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人类产热脂肪细胞的调节模块:大样本队列的功能基因组学和 Meta 分析衍生的标记基因。

Regulatory modules of human thermogenic adipocytes: functional genomics of large cohort and Meta-analysis derived marker-genes.

机构信息

Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem Tér 1, Debrecen, H-4032, Hungary.

MTA-DE Behavioural Ecology Research Group, Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, Debrecen, H-4032, Hungary.

出版信息

BMC Genomics. 2021 Dec 11;22(1):886. doi: 10.1186/s12864-021-08126-8.

Abstract

BACKGROUND

Recently, ProFAT and BATLAS studies identified brown and white adipocytes marker genes based on analysis of large databases. They offered scores to determine the thermogenic status of adipocytes using the gene-expression data of these markers. In this work, we investigated the functional context of these genes.

RESULTS

Gene Set Enrichment Analyses (KEGG, Reactome) of the BATLAS and ProFAT marker-genes identified pathways deterministic in the formation of brown and white adipocytes. The collection of the annotated proteins of the defined pathways resulted in expanded white and brown characteristic protein-sets, which theoretically contain all functional proteins that could be involved in the formation of adipocytes. Based on our previously obtained RNA-seq data, we visualized the expression profile of these proteins coding genes and found patterns consistent with the two adipocyte phenotypes. The trajectory of the regulatory processes could be outlined by the transcriptional profile of progenitor and differentiated adipocytes, highlighting the importance of suppression processes in browning. Protein interaction network-based functional genomics by STRING, Cytoscape and R-Igraph platforms revealed that different biological processes shape the brown and white adipocytes and highlighted key regulatory elements and modules including GAPDH-CS, DECR1, SOD2, IL6, HRAS, MTOR, INS-AKT, ERBB2 and 4-NFKB, and SLIT-ROBO-MAPK. To assess the potential role of a particular protein in shaping adipocytes, we assigned interaction network location-based scores (betweenness centrality, number of bridges) to them and created a freely accessible platform, the AdipoNET ( https//adiponet.com ), to conveniently use these data. The Eukaryote Promoter Database predicted the response elements in the UCP1 promoter for the identified, potentially important transcription factors (HIF1A, MYC, REL, PPARG, TP53, AR, RUNX, and FoxO1).

CONCLUSION

Our integrative approach-based results allowed us to investigate potential regulatory elements of thermogenesis in adipose tissue. The analyses revealed that some unique biological processes form the brown and white adipocyte phenotypes, which presumes the existence of the transitional states. The data also suggests that the two phenotypes are not mutually exclusive, and differentiation of thermogenic adipocyte requires induction of browning as well as repressions of whitening. The recognition of these simultaneous actions and the identified regulatory modules can open new direction in obesity research.

摘要

背景

最近,ProFAT 和 BATLAS 研究基于对大型数据库的分析,确定了棕色和白色脂肪细胞标记基因,并提供了评分,以利用这些标记基因的基因表达数据来确定脂肪细胞的产热状态。在这项工作中,我们研究了这些基因的功能背景。

结果

BATLAS 和 ProFAT 标记基因的基因集富集分析(KEGG、Reactome)鉴定了决定棕色和白色脂肪细胞形成的途径。所定义途径注释蛋白的集合导致了扩展的白色和棕色特征蛋白集,理论上包含了所有可能参与脂肪细胞形成的功能蛋白。基于我们之前获得的 RNA-seq 数据,我们可视化了这些蛋白质编码基因的表达谱,并发现了与两种脂肪细胞表型一致的模式。通过祖细胞和分化的脂肪细胞的转录谱可以描绘出调控过程的轨迹,突出了褐变过程中抑制过程的重要性。STRING、 Cytoscape 和 R-Igraph 平台的基于蛋白质相互作用网络的功能基因组学揭示了不同的生物学过程塑造了棕色和白色脂肪细胞,并突出了关键的调节因子和模块,包括 GAPDH-CS、 DECR1、 SOD2、 IL6、 HRAS、 MTOR、 INS-AKT、 ERBB2 和 4-NFKB,以及 SLIT-ROBO-MAPK。为了评估特定蛋白质在塑造脂肪细胞中的潜在作用,我们根据它们在互作网络中的位置(介数中心度、桥梁数量)为它们分配了分数,并创建了一个可免费访问的平台,AdipoNET(https://adiponet.com),以方便使用这些数据。真核启动子数据库预测了 UCP1 启动子中已识别的潜在重要转录因子(HIF1A、MYC、REL、PPARG、TP53、AR、RUNX 和 FoxO1)的反应元件。

结论

我们基于整合方法的结果允许我们研究脂肪组织中产热的潜在调节因子。分析表明,一些独特的生物学过程形成了棕色和白色脂肪细胞表型,这意味着存在过渡状态。这些数据还表明,这两种表型并非相互排斥,生热脂肪细胞的分化既需要诱导褐变,也需要抑制白化。识别这些同时发生的作用和已确定的调节模块可以为肥胖研究开辟新的方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cde8/8665548/58e7b1a4bdf0/12864_2021_8126_Fig1_HTML.jpg

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