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Using AI and CRISPR to detect ToBRFV

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, researchers 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.

Karimi, M., Ghorbani, A., Niazi, A. et al. Integrating AI and CRISPR Cas13a for rapid detection of tomato brown rugose fruit virus. Sci Rep 15, 25422 (2025). https://doi.org/10.1038/s41598-025-11405-z

Source: Nature Magazine