line indicates the position of FDR 0.25. <b>(K)</b> Overlap of the genomic location of brown adipose tissue–enriched lncRNA 10 (lncBATE10) with Peroxisome proliferator-activated receptor gamma (PPARγ) and PR domain containing 16 (PRDM16) binding sites. The PPARγ and PRDM16 binding sites are indicated by red bars. The 3 tracks at the bottom represent the relative abundance of RNA sequencing reads (corresponding to exons) in this region for the different browning-inducing treatments.</p

Transcription of brown adipose tissue–enriched lncRNA 10 (lncBATE10) is controlled by cAMP-cAMP response element-binding protein (Creb) signaling pathway.

<p>(<b>A</b>) Real-time PCR analysis of the expression of lncBATE10 in primary brown adipocytes culture treated with cAMP and norepinephrine (NE) for 4 hours. <i>n</i> = 3 (<b>B</b>) Potential transcriptional factor binding sites in the lncBATE10 promoter region. Predicted by online program MatInspector (<a href="http://www.genomatix.de" target="_blank">www.genomatix.de</a>). The arrow indicates the transcriptional orientation. (<b>C</b>) LncBATE10 Promoter reporter assay. Promoter regions upstream of the transcriptional start site of lncBATE10 with different truncations were cloned into pGL3-Basic vector. Reporters were transfected into 293T cells. Thirty-six hours after transfection, cells were further treated with 1 uM forskolin for 2 hours and subjected to luciferase assay. Error bars are mean ± SEM, <i>n</i> = 3, *<i>P</i> < 0.05 (Student <i>t</i> test). (<b>D</b>) Four site-specific mutations were made in the functional Creb binding site to construct the mutant promoter. (E) 293T cells transfected with wide-type or mutant reporter were treated with a different dose of forskolin, followed by luciferase assay. Data were normalized by Renilla activities of a cotransfected pRL-CMV plasmid. Error bars are mean ± SEM, <i>n</i> = 3, *<i>P</i> < 0.05 (1-way ANOVA). (F) Chromatin immunoprecipitation (ChIP)-PCR with primers detecting the CREB binding site and a control region 3,000 bp upstream the promoter before and after forskolin treatment. The individual numerical values that underlie the summary data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002176#pbio.2002176.s020" target="_blank">S13 Data</a>.</p

Brown adipose tissue–enriched lncRNA 10 (lncBATE10) is required for a brown adipose tissue (BAT)-selective gene program in brown adipocytes.

<p>(<b>A</b>) Northern blot to examine the expression of lncBATE10 in mouse brown-, inguinal-, and epididymal adipose tissues. (<b>B</b>) Real-time PCR result of lncBATE10 across mouse tissues and (<b>C</b>) differentiation time course of primary brown and white adipocyte culture. Error bars represent mean ± SEM, <i>n</i> = 3. *<i>P</i> < 0.05. (<b>D</b>) Expression of lncBATE10 in BAT isolated from animals treated with acute cold exposure (4°C for 6 hours). Error bars represent mean ± SEM, <i>n</i> = 4. *<i>P</i> < 0.05. (<b>E</b>) Hosted at thermoneutrality (30°C for 7 days). Error bars represent mean ± SEM, <i>n</i> = 4. *<i>P</i> < 0.05. <b>(F)</b> Expression of lncBATE10 in inguinal white adipose tissue (iWAT) browning, induced by indicated conditions. Error bars represent mean ± SEM, <i>n</i> ≥ 6. *<i>P</i> < 0.05. (<b>G</b>) Primary brown preadipocytes were infected by retroviral control small hairpin RNA (shRNA) and shRNAs targeting lncBATE10, followed by differentiation for 5 days. Oil-red-O (ORO) staining was conducted to examine the lipid accumulation. (<b>H</b>) Real-time PCR was used to detect the expression of lncBATE10, (<b>I</b>) pan-adipogenic markers, and (<b>J</b>) BAT-selective markers. Error bars represent mean ± SEM, <i>n</i> = 4. *<i>P</i> < 0.05. (<b>K</b>) Western blot to examine the expression of Ucp1, Pgc1α, and Peroxisome proliferator-activated receptor gamma (Pparγ) upon lncBATE10 knockdown. (<b>L</b>) Gene-set enrichment analysis (GSEA) analysis was performed on RNA-seq data from control and lncBATE10 knockdown BAT samples. An enrichment plot for genes involved in respiratory electron transport pathway is shown. (<b>M</b>) Expression of thermogenic gene Ucp1 and Pgc1α in the norepinephrine (NE)-treated control and the shRNA-infected brown adipocytes treated. Error bars represent mean ± SEM, <i>n</i> = 4. *<i>P</i> < 0.05 (Student <i>t</i> test). The individual numerical values that underlie the summary data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002176#pbio.2002176.s020" target="_blank">S13 Data</a>.</p

Brown adipose tissue–enriched lncRNA 10 (lncBATE10) is required for a brown adipose tissue (BAT)-selective gene program in the browning of white fat.

