Evidence map›Paper›PMID 37467453›Full record

ArticlePloS one2023

FAVIS: Fast and versatile protocol for non-destructive metabarcoding of bulk insect samples.

Elzbieta Iwaszkiewicz-Eggebrecht, Piotr Łukasik, Mateusz Buczek, Junchen Deng, Emily A Hartop, Harald Havnås, Monika Prus-Frankowska, Carina R Ugarph, Paulina Viteri, Anders F Andersson and 4 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Accuracy of occurrence and abundance estimates from insect metabarcoding.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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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

14 authors.

Elzbieta Iwaszkiewicz-EggebrechtDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Piotr ŁukasikInstitute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.
Mateusz BuczekInstitute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.
Junchen DengInstitute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.ORCID 0000-0003-3669-7172
Emily A HartopStation Linné, Färjestaden, Sweden.
Harald HavnåsStation Linné, Färjestaden, Sweden.
Monika Prus-FrankowskaInstitute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland.
Carina R UgarphStation Linné, Färjestaden, Sweden.
Paulina ViteriDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Anders F AnderssonScience for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
Tomas RoslinDepartment of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Ayco J M TackDepartment of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden.
Fredrik RonquistDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Andreia MiraldoDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insects are diverse and sustain essential ecosystem functions, yet remain understudied. Recent reports about declines in insect abundance and diversity have highlighted a pressing need for comprehensive large-scale monitoring. Metabarcoding (high-throughput bulk sequencing of marker gene amplicons) offers a cost-effective and relatively fast method for characterizing insect community samples. However, the methodology applied varies greatly among studies, thus complicating the design of large-scale and repeatable monitoring schemes. Here we describe a non-destructive metabarcoding protocol that is optimized for high-throughput processing of Malaise trap samples and other bulk insect samples. The protocol details the process from obtaining bulk samples up to submitting libraries for sequencing. It is divided into four sections: 1) Laboratory workspace preparation; 2) Sample processing-decanting ethanol, measuring the wet-weight biomass and the concentration of the preservative ethanol, performing non-destructive lysis and preserving the insect material for future work; 3) DNA extraction and purification; and 4) Library preparation and sequencing. The protocol relies on readily available reagents and materials. For steps that require expensive infrastructure, such as the DNA purification robots, we suggest alternative low-cost solutions. The use of this protocol yields a comprehensive assessment of the number of species present in a given sample, their relative read abundances and the overall insect biomass. To date, we have successfully applied the protocol to more than 7000 Malaise trap samples obtained from Sweden and Madagascar. We demonstrate the data yield from the protocol using a small subset of these samples.

Indexed as

BiodiversityEcosystemAnimalsDNADNA Barcoding, TaxonomicEthanolInsectaDNAEthanol

Identifiers

PMID37467453
PMCPMC10356154

What OpenQuestion holds

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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.