Gestational giant panda plasma metabolomics: amino acid metabolism characteristics may predict panda pregnancy outcomes.
Reproduction
; 168(3)2024 Sep 01.
Article
em En
| MEDLINE
| ID: mdl-38941177
ABSTRACT
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Ursidae
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Resultado da Gravidez
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Biomarcadores
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Metabolômica
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Aminoácidos
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article