Deciphering the Structure and Genetic Basis of Adaptive Mechanism of Soil Microbial Communities in a Manganese Electrolysis Plant

The development of China's manganese (Mn) industries has caused severe water and soil pollution, threatening ecological and human health. Microbes are usually regarded as an important indicator of environmental pollution assessment. However, the current understanding of microbial community characteristics and their formation mechanisms in Mn production areas remains limited. In order to address this, soil properties and microbial structural characteristics across different functional zones in a typical Mn electrolysis plant in China's "Manganese Triangle" were investigated via metagenomic sequencing. Results showed soil Mn levels significantly exceeded background values, indicating high environmental risk. <i>Acidobacteria</i> and <i>Proteobacteria</i> were dominant phyla. Microbial abundance was lowest in the adjacent natural reservoir, whereas diversity was highest in the sewage treatment plant. Correlation analyses identified Mn, nitrate nitrogen, ammonium nitrogen, pH, and moisture as key environmental drivers, with Mn being the primary one. Metagenomic analysis revealed abundant Mn resistance genes, enabling microbial survival under high Mn stress. This study demonstrated that excessive Mn exposure enriched Mn-resistant genes, thereby shaping unique microbial communities dominated by Mn-resistant bacteria. These findings clarified the structural characteristics and adaptive mechanisms of soil microbial communities in Mn-contaminated areas, providing a theoretical basis for ecological risk management and bioremediation.

Authors

Institutions

Publication Details

Journal
Microorganisms
Published
2025-12-20
DOI
https://doi.org/10.3390/microorganisms14010015
Primary Topic
Geochemistry and Elemental Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deciphering the Structure and Genetic Basis of Adaptive Mechanism of Soil Microbial Communities in a Manganese Electrolysis Plant

Chunlian Ding, Song Liu, Yuan Xiang, Yan Shi et al.
Microorganisms
Geochemistry and Elemental Analysis
article

Deciphering the Structure and Genetic Basis of Adaptive Mechanism of Soil Microbial Communities in a Manganese Electrolysis Plant

Chunlian Ding, Song Liu, Yuan Xiang, Yan Shi, Yong Wang, Lanyan Wu, Jun Ma, Ziyi Zheng
article en

Abstract

The development of China's manganese (Mn) industries has caused severe water and soil pollution, threatening ecological and human health. Microbes are usually regarded as an important indicator of environmental pollution assessment. However, the current understanding of microbial community characteristics and their formation mechanisms in Mn production areas remains limited. In order to address this, soil properties and microbial structural characteristics across different functional zones in a typical Mn electrolysis plant in China's "Manganese Triangle" were investigated via metagenomic sequencing. Results showed soil Mn levels significantly exceeded background values, indicating high environmental risk. <i>Acidobacteria</i> and <i>Proteobacteria</i> were dominant phyla. Microbial abundance was lowest in the adjacent natural reservoir, whereas diversity was highest in the sewage treatment plant. Correlation analyses identified Mn, nitrate nitrogen, ammonium nitrogen, pH, and moisture as key environmental drivers, with Mn being the primary one. Metagenomic analysis revealed abundant Mn resistance genes, enabling microbial survival under high Mn stress. This study demonstrated that excessive Mn exposure enriched Mn-resistant genes, thereby shaping unique microbial communities dominated by Mn-resistant bacteria. These findings clarified the structural characteristics and adaptive mechanisms of soil microbial communities in Mn-contaminated areas, providing a theoretical basis for ecological risk management and bioremediation.

MicroorganismsVol. 14(1)
Central South University (CN), Chongqing University (CN), Tongren University (CN)
Clean water and sanitation
Openalex Percentile: Top 32%
Geochemistry and Elemental Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.