College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, 310032, PR China.
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang, 310032, PR China.
Environ Pollut. 2022 Aug 15;307:119528. doi: 10.1016/j.envpol.2022.119528. Epub 2022 May 24.
With the rapid development of nanotechnology in agriculture, there is increasing urgency to assess the impacts of nanoparticles (NPs) on the soil environment. This study merged raw high-throughput sequencing (HTS) data sets generated from 365 soil samples to reveal the potential ecological effects of NPs on soil microbial community by means of metadata analysis and machine learning methods. Metadata analysis showed that treatment with nanoparticles did not have a significant impact on the alpha diversity of the microbial community, but significantly altered the beta diversity. Unfortunately, the abundance of several beneficial bacteria, such as Dyella, Methylophilus, Streptomyces, which promote the growth of plants, and improve pathogenic resistance, was reduced under the addition of synthetic nanoparticles. Furthermore, metadata demonstrated that nanoparticles treatment weakened the biosynthesis ability of cofactors, carriers, and vitamins, and enhanced the degradation ability of aromatic compounds, amino acids, etc. This is unfavorable for the performance of soil functions. Besides the soil heterogeneity, machine learning uncovered that a) the exposure time of nanoparticles was the most important factor to reshape the soil microbial community, and b) long-term exposure decreased the diversity of microbial community and the abundance of beneficial bacteria. This study is the first to use a machine learning model and metadata analysis to investigate the relationship between the properties of nanoparticles and the hazards to the soil microbial community from a macro perspective. This guides the rational use of nanoparticles for which the impacts on soil microbiota are minimized.
随着农业纳米技术的快速发展，评估纳米颗粒（NPs）对土壤环境的影响变得愈发紧迫。本研究合并了 365 个土壤样本的原始高通量测序（HTS）数据集，通过元数据分析和机器学习方法揭示了 NPs 对土壤微生物群落的潜在生态影响。元数据分析表明，纳米颗粒处理并未显著影响微生物群落的α多样性，但显著改变了β多样性。不幸的是，一些有益细菌（如 Dyella、Methylophilus、Streptomyces 等）的丰度降低了，这些细菌能促进植物生长，提高对病原体的抗性，但在添加合成纳米颗粒后，它们的丰度降低了。此外，元数据表明，纳米颗粒处理削弱了辅酶、载体和维生素的生物合成能力，并增强了芳香族化合物、氨基酸等的降解能力。这对土壤功能的发挥不利。除了土壤异质性外，机器学习还揭示了 a）纳米颗粒的暴露时间是重塑土壤微生物群落的最重要因素，b）长期暴露会降低微生物群落的多样性和有益细菌的丰度。本研究首次使用机器学习模型和元数据分析从宏观角度研究了纳米颗粒的性质与土壤微生物群落危害之间的关系。这为合理利用纳米颗粒提供了指导，以最大程度地减少其对土壤微生物群的影响。
