Evidence map›Paper›PMID 37287448›Full record

ArticleFrontiers in microbiology2023

Petroleum pollution changes microbial diversity and network complexity of soil profile in an oil refinery.

Jugui Zhuang, Ruihuan Zhang, Yufei Zeng, Tianjiao Dai, Zhencheng Ye, Qun Gao, Yunfeng Yang, Xue Guo, Guanghe Li, Jizhong Zhou

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. 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.

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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

10 authors.

Jugui ZhuangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Ruihuan ZhangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Yufei ZengState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Tianjiao DaiSchool of Water Resources and Environment, China University of Geosciences, Beijing, China.
Zhencheng YeState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Qun GaoState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Yunfeng YangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Xue GuoState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Guanghe LiState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
Jizhong ZhouInstitute for Environmental Genomics, University of Oklahoma, Norman, OK, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Petroleum pollution resulting from spills and leakages in oil refinery areas has been a significant environmental concern for decades. Despite this, the effects of petroleum pollutants on soil microbial communities and their potential for pollutant biodegradation still required further investigation. Methods: In this study, we collected 75 soil samples from 0 to 5 m depths of 15 soil profiles in an abandoned refinery to analyze the effect of petroleum pollution on soil microbial diversity, community structure, and network co-occurrence patterns. Results: Our results suggested soil microbial a-diversity decreased under high C10-C40 levels, coupled with significant changes in the community structure of soil profiles. However, soil microbial network complexity increased with petroleum pollution levels, suggesting more complex microbial potential interactions. A module specific for methane and methyl oxidation was also found under high C10-C40 levels of the soil profile, indicating stronger methanotrophic and methylotrophic metabolic activities at the heavily polluted soil profile. Discussion: The increased network complexity observed may be due to more metabolic pathways and processes, as well as increased microbial interactions during these processes. These findings highlight the importance of considering both microbial diversity and network complexity in assessing the effects of petroleum pollution on soil ecosystems.

Indexed as

co-occurrence networkmicrobial diversitypetroleum pollutionrefinerysoil

Identifiers

PMID37287448
PMCPMC10242060

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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.