Zebrafish (Danio rerio) have attracted much attention over the past decade as a reliable model for gut microbiome research. Owing to their low cost, strong genetic and development coherence, efficient preparation of germ‐free (GF) larvae, availability in high‐throughput chemical screening, and fitness for intravital imaging in vivo, zebrafish have been extensively used to investigate microbiome‐host interactions and evaluate the toxicity of environmental pollutants. In this review, the advantages and disadvantages of zebrafish for studying the role of the gut microbiome compared with warm‐blooded animal models are first summarized. Then, the roles of zebrafish gut microbiome on host development, metabolic pathways, gut‐brain axis, and immune disorders and responses are addressed. Furthermore, their applications for the toxicological assessment of aquatic environmental pollutants and exploration of the molecular mechanism of pathogen infections are reviewed. We highlight the great potential of the zebrafish model for developing probiotics for xenobiotic detoxification, resistance against bacterial infection, and disease prevention and cure. Overall, the zebrafish model promises a brighter future for gut microbiome research.

Background: Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown. Results: Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and β diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn’t entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R² = 0.6563), links (P < 0.01, R² = 0.4543), number of modules (P = 0.0672, R² = 0.2523), relative modularity (P = 0.6714, R² = 0.0155), number of keystones (P = 0.1003, R² = 0.2090), robustness_random (P = 0.79, R² = 0.0063), and vulnerability (P = 0.0528, R² = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice. Conclusions: These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children’s brief exposure to antibiotics if the results observed in mice are applicable to humans.

Arsenic, a global pollutant and a threshold-free primary carcinogen, can accumulate in rice. Previous studies have focused on arsenic poisoning in drinking water and the effects on gut microbes. The research on arseniasis through food, which involves the bio-transformation of arsenic, and the related changes in gut microbiome is insufficient. Mice were exposed from animal feed prepared with four arsenic species (iAsIII, iAsV, MMA, and DMA) at a dose of 30 mg/kg according to the arsenic species proportion in rice for 30 days and 60 days. The levels of total arsenic (tAs) and arsenic species in mice feces and urine samples were determined using ICP-MS and HPLC-ICP-MS, respectively. 16S rRNA and ITS gene sequencing were conducted on microbial DNA extracted from the feces samples. At 30 days and 60 days exposure, the tAs levels excreted from urine were 0.0092 and 0.0093 mg/day, and tAs levels in feces were 0.0441 and 0.0409 mg/day, respectively. We found significant differences in arsenic species distribution in urine and feces (p < 0.05). In urine, the predominant arsenic species were iAsIII (23% and 14%, respectively), DMA (55% and 70%, respectively), and uAs (unknown arsenic, 14% and 10%, respectively). In feces, the proportion of major arsenic species (iAsV, 26% and 21%; iAsIII, 16% and 15%; MMA, 14% and 14%; DMA, 19% and 19%; and uAs, 22% and 29%, respectively) were evenly distributed. Microbiological analysis (MRPP test, α- and β-diversities) showed that diversity of gut bacteria was significantly related to arsenic exposure through food, but diversity of gut fungi is less affected. Manhattan plot and LEfSe analysis showed that arsenic exposure significantly changes microbial taxa, which might be directly associated with arsenic metabolism and diseases mediated by arsenic exposure, such as Deltaproteobacteria, Polynucleobacter, Saccharomyces, Candida, Amanitaceae, and Fusarium. Network analysis was used to identify the changing hub taxa in feces along with arsenic exposure. Function predicting analysis indicated that arsenic exposure might also significantly increase differential metabolic pathways and would disturb carbohydrates, lipid, and amino acids metabolism of gut bacteria. The results demonstrate that subchronic arsenic exposure via food significantly changes the gut microbiome, and the toxicity of arsenic in food, especially in staples, should be comprehensively evaluated in terms of the disturbance of microbiome, and feces might be the main pathway through which arsenic from food exposure is excreted and bio-transformed, providing a new insight into the investigation of bio-detoxification for arseniasis.

