Ding Xia, Jin Feng, Xu Jiawang, Zhang Shulei, Chen Dongxu, Hu Beijuan, Hong Yijiang
School of Life Sciences Nanchang University Nanchang Jiangxi China.
Imeta. 2022 Apr 5;1(2):e17. doi: 10.1002/imt2.17. eCollection 2022 Jun.
The commercial aquatic animal microbiome may markedly affect the successful host's farming in various aquaculture systems. However, very little was known about it. Here, two different aquaculture systems, the rice-fish culture (RFC) and intensive pond culture (IPC) systems, were compared to deconstruct the skin, oral, and gut microbiome, as well as the gut metabolome of juvenile Chinese softshell turtle (). Higher alpha-diversity and functional redundancy of microbial community were found in the RFC than those of the IPC. The aquaculture systems have the strongest influence on the gut microbiome, followed by the skin microbiome, and finally the oral microbiome. Source-tracking analysis showed that the RFC's microbial community originated from more unknown sources than that of the IPC across all body regions. Strikingly, the RFC's oral and skin microbiome exhibited a significantly higher proportion of generalists and broader habitat niche breadth than those of the IPC, but not the gut. Null model analysis revealed that the RFC's oral and skin microbial community assembly was governed by a significantly greater proportion of deterministic processes than that of the IPC, but not the gut. We further identified the key gene and microbial contribution to five significantly changed gut metabolites, 2-oxoglutarate, -acetyl-d-mannosamine, -4-hydroxy-d-proline, nicotinamide, and l-alanine, which were significantly correlated with important categories of microbe-mediated processes, including the amino acid metabolism, GABAergic synapse, ABC transporters, biosynthesis of unsaturated fatty acids, as well as citrate cycle. Moreover, different aquaculture systems have a significant impact on the hepatic lipid metabolism and body shape of . Our results provide new insight into the influence of aquaculture systems on the microbial community structure feature and assembly mechanism in an aquatic animal, also highlighting the key microbiome and gene contributions to the metabolite variation in the gut microbiome-metabolome association.
商业水产动物的微生物群可能会显著影响各种水产养殖系统中宿主养殖的成功与否。然而，人们对其了解甚少。在此，比较了两种不同的水产养殖系统，即稻鱼共生养殖（RFC）和集约化池塘养殖（IPC）系统，以解析中华鳖幼鳖的皮肤、口腔和肠道微生物群以及肠道代谢组。结果发现，RFC中微生物群落的α多样性和功能冗余度高于IPC。水产养殖系统对肠道微生物群的影响最大，其次是皮肤微生物群，最后是口腔微生物群。溯源分析表明，在所有身体部位，RFC的微生物群落比IPC的微生物群落来源更多未知。引人注目的是，RFC的口腔和皮肤微生物群中泛养菌的比例显著高于IPC，且栖息地生态位宽度更广，但肠道微生物群并非如此。空模型分析表明，RFC的口腔和皮肤微生物群落组装受确定性过程控制的比例显著高于IPC，但肠道微生物群并非如此。我们进一步确定了对五种显著变化的肠道代谢物（2-氧代戊二酸、N-乙酰-D-甘露糖胺、N-4-羟基-D-脯氨酸、烟酰胺和L-丙氨酸）有重要贡献 的关键基因和微生物，这些代谢物与微生物介导的重要过程类别显著相关，包括氨基酸代谢、GABA能突触、ABC转运蛋白、不饱和脂肪酸生物合成以及柠檬酸循环。此外，不同的水产养殖系统对中华鳖的肝脏脂质代谢和体型有显著影响。我们的研究结果为水产养殖系统对水生动物微生物群落结构特征和组装机制的影响提供了新的见解，同时也突出了关键微生物群和基因对肠道微生物群-代谢组关联中代谢物变化的贡献。
