Evidence map›Paper›PMID 36406450›Full record

ArticleFrontiers in microbiology2022

Application of ecosystem-specific reference databases for increased taxonomic resolution in soil microbial profiling.

Christina Karmisholt Overgaard, Ke Tao, Sha Zhang, Bent Tolstrup Christensen, Zuzana Blahovska, Simona Radutoiu, Simon Kelly, Morten Kam Dahl Dueholm

Abstract read
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Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

8 authors.

Christina Karmisholt OvergaardDepartment of Chemistry and Bioscience, Center for Microbial Communities, Aalborg University, Aalborg, Denmark.
Ke TaoDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Sha ZhangDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Bent Tolstrup ChristensenDepartment of Agroecology, Aarhus University, AU-Foulum, Tjele, Denmark.
Zuzana BlahovskaDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Simona RadutoiuDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Simon KellyDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Morten Kam Dahl DueholmDepartment of Chemistry and Bioscience, Center for Microbial Communities, Aalborg University, Aalborg, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intensive agriculture systems have paved the way for a growing human population. However, the abundant use of mineral fertilizers and pesticides may negatively impact nutrient cycles and biodiversity. One potential alternative is to harness beneficial relationships between plants and plant-associated rhizobacteria to increase nutrient-use efficiency and provide pathogen resistance. Plant-associated microbiota profiling can be achieved using high-throughput 16S rRNA gene amplicon sequencing. However, interrogation of these data is limited by confident taxonomic classifications at high taxonomic resolution (genus- or species level) with the commonly applied universal reference databases. High-throughput full-length 16S rRNA gene sequencing combined with automated taxonomy assignment (AutoTax) can be used to create amplicon sequence variant resolved ecosystems-specific reference databases that are superior to the traditional universal reference databases. This approach was used here to create a custom reference database for bacteria and archaea based on 987,353 full-length 16S rRNA genes from Askov and Cologne soils. We evaluated the performance of the database using short-read amplicon data and found that it resulted in the increased genus- and species-level classification compared to commonly use universal reference databases. The custom database was utilized to evaluate the ecosystem-specific primer bias and taxonomic resolution of amplicon primers targeting the V5-V7 region of the 16S rRNA gene commonly used within the plant microbiome field. Finally, we demonstrate the benefits of custom ecosystem-specific databases through the analysis of V5-V7 amplicon data to identify new plant-associated microbes for two legumes and two cereal species.

Indexed as

16S rRNA (16S rDNA)host preferencemicrobiotarhizospheresoil

Identifiers

PMID36406450
PMCPMC9669317

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.