水生动物中的微生物群落与周围环境中的微生物群落之间的相互作用对于健康的水生动物和水生环境的生态平衡都很重要。小龙虾(Clarkii),具有很高的商业价值,已成为中国产量最高的淡水虾。传统的池塘种植(即,单一文化,MC)和水稻共育领域的新兴种植(即,大米-小龙虾共同养殖,RC)是小龙虾的两种主要养殖模式,综合RC被认为是生态农业系统中成功的稻畜一体化实践。本研究探索了小龙虾肠道微生物群落与周围环境之间的生态相互作用,迄今为止尚未完全描述。小龙虾肠道中的细菌群落,周围的水,利用MiSeq测序和遗传网络分析了两种主要小龙虾养殖模式中的沉积物。总的来说,鉴定出53门和1,206属,其中变形杆菌,放线菌,Tenericutes,Firmicutes,蓝细菌,氯氟菌,拟杆菌,酸杆菌,RsaHF231和Nitrosirae是主要的门。水之间的微生物群组成显着不同,沉积物,和小龙虾的肠道,虽然它不在两种育种模式之间。我们还基于Spearman相关性ρ≥0.75的高置信度相互作用生成了共生相关网络。在属相关网络中,识别了95个节点和1,158条边,表明小龙虾肠道与环境之间存在显著的属相互作用。此外,属分为三个模块,基于不同的环境。此外,念珠菌_支原体,g_norank_f_类固醇杆菌科,Dinghuibacter,Hydrogenophaga,甲基副球菌,Defluviicoccus具有最高的介数中心性,在小龙虾与周围环境之间的相互作用中可能很重要。总的来说,这项研究增强了我们对小龙虾及其周围环境中微生物群特征的理解。此外,我们的发现为小龙虾生态农业系统的微生态平衡提供了见解,并为此类系统的发展提供了理论参考。
The interaction between the microbial communities in aquatic animals and those in the ambient environment is important for both healthy aquatic animals and the ecological balance of aquatic environment. Crayfish (Procambarus clarkii), with their high commercial value, have become the highest-yield freshwater shrimp in
China. The traditional cultivation in ponds (i.e., monoculture, MC) and emerging cultivation in rice co-culture fields (i.e., rice-crayfish co-culture, RC) are the two main breeding modes for crayfish, and the integrated RC is considered to be a successful rice-livestock integration practice in eco-agricultural systems. This study explored the ecological interactions between the microbial communities in crayfish intestine and the ambient environment, which have not been fully described to date. The bacterial communities in crayfish intestine, the surrounding water, and sediment in the two main crayfish breeding modes were analyzed with MiSeq sequencing and genetic networks. In total, 53 phyla and 1,206 genera were identified, among which Proteobacteria, Actinobacteria, Tenericutes, Firmicutes, Cyanobacteria, Chloroflexi, Bacteroidetes, Acidobacteria, RsaHF231, and Nitrospirae were the dominant phyla. The microbiota composition significantly differed between the water, sediment, and crayfish intestine, while it did not between the two breeding modes. We also generated a co-occurrence correlation network based on the high-confidence interactions with Spearman correlation ρ ≥ 0.75. In the genera co-correlation network, 95 nodes and 1,158 edges were identified, indicating significant genera interactions between crayfish intestine and the environment. Furthermore, the genera clustered into three modules, based on the different environments. Additionally, Candidatus_Bacilloplasma, g_norank_f_Steroidobacteraceae, Dinghuibacter, Hydrogenophaga, Methyloparacoccus, and Defluviicoccus had the highest betweenness centrality and might be important in the interaction between crayfish and the ambient environment. Overall, this study enhances our understanding of the characteristics of the microbiota in crayfish and their surrounding environment. Moreover, our findings provide insights into the microecological balance in crayfish eco-agricultural systems and theoretical reference for the development of such systems.