Evidence map›Paper›PMID 26391875›Full record

ArticleScientific reports2015

An integrated insight into the response of sedimentary microbial communities to heavy metal contamination.

Huaqun Yin, Jiaojiao Niu, Youhua Ren, Jing Cong, Xiaoxia Zhang, Fenliang Fan, Yunhua Xiao, Xian Zhang, Jie Deng, Ming Xie and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing 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

59 citing papers in PubMed.

  1. Catchment to coast contaminant transport to a protected marine park on the East coast of Australia.Environmental science and pollution research international · 2026
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  5. Review
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  15. Journal of microbiology and biotechnology · 2022
    Article
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  18. Review
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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

14 authors.

Huaqun YinSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Jiaojiao NiuSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Youhua RenCollege of Food Science and Technology, Hunan Agricultural University, Changsha 410083, China.
Jing CongSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Xiaoxia ZhangKey Laboratory of Microbial Resources Collection and Preservation, Ministry of Agriculture, Beijing 100081, China.
Fenliang FanKey Laboratory of Plant Nutrition and Fertilizer, Beijing 100081, China.
Yunhua XiaoSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Xian ZhangSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Jie DengInstitute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman 73019, USA.
Ming XieInstitute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman 73019, USA.
Zhili HeInstitute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman 73019, USA.
Jizhong ZhouInstitute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman 73019, USA.
Yili LiangSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.
Xueduan LiuSchool of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Response of biological communities to environmental stresses is a critical issue in ecology, but how microbial communities shift across heavy metal gradients remain unclear. To explore the microbial response to heavy metal contamination (e.g., Cr, Mn, Zn), the composition, structure and functional potential of sedimentary microbial community were investigated by sequencing of 16S rRNA gene amplicons and a functional gene microarray. Analysis of 16S rRNA sequences revealed that the composition and structure of sedimentary microbial communities changed significantly across a gradient of heavy metal contamination, and the relative abundances were higher for Firmicutes, Chloroflexi and Crenarchaeota, but lower for Proteobacteria and Actinobacteria in highly contaminated samples. Also, molecular ecological network analysis of sequencing data indicated that their possible interactions might be enhanced in highly contaminated communities. Correspondently, key functional genes involved in metal homeostasis (e.g., chrR, metC, merB), carbon metabolism, and organic remediation showed a higher abundance in highly contaminated samples, indicating that bacterial communities in contaminated areas may modulate their energy consumption and organic remediation ability. This study indicated that the sedimentary indigenous microbial community may shift the composition and structure as well as function priority and interaction network to increase their adaptability and/or resistance to environmental contamination.

Indexed as

BiodiversityEnvironmental PollutionMicrobiotaSoil MicrobiologyGeologic SedimentsMetagenomeMetagenomicsMetals, HeavyPhylogenyRNA, Ribosomal, 16SMetals, HeavyRNA, Ribosomal, 16S

Identifiers

PMID26391875
PMCPMC4585741

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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.