Evidence map›Paper›PMID 33939728›Full record

ArticlePloS one2021

Investigating variability in microbial community composition in replicate environmental DNA samples down lake sediment cores.

John K Pearman, Georgia Thomson-Laing, Jamie D Howarth, Marcus J Vandergoes, Lucy Thompson, Andrew Rees, Susanna A Wood

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

7 authors.

John K PearmanCoastal and Freshwater Group, Cawthron Institute, Nelson, New Zealand.ORCID 0000-0002-2237-9723
Georgia Thomson-LaingCoastal and Freshwater Group, Cawthron Institute, Nelson, New Zealand.
Jamie D HowarthVictoria University of Wellington, Wellington, New Zealand.
Marcus J VandergoesGNS Science, Lower Hutt, New Zealand.
Lucy ThompsonCoastal and Freshwater Group, Cawthron Institute, Nelson, New Zealand.
Andrew ReesVictoria University of Wellington, Wellington, New Zealand.
Susanna A WoodCoastal and Freshwater Group, Cawthron Institute, Nelson, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lake sediments are natural archives that accumulate information on biological communities and their surrounding catchments. Paleolimnology has traditionally focussed on identifying fossilized organisms to reconstruct past environments. In the last decade, the application of molecular methodologies has increased in paleolimnological studies, but further research investigating factors such as sample heterogeneity and DNA degradation are required. In the present study we investigated bacterial community heterogeneity (16S rRNA metabarcoding) within depth slices (1-cm width). Sediment cores were collected from three lakes with differing sediment compositions. Samples were collected from a variety of depths which represent a period of time of approximately 1,200 years. Triplicate samples were collected from each depth slice and bacterial 16S rRNA metabarcoding was undertaken on each sample. Accumulation curves demonstrated that except for the deepest (oldest) slices, the combination of three replicate samples were insufficient to characterise the entire bacterial diversity. However, shared Amplicon Sequence Variants (ASVs) accounted for the majority of the reads in each depth slice (max. shared proportional read abundance 96%, 86%, 65% in the three lakes). Replicates within a depth slice generally clustered together in the Non-metric multidimensional scaling analysis. There was high community dissimilarity in older sediment in one of the cores, which was likely due to the laminae in the sediment core not being horizontal. Given that most paleolimnology studies explore broad scale shifts in community structure rather than seeking to identify rare species, this study demonstrates that a single sample is adequate to characterise shifts in dominant bacterial ASVs.

Indexed as

BacteriaGeologic SedimentsLakesRNA, Ribosomal, 16SBiodiversityDNA, BacterialDNA Barcoding, TaxonomicDNA, EnvironmentalMicrobiotaDNA, BacterialDNA, EnvironmentalRNA, Ribosomal, 16S

Identifiers

PMID33939728
PMCPMC8092796

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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.