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Updated: Jun 28, 2025

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Published on: February 15, 2021
Arsenic stress on soil microbial nutrient metabolism interpreted by microbial utilization of dissolved organic carbon
Huayong Li1, Ziquan Wang1, Bingcong Feng1
1College of Natural Resources and Environment, Northwest A&F University, Key Laboratory of Plant Nutrition and Agro-environment in Northwest China, Ministry of Agriculture, Yangling 712100, Shaanxi, China.
Abstract:
In a 120-day microcosm incubation experiment, we investigated the impact of arsenic contamination on soil microbial nutrient metabolism, focusing on carbon cycling processes. Our study encompassed soil basal respiration, key enzyme activities (particularly, β-1,4-N-acetylglucosaminidase and phosphatases), microbial biomass, and community structure. Results revealed a substantial increase (1.21-2.81 times) in β-1,4-N-acetylglucosaminidase activities under arsenic stress, accompanied by a significant decrease (9.86%-45.20%) in phosphatase activities (sum of acid and alkaline phosphatases). Enzymatic stoichiometry analysis demonstrated the mitigation of microbial C and P requirements in response to arsenic stress. The addition of C-sources alleviated microbial C requirements but exacerbated P requirements, with the interference amplitude increasing with the complexity of the C-source. Network analysis unveiled altered microbial nutrient requirements and an increased resistance process of microbes under arsenic stress. Microbial carbon use efficiency (CUE) and basal respiration significantly increased (1.17-1.59 and 1.18-3.56 times, respectively) under heavy arsenic stress (500 mg kg-1). Arsenic stress influenced the relative abundances of microbial taxa, with Gemmatimonadota increasing (5.5-50.5%) and Bacteroidota/ Nitrospirota decreasing (31.4-47.9% and 31.2-63.7%). Application of C-sources enhanced microbial resistance to arsenic, promoting cohesion among microorganisms. These findings deepen our understanding of microbial nutrient dynamics in arsenic-contaminated areas, which is crucial for developing enzyme-based toxicity assessment systems for soil arsenic contamination.
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