Author
Listed:
- Lianhui Sun
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Guangjian Fan
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Peipei Shan
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Xiaoying Qiu
(Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Shuxian Dong
(Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Lujian Liao
(Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Chunlei Yu
(Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
- Tingting Wang
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine)
- Xiaoyang Gu
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine)
- Qian Li
(School of Life Science & Technology, China Pharmaceutical University)
- Xiaoyu Song
(Key Laboratory of Medical Cell Biology, College of Translational Medicine, China Medical University)
- Liu Cao
(Key Laboratory of Medical Cell Biology, College of Translational Medicine, China Medical University)
- Xiaotao Li
(Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University
Baylor College of Medicine. One Baylor Plaza)
- Yongping Cui
(Key Laboratory of Cellular Physiology Ministry of Education, Shanxi Medical University)
- Shengping Zhang
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine)
- Chuangui Wang
(Institute of Translational Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University)
Abstract
Maintenance of energy homeostasis is essential for cell survival. Here, we report that the ATP- and ubiquitin-independent REGγ-proteasome system plays a role in maintaining energy homeostasis and cell survival during energy starvation via repressing rDNA transcription, a major intracellular energy-consuming process. Mechanistically, REGγ-proteasome limits cellular rDNA transcription and energy consumption by targeting the rDNA transcription activator SirT7 for ubiquitin-independent degradation under normal conditions. Moreover, energy starvation induces an AMPK-directed SirT7 phosphorylation and subsequent REGγ-dependent SirT7 subcellular redistribution and degradation, thereby further reducing rDNA transcription to save energy to overcome cell death. Energy starvation is a promising strategy for cancer therapy. Our report also shows that REGγ knockdown markedly improves the anti-tumour activity of energy metabolism inhibitors in mice. Our results underscore a control mechanism for an ubiquitin-independent process in maintaining energy homeostasis and cell viability under starvation conditions, suggesting that REGγ-proteasome inhibition has a potential to provide tumour-starving benefits.
Suggested Citation
Lianhui Sun & Guangjian Fan & Peipei Shan & Xiaoying Qiu & Shuxian Dong & Lujian Liao & Chunlei Yu & Tingting Wang & Xiaoyang Gu & Qian Li & Xiaoyu Song & Liu Cao & Xiaotao Li & Yongping Cui & Shengpi, 2016.
"Regulation of energy homeostasis by the ubiquitin-independent REGγ proteasome,"
Nature Communications, Nature, vol. 7(1), pages 1-15, November.
Handle:
RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12497
DOI: 10.1038/ncomms12497
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Cited by:
- Li, Shangge & Jian, Jinfeng & Poopal, Rama Krishnan & Chen, Xinyu & He, Yaqi & Xu, Hongbin & Yu, Huimin & Ren, Zongming, 2022.
"Mathematical modeling in behavior responses: The tendency-prediction based on a persistence model on real-time data,"
Ecological Modelling, Elsevier, vol. 464(C).
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