Evidence map›Paper›PMID 41011342›Full record

ArticleMicroorganisms2025

Spatial Differentiation of Heavy Metals/Metalloids, Microbial Risk Genes and Soil Microbiota in a Sulfur-Contaminated Landscape.

Lina Li, Jiayin Zhao, Chang Liu, Yiyan Deng, Yunpeng Du, Yu Liu, Yuncheng Wu, Wenwei Wu, Xuejun Pan

Abstract read
In one paragraph

Article in Microorganisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lina LiFaculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
Jiayin ZhaoNanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
Chang LiuYunnan Academy of Ecological and Environmental Sciences, Kunming 650034, China.
Yiyan DengYunnan Academy of Ecological and Environmental Sciences, Kunming 650034, China.
Yunpeng DuYunnan Academy of Ecological and Environmental Sciences, Kunming 650034, China.ORCID 0000-0003-1576-2107
Yu LiuNanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
Yuncheng WuNanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
Wenwei WuYunnan Academy of Ecological and Environmental Sciences, Kunming 650034, China.
Xuejun PanFaculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.ORCID 0000-0003-3772-6908

Funding

Yunnan Province Science and Technology Plan project 202203AC100001
6 · The paper itself

Abstract

Legacy sulfur smelting has left behind complex contamination landscapes, yet the spatial structuring of microbial risks and adaptation strategies across soil profiles remains insufficiently understood. Microbial risk genes, including those conferring resistance to antibiotic resistance (ARGs), biocide and metal resistance (BRGs/MRGs), and virulence (VFGs), are increasingly recognized as co-selected under heavy metal stress, posing both ecological and public health concerns. In this study, we integrated geochemical analyses with metagenomic sequencing and functional annotation to jointly characterize the vertical (0-7 m) and horizontal (~2 km) distribution of heavy metals/metalloids, microbial communities, and functional risk genes at a historic smelting site in Zhenxiong, Yunnan. Heavy metals and metalloids such as arsenic (As), chromium (Cr), copper (Cu), and lead (Pb) showed clear accumulation with depth, while significantly lower concentrations were observed in both upstream and downstream locations, revealing persistent vertical and horizontal pollution gradients. Correspondingly, resistance and virulence genes were co-enriched at contaminated sites, suggesting potential co-selection under prolonged stress. LEfSe analysis revealed distinct ecological patterns: vertically, upper layers were dominated by nutrient-cycling and mildly stress-tolerant taxa, while deeper layers favored metal-resistant, oligotrophic, and potentially pathogenic microorganisms; horizontally, beneficial and diverse microbes characterized low-contamination zones, whereas heavily polluted areas were dominated by resistant and stress-adapted genera. These findings provide new insights into microbial resilience and ecological risk under long-term smelting stress.

Indexed as

heavy metal and metalloids contaminationmetagenomicssoil microbial communitiesspatial distributionsulfur smelting

Identifiers

PMID41011342
PMCPMC12473080

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.