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Kailai Cai Key Laboratory of Education Ministry of China in Agricultural Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China

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Guohua Hua Key Laboratory of Education Ministry of China in Agricultural Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China

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Li Han Key Laboratory of Education Ministry of China in Agricultural Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China

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Xiang Li Key Laboratory of Education Ministry of China in Agricultural Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China

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Liguo Yang Key Laboratory of Education Ministry of China in Agricultural Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China

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Wen Zheng Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, PR China
Metabolomics and Proteomics Technology Platform, West China Hospital, Sichuan University, Chengdu, PR China

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Liang Zhang Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Kailai Cai Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Kongju Wu Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Ge Liang Metabolomics and Proteomics Technology Platform, West China Hospital, Sichuan University, Chengdu, PR China

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Lu Zhang Metabolomics and Proteomics Technology Platform, West China Hospital, Sichuan University, Chengdu, PR China

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Lihui Liao Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Fujun Shen Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Wenping Zhang Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Li Wang Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Yan Li Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Ye Wang Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Jie Kou Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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Yi Zhong Metabolomics and Proteomics Technology Platform, West China Hospital, Sichuan University, Chengdu, PR China

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Xin Li Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, PR China

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Jingqiu Cheng Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, PR China

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Meng Gong Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, PR China

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Rong Hou Chengdu Research Base of Giant Panda Breeding, Chengdu, PR China

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In brief

The metabolic processes of the gestation period in pandas remain poorly understood. Our study comprehensively characterizes the metabolism of giant pandas during gestation and proposes arginine and histidine as potential novel biomarkers for detecting the pregnancy state of giant pandas.

Abstract

There has been remarkable progress in the conservation and reproduction of giant pandas. However, the physiology of the gestation period in pandas remains poorly understood. The metabolic processes from estrus to pregnancy are dynamic and precisely regulated, playing a crucial role in pregnancy and related dysfunctions. In this study, we conducted a metabolomic analysis of 37 blood samples collected from pandas in estrus, acyclic, and potential pregnant states, employing rigorous screening to minimize the influence of diet. Our findings suggest that a reduced appetite can serve as an indicator for evaluating implantation time, representing a characteristic response to pregnancy and aiding in the prediction of delivery time in pregnant pandas. Metabolomic results indicate great metabolism variation from estrus to pregnancy, highlighting the association between amino acid metabolism and pregnancy outcomes. Compared to other pandas, individuals who successfully bred exhibit significantly elevated levels of arginine and histidine, even 2 months before experiencing a reduced appetite. Furthermore, the lipid profile undergoes distinct dynamic changes only in estrus samples. In summary, our study comprehensively characterizes the metabolism of giant pandas during gestation and proposes arginine and histidine as potential novel biomarkers for detecting the pregnancy state of giant pandas.

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