Evidence map›Paper›PMID 37888995›Full record

ArticleMolecular ecology resources2024

CRISPR-based diagnostics detects invasive insect pests.

Pathour R Shashank, Brandon M Parker, Santosh R Rananaware, David Plotkin, Christian Couch, Lilia G Yang, Long T Nguyen, N R Prasannakumar, W Evan Braswell, Piyush K Jain and 1 more

Abstract read
In one paragraph

Article in Molecular ecology resources, 2024. 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. Species-SpecificInsects · 2026
    Article
  2. Article
  3. A Species-SpecificBiology · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Pathour R ShashankMcGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
Brandon M ParkerMcGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
Santosh R RananawareDepartment of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
David PlotkinMcGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
Christian CouchMcGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
Lilia G YangDepartment of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
Long T NguyenDepartment of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
N R PrasannakumarDivision of Crop Protection, ICAR-Indian Institute of Horticultural Research, Bengaluru, India.
W Evan BraswellInsect Management and Molecular Diagnostics Laboratory, USDA APHIS PPQ S&T, Edinburg, Texas, USA.
Piyush K JainDepartment of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
Akito Y KawaharaMcGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.ORCID https://orcid.org/0000-0002-3724-4610

Funding

Discovery and engineering of CRISPR/Cas systemsR35GM147788 · NIGMS · UNIVERSITY OF FLORIDA · PI Piyush K Jain · 2022 to 2026
$1.8M
NIGMS NIH HHS R35 GM147788NIH HHS NIH-NIGMS R35GM147788
6 · The paper itself

Abstract

Rapid identification of organisms is essential for many biological and medical disciplines, from understanding basic ecosystem processes, disease diagnosis, to the detection of invasive pests. CRISPR-based diagnostics offers a novel and rapid alternative to other identification methods and can revolutionize our ability to detect organisms with high accuracy. Here we describe a CRISPR-based diagnostic developed with the universal cytochrome-oxidase 1 gene (CO1). The CO1 gene is the most sequenced gene among Animalia, and therefore our approach can be adopted to detect nearly any animal. We tested the approach on three difficult-to-identify moth species (Keiferia lycopersicella, Phthorimaea absoluta and Scrobipalpa atriplicella) that are major invasive pests globally. We designed an assay that combines recombinase polymerase amplification (RPA) with CRISPR for signal generation. Our approach has a much higher sensitivity than real-time PCR assays and achieved 100% accuracy for identification of all three species, with a detection limit of up to 120 fM for P. absoluta and 400 fM for the other two species. Our approach does not require a sophisticated laboratory, reduces the risk of cross-contamination, and can be completed in less than 1 h. This work serves as a proof of concept that has the potential to revolutionize animal detection and monitoring.

Indexed as

EcosystemLepidopteraAnimalsBiological AssayElectron Transport Complex IVInsectaElectron Transport Complex IVCas12aCRISPRdiagnosticsgenetic identificationKeiferia lycopersicellaleaf minerPhthorimaea absolutaRPAScrobipalpa atriplicellaTuta absoluta

Identifiers

PMID37888995
PMCPMC10842307

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.