Evidence map›Paper›PMID 40705368›Full record

ArticleFEMS microbiology ecology2025

Counting soil microbial communities: the impact of qPCR platform and mastermix on accuracy and precision.

Aoife M Duff, Madeline Giles, Syaliny Ganasamurthy, Antonia Santos, Sergio E Morales, Fiona Brennan

Abstract read
In one paragraph

Article in FEMS microbiology ecology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Aoife M DuffDepartment of Environment, Soils and Land-Use, Teagasc, Johnstown Castle, Wexford Y35 TC97, Ireland.ORCID 0000-0003-0433-7623
Madeline GilesJames Hutton Institute, Dundee DD2 5DA, Scotland.
Syaliny GanasamurthyDepartment of Microbiology and Immunology, University of Otago, PO Box 56, Dunedin 9054, New Zealand.
Antonia SantosTeagasc, Food Research Centre, Ashtown, Dublin D15 KN3K, Ireland.
Sergio E MoralesDepartment of Microbiology and Immunology, University of Otago, PO Box 56, Dunedin 9054, New Zealand.ORCID 0000-0002-5862-0726
Fiona BrennanDepartment of Environment, Soils and Land-Use, Teagasc, Johnstown Castle, Wexford Y35 TC97, Ireland.

Funding

European Union 696356
6 · The paper itself

Abstract

Quantitative polymerase chain reaction (qPCR) is widely used in soil microbial ecology to quantify microbial communities, but its accuracy can be compromised by coextracted inhibitors. Furthermore, large-scale international studies involving multiple laboratories or meta-analyses studies can introduce variation in qPCR results when data generated from different sources are compared. This study evaluated the performance of four commercial mastermixes across different soil types, a mock community, and a positive template control against three targets on three widely used platforms. Sensitivity to inhibitors was tested, with one mastermix affected, although this was mitigated by adding 1 mg/ml bovine serum albumin. Amplification success varied by mastermix, platform, gene, and sample matrix. Most mastermix-platform combinations showed low accuracy emphasizing the need for careful pairing. Precision was primarily influenced by gene target, followed by platform, sample matrix, and mastermix, and was reduced at lower template concentrations. Only 64.67% of intraassay (within an assay) measurements meet accepted thresholds. Interassay (between platforms) quantification was unreliable due to significant variability, which increased the risk of inaccurate data interpretation. The study highlights the necessity of considering inter- and intraassay variation, assay accuracy, and inhibitors that may impact sample amplification when utilizing qPCR for quantification of microbial communities in environmental samples.

Indexed as

BacteriaMicrobiotaReal-Time Polymerase Chain ReactionSoil Microbiologyenvironmentoptimizationquantitative PCRtaq polymerasevalidation

Identifiers

PMID40705368
PMCPMC13223730

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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.