In Integrative zoology
The harsh environment in the Tibetan plateau, the highest place in the world, poses thermoregulatory challenges and hypoxic stress to animals. The impacts of plateau environment on animal physiology and reproduction include external factors such as strong ultraviolet radiation and low temperature, and internal factors such as animal metabolites and gut microbiota. However, it remains unclear how plateau pika adapt to high altitudes through the combination of serum metabolites and gut microbiota. To this end, we captured 24 wild plateau pikas at the altitudes of 3400 m, 3600 m, or 3800 m a.s.l. in a Tibetan alpine grassland. Using the machine learning algorithms (random forest), we identified five biomarkers of serum metabolites indicative of the altitudes, i.e., dihydrotestosterone, homo-L-arginine, alpha-ketoglutaric-acid, serotonin and threonine, which were related to body weight, reproduction, and energy metabolism of pika. Those metabolic biomarkers were positively correlated with Lachnospiraceae_ Agathobacter, Ruminococcaceae, or Prevotellaceae_Prevotella, suggesting the close relationship between metabolites and gut microbiota. By identifying the metabolic biomarkers and gut microbiota analysis, we reveal the mechanisms of adaptation to high altitudes in plateau pika. This article is protected by copyright. All rights reserved.
Chen Xi, Wang Zaiwei, Su Junhu, Li Huan, Xiong Jinbo, Fu Keyi, Wang Zilong, Yuan Xuefeng, Shi Ziyue, Miao Xiumei, Yang Mei, Yang Yunfeng, Shi Zunji
2023-Mar-07
Biomarkers, Gut microbiota, Machine, Metabolomics, Plateau pika, learning
