Effects of Dietary Changes on the Gut Microbiota of Cynops orientalis

Headnote

Abstract The gut microbiota plays a pivotal role in the maintenance of health for amphibians, and it has been fully recognized, but the effectiveness of various influencing factors has not yet been fully clarified. Although this association should be considered while the amphibian order Caudata is facing a severe situation of population decline and extinction, there is little understanding of the association between diets and the diversity of gut microbiota in the amphibian order Caudata. Here, we conducted an extensive analysis of the gut microbiota of Cynops orientalis fed different diets using functional prediction and 16S rRNA amplicon sequencing techniques. First, we found that wild individuals had greater gut microbial diversity and richness in comparison to captive individuals. Second, we identified the bacterial taxa associated with diets and observed differences in the relative abundance of gut microbiota among people on various diets. Finally, we have a predictive comprehension of the selection and adaptative significance of shared core ASVs in the gut microbiota in maintaining the healthy survival of C. orientalis in a large-scale spatiotemporal map. Our study emphasizes how diets alter the gut microbiota of Caudata and offers fresh perspectives on the conservation and captive management of species in Caudata.

Keywords 16S rRNA, Caudata, core microbiota, diet, gut microbiota

1. Introduction

The gut microbiota is extensively distributed and plays an integral part in numerous physiological processes of the host in vertebrates (Bletz et al., 2016; Liu et al., 2022; Niu et al., 2022; Yi et al., 2019). However, numerous current researches on gut microbiota have mainly focused on mammals, up to now, far too little attention has been paid to exploring amphibians to a certain extent (Bolnick et al., 2014). Amphibians are important species that connect aquatic and terrestrial environments, which can be regarded as important systems for studying the adaptation and selection of gut microbial communities. At present, amphibians have become the most threatened vertebrates in the world, with about 41% of existing species listed as threatened at different threat levels. The study of Yang et al. (2022) indicated that the order with the highest proportion of amphibians under threat is Caudata, which has been less researched and has a higher threat level than Anura. In addition, it is more difficult for Caudatans to recover when damaged (Yang et al., 2022). Therefore, it is urgent to strengthen research on amphibians in the order Caudata and explore protective measures for caudatans (Wei et al, 2019).

Studying various factors that affect the host gut microbial assembly and structure, elucidating the dynamic shifts in diversity and composition of microbes, and analyzing the host's gut microbial adaptive mechanisms in reaction to various external disturbances are important for protecting amphibians. In the past 30 years, research on the association between amphibians and their gut microbial composition has mainly focused on the order Anura, such as Xenopus tropkalis, Rana dybowskii, Bufo gargarizans, Pelophylax nigromaculatus, and Fejervarya limnocharis (Chai et al, 2022; Huang et al, 2021; Huang et al, 2022; Li et al, 2020; Tong et al, 2020a; Xu et al, 2020; Zhang et al, 2023; Zhao et al, 2022; Zheng et al, 2021; Zhu et al, 2023), while only a few studies have focused on the order Caudata (Jiang et al, 2022; Li et al, 2022; Lv et al, 2022; Mu et al, 2018). Although knowledge about environmental factors driving shifts in the gut microbiota of amphibians is constantly being supplemented, the understanding of the external environment on the composition, source, and dynamic shifts of the gut microbiota of Caudata is still limited. Complementation of this understanding will help maintain the health of highly affected caudatans, which is important for all aspects of the protection and management of the gut microbiota of amphibians.

Diet, as a source of colonized bacteria, plays a pivotal role in reshaping the gut microbiota of vertebrates, it also contributes to altering the nutritional environment of the gut (Bolnick et al, 2014). One of the most significant current discussions on gut microbiota is the relative importance of the composite effects of multiple factors, but this synergistic effect has certain limitations (Song et al, 2021). As a component of various environmental factors (habitat, season, etc.), food habits themselves have strong research value and deserve more attention and exploration. Diet is seen as a factor strongly related to influencing the variety of the gut microbiome (Thomas et al, 2022). Food habits contribute to the selection and reshaping of the gut microbiota of hosts (Lemieux-Labonte et al, 2022). Diets, nutritional content and diversity of food are important driving factors of the gut microbial composition. However, researchers have not treated the impact of diets on the gut microbial diversity in amphibians in much detail, and it is currently unclear how quickly the composition changes with dietary changes. The correlation between diets and gut microbiota diversity in amphibians needs further research and whether dietary changes alter the function of the core microbial community in amphibians' gut microbiota needs to be further determined. Further in-depth exploration is needed on how diets affect the dynamic gut bacterial community in amphibians and how diets affect their environmental adaptability.

