Evidence map›Paper›PMID 24691166›Full record

ArticlePloS one2014

Bioinformatic approaches reveal metagenomic characterization of soil microbial community.

Zhuofei Xu, Martin Asser Hansen, Lars H Hansen, Samuel Jacquiod, Søren J Sørensen

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Zhuofei XuSection of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Martin Asser HansenSection of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Lars H HansenSection of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Samuel JacquiodSection of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Søren J SørensenSection of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.

Indexed as

BiodiversitySoil MicrobiologyBiomarkersComputational BiologyEcosystemMetabolomicsMetagenomeMetagenomicsMicrobial InteractionsPhylogenyBiomarkers

Identifiers

PMID24691166
PMCPMC3972102

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.