Molecular MetabolismGenomicsPeer-reviewed journal article
Diet and temperature interactively impact brown adipose tissue gene regulation controlled by DNA methylation
Tobias HagemanniD, Anne HoffmanniD, Kerstin Rohde‐ZimmermanniD, Helen BroghammeriD, Lucas MassieriD, Peter KovacsiD, Michael StümvolliD, Matthias BlüheriD, John T. HeikeriD, Juliane WeineriD
Abstract
Controlling brown adipose tissue (BAT) plasticity in adulthood holds promising potential for effective new obesity therapies by targeting the mechanisms of adaptive thermogenesis. Recent studies have shown that BAT development and function are under epigenetic control, with DNA methylation linked to the regulation of key thermogenic and metabolic genes. Here we sought to understand how diet and cold exposure interactively shape BAT gene regulation controlled by DNA methylation. Mice (N = 8 per group) were housed under cold exposure (8{degrees}C) or thermoneutrality (30{degrees}C) and fed either chow or high-fat diet (HFD). BAT was isolated for transcriptome (RNAseq) and methylome (RRBS) analyses. We identified differentially methylated and expressed genes (DMEGs) by comparing the effects of cold exposure under chow and high-fat diet, as well as by analyzing the interaction between temperature and diet. Functional pathway enrichment and EpiFactors Database screening were used to assess epigenetic regulators, and candidate gene expression was validated by modulating DNA-methylation in vitro. We identified [~]1,360 differentially expressed genes (DEGs) uniquely affected by the diet-temperature interaction with most downregulated in HFD-fed mice, indicating that obesity limits the transcriptional response of BAT to cold. 65 DMEGs (4% of DEGs) were largely diet-specific in response to cold exposure, suggesting that DNA methylation contributes to a selective layer of gene regulation during BAT adaptation to distinct metabolic states. In HFD-fed mice, DMEGs were enriched in pathways related to mitochondrial dysfunction, altered lipid metabolism, neuroendocrine signaling, and compensatory stress responses, contrasting the adaptive thermogenic profile observed in chow-fed controls. Differentially expressed genes of epigenetic regulators such as Tet2, Dnmt3a and Apobec1 showed diet- and cold-dependent regulation, indicating impaired methylation flexibility under obesogenic conditions. Using cell culture experiments, we confirmed the regulation of gene expression of candidate genes, validating the functional link between DNA methylation and thermogenic gene regulation. This is the first study to demonstrate an epigenetic response to cold exposure that differs by dietary condition, particularly in obesity. Our findings highlight a coordinated transcriptional and epigenetic remodeling of BAT, shaped by both environmental and metabolic signals. These insights may inform targeted epigenetic or nutritional strategies to restore BAT function and would further strengthen our understanding of how these might be used as therapeutic basis to improve metabolic health in obesity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/672110v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1f99b80org.highwire.dtl.DTLVardef@502d02org.highwire.dtl.DTLVardef@1bb0a93org.highwire.dtl.DTLVardef@b34e4c_HPS_FORMAT_FIGEXP M_FIG C_FIG Mice were housed under cold exposure or thermoneutrality and fed either chow or high-fat diet (HFD). RNA sequencing (RNAseq) and reduced representation bisulfite sequencing (RRBS) was performed on brown adipose tissue (BAT) which provide the fundament for the identification of differentially methylated positions (DMP) and regions (DMR) as well as differentially expressed genes (DEG) in three models: COLDchow, comparing 8{degrees} vs 30{degrees}C mice on chow diet; COLDHFD, comparing 8{degrees} vs 30{degrees}C mice on HFD diet and{Delta} COLDdiet, comparing COLDchow vs COLDHFD. Differentially methylated and expressed genes (DMEGs; circos plot shows a representative example) were identified for all comparisons based on those DMPs which correlated significantly with differentially expressed genes (DEGs; the heatmap shows a representative example). DMEGs were taken forward for pathways enrichment analyses and to identify differentially regulated epigenetic regulators using the EpiFactors Database. The figure was created with BioRender.
- organism: mouse
- assay: bulk RNA-seq
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 1
- FWCI
- 4.51
- Field percentile
- top 12%
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