The extensive spatiotemporal distribution and diffusion ability of Cynops orientalis make it a potential nationwide biogeographical model of the order Caudata, and C. orientalis provides an excellent natural amphibian system, which can be used as a model species for studying Caudata (Peng et al, 2021). Data from several studies suggest that both the nutritional content and diversity of food can affect the abundance of gut microbiota in amphibians (Zhang et al, 2020; Zmora et al, 2019). On this basis, we hypothesized that diets were strongly linked to the gut microbiota variance of C. orientalis, predicted that diet is a major influence on its gut microbiota composition. We explored whether there is a connection between the gut microbial constitution of C. orientalis and diet, to evaluate the impact of diet on the composition of the gut microbiota of C. orientalis, intending to explore whether diets will alter its adaptability to the environment Our research provided valuable information for future research on the gut microbiome in Caudata, helped to monitor the survival, protection, and captive management of Caudata, as well as to enhance the dynamic data of the gut microbiota of the hosts.

2. Materials and Methods

2.1. Animal capture and sample collection In August 2022, a total of 30 C. orientalis were caught by us in Sikong Mountain (115?56'55" E, 30?44'6" N), Yuexi County, Anqing City, Anhui Province, China. To minimize the spatial and temporal heterogeneity of food habits and gut microbiota, we wore sterile gloves to catch C. orientalis along a small section (200 m) of still water within one day.

We conducted a diet manipulation experiment (Bolnick et al, 2014). Related research reports and our direct observations in the wild have shown that C. orientalis in a natural diet state have abundant food resources, mainly including Gastropoda, Diplopoda, Chilopoda, Anelida (Lumbricidae), and some insect animals (Wang et al, 2021). We used natural diet to describe the long-term habitual diet of wild animal populations. First of all, after the animals were captured, we immediately measured the morphological signs (including weight, total length, tail length, mouth width, fore limb length, and hind limb length) of C. orientalis, and calculated their Body mass index (supplementary Table SI; Peig and Green, 2009; Zhang et al, 2020). To eliminate the influence of physical signs and environmental factors while avoiding cross-contamination, we selected 8 C. orientalis with similar physical signs as the natural diet group (denoted as the wild group, including 4 males and 4 females), and placed them in 8 sterile containers containing water quality in the still water domain of the capture area. Individuals in the wild group fasted for 24 h, then fecal samples from distinct individuals were placed in different sterile tubes and stored in a cool box containing ice packs.

Immediately transfer the samples to the laboratory and freeze them at -20 癈 until the next experimental operation is carried out. Next, we will change the diet of the wild group to a non-natural diet group (denoted as the captive group, including 4 males and 4 female animals). We placed the container around the capture site, under simulated outdoor environmental conditions, changed the water (water is taken from the still water area where animals are captured), and fed it (single red worms feed) once a day. After 8 weeks of feeding, the C. orientalis were given a 24-h fasting treatment to clean their intestines. Collected fecal samples from each individual in the captive group and kept them at -20 癈 in separate sterile tubes until further experimental analysis was conducted (Song etal, 2018).

2.2. DNA extraction, PCR amplification, and sequencing Using and following the operational steps of the DNeasy (r) PowerSoil (r) Pro kit (Qiagen, Germany) to extract genomic DNA The following primer pairs were used to amplify the 16S ribosomal RNA gene of bacteria in the V3-V4 region: 5'-ACTCCACGGGAGGCAGCAG-3' and 806R 5'-GGACACHVGGGTWTCTAAT-3'. The polymerase chain reaction (PCR) conducted was a 5-min initial denaturation step at 95 癈; 30 cycles of 95 癈 for 30 s, 55 癈 for 30 s, 72 癈 for 30 s; and a 5-min final extension at 72 癈. Every sample underwent sequencing on the Illumina MiSeq platform (Illumina, San Diego, USA) carried out by Shanghai Majorbio Bio-Pharm Technology Co. Ltd. (Majorbio, Shanghai, China) (Zhao et al, 2022).

2.3. Bioinformatic analyses VSEARCH (v2.18.0; Rognes et al, 2016) and USEARCH (vl 0.240) were used to integrate the paired-end reads after the barcode and primer sequences were removed. The raw reads underwent demultiplexing, merging, and quality filtering using UPARSE (Edgar, 2013). After that, we used USEARCH's "-unoise3" parameter for identifying precise amplicon sequence variations (ASVs) (Edgar, 2013). By comparing ASV representative sequences with the Silva database, the species information for each sample was obtained. Normalized annotation information was organized based on the classification criteria of the kingdom, phylum, class, order, family, and genus, and then alpha and beta diversity analyses were conducted (Segata et al, 2011).

