School of Environmental and Safety Engineering, Changzhou University, Changzhou, 213164, China; State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China.
School of Environmental and Safety Engineering, Changzhou University, Changzhou, 213164, China.
Environ Res. 2021 Oct;201:111584. doi: 10.1016/j.envres.2021.111584. Epub 2021 Jun 27.
Microbes mediate the arsenic detoxification in paddy soils, determining the fate of arsenic in soils and its availability to rice plants, yet little is known about the structures and abundances of functional genes as well as the driving forces in low-arsenic paddy fields. To depict the arsenic detoxification functional gene patterns, 429 soil samples were collected from 39 paddy fields across four climatic zones in China, with the arsenic contents ranged from 9.76 to 19.74 mg kg. GeoChip, a microarray-based metagenomic technique, was used to analyze the functional genes involved in arsenic detoxification. A total of three arsenic detoxification gene families were detected, aoxB, arxA (arsenite oxidase), and arsM (methyltransferase). Both the diversity and abundance of functional genes varied significantly among sampling sites (p < 0.05) and decreased along the arsenic gradient. Arsenic detoxification genes were carried by bacteria, archaea, and eukaryotes. Redundancy analysis showed that soil samples were grouped according to both climatic zones they located in and arsenic gradients at the continental scale. Soil pH, average annual temperature (AAT), arsenic, annual average precipitation (AAP), and CEC were the most important factors in shaping the functional structure. Structural equation modeling showed that AAT (r = 0.21), pH (r = -0.20), and arsenic contents (r = -0.11) directly affected the arsenic detoxification gene abundances. These findings provide an overall picture of microbial communities involved in arsenic detoxification in paddy soils and reveal the importance of climatic factors in shaping functional genes across a large spatial scale.
微生物介导了稻田中砷的解毒作用，决定了砷在土壤中的归宿及其对水稻植株的有效性，但对于低砷稻田中功能基因的结构和丰度以及驱动因素知之甚少。为了描绘砷解毒功能基因的模式，我们从中国四个气候带的 39 个稻田中采集了 429 个土壤样本，砷含量范围为 9.76 至 19.74mg/kg。GeoChip 是一种基于微阵列的宏基因组技术，用于分析参与砷解毒的功能基因。共检测到三种砷解毒基因家族，aoxB、arxA（亚砷酸盐氧化酶）和 arsM（甲基转移酶）。功能基因的多样性和丰度在采样点之间存在显著差异（p<0.05），并沿砷梯度下降。砷解毒基因由细菌、古菌和真核生物携带。冗余分析表明，土壤样本根据其所处的气候带和大陆尺度上的砷梯度进行分组。土壤 pH 值、年平均温度（AAT）、砷含量、年平均降水量（AAP）和 CEC 是塑造功能结构的最重要因素。结构方程模型表明，AAT（r=0.21）、pH（r=-0.20）和砷含量（r=-0.11）直接影响砷解毒基因的丰度。这些发现提供了一个整体的图景，说明了参与稻田中砷解毒的微生物群落，并揭示了气候因素在塑造大空间尺度上的功能基因方面的重要性。
