Evidence map›Paper›PMID 36061686›Full record

ArticleACS omega2022

Keystone Microorganisms Regulate the Methanogenic Potential in Coals with Different Coal Ranks.

Bingjun Liu, Jian Chen, Yang Li

Abstract read
In one paragraph

Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

  1. 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

3 authors.

Bingjun LiuInstitute of Energy, Hefei Comprehensive National Science Center, Anhui, Hefei 230031, China.ORCID https://orcid.org/0000-0003-4437-0102
Jian ChenCoal Mining National Engineering and Technology Research Institute, Huainan, Anhui Province 232033, China.
Yang LiState Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science & Technology, Huainan, Anhui Province 232001, China.ORCID https://orcid.org/0000-0002-8946-3962

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms are the core drivers of coal biogeochemistry and are closely related to the formation of coalbed methane. However, it remains poorly understood about the network relationship and stability of microbial communities in coals with different ranks. In this study, a high-throughput sequencing data set was analyzed to understand the microbial co-occurrence network in coals with different ranks including anthracite, medium-volatile bituminous, and high-volatile bituminous. The results showed similar topological properties for the microbial networks among coals with different ranks, but a great difference was found in the microbial composition in different large modules among coals with different ranks, and these three networks had three, four, and four large modules with seven, nine, and nine phyla, respectively. Among these networks, a total of 46 keystone taxa were identified in large modules, and these keystone taxa were different in coals with different ranks. Bacteria dominated the keystone taxa in the microbial network, and these bacterial keystone taxa mainly belonged to phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Besides, the removal of the key microbial data could reduce the community stability of microbial communities in bituminous coals. A partial least-squares path model further showed that these bacterial keystone taxa indirectly affected methanogenic potential by maintaining the microbial community stability and bacterial diversity. In summary, these results showed that keystone taxa played an important role in determining the community diversity, maintaining the microbial community stability, and controlling the methanogenic potential, which is of great significance for understanding the microbial ecology and the geochemical cycle of coal seams.

Identifiers

PMID36061686
PMCPMC9435036

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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.