2.4. Statistical analyses We used the Mann-Whitney U test to examine the variations in the gut microbiota of C. orientalis populations within the captive and wild groups. Based on the ASV table, we use R software (version 4.2.0) for alpha diversity to determine and visually reflect the diversity and abundance of gut microbiota in each sample. The results were used to analyze the diversity and richness of bacteria in the sample, resulting in the Shannon index, Chaol index, and richness index (Vegan package). We compared distinctions in gut microbial diversity and richness between the two groups using Tukey's HSD test. Furthermore, the rarefaction curves were obtained using the Vegan package. In addition, while using R software for beta diversity, by calculating the Euclidean distance, the Jaccard matrix was measured using principal coordinate analysis (PCoA) to display the similarity or dissimilarity in microbial community composition between samples. Linear discriminant analysis (LDA) effect size (LEfSe) was used to determine the differences in the relative abundance of the microbial features (Segata et al, 2011). PICRUSt2 was used to analyze functional genes (Douglas et al, 2020). The Mann-Whitney U test was used to examine the functional differences between the microorganisms in the KEGG pathway.

3. Results

3.1. Characteristics of the gut microbiota We collected fecal samples of C. orientalis that were fed different diets and obtained 1 467 462 high-quality sequences in total (mean 91 716). A total of 931 ASVs were identified. The gut microbiota undergoes significant changes in diets at the phylum level. Four phyla with higher abundance were identified in the captive and wild groups (such as Firmicutes, Bacteroidetes, Proteobacteria, and Fusobacteria), and the difference between the captive and wild groups was significant. The dominant phylum in the captive group was Firmicutes (15.85%), while Bacteroidetes (10.98%) and Proteobacteria (10.59%) were the dominant phyla in the wild group (Mann-Whitney U test, P < 0.05; Figure 1A and supplementary Table S2).

At the family level, the gut microbiota undergoes significant changes in diets (Mann-Whitney U test, P < 0.05; supplementary Table S2). Some of the families with higher abundance appearing in the captive group included Peptostreptococcaceae (10.83%), Porphyromonadaceae (7.67%), Fusobacteriaceae (4.87%), Clostridiaceae_l (4.61%), and Flavobacteriumeae (3.48%), and some families with higher abundance in the wild group included Fusobacteriaceae (7.68%), Flavobacteriumeae (7.16%), Enterobacteriaceae (3.84%), Oxalobacteriumeae (3.26%), Comonadaceae (2.88%), and Peptostreptococcaceae (2.83%) (Figure IB).

3.2. Decreased bacterial diversity and richness associated with diet The majority of gut microbiota members were covered by each individual according to rarefaction analysis (Figure 2A). We evaluated the diversity indices (Shannon-Wiener, Chao 1, and richness indices) in order to assess the variations in gut microbiota that occur between the two groups. Compared to captive individuals, the diversity and richness of gut microbes were higher in wild individuals (ANOVA,

Tukey-HSD test, all P < 0.05; Figure 2B and supplementary Figure SI). A Venn diagram showed that 473 out of the 931 ASVs (50.81%) were common in these two groups (Figure 2C).

3.3. Diet-associated dissimilarity For the purpose of measuring the degree of difference in gut microbiota produced by diet between two groups, PCoA was used based on these distance matrices (Euclidean distance, Jaccard distance matrices) between the fecal samples. This analysis presents that the microbiota of individuals fed of captive diet are strongly different from those of wild individuals. PCoA can clearly separate the fecal microbiota of two groups with significant interindividual differences through different matrices (Figure 3). Moreover, the wild group and the captive group both exhibited highly similar bacterial compositions within the group.

We used LDA effect size (LEfSe) to analyze and detect differences in the relative abundance of gut microbiota among individuals with different diets and determine the bacterial taxa related to diets. The results indicate that there are 3 significant phyla of difference between the captive group and the wild group: Fiberobates (wild group), Deinococus Thermus (wild group), and Chloroflexi (wild group) (Figure 4A). A total of 74 gut bacterial groups showed significant differences, of which 59 belonged to the wild group and 15 belonged to the captive group (Figure 4B).