Gut microbiome can participate in arsenic metabolism. However, its efficacy in the host under arsenic stress is still controversial. To clarify their roles in fecal arsenic excretion, tissue arsenic accumulation, host physiological states and metabolism, in this study, ninety-six C57BL/6 male mice were randomly divided to four groups, groups A and B were given sterile water, and groups C and D were given the third generation of broad-spectrum antibiotic (ceftriaxone) to erase the background gut microbiome. Subsequently, groups B and D were subchronicly exposed to arsenic containing feed prepared by adding arsenical mixture (rice arsenic composition) into control feed. In group D, the fecal total arsenic (C_tAs) decreased by 25.5 %, iAs^III composition increased by 46.9 %, unclarified As (uAs) composition decreased by 92.4 %, and the liver C_tAs increased by 26.7 %; the fecal C_tAs was positively correlated with microbial richness and some metabolites (organic acids, amino acids, carbohydrates, SCFAs, hydrophilic bile acids and their derivatives); and fecal DMA was positively correlated with microbial richness and some metabolites (ferulic acid, benzenepropanoic acid and pentanoic acid); network analysis showed that the numbers of modules, nodes, links were decreased and vulnerability was increased; some SCFAs and hydrophilic bile acid decreased, and hydrophobic bile acids increased (Ps < 0.05). In the tissue samples of group D, Il-18 and Ifn-γ gene expression increased and intestinal barrier-related genes Muc2, Occludin and Zo-1 expression decreased (Ps < 0.05); serum glutathione and urine malondialdehyde significantly increased (Ps < 0.05); urine metabolome significantly changed and the variation was correlated with six SCFAs-producing bacteria, and some SCFAs including isobutyric acid, valeric acid and heptanoic acid decreased (Ps < 0.05). Therefore, the normal gut microbiome increases fecal arsenic excretion and biotransformation, which can maintain a healthier microbiome and metabolic functions, and alleviate the metabolic disorder for their mammal host under arsenic exposure.

Chinese Cordyceps is a well-known medicinal larva-fungus symbiote distributed in the Qinghai-Tibetan Plateau and adjacent areas. Previous studies have involved its artificial cultivation but commercial cultivation is difficult to perform because the crucial factors triggering the occurrence of Chinese Cordyceps are not quite clear. The occurrence of Chinese Cordyceps is greatly affected by the soil environment, including the soil’s physicochemical and microecological properties. In this study, the effects of these soil properties on the occurrence of Chinese Cordyceps were investigated. The results show that the physicochemical properties, including easily oxidizable organic carbon (EOC), soil organic carbon (SOC), humic acid carbon (HAC), humin carbon (HMC), and pH, might be negatively related to the occurrence of Chinese Cordyceps, and soil water content (SWC) might be positively related. Several soil physicochemical parameters (pH, SOC, HMC, HAC, available potassium (APO), available phosphorus (APH), microbial biomass carbon (MBC), and the ratio of NH₄⁺ to NO₃⁻ (NH₄⁺/NO₃⁻)) and microbial properties interact and mix together, which might affect the occurrence of Chinese Cordyceps. Soil microbial community structure was also a possible factor, and a low level of bacterial and fungal diversity was suitable for the occurrence of Chinese Cordyceps. The intra-kingdom network revealed that a closer correlation of the bacterial community might help the occurrence of Chinese Cordyceps, while a closer correlation of the fungal community might suppress it. The inter-kingdom network revealed that the occurrence rate of Chinese Cordyceps might be negatively correlated with the stability of the correlation state of the soil habitat. In conclusion, this study shows that soil physicochemical properties and microbial communities could be greatly related with the occurrence of Chinese Cordyceps. In addition, soil physicochemical properties, the level of bacterial and fungal diversity, and correlations of bacterial and fungal communities should be controlled to a certain level to increase the production of Chinese Cordyceps in artificial cultivation.