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Lei Y, Liang X, Sun Y, Yao T, Gong H, Chen Z, Gao Y, Wang H, Wang R, Huang Y, Yang T, Yu M, Liu L, Yi CX, Wu QF, Kong X, Xu X, Liu S, Zhang Z, Liu T. Region-specific transcriptomic responses to obesity and diabetes in macaque hypothalamus. Cell Metab 2024; 36:438-453.e6. [PMID: 38325338 DOI: 10.1016/j.cmet.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/27/2023] [Accepted: 01/05/2024] [Indexed: 02/09/2024]
Abstract
The hypothalamus plays a crucial role in the progression of obesity and diabetes; however, its structural complexity and cellular heterogeneity impede targeted treatments. Here, we profiled the single-cell and spatial transcriptome of the hypothalamus in obese and sporadic type 2 diabetic macaques, revealing primate-specific distributions of clusters and genes as well as spatial region, cell-type-, and gene-feature-specific changes. The infundibular (INF) and paraventricular nuclei (PVN) are most susceptible to metabolic disruption, with the PVN being more sensitive to diabetes. In the INF, obesity results in reduced synaptic plasticity and energy sensing capability, whereas diabetes involves molecular reprogramming associated with impaired tanycytic barriers, activated microglia, and neuronal inflammatory response. In the PVN, cellular metabolism and neural activity are suppressed in diabetic macaques. Spatial transcriptomic data reveal microglia's preference for the parenchyma over the third ventricle in diabetes. Our findings provide a comprehensive view of molecular changes associated with obesity and diabetes.
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Affiliation(s)
- Ying Lei
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China
| | - Xian Liang
- State Key Laboratory of Genetic Engineering, Department of Endocrinology and Metabolism, Human Phenome Institute, Institute of Metabolism and Integrative Biology, and School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200438, China; School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Yunong Sun
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China
| | - Ting Yao
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi'an Jiaotong University School of Medicine, Xi'an, Shanxi 710063, China
| | - Hongyu Gong
- School of Life Sciences, Institues of Biomedical Sciences, Inner Mongolia University, Hohhot 010000, China
| | - Zhenhua Chen
- State Key Laboratory of Molecular Development Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yuanqing Gao
- Jiangsu Provincial Key Laboratory of Cardiovascular and Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing 211166, China
| | - Hui Wang
- School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ru Wang
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China
| | - Yunqi Huang
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China
| | - Tao Yang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Miao Yu
- School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Longqi Liu
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China
| | - Chun-Xia Yi
- Department of Endocrinology and Metabolism, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105AZ Amsterdam, the Netherlands
| | - Qing-Feng Wu
- State Key Laboratory of Molecular Development Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xingxing Kong
- School of Life Sciences, Fudan University, Shanghai 200438, China.
| | - Xun Xu
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China.
| | - Shiping Liu
- BGI-Research, Hangzhou 310012, China; BGI-Research, Shenzhen 518103, China.
| | - Zhi Zhang
- State Key Laboratory of Genetic Engineering, Department of Endocrinology and Metabolism, Human Phenome Institute, Institute of Metabolism and Integrative Biology, and School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200438, China; School of Life Sciences, Fudan University, Shanghai 200438, China.
| | - Tiemin Liu
- State Key Laboratory of Genetic Engineering, Department of Endocrinology and Metabolism, Human Phenome Institute, Institute of Metabolism and Integrative Biology, and School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200438, China; School of Life Sciences, Fudan University, Shanghai 200438, China; School of Life Sciences, Institues of Biomedical Sciences, Inner Mongolia University, Hohhot 010000, China.
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Expression patterns of AMPK and genes associated with lipid metabolism in newly hatched chicks during the metabolic perturbation of fasting and refeeding. Poult Sci 2022; 101:102231. [PMID: 36334428 PMCID: PMC9630794 DOI: 10.1016/j.psj.2022.102231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 09/26/2022] [Accepted: 10/01/2022] [Indexed: 11/07/2022] Open
Abstract
Fasting–refeeding perturbation has been extensively used to reveal specific genes and metabolic pathways that control energy metabolism in chickens. In this study, 200 chickens were randomly assigned to 2 groups after hatching: the control group (C, fed ad libitum) and the fasting–refeeding group (T, water ad libitum). The chicks in Group T were fasted for 72 h, and then fed for another 48 h. Liver, hypothalamus, and adipose samples were collected at 0 (F0), 24 (F24), 48 (F48), and 72 h (F72) after fasting and 4 (FR4), 12 (FR12), 24 (FR24), and 48 h (FR48) after refeeding, respectively. Results showed that Group T had a significantly higher number of liver vacuoles (P < 0.05 or P < 0.01) and a significantly lower gray value of Sudan IIIstained sections (P < 0.05 or P < 0.01) than Group C at F48–FR48. In addition, compared with the Group C, fasting and refeeding reduced the expression of stearoyl CoA desaturase (SCD) mRNA (P < 0.05 or P < 0.01) in the liver and adipose tissues, the expression of glucocorticoid receptor (GR) mRNA (P < 0.05 or P < 0.01) in the liver, adipose, and hypothalamus tissues, and the expression of fatty acid synthase (FAS) mRNA (P < 0.05 or P < 0.01) in the liver at F24–FR24. Moreover, relative to those in Group C, fasting and refeeding increased the mRNA expression levels of adenosine monophosphate-activated protein kinase (AMPK) α, AMPKβ, and AMPKγ in the hypothalamus (P < 0.05 or P < 0.01) at F24–FR24. In conclusion, fasting and refeeding increased the fat content of the liver, and the expression of lipolytic genes in the hypothalamus (e.g., AMPKα, AMPKβ, and AMPKγ) but decreased the expression of fat synthesis genes in the liver (e.g., SCD, GR, and FAS), adipose (SCD and GR), and hypothalamus (GR).
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