3.4. Variations in the functional distribution of gut microbiota Using PICRUSt2 to forecast the functional makeup of the gut microbiota of C. orientalis in response to different diets, 428 functional genes mapped to specific KEGG pathways were obtained. Among the 9 functional hierarchy abundances predicted in the first level pathway, there were significant intergroup functional hierarchies, including Cellular processes, Metabolism, Not included in pathway or Brite. Among the 54 functional hierarchy abundances predicted by the second level pathway, there were significant intergroup functional hierarchies, including Carbohydrate metabolism, Drug resistance, and Infectious disease (Mann-Whitney U test, P < 0.05; Table 1).

4. Discussion

4.1. Differences in the gut microbiota and the gut core bacteria Our research demonstrated that under a state of natural diet, Firmicutes and Bacteroidetes had higher abundances of the gut microbiota of C. orientalis, while Proteobacteria and Bacteroidetes were enriched in a non-natural diet state. We speculated that the reason for this difference is that changes in diets reduce the nutritional richness of intake. New food resources after dietary changes can be consumed and effectively digested, which may alter the competitiveness of gut microbiota members. The high selectivity and adaptability of the gut microbiota of the order Caudata to environmental changes can be demonstrated by the composition, density, and metabolic ability of the microbiota (Tong et al, 2020a). This suggests a strong link may exist between bacteria colonized in the gut of C. orientalis and diets.

The gut microbial composition and function are closely associated with the healthy survival of hosts. In our study, the proportion of Firmicutes/Bacteroidetes significantly rose to a high point in the captive group, which may be due to the adaptive alterations in the gut microbiota resulting from the captive group's unnatural diet, which shaped a higher ratio of Firmicutes/Bacteroidetes to help C. orientalis more effectively absorb calories from less abundant foods. Related studies have shown that human obesity is related to the distribution of gut bacteria when the proportion of Firmicutes/Bacteroidetes increases, the host's potential to absorb or store energy is enhanced, and calories in food are more easily absorbed by the host (Murphy et al, 2010). Compared to that summer, R. dybowskii has a high proportion of Firmicutes/Bacteroides during hibernation, which is used to assist R. dybowskii in going through the winter fasting phase (Tong et al, 2020a). Moreover, our data presented that Proteobacteria was the dominant phylum in the wild group, and the large proliferation of Proteobacteria in the gut microbiota reflects ecological imbalance or unstable gut microbiota structure (Shin et al, 2015). The proportion of Proteobacteria was still relatively small, and as a natural gut microbe, it can still be in a benign state. However, it is undeniable that in certain gut environments, Proteobacteria can become a colitis microbe that triggers inflammatory reactions. Although food restriction is an "energy crisis" for gut microbiota (Kohl et al, 2014), our results mainly focused on the impact of diets on gut microbiota, but we did not track and investigate in advance whether C. orientalis experienced food restriction before being captured.

We found that the composition of shared core ASVs in the gut microbiota of the order Caudata was associated with diet, and diet may weaken the selection and adaptability of core ASVs in the order Caudata. Different core ASVs were accommodated in the two experimental groups with diets as variables detected, but there were 31 stable and shared core ASVs between the two groups, reflecting the strong selection signals of Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria. Shared core ASVs are essential in the

interaction of the complex gut microbiota because they indicate the possible existence of selective functions and adaptive mechanisms, promoting the increase in core ASV under natural dietary conditions, they also encourage the concentration and upregulation of the gut microbial composition and function. In the process of coevolution between the host and gut ecology, the relative stability of the core gut microbiota may reflect the flexibility of the host to respond to new diets and may be a necessary factor to ensure the long-term health of the host (Tong et al, 2019). C. orientalis, the most widely distributed Caudata species in China, has different diets in different geographical regions. It can be inferred that the shared core ASVs have played a certain evolutionary and adaptive role in helping C. orientalis survive stably for hundreds of millions of years, and it is predicted that shared core ASVs play a role in resisting environmental interference in the long-term evolution of species in the order Caudata. The shared core ASVs predicted in this study provide insights into the conservation and ecosystem sustainability of species in the order Caudata, but further research and experiments are needed, such as adding more spatial and ecological samples of Caudata gut microbiota to support and certify the adaptive function of shared core ASVs in the Caudata gut (Chen et al, 2020; Jacquiod et al, 2020).

