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CRISPR-based diagnostics detects invasive insect pests.
Shashank, Pathour R; Parker, Brandon M; Rananaware, Santosh R; Plotkin, David; Couch, Christian; Yang, Lilia G; Nguyen, Long T; Prasannakumar, N R; Braswell, W Evan; Jain, Piyush K; Kawahara, Akito Y.
Afiliação
  • Shashank PR; McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
  • Parker BM; Division of Entomology, ICAR-Indian Agricultural Research Institution, New Delhi, India.
  • Rananaware SR; McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
  • Plotkin D; Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA.
  • Couch C; Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA.
  • Yang LG; Department of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
  • Nguyen LT; McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
  • Prasannakumar NR; McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA.
  • Braswell WE; Department of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
  • Jain PK; Department of Chemical Engineering, University of Florida, Gainesville, Florida, USA.
  • Kawahara AY; Division of Crop Protection, ICAR-Indian Institute of Horticultural Research, Bengaluru, India.
Mol Ecol Resour ; 24(1): e13881, 2024 Jan.
Article em En | MEDLINE | ID: mdl-37888995
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Lepidópteros Limite: Animals Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Lepidópteros Limite: Animals Idioma: En Ano de publicação: 2024 Tipo de documento: Article