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. 2024 Nov 1:15:1499028.
doi: 10.3389/fmicb.2024.1499028. eCollection 2024.

High-altitude environments enhance the ability of Eothenomys miletus to regulate body mass during food limitation, with a focus on gut microorganisms and physiological markers

Tianxin Zhang  1   2 , Ting Jia  1   2 , Wanlong Zhu  1   2   3 , Lixian Fan  1   2
Affiliations

High-altitude environments enhance the ability of Eothenomys miletus to regulate body mass during food limitation, with a focus on gut microorganisms and physiological markers

Tianxin Zhang et al. Front Microbiol. .

Abstract

Animals' digestion, energy metabolism, and immunity are significantly influenced by interactions between the gut microbiota and the intestinal environment of the host. Previous studies have shown that gut microbiota of Eothenomys miletus can respond to environmental changes, high fiber or fat foods. But how E. miletus in high-altitude adapt to their environment through gut microbiota and physiological changes during winter food shortages period was unclear. In the present study, we evaluated the altitude differences in gut microbiota and their interactions with physiology in terms of body mass regulation in order to study the adaptation of the gut microbiota and physiological indicators of the E. miletus under food restriction settings. E. miletus were collected for this study from Jingdong County (JD, low-altitude) and Xianggelila County (XGLL, high-altitude) in Yunnan Province, China, and split into three groups: control group, food-restricted feeding group for 7 days, and re-feeding group was offered a standard diet for 14 days. 16S rRNA gene sequencing and physiological methods were used to analyze the abundance and community structure of gut microbiota, as well as physiological indicators of each group in E. miletus. The results showed that while the RMR changed more during the period of food restriction, the body mass and major organ masses of E. miletus from high-altitude changed less. After food restriction, RMR in XGLL decreased by 25.25%, while that of in JD decreased by 16.54%. E. miletus from the XGLL had gut bacteria that were more abundant in Firmicutes and had fewer OTUs, and the microbiota had a closer interaction with physiological indicators. Moreover, the gut microbiota adapted to the food shortage environment by enhancing the genera of Bacterroides, Ruminococcus, Turicibacter, and Treponema to improve the utilization of nutrient resources. The interactions between microbial species and the equilibrium of energy homeostasis were further impacted by alterations in physiological indicators and microbial community structure. These variations were important for E. miletus to adapt to the fluctuations and changes of food resources in high-altitude region, which also expand our knowledge of organismal adaptations and the mechanisms behind the interactions between gut bacteria and host physiology.

Keywords: Eothenomys miletus; adaptation; food restriction; gut microbiota; high altitude.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Experimental design.
Figure 2
Figure 2
Effects of different regions and food restriction on physiological indices of E. miletus. Control, Control group; FR7d, Restricted food for 7 days group; FR-Re21d, 14 days re-feeding group after food restriction.
Figure 3
Figure 3
Effect of different regions and food restriction on serum indices of E. miletus. Control, Control group; FR7d, Restricted food for 7 days group; FR-Re21d, 14 days re-feeding group after food restriction. Data were mean ± standard deviation. Different letters indicated significant differences between treatments in the same region, xy indicates JD region and ab indicates XGLL region. *p < 0.05, **p < 0.01, JD and XGLL were compared on the same day.
Figure 4
Figure 4
Microbial phylum level community composition. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 5
Figure 5
Microbial composition at the genus level. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 6
Figure 6
Microbial α-diversity of fecal microorganisms of E. miletus in different regions and time periods. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 7
Figure 7
β-diversity of fecal microorganisms of E. miletus in different regions and periods in the food-restricted group. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 8
Figure 8
Venn diagram of fecal microorganisms of E. miletus feces at different time periods. CJD0, Jingdong control group; FRJD7, Jingdong restricted food group; FR-ReJD21, Jingdong re-feeding group; CXGLL, Xianggelia control group; FRXGLL7, Xianggelila restricted food group; FR-ReXGLL21, Xianggelila re-feeding group.
Figure 9
Figure 9
Venn diagram of fecal microorganisms of E. miletus in different regions and time periods. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 10
Figure 10
Differential microbial analysis of the feces of E. miletus in the food-restricted groups in Jindong and Xianggelila at different periods of time. CJD0, JD control group; FRJD7, JD restricted food group; FR-ReJD21, JD re-feeding group; CXGLL, XGLL control group; FRXGLL7, XGLL restricted food group; FR-ReXGLL21, XGLL re-feeding group.
Figure 11
Figure 11
Heat map of physiological indicators related to the dominant microorganisms in the feces of E. miletus in JD.
Figure 12
Figure 12
Heat map of the correlation between the detection indicators and the dominant microorganisms in the feces of E. miletus in JD.
Figure 13
Figure 13
Heat map of physiological indicators related to the dominant microorganisms in the feces of E. miletus in XGLL.
Figure 14
Figure 14
Heat map of the correlation between detected indicators and the dominant microorganisms in the feces of E. miletus in XGLL.
Figure 15
Figure 15
Redundancy analysis (RDA) of correlations between physiological indicators and dominant microbial communities. Blue arrows represent gut microbiota genera, yellow arrows represent physiological markers. The length of the physiological markers arrow can represent the influence of the factor on the gut microbiota. The angles between the arrows represent positive and negative correlations.
Figure 16
Figure 16
Dominant OTU co-occurrence network of feces of E. miletus in all regions. The size of each node is proportional to the number of connections, each module is presented as a specific color.
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