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单细胞 RNA 测序与单细胞蛋白质组学联合鉴定了高脂饮食诱导的小鼠胰岛细胞亚群的代谢适应性。

Single-cell RNA sequencing combined with single-cell proteomics identifies the metabolic adaptation of islet cell subpopulations to high-fat diet in mice.

机构信息

Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

BGI-Shenzhen, Shenzhen, China.

出版信息

Diabetologia. 2023 Apr;66(4):724-740. doi: 10.1007/s00125-022-05849-5. Epub 2022 Dec 20.

DOI:10.1007/s00125-022-05849-5
PMID:36538064
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9765371/
Abstract

AIMS/HYPOTHESIS: Islets have complex heterogeneity and subpopulations. Cell surface markers representing alpha, beta and delta cell subpopulations are urgently needed for investigations to explore the compositional changes of each subpopulation in obesity progress and diabetes onset, and the adaptation mechanism of islet metabolism induced by a high-fat diet (HFD).

METHODS

Single-cell RNA sequencing (scRNA-seq) was applied to identify alpha, beta and delta cell subpopulation markers in an HFD-induced mouse model of glucose intolerance. Flow cytometry and immunostaining were used to sort and assess the proportion of each subpopulation. Single-cell proteomics was performed on sorted cells, and the functional status of each alpha, beta and delta cell subpopulation in glucose intolerance was deeply elucidated based on protein expression.

RESULTS

A total of 33,999 cells were analysed by scRNA-seq and clustered into eight populations, including alpha, beta and delta cells. For alpha cells, scRNA-seq revealed that the Ace2 subpopulation had downregulated expression of genes related to alpha cell function and upregulated expression of genes associated with beta cell characteristics in comparison with the Ace2 subpopulation. The impaired function and increased fragility of ACE2 alpha cells exposure to HFD was further suggested by single-cell proteomics. As for beta cells, the CD81 subpopulation may indicate an immature signature of beta cells compared with the CD81 subpopulation, which had robust function. We also found differential expression of Slc2a2 in delta cells and a potentially stronger cellular function and metabolism in GLUT2 delta cells than GLUT2 delta cells. Moreover, an increased proportion of ACE2 alpha cells and CD81 beta cells, with a constant proportion of GLUT2 delta cells, were observed in HFD-induced glucose intolerance.

CONCLUSIONS/INTERPRETATION: We identified ACE2, CD81 and GLUT2 as surface markers to distinguish, respectively, alpha, beta and delta cell subpopulations with heterogeneous maturation and function. The changes in the proportion and functional status of islet endocrine subpopulations reflect the metabolic adaptation of islets to high-fat stress, which weakened the function of alpha cells and enhanced the function of beta and delta cells to bring about glycaemic homeostasis. Our findings provide a fundamental resource for exploring the mechanisms maintaining each islet endocrine subpopulation's fate and function in health and disease.

DATA AVAILABILITY

The scRNA-seq analysis datasets from the current study are available in the Gene Expression Omnibus (GEO) repository under the accession number GSE203376.

摘要

目的/假设:胰岛具有复杂的异质性和亚群。细胞表面标志物代表 alpha、beta 和 delta 细胞亚群,对于研究肥胖进展和糖尿病发病过程中每个亚群组成的变化以及高脂肪饮食(HFD)诱导的胰岛代谢适应机制非常重要。

方法

应用单细胞 RNA 测序(scRNA-seq)鉴定 HFD 诱导的葡萄糖耐量受损小鼠模型中 alpha、beta 和 delta 细胞亚群标志物。采用流式细胞术和免疫染色对各亚群进行分选和评估。对分选细胞进行单细胞蛋白质组学分析,根据蛋白质表达深入阐明葡萄糖耐量受损时每个 alpha、beta 和 delta 细胞亚群的功能状态。

结果

通过 scRNA-seq 分析了 33999 个细胞,并聚类为 8 个群体,包括 alpha、beta 和 delta 细胞。对于 alpha 细胞,scRNA-seq 显示与 Ace2 亚群相比,Ace2 亚群中与 alpha 细胞功能相关的基因表达下调,与 beta 细胞特征相关的基因表达上调。单细胞蛋白质组学进一步表明,HFD 暴露会损害 ACE2 alpha 细胞的功能并增加其脆弱性。对于 beta 细胞,与功能强大的 CD81 亚群相比,CD81 亚群可能提示 beta 细胞具有不成熟的特征。我们还发现 delta 细胞中 Slc2a2 表达差异,GLUT2 delta 细胞比 GLUT2 delta 细胞具有更强的细胞功能和代谢。此外,在 HFD 诱导的葡萄糖耐量受损中,ACE2 alpha 细胞和 CD81 beta 细胞的比例增加,而 GLUT2 delta 细胞的比例保持不变。

结论/解释:我们确定 ACE2、CD81 和 GLUT2 分别作为表面标志物,以区分具有不同成熟度和功能的 alpha、beta 和 delta 细胞亚群。胰岛内分泌亚群比例和功能状态的变化反映了胰岛对高脂肪应激的代谢适应,削弱了 alpha 细胞的功能,增强了 beta 和 delta 细胞的功能,从而实现血糖稳态。我们的研究结果为探索维持健康和疾病状态下每个胰岛内分泌亚群命运和功能的机制提供了基础资源。

数据可用性

本研究的 scRNA-seq 分析数据集可在基因表达综合数据库(GEO)中以注册号 GSE203376 获得。

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