Tai Xin, Li Rui, Zhang Bao, Yu Hao, Kong Xiao, Bai Zhihui, Deng Ye, Jia Lan, Jin Decai
College of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China.
CAS Key Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Microorganisms. 2020 Feb 24;8(2):311. doi: 10.3390/microorganisms8020311.
Understanding the effects of pollution on ecological communities and the underlying mechanisms that drive them will helpful for selecting a method to mediate polluted ecosystems. Quantifying the relative importance of deterministic and stochastic processes is a very important issue in ecology. However, little is known about their effects on the succession of microbial communities in different pollution levels rural ponds. Also, the processes that govern bacterial communities in polluted ponds are poorly understood. In this study, the microbial communities in water and sediment from the ponds were investigated by using the 16S rRNA gene high-throughput sequencing technology. Meanwhile, we used null model analyses based on a taxonomic and phylogenetic metrics approach to test the microbial community assembly processes. Pollution levels were found to significantly alter the community composition and diversity of bacteria. In the sediment samples, the bacterial diversity indices decreased with increasing pollutant levels. Between-community analysis revealed that community assembly processes among water and sediment samples stochastic ratio both gradually decreased with the increased pollution levels, indicating a potential deterministic environmental filtering that is elicited by pollution. Our results identified assemblage drivers of bacterial community is important for improving the efficacies of ecological evaluation and remediation for contaminated freshwater systems.
了解污染对生态群落的影响以及驱动这些影响的潜在机制,将有助于选择调节受污染生态系统的方法。量化确定性和随机过程的相对重要性是生态学中的一个非常重要的问题。然而,对于它们对不同污染水平的农村池塘中微生物群落演替的影响知之甚少。此外,对受污染池塘中细菌群落的控制过程也了解不足。在本研究中,利用16S rRNA基因高通量测序技术对池塘水体和沉积物中的微生物群落进行了调查。同时,我们基于分类学和系统发育指标方法使用零模型分析来测试微生物群落组装过程。研究发现污染水平会显著改变细菌的群落组成和多样性。在沉积物样本中,细菌多样性指数随污染物水平的增加而降低。群落间分析表明,水体和沉积物样本中的群落组装过程随机比率均随着污染水平的增加而逐渐降低,这表明污染引发了潜在的确定性环境过滤作用。我们的研究结果表明,确定细菌群落的组装驱动因素对于提高受污染淡水系统的生态评估和修复效果非常重要。