Evidence map›Paper›PMID 33452291›Full record

ArticleScientific reports2021

Assessing the efficacy of eDNA metabarcoding for measuring microbial biodiversity within forest ecosystems.

Zachary S Ladin, Barbra Ferrell, Jacob T Dums, Ryan M Moore, Delphis F Levia, W Gregory Shriver, Vincent D'Amico, Tara L E Trammell, João Carlos Setubal, K Eric Wommack

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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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

10 authors.

Zachary S LadinDepartment of Plant and Soil Sciences, University of Delaware, 264 Townsend Hall, Newark, DE, 19716, USA. zach@udel.edu.
Barbra FerrellDepartment of Plant and Soil Sciences, Delaware Biotechnology Institute, University of Delaware, Newark, DE, 19716, USA.
Jacob T DumsBiotechnology Program, North Carolina State University, Raleigh, NC, 27695, USA.
Ryan M MooreDepartment of Plant and Soil Sciences, Delaware Biotechnology Institute, University of Delaware, Newark, DE, 19716, USA.
Delphis F LeviaDepartment of Entomology and Wildlife Ecology, University of Delaware, 250 Townsend Hall, Newark, DE, 19716, USA.
W Gregory ShriverDepartments of Geography and Spatial Sciences and Plant and Soil Sciences, University of Delaware, 216C Pearson Hall, Newark, DE, 19716, USA.
Vincent D'AmicoUS Forest Service, Northern Research Station, Newark, DE, USA.
Tara L E TrammellDepartment of Plant and Soil Sciences, University of Delaware, 264 Townsend Hall, Newark, DE, 19716, USA.
João Carlos SetubalInstituto de Química, University of Sao Paulo, São Paulo, SP, 05508-000, Brazil.
K Eric WommackDepartment of Plant and Soil Sciences, University of Delaware, 264 Townsend Hall, Newark, DE, 19716, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated the nascent application and efficacy of sampling and sequencing environmental DNA (eDNA) in terrestrial environments using rainwater that filters through the forest canopy and understory vegetation (i.e., throughfall). We demonstrate the utility and potential of this method for measuring microbial communities and forest biodiversity. We collected pure rainwater (open sky) and throughfall, successfully extracted DNA, and generated over 5000 unique amplicon sequence variants. We found that several taxa including Mycoplasma sp., Spirosoma sp., Roseomonas sp., and Lactococcus sp. were present only in throughfall samples. Spiroplasma sp., Methylobacterium sp., Massilia sp., Pantoea sp., and Sphingomonas sp. were found in both types of samples, but more abundantly in throughfall than in rainwater. Throughfall samples contained Gammaproteobacteria that have been previously found to be plant-associated, and may contribute to important functional roles. We illustrate how this novel method can be used for measuring microbial biodiversity in forest ecosystems, foreshadowing the utility for quantifying both prokaryotic and eukaryotic lifeforms. Leveraging these methods will enhance our ability to detect extant species, describe new species, and improve our overall understanding of ecological community dynamics in forest ecosystems.

Indexed as

ForestsBiodiversityCluster AnalysisCytophagaceaeDNA Barcoding, TaxonomicDNA, EnvironmentalFresh WaterLactococcusMycoplasmaRNA, Ribosomal, 16SDNA, EnvironmentalRNA, Ribosomal, 16S

Identifiers

PMID33452291
PMCPMC7811025

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.