Integrative analyses of geochemical parameters-microbe interactions reveal the variation of bacterial community assembly in multiple metal(loid)s contaminated arable regions

文献类型： 外文期刊

第一作者： Liu, Huakang

作者： Liu, Huakang;Wei, Mingyang;Huang, Huayan;Wu, Bohan;Xu, Heng;Shangguan, Yuxian;Xu, Heng;Xu, Heng

作者机构：

关键词： Arable soils; Multiple metals contamination; Bacterial community assemblages; Geochemical parameters-microbes interactions; Dehydrogenase

期刊名称：ENVIRONMENTAL RESEARCH （ 影响因子：8.431； 五年影响因子：8.399 ）

ISSN： 0013-9351

年卷期： 2022 年 208 卷

页码：

收录情况： SCI

摘要： Soil microbes play crucial roles in biochemical and geochemical processes in contaminated arable ecosystems. However, what factors determine the assembling process of soil bacterial community under multiple heavy metal (loid)s (HMs) stress and how communities respond to geochemical changes have rarely been understood. Therefore, a number of contaminated soils were sampled to explore the interactions among geochemical parameters, HMs and innate bacterial community. The results showed that soil biochemical activities were inhibited obviously with the increase of HMs. Significant differences were observed in bacterial composition and abundance in studied areas, with Actinobacteria, Proteobacteria, Chloroflexi, Acidobacteria and Firmicutes governing the bacterial community structure. Redundancy analysis and variation partition analysis revealed that about 67.33% of the variation in bacterial assemblages could be explained by physiochemical parameters (21.59%), biochemical parameters (11.64%), toxic metal (loid)s (9.11%) and the interaction effect of these variables (24.99%), among which total-arsenic and moisture were the main factors. Spearman correlation analysis also demonstrated that dehydrogenase, moisture and TOC have a positive correlation with bacterial community structure with As-Cd-Pb gradient. Altogether, this study would provide a comprehensive relationship between major environmental factors and bacterial assemblages, which could offer some baseline data to investigate the mechanisms of how communities respond to physiochemical changes.

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