Evidence map›Paper›PMID 30726542›Full record

ArticleEnvironmental science and pollution research international2019

Characterization of iron-metabolizing communities in soils contaminated by acid mine drainage from an abandoned coal mine in Southwest China.

Pin Gao, Xiaoxu Sun, Enzong Xiao, Zhixian Xu, Baoqin Li, Weimin Sun

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  4. Effects of Wildfire on Soil COMicroorganisms · 2024
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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

6 authors.

Pin GaoGuangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, 808 Tianyuan Road, Guangzhou, 510650, Guangdong, China.
Xiaoxu SunGuangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, 808 Tianyuan Road, Guangzhou, 510650, Guangdong, China.
Enzong XiaoInnovation Center and Key Laboratory of Waters Safety and Protection in the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou, 510006, China.
Zhixian XuGuangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, 808 Tianyuan Road, Guangzhou, 510650, Guangdong, China.
Baoqin LiGuangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, 808 Tianyuan Road, Guangzhou, 510650, Guangdong, China.
Weimin SunGuangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, 808 Tianyuan Road, Guangzhou, 510650, Guangdong, China. wmsun@soil.gd.cn.

Funding

GDAS' Special Project of Science and Technology Development 2017GDASCX-0106GDAS' Special Project of Science and Technology Development 2018GDASCX-0601the Guangxi Innovation Drive Development Fund AA17204076the High-level Leading Talent Introduction Program of GDAS 2016GDASRC-0103the National Natural Science Foundation of China 41771301, 41420104007the Science and Technology Planning Project of Guangdong Province 2016B070701015
6 · The paper itself

Abstract

Acid mine discharge (AMD) has been demonstrated to have significant impacts on microbial community composition in the surrounding soil environment. However, their effect on adjacent soil has not been extensively studied. In this study, microbial community composition of 20 AMD-contaminated soil samples collected from an abandoned coal mine along an AMD creek was characterized using high-throughput sequencing. All samples were characterized as extremely low in pH (< 3) and relatively enriched in HCl-extractable Fe species. The dominant phylotypes were belonging to genera Ochrobactrum, Acidiphilium, Staphylococcus, Brevibacterium, and Corynebacterium. Canonical correspondence analysis results revealed that the HCl-extractable Fe(III) had a strong impact on the soil microbial assemblage. Co-occurrence network analysis revealed that Aquicella, Acidobacteriaceae, Ochrobactrum, Enhydrobacter, Sphingomonas, and Legionellales were actively correlated with other taxa. As expected, most of the abundant taxa have been reported as acidophilic Fe-metabolizing bacteria. Hence, a co-occurring sub-network and a phylogenetic tree related to microbial taxa responsible for Fe metabolism were constructed and described. The biotic interaction showed that Dechloromonas exhibited densely connections with Fe(III)-reducing bacteria of Comamonas, Burkholderia, Shewanella, Stenotrophomonas, Acidithiobacillus, and Pseudomonas. These results demonstrated that Fe-metabolizing bacteria could have an important role in the Fe biogeochemical cycling.

Indexed as

MiningSoil MicrobiologyAcidsBacteriaBiodegradation, EnvironmentalChinaCoalEnvironmental PollutionHydrogen-Ion ConcentrationIronPhylogenySoilAcidsCoalIronSoilAcid mine drainageCo-occurrence networkFe-metabolizing bacteriaMicrobial community

Identifiers

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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.