Differences in weight regulation of T. belangeri in two regions
It was found that there was a significant difference in body weight of the
T. belangeri between the two regions (t=6.142, P<0.01); The body mass of
T. belangeri in CX is significantly smaller than that in ML (Fig 1).
The maintenance of animal body weight relies on the balance between energy consumption and acquisition, with various environmental factors influencing these processes, such as temperature and humidity
(Li et al., 2003). For instance, species like
E. miletus and
Apodemus chevrieri lose body weight to ensure survival in cold temperatures (
Zhu and Gao, 2017;
Jia and Zhu, 2021). In winter, the ambient temperature in CX was lower than that in ML, which resulted in higher temperatures and abundant food resources in ML. Therefore,
T. belangeri did not need to reduce its body weight to reduce absolute energy consumption. Moreover, the average relative humidity in ML was higher than that in CX, Research had shown that under high temperature or high humidity environments, animals’ evaporative heat dissipation and energy consumption were reduced and they can maintain a higher body weight
(Li et al., 2013). Through gut microbiota analysis, it was found that Firmicutes had significant differences between the two regions. studies have shown that the ratio of Firmicutes and Bacteroidetes is correlated with host body weight
(Du et al., 2013), explaining the mutual influence and regulation between gut microbiota and body mass of
T. belangeri. Therefore, the difference in mass between the two regions was a response to the differences in environmental temperature and humidity conditions.
Microbial community composition
Phylum-level analysis revealed that the dominant phylum of gut microbiota in the
T. belangeri in CX were Proteobacteria, Bacteroidetes and Firmicutes, the average relative abundance as follows 79.69%, 8.56% and 4.98%. The dominant phylum of gut microbiota in the
T. belangeri in ML were Proteobacteria, Firmicutes and Spirochaetes; the average relative abundance was 68.36%, 14.84% and 9.20%, respectively. There was a significant difference in the relative abundance of Firmicutes between CX and ML (Mann Whitney U test, P<0.05, Fig 2).
At the door-level taxonomic, the dominant genus of gut microbiota in the
T. belangeri in CX were as follows:
Escherichia (64.31%),
Bacteroides (5.37%) and
Flexispira (3.12%). The dominant genus of gut microbiota in the
T. belangeri in ML were
Escherichia (44.14%),
Campylobacter (12.04%) and
Bacillus (5.48%). However, there was no significant difference in the relative abundance of dominant genera between the two regions (Mann Whitney U test, P>0.05, Fig 3).
The gut microbiota comprises a diverse microbial population that undergoes dynamic changes and engages in mutually beneficial symbiosis with the host over extended periods, depending on its state
(Zhang et al., 2017). The results indicated that the dominant phyla in
T. belangeri from CX at the phylum level were Proteobacteria, Bacteroidetes and Firmicutes, which were Proteobacteria, Firmicutes and Spirochaetes in ML and the relative abundance of Firmicutes showed significant differences. The difference in relative abundance of Firmicutes between the two regions may be related to environmental temperature, studies had shown that bacteria with carbohydrate and energy metabolism pathway related functions in the gut of Macaca thibetana in winter and spring significantly increase in spring, enabling them to quickly recover from severe energy loss experienced in winter
(Sun et al., 2016). Furthermore, the relative abundance of Proteobacteria was the highest in the two regions of
T. belangeri, which may be related to their feeding on corn, rice and other crops. Studies have shown that dietary resources rich in plant-based substances are usually associated with a higher proportion of Firmicutes and Proteobacteria
(Kuo et al., 2024). Escherichia is a dominant genus in both regions, it belongs to the phylum Proteobacteria and was a common and important bacterium in the gut that helps stabilize the gut microbiota, increase intestinal peristalsis and enhance digestive capacity. But it is also an opportunistic pathogen, but when the host’s immune system is weakened or it invades tissues and organs outside the intestine, it can cause infectious diseases such as sepsis
(Shin et al., 2015). This warns local authorities to strengthen management and monitoring of the
T. belangeri to reduce the risk of disease spread.
Analysis of microbial community α and β diversity
The Mann-Whitney U test revealed no significant differences in gut microbiota diversity metrics between
T. belangeri populations from the two study regions (Chao1 index: P= 0.12; Shannon index: P= 0.07, Fig 4). The distribution of β diversity in the gut microbiota of the
T. belangeri in CX and ML was scattered on the PCoA map, with no obvious clustering trend (P>0.05, Fig 5).
Distribution of common and unique microorganisms in different regions
There was a total of 135 genera (55.79%) of
T. belangeri in CX and ML. There were 36 genera (14.88%) unique to
T. belangeri in CX and 71 genera (29.34%) unique to
T. belangeri in ML. ML had a higher number of gut microbiota belonging to the endemic genus (Fig 6).
Analysis of microbial enrichment differences in different regions
Escherichia,
Enterobacteriaceae (UG),
Yersinia,
Slackia,
Morganella and
Providencia were significantly enriched in CX (P<0.05). Adlercreutzia, Clostridiales (UG), Proteobacteria (UG),
Brachyspira,
Campylobacter and
[Ruminococcus] were significantly enriched in ML (P<0.05, Fig 7).
