Analysis of Kidney Differential Metabolites and Hypoxia Adaptation Mechanism of Plateau Pikas Based on UHPLC-QE-MS
10.12300/j.issn.1674-5817.2024.095
- VernacularTitle:基于UHPLC-QE-MS的高原鼠兔肾脏差异代谢物及低氧适应机制分析
- Author:
Yuxin HE
1
;
Zhenzhong BAI
1
;
Hua XUE
1
;
Zixu GUO
1
;
Xuefeng CAO
1
Author Information
1. Medical College of Qinghai University, Xining 810001, China
- Publication Type:Journal Article
- Keywords:
High-altitude hypoxia;
Plateau pika;
Kidney;
UHPLC-QE-MS;
Metabolic pathway
- From:
Laboratory Animal and Comparative Medicine
2025;45(1):3-12
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the potential mechanisms of hypoxic adaptive metabolic changes in the kidneys of plateau pikas at different altitudes using non-targeted metabolomics analysis via ultra-high-performance liquid chromatography coupled with quadrupole electrostatic field orbital trap-mass spectrometry (UHPLC-QE-MS). Methods 10 plateau pikas were captured at an altitude of 4 360 m in Xingxiuhai area, Maduo County, Guoluo Tibetan Autonomous Prefecture, Qinghai Province (MD group), and 10 plateau pikas were captured at an altitude of 2 900 m in Menyuan area, Haibei Tibetan Autonomous Prefecture, Qinghai Province (MY group). After anesthesia, serum samples were collected, and kidney samples were collected after euthanasia. General physiological and biochemical indicators were measured and metabolomics analysis was performed. Part of the serum samples was used for hematology analysis, another part for blood gas analysis, and the remaining part for biochemical indicator detection. Metabolites were extracted from the kidney tissue samples and then analyzed using UHPLC-QE-MS. Differential metabolites were analyzed using metabolomics principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), with screening criteria set as variable importance in projection (VIP)>1.5 and fold change (FC)>1.5, or VIP>1.5 and FC<1/1.5. Correlation analysis heatmaps, significance analysis volcano plots, signaling pathway recognition bubble charts, and rectangular graphs were used for the analysis of differential metabolites and related signaling pathways. Results The red blood cell count, glucose, urea nitrogen, uric acid, and homocysteine levels in the MD group plateau pikas were higher than those in the MY group, while hemoglobin, hematocrit, creatinine, and carbon dioxide combining power were lower than those in the MY group. This indicated a significant difference in the blood oxygen-carrying capacity of plateau pikas at different altitudes. The principal component pattern recognition analyses, and OPLS-DA permutation test showed that the kidney metabolites of the MD and MY groups of plateau pikas had distinct clustering distributions (R²Y=0.930, Q²=0.655). According to the screening criteria and database comparison, 46 differential metabolites were identified in the kidneys of plateau pikas at different altitudes. In the MD group of plateau pikas, the expression levels of bufadienolide, adenosine, adenine, diosgenin, berberine chloride, carnosol, and astaxanthin were significantly increased (VIP>1.5, P<0.05), while the levels of arachidonic acid, histamine, and coumarin were significantly decreased (VIP>1.5, P<0.05). The analysis of related signaling pathways showed that the biosynthetic pathways of valine, leucine, and isoleucine had the largest impact factors (P<0.05), while the biosynthetic pathways of pantothenate and coenzyme A showed the most significant enrichment (P<0.05). Conclusion The differential metabolites of amino acids, pantothenate, and coenzyme A pathways in the kidneys of plateau pikas at different altitudes may be involved in the metabolic mechanisms of plateau pikas' hypoxia adaptation in high-altitude environments.
