Integrating AI and CRISPR Cas13a for rapid detection of tomato brown rugose fruit virus

The Tomato Brown Rugose Fruit Virus (ToBRFV) has recently emerged as a serious threat to global tomato production, underscoring the need for rapid and sensitive diagnostic tools. Here, we present an AI-driven CRISPR-Cas13a pipeline for designing crRNAs with high specificity to enable the detection o...

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Vydané v:	Scientific reports Ročník 15; číslo 1; s. 25422 - 15
Hlavní autori:	Karimi, Marzieh, Ghorbani, Abozar, Niazi, Ali, Rostami, Mahsa, Tahmasebi, Ahmad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 14.07.2025 Nature Publishing Group Nature Portfolio
Predmet:	631/208 631/326 631/337 631/61 Automation Bioinformatics Cas13 Computational Biology - methods Conserved sequence CRISPR CRISPR-Cas Systems CrRNA Design Enzymes Fruits Genomes Humanities and Social Sciences Machine learning multidisciplinary Pathogens Plant Diseases - virology Plant viruses Plant Viruses - genetics Plant Viruses - isolation & purification Rapid detection RNA, Viral - genetics Science Science (multidisciplinary) Sensitive diagnostic Solanum lycopersicum - virology ToBRFV Tomatoes Viral infections Viruses ToBRFV Cas13 CrRNA Sensitive diagnostic Rapid detection
ISSN:	2045-2322, 2045-2322
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Shrnutí:	The Tomato Brown Rugose Fruit Virus (ToBRFV) has recently emerged as a serious threat to global tomato production, underscoring the need for rapid and sensitive diagnostic tools. Here, we present an AI-driven CRISPR-Cas13a pipeline for designing crRNAs with high specificity to enable the detection of ToBRFV. A computational pipeline that retrieves viral sequences, aligns them in multiple sequence alignments, analyzes their conservation, and screens for off-targets—all coupled with machine learning to optimize crRNA sequences. Experimentally validated crRNAs were evaluated with a fluorescence-based Cas13a assay and showed better sensitivity than RT-PCR, RT-qPCR, and RT-LAMP. By the CRISPR-Cas13a system, ToBRFV was detected at 1:200 (1 ng/µL) dilutions, which performed superior to conventional methods. Integrating bioinformatics with experimental workflows, this pipeline provides a powerful framework for rapid diagnostics that can be deployed in the field, addressing significant challenges in plant virus surveillance and management.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	2045-2322 2045-2322
DOI:	10.1038/s41598-025-11405-z