Evidence map›Paper›PMID 26010362›Full record

ArticlePloS one2015

New perspectives on microbial community distortion after whole-genome amplification.

Alexander J Probst, Thomas Weinmaier, Todd Z DeSantis, Jorge W Santo Domingo, Nicholas Ashbolt

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 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

5 authors.

Alexander J ProbstDepartment for Bioinformatics, Second Genome Inc., South San Francisco, California, United States of America.
Thomas WeinmaierDepartment for Bioinformatics, Second Genome Inc., South San Francisco, California, United States of America.
Todd Z DeSantisDepartment for Bioinformatics, Second Genome Inc., South San Francisco, California, United States of America.
Jorge W Santo DomingoU.S. Environmental Protection Agency, Cincinnati, Ohio, United States of America.
Nicholas AshboltU.S. Environmental Protection Agency, Cincinnati, Ohio, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-genome amplification (WGA) has become an important tool to explore the genomic information of microorganisms in an environmental sample with limited biomass, however potential selective biases during the amplification processes are poorly understood. Here, we describe the effects of WGA on 31 different microbial communities from five biotopes that also included low-biomass samples from drinking water and groundwater. Our findings provide evidence that microbiome segregation by biotope was possible despite WGA treatment. Nevertheless, samples from different biotopes revealed different levels of distortion, with genomic GC content significantly correlated with WGA perturbation. Certain phylogenetic clades revealed a homogenous trend across various sample types, for instance Alpha- and Betaproteobacteria showed a decrease in their abundance after WGA treatment. On the other hand, Enterobacteriaceae, an important biomarker group for fecal contamination in groundwater and drinking water, were strongly affected by WGA treatment without a predictable pattern. These novel results describe the impact of WGA on low-biomass samples and may highlight issues to be aware of when designing future metagenomic studies that necessitate preceding WGA treatment.

Indexed as

Genome, BacterialBacteriaBase CompositionBiofilmsEcosystemGenome SizeMicrobiotaNitrogenNucleic Acid Amplification TechniquesSewageNitrogenSewage

Identifiers

PMID26010362
PMCPMC4444113

What OpenQuestion holds

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Registered trials

None linked

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.