<p><b>(A)</b> The effect of lncBATE10 knockdown on lipid accumulation in primary white adipocyte culture was examined by Oil-Red-O (ORO) staining. <b>(B)</b> The knockdown efficiency, <b>(C)</b> pan-adipogenic markers, <b>(D)</b> mitochondria genes, and <b>(E)</b> BAT-selective genes were examined by real-time PCR. Error bars represent mean ± SEM, <i>n</i> = 3. *<i>P</i> < 0.05 (1-way ANOVA). <b>(F)</b> Gene-set enrichment analysis (GSEA) analysis was performed on RNA-seq data from control and lncBATE10 knockdown white adipose tissue (WAT) samples. An enrichment plot for genes involved in respiratory electron transport pathway is shown. <b>(G)</b> Heatmap for significantly affected Reactome pathways (false discovery rate [FDR] < 0.05) due to lncBATE10 knockout in brown and white adipocyte cultures. The heatmap is color coded by the pathway normalized enrichment scores (NES) obtained from GSEA, with blue representing down-regulated pathways and purple representing up-regulated pathways in knockout samples. <b>(H)</b> Cidea and <b>(I)</b> Ucp1 expression were examined by real-time PCR to determine the effect of lncBATE10 deception on browning induced by rosiglitazone and norepinephrine (NE). Error bars represent mean ± SEM, <i>n</i> = 4. *<i>P</i> < 0.05. <b>(J)</b> The in vivo function of lncBATE10 depletion on maker expression was examined by real-time PCR on inguinal white adipose tissue (iWAT) injected with adenovirus expressing empty vector or small hairpin RNA (sh)-lncBATE10. <b>(K)</b> Western blot was performed to examine the expression of Ucp1 and Pgc1α. Error bars represent mean ± SEM, <i>n</i> = 8. *<i>P</i> < 0.05 (Student <i>t</i> test). The individual numerical values that underlie the summary data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002176#pbio.2002176.s020" target="_blank">S13 Data</a>.</p

Gene and network expression in browning and whitening studies.

<p><b>(A)</b> Schematic representation of cellular transitions in brown adipose tissue (BAT) due to cold (4°C) or warm exposure (30°C). <b>(B,C)</b> Comparison of the overlap between differentially expressed genes due to contrasting thermal shifts in BAT. Genes (mRNAs) up-regulated at 4°C are compared to genes down-regulated at 30°C (B) and vice versa (C). <b>(D)</b> Five-way Venn diagram comparing the overlap among significantly up-regulated long noncoding RNAs (lncRNAs) due to browning-inducing treatments in white adipose tissue (WAT) and cold exposure in BAT, and lncRNAs significantly down-regulated in BAT due to exposure at 30°C. <b>(E)</b> Heatmap summarizing expression patterns of lncRNAs regulated in at least 4 out of 5 conditions. The—log false discovery rate (FDR) was used as input. <b>(F,G)</b> Principal components analysis (PCA) on mRNA and lncRNA expression in response to treatments of WAT and BAT. Genes with a fragments per kilobase of exon per million reads (FPKM) > 5 are included for both plots. Treatments are color coded as per the PCA legend, with squares and circles representing WAT and BAT samples, respectively. The first 2 principal components are plotted, and the percent variation of mRNA/lncRNA expression explained by each component is noted in the axis label. <b>(H)</b> mRNA–lncRNA coexpression network based on expression data from WAT and BAT samples. Included in the analysis were 819 mRNAs and 79 lncRNAs showing differential expression in at least 3 of 5 conditions (FDR ≤ 5%, ≥2-fold absolute change). The partial correlation matrix for each pair of mRNAs/lncRNAs was determined via GeneNet, and a clustered gene coexpression network was constructed using iGraph. The size of the cluster was proportional to the number of mRNAs/lncRNAs contained in it, and the width of the edges connecting the clusters was proportional to the total number of inter-cluster links arising from correlated genes in the different clusters. The major functional categories, and the overrepresentation of Gene Ontology Biological Processes (GOBPs) in each cluster, were determined via PANTHER. GOBPs were categorized into 4 broad groups in each cluster. Statistical overrepresentation of GOBP in each cluster was tested via the binomial test. Highly significant processes (<i>P</i> < 1E⁻⁰⁹) are listed beside their relevant clusters.</p