PDF(Pubmed)
Abstract：
Understanding the interactions between fish gut microbiota and the aquatic environment is a key issue for understanding aquatic microorganisms. Environmental microorganisms enter fish intestines through feeding, and the amount of invasion varies due to different feeding habits. Traditional fish feeding habitat preferences are determined by fish morphology or behavior. However, little is known about how the feeding behavior of fish relative to the vertical structure in a shallow lake influences gut microbiota. In our study, we used nitrogen isotopes to measure the trophic levels of fish. Then high-throughput sequencing was used to describe the composition of environmental microbiota and fish gut microbiota, and FEAST (fast expectation-maximization for microbial source tracking) method was used to trace the source of fish gut microbiota. We investigated the microbial diversity of fish guts and their habitats in Lake Sanjiao and verified that the sediments indeed played an important role in the assembly of fish gut microbiota. Then, the FEAST analysis indicated that microbiota in water and sediments acted as the primary sources in half of the fish gut microbiota respectively. Furthermore, we classified the vertical habitat preferences using microbial data and significant differences in both composition and function of fish gut microbiota were observed between groups with distinct habitat preferences. The performance of supervised and unsupervised machine learning in classifying fish gut microbiota by habitat preferences actually exceeded classification by fish species taxonomy and fish trophic level. Finally, we described the stability of fish co-occurrence networks with different habitat preferences. Interestingly, the co-occurrence network seemed more stable in pelagic fish than in benthic fish. Our results show that the preferences of fish in the vertical structure of habitat was the main factor affecting their gut microbiota. We advocated the use of microbial interactions between fish gut and their surrounding environment to reflect fish preferences in vertical habitat structure. This approach not only offers a novel perspective for understanding the interactions between fish gut microbiota and environmental factors, but also provides new methods and ideas for studying fish habitat selection in aquatic ecosystems.
摘要：
了解鱼类肠道微生物群与水生环境之间的相互作用是理解水生微生物的关键问题。环境微生物通过摄食进入鱼肠，入侵的数量因喂养习惯的不同而不同。传统的养鱼栖息地偏好取决于鱼类的形态或行为。然而,人们对浅湖中鱼相对于垂直结构的摄食行为如何影响肠道微生物群知之甚少。在我们的研究中,我们用氮同位素来测量鱼类的营养水平。然后采用高通量测序技术描述环境微生物群和鱼类肠道微生物群的组成,和FEAST（微生物来源追踪的快速期望最大化）方法用于追踪鱼肠微生物群的来源。我们调查了三焦湖鱼类肠道及其栖息地的微生物多样性，并验证了沉积物确实在鱼类肠道微生物群的组装中发挥了重要作用。然后，FEAST分析表明，水和沉积物中的微生物群分别是一半鱼类肠道微生物群的主要来源。此外，我们使用微生物数据对垂直栖息地偏好进行了分类，在具有不同栖息地偏好的群体之间，观察到鱼类肠道微生物群的组成和功能存在显着差异。有监督和无监督的机器学习在根据栖息地偏好对鱼肠微生物群进行分类方面的表现实际上超过了鱼类物种分类法和鱼类营养水平的分类。最后,我们描述了不同栖息地偏好的鱼类共生网络的稳定性。有趣的是,与底栖鱼类相比，中上层鱼类的共现网络似乎更稳定。我们的结果表明，鱼类在栖息地垂直结构中的偏好是影响其肠道菌群的主要因素。我们提倡利用鱼肠与其周围环境之间的微生物相互作用来反映鱼类在垂直栖息地结构中的偏好。这种方法不仅为理解鱼类肠道微生物群与环境因素之间的相互作用提供了新的视角。同时也为研究水生生态系统中鱼类生境选择提供了新的方法和思路。
