Evidence map›Paper›PMID 39346007›Full record

ArticleISME communications2024

Quantifying microbial DNA in metagenomes improves microbial trait estimation.

Raphael Eisenhofer, Antton Alberdi, Ben J Woodcroft

Abstract read
In one paragraph

Article in ISME communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

3 authors.

Raphael EisenhoferCentre for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Antton AlberdiCentre for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Ben J WoodcroftCentre for Microbiome Research, School of Biomedical Sciences, Translational Research Institute, Brisbane, Queensland University of Technology (QUT), Woolloongabba, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shotgun metagenomics is a powerful tool for studying the genomic traits of microbial community members, such as genome size, gene content, etc. While such traits can be used to better understand the ecology and evolution of microbial communities, the accuracy of their estimations can be critically influenced by both known and unknown factors. One factor that can bias trait estimations is the proportion of eukaryotic and viral DNA in a metagenome, as some bioinformatic tools assume that all DNA reads in a metagenome are bacterial or archaeal. Here, we add to a recent debate about the influence of eukaryotic DNA in the estimation of average genome size from a global soil sample dataset using a new bioinformatic tool. Contrary to what was assumed, our reanalysis of this dataset revealed that soil samples can contain a substantial proportion of non-microbial DNA, which severely inflated the original estimates of average genome size. Correcting for this bias significantly improves the statistical support for the negative relationship between average bacterial genome size and soil pH. These results highlight that metagenomes can contain large quantities of non-microbial DNA and that new methods that correct for this can improve microbial trait estimation.

Indexed as

bioinformaticsmetagenomicsmicrobial ecologymicrobiologymicrobiomesoil

Identifiers

PMID39346007
PMCPMC11439404

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.