Evidence map›Paper›PMID 35877652›Full record

ArticlePloS one2022

Next generation biosecurity: Towards genome based identification to prevent spread of agronomic pests and pathogens using nanopore sequencing.

Jürg E Frey, Beatrice Frey, Daniel Frei, Simon Blaser, Morgan Gueuning, Andreas Bühlmann

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. 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
2.5field-weighted citation impact, top 11% of its field
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, 12 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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

6 authors at 2 institutions in 1 country.

Jürg E FreyResearch Group Molecular Diagnostics Genomics and Bioinformatics, Department of Method Development and Analytics, Agroscope, Wädenswil, Switzerland.
Beatrice FreyResearch Group Molecular Diagnostics Genomics and Bioinformatics, Department of Method Development and Analytics, Agroscope, Wädenswil, Switzerland.
Daniel FreiResearch Group Molecular Diagnostics Genomics and Bioinformatics, Department of Method Development and Analytics, Agroscope, Wädenswil, Switzerland.
Simon BlaserDepartment of Plants and Plant Products, Agroscope Phytosanitary Service, Agroscope, Wädenswil, Switzerland.
Morgan GueuningResearch Group Molecular Diagnostics Genomics and Bioinformatics, Department of Method Development and Analytics, Agroscope, Wädenswil, Switzerland.
Andreas BühlmannStrategic Research Division Food Microbial Systems, Research Group Product Quality and -Innovation, Agroscope, Wädenswil, Switzerland.ORCID 0000-0002-8255-3228
Agroscope · CHSwiss Federal Institute for Forest, Snow and Landscape Research · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The unintentional movement of agronomic pests and pathogens is steadily increasing due to the intensification of global trade. Being able to identify accurately and rapidly early stages of an invasion is critical for developing successful eradication or management strategies. For most invasive organisms, molecular diagnostics is today the method of choice for species identification. However, the currently implemented tools are often developed for certain taxa and need to be adapted for new species, making them ill-suited to cope with the current constant increase in new invasive species. To alleviate this impediment, we developed a fast and accurate sequencing tool allowing to modularly obtain genetic information at different taxonomical levels. Using whole genome amplification (WGA) followed by Oxford nanopore MinION sequencing, our workflow does not require any a priori knowledge on the investigated species and its classification. While mainly focusing on harmful plant pathogenic insects, we also demonstrate the suitability of our workflow for the molecular identification of bacteria (Erwinia amylovora and Escherichia coli), fungi (Cladosporium herbarum, Colletotrichum salicis, Neofabraea alba) and nematodes (Globodera rostochiensis). On average, the pairwise identity between the generated consensus sequences and best GenBank BLAST matches was 99.6 ± 0.6%. Additionally, assessing the generated insect genomic dataset, the potential power of the workflow to detect pesticide resistance genes, as well as arthropod-infecting viruses and endosymbiotic bacteria is demonstrated.

Indexed as

AscomycotaNanoporesNanopore SequencingBacteriaBiosecurityHigh-Throughput Nucleotide SequencingSequence Analysis, DNAWhole Genome Sequencing

Identifiers

PMID35877652
PMCPMC9312391
OpenAlexW4287578669

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.