Optimization of CRISPR/Cas12a detection assay and its application in the detection of Echinococcus granulosus.

CRISPR/Cas12a Detection Echinococcus granulosus POCT Suboptimal PAM Suboptimal structure

Journal

Veterinary parasitology
ISSN: 1873-2550
Titre abrégé: Vet Parasitol
Pays: Netherlands
ID NLM: 7602745

Informations de publication

Date de publication:
30 Jul 2024
Historique:
received: 03 02 2024
revised: 25 07 2024
accepted: 28 07 2024
medline: 2 8 2024
pubmed: 2 8 2024
entrez: 1 8 2024
Statut: aheadofprint

Résumé

Cystic echinococcosis, resulting from infection with Echinococcus granulosus, poses a significant challenge as a neglected tropical disease owing to the lack of any known effective treatment. Primarily affecting under-resourced, remote, and conflict-ridden regions, the disease is compounded by the limitations of current detection techniques, such as microscopy, physical imaging, ELISA, and qPCR, which are unsuitable for application in these areas. The emergence of CRISPR/Cas12a as a promising tool for nucleic acid detection, characterized by its unparalleled specificity, heightened sensitivity, and rapid detection time, offers a potential solution. In this study, we present a one-pot CRISPR/Cas12a detection method for E. granulosus (genotype G1, sheep strain) integrating recombinase polymerase amplification (RPA) with suboptimal protospacer adjacent motif (PAM) and structured CRISPR RNA (crRNA) to enhance reaction efficiency. The evaluation of the assay's performance using hydatid cyst spiked dog feces and the examination of 62 dog fecal samples collected from various regions of Western China demonstrate its efficacy. The assay permits visual observation of test results about 15 minutes under blue light and displays superior portability and reaction speed relative to qPCR, achieving a sensitivity level of 10 copies of standard plasmids of the target gene. Analytic specificity was verified against four tapeworm species (E. multilocularis, H. taeniaeformis, M. benedeni, and D. caninum) and two other helminths (T. canis and F. hepatica), with negative results also noted for Mesocestoides sp. This study presents a rapid, sensitive, and time-efficient DNA detection method for E. granulosus of hydatid cyst spiked and clinical dog feces, potential serving as an alternative tool for field detection. This novel assay is primarily used to diagnose the definitive host of E. granulosus. Further validation using a larger set of clinical fecal samples is warranted, along with additional exploration of more effective approaches for nucleic acid release.

Identifiants

pubmed: 39089176
pii: S0304-4017(24)00165-1
doi: 10.1016/j.vetpar.2024.110276
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

110276

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Fuqiang Huang (F)

School of Life Science and Engineering, Foshan University, Foshan, China. Electronic address: qxhuangfuqiang@fosu.edu.cn.

Xin Li (X)

School of Life Science and Engineering, Foshan University, Foshan, China; College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China.

Yule Zhou (Y)

School of Life Science and Engineering, Foshan University, Foshan, China.

Wenqiang Tang (W)

State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, China; Tibet Academy of Agriculture and Animal Husbandry Sciences, Lhasa, China.

Zhisheng Dang (Z)

National Institute of Parasitic Diseases at China CDC/Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, NHC Key Laboratory for Parasite and Vector Biology, Shanghai, China.

Jun Kui (J)

Huangzhong District Animal Husbandry and Veterinary Station, Xining, China.

Chunxia Zhang (C)

Qinghai Agri-animal Husbandry Vocational College, Huangyuan, China.

Xu Zhang (X)

School of Life Science and Engineering, Foshan University, Foshan, China.

Classifications MeSH