The diversity index describes the statistical measure of microbial community diversity, including the richness and evenness of microbial species
(Duarte et al., 2025). A series of research results all indicated that the structure and composition of gut microbiota was closely related to the environment. Although there was no significant difference in β diversity and β diversity between the two regions, but there are CX and ML had differences in their unique gut microbiota. ML had a higher environmental temperature in winter than CX, which also means that ML had more abundant food resources in winter,
T. belangeri can consume a more diverse range of food, thus requiring a more structurally complex and diverse gut microbiota with more species. Moreover, it was found that the impact of gut microbiota between the two regions was almost equal, indicating that the difference in gut microbiota structure between the two may be related to the different humidity and temperature levels between the two regions, which was one of the adaptation and regulation methods of the
T. belangeri to different environments.
Influencing factors of gut microbiota
Body weight had a significant impact on its gut microbiota (P<0.05), compared with altitude and gender, temperature and humidity have a greater impact on the gut microbiota of
T. belangeri in CX and ML (P>0.05, Fig 8).
Assembly process of gut microbiota
Quantifying the assembly process of gut microbiota in
T. belangeri in CX and cities using corrected random rate (MST), the MST values of the gut microbiota of the
T. belangeri in CX and ML were mostly below the threshold line of 0.5, indicating that deterministic processes play a more important role in both communities. And there was no significant difference in MST values between the CX and the ML (Mann Whitney U test, P>0.05, Fig 9).
Co-occurrence network of gut microbiota
This network analysis included the top 200 OTUs with relative abundance and based on Gephi 0.10, constructed a network with 200 nodes and 3030 edges, among them, there are 2998 positive edges (98.94%) and 32 negative edges (1.06%), with different colors representing different modules. This may mean that the microorganisms in the OTUs co-occurrence network are dominated by cooperative relationships (Fig 10). Further construct dominant OTUs co-occurrence networks for the top 200 relative abundance of
T. belangeri in CX and ML and calculate their network topology characteristics (Table 2). The average degree and graph density of the co-occurrence network in CX were higher than those in ML and the average path length is shorter than that in ML, indicating that the co-occurrence network in CX had stronger connectivity, closer relationships and higher modularity than that in ML. The correlation between dominant OTUs in the gut of the
T. belangeri in CX was stronger than that in ML.
Opportunistic pathogenic bacteria in the gut
The bubble chart showed the opportunistic pathogenic bacteria in the gut of the
T. belangeri in CX and ML. The size of the bubbles represents the relative abundance of the opportunistic pathogenic bacteria and the color represents the grouping. A total of 25 opportunistic pathogenic bacterial genera were detected, including 14 species detected in the gut of the
T. belangeri in CX and 16 species detected in ML (Fig 10). It was found that
Escherichia was widely present in the gut of
T. belangeri in both regions.
Bacillus and
Campylobacter had higher relative abundance in ML, while
Bacteroides had higher relative abundance in CX (Fig 11).
Abnormalities in the gut microbiota was associated with various diseases. For instance, inflammatory bowel disease is related to the decrease in relative abundance of Clostridia and an overall decline in bacterial diversity (
Koch and Schmid-Hempel, 2011;
Dominianni et al., 2015). This indicates that the stability of the microbial community in the body and the importance of maintaining the stability of gut microbiota after changes in gut bacterial community structure or catastrophic depletion of certain microbial communities in the gut are crucial. In our study, a total of 25 opportunistic pathogenic bacteria were detected, among which Escherichia was widely present in two regions. This is a common pathogenic bacterium of the Proteobacteria phylum. When it captures pathogenic or toxic factors from the outside, it can cause tissue and organ inflammation or diarrhea, sepsis, etc. in animals
(Shin et al., 2015). Bacteroides was relatively more abundant in the gut of the
T. belangeri in CX. This bacterium can enhance the host’s innate immune response (
Bry et al., 1996;
Ley et al., 2005; Corthier et al., 1985). But when it is distributed outside the intestine, it can lead to host diseases such as diarrhea, osteomyelitis, endogenous abdominal abscess, tonsillitis, etc.
(Hesham et al., 2007; Swidsinski et al., 2007). The different speculations of pathogenic bacteria between two regions may be related to their environment, such as temperature, water quality, food resources, etc. This also warns the local government to strengthen monitoring and management of the
T. belangeri to avoid the occurrence of zoonotic diseases.
