Evidence map›Paper›PMID 36156998›Full record

ArticleEnvironmental science and ecotechnology2021

Standardized high-throughput biomonitoring using DNA metabarcoding: Strategies for the adoption of automated liquid handlers.

Dominik Buchner, Till-Hendrik Macher, Arne J Beermann, Marie-Thérése Werner, Florian Leese

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In one paragraph

Article in Environmental science and ecotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 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.

Dominik BuchnerUniversity of Duisburg-Essen, Aquatic Ecosystem Research, Universitätsstr. 5, 45141, Essen, Germany.
Till-Hendrik MacherUniversity of Duisburg-Essen, Aquatic Ecosystem Research, Universitätsstr. 5, 45141, Essen, Germany.
Arne J BeermannUniversity of Duisburg-Essen, Aquatic Ecosystem Research, Universitätsstr. 5, 45141, Essen, Germany.
Marie-Thérése WernerUniversity of Duisburg-Essen, Aquatic Ecosystem Research, Universitätsstr. 5, 45141, Essen, Germany.
Florian LeeseUniversity of Duisburg-Essen, Aquatic Ecosystem Research, Universitätsstr. 5, 45141, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable and comprehensive monitoring data are required to trace and counteract biodiversity loss. High-throughput metabarcoding using DNA extracted from community samples (bulk) or from water or sediment (environmental DNA) has revolutionized biomonitoring, given the capability to assess biodiversity across the tree of life rapidly with feasible effort and at a modest price. DNA metabarcoding can be upscaled to process hundreds of samples in parallel. However, while automated high-throughput analysis workflows are well-established in the medical sector, manual sample processing still predominates in biomonitoring laboratory workflows limiting the upscaling and standardization for routine monitoring applications. Here we present an automated, scalable, and reproducible metabarcoding workflow to extract DNA from bulk samples, perform PCR and library preparation on a liquid handler. Key features are the independent sample replication throughout the workflow and the use of many negative controls for quality assurance and quality control. We generated two datasets: i) a validation dataset consisting of 42 individual arthropod specimens of different species, and ii) a routine monitoring dataset consisting of 60 stream macroinvertebrate bulk samples. As a marker, we used the mitochondrial COI gene. Our results show that the developed single-deck workflow is free of laboratory-derived contamination and produces highly consistent results. Minor deviations between replicates are mostly due to stochastic differences for low abundant OTUs. Thus, we successfully demonstrated that robotic liquid handling can be used reliably from DNA extraction to final library preparation on a single deck, thereby substantially increasing throughput, reducing costs, and increasing data robustness for biodiversity assessments and monitoring.

Indexed as

AutomatizationHigh-throughput sequencingPipetting robotStandardization

Identifiers

PMID36156998
PMCPMC9488008

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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.