4.2. Effects of dietary factors on the diversity of gut microbiota in C. orientalis Studying the patterns by which environmental factors promote the adaptation of amphibian hosts to new environments can help Caudata better cope with rapidly occurring global environmental changes. Our study demonstrated that the wild group had a more diverse and abundant gut microbiota than the captive group did. Diets significantly affected alpha and beta diversity. We identified the dynamic alterations before and following food modifications in gut microbiota in C. orientalis, evaluated the impact of diets on the trend of gut microbiota diversity in C. orientalis, confirmed that dietary habits (an environmental factor) regulate the structure of gut microbiota, and provided potential evidence that changes in dietary habits may alter the function of microbial ecosystems. A rich natural diet may endow members of the wild group C. orientalis gut microbiota with diversity, which has advantages at both the functional and microbial shaping levels, as bacterial diversity to some extent determines the stability and resilience of the community to respond to internal or external disturbances (Tong et al, 2020b).

Our results demonstrated the clear contribution and crucial role that diets have in controlling the gut microbiota of C. orientalis. Different dietary patterns affected the composition and diversity of the gut microbiota in C. orientalis, which is particularly important in the context of the urgent need for protection in the order of Caudata. Changes in gut microbiota diversity in the order Caudata may directly affect gut microbiota-related functions. Our study showed that functions related to gut microbiota metabolism, digestion, and drug resistance are significantly enriched under natural dietary conditions. We speculated that diet might be an important factor in selecting microorganisms with the ability to degrade specific molecules and predicted that the gut microbiota of the order Caudata, which lives in a food-rich environment, may be more resistant and competitive, this relationship may partly be attributed to that diet represent an important source of gut microbiota. A more diverse gut microbiota could mobilize more microbial functions, effectively enhancing the adaptability and survival of the order under different abiotic and biological conditions (Bolnick et al, 2014). Our study described food intake as a dietary pattern rather than a specific food composition. This description method is based on the host's long-term habitual diet, which is conducive to an in-depth exploration of the relationship between gut microbiota and complex dietary habits. However, it simplified dietary habits, making it difficult to clarify the interaction effects between specific intake foods. Furthermore, although some diets may be beneficial for the survival and reproduction of Caudata at the single-factor level, the complex interaction between diet, microorganisms, and hosts should be considered in research focusing on the specific effects of multiple factors (Zmora et al, 2019).

The reduction in biodiversity may lead to various ecological and health crises worldwide, and biodiversity conservation has received widespread attention (Sun et al, 2018; Zhao et al, 2018). The reintroduction of artificial reproduction is the main method for reconstructing the wild population of the order Caudata (Wang et al, 2021). Diets, as a crucial component of captive breeding and management, have significant implications for species conservation. We used C. orientalis as a research animal to explore the impact of dietary habits on the composition and diversity of gut microbiota in the order Caudata and determined the selection and adaptive mechanisms of gut microbiota toward diets, providing a reference for the health and physiological monitoring of rare species of Caudata (such as Andrias davidianus) (Feng et al, 2022; Zhu et al, 2022). We suggest that during captivity management, we should enrich diets, promote good nutrient intake, monitor gut microbiome ecology, and improve dietary plans by combining multiple environmental factors.

5. Conclusion

In summary, this study set out to ascertain whether diets and the gut microbiota of Caudata are correlated. 1) We have revealed that diets profoundly affect the composition and diversity of the gut microbiota in the order Caudata and speculate that diets may affect the selection and adaptability of shared core ASVs in the order Caudata 2) Changes in diets lead to potential adaptation of the gut microbiota in Caudata, and we predict that diets have profound consequences for the potential function of the gut microbiota.

This research advances our knowledge of the ecological adaptability of the gut microbiota of amphibians and the insights gained from this study may be of assistance to extending knowledge of the effects of human-induced environmental disruptions on the symbiotic microbiota of amphibians. This is particularly important for amphibians belonging to the order Caudata, as feeding habits are to some extent closely related to the function of amphibian gut microbiota Our study is an empirical investigation of how diets affect the gut microbiota of the order Caudata in amphibians which provides fundamental knowledge for the management and protection of Caudata.

Acknowledgements This research was funded by the National Natural Science Foundation of China (31901120 and 31700320), China Postdoctoral Science Foundation (2022M723135), Beijing Natural Science Foundation (5192016), Anhui Provincial Key Laboratory of the Conservation and Exploitation of Biological Resources (swzy202006), Innovation and Entrepreneurship Training Program for college students of Anhui Normal University. The animal study was reviewed and approved by Anhui Normal University.

Supplementary information Supplementary information for this paper is available at https://doi.org/ 10.3724/ahr.2095-0357.2023.0028

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