CRISPR-Based Environmental Biosurveillance Assisted via Artificial Intelligence Design of Guide-RNAs

Abstract

Environmental biosecurity challenges are intensifying as climate change and human activities accelerate the spread of invasive species, disrupting ecosystem composition, function, and essential services. Environmental DNA (eDNA) has transformed traditional biosurveillance by detecting trace DNA fragments left by organisms in their surroundings, primarily by applying quantitative polymerase chain reaction (qPCR) methods. However, qPCR presents challenges, including limited portability, reliance on precise thermal cycling, and susceptibility to inhibitors. To address these challenges and enable field-deployable monitoring, isothermal amplification techniques such as recombinase polymerase amplification (RPA) paired with clustered regularly interspaced short palindromic repeats and associated proteins (CRISPR-Cas) have been proposed as promising alternatives. CRISPR-Cas technology also presents challenges, including searching and optimizing a guide RNA (gRNA) that is highly sensitive and has no off-target interactions for use as an effective environmental biosurveillance tool. We present here the development of SENTINEL (Smart Environmental Nucleic-acid Tracking using Inference from Neural-networks for Early-warning Localization) that harnesses the programmability, specificity and sensitivity of a one-pot RPA-CRISPR-Cas13a reaction by integrating an accessible and pre-trained neural network to accelerate assay design for rapid deployment. We challenged SENTINEL with waterborne eDNA from two marine sites invaded by species not native to New Zealand as proof-of-concept fluorescence-based tests: Sabella spallanzanii (Mediterranean fanworm) and Undaria pinnatifida (Wakame). Off-target effects were explored by challenging the SENTINEL assays on gDNA from a suite of co-occurring species. SENTINEL presented a robust, streamlined method incorporating the trained neural network, achieving a sensitivity down to 10 attomolar using recombinant DNA and down to ~0.34 copies/μL for eDNA samples with 1 h, costing 3.5 USD per sample. There was a 100% agreement between SENTINEL results and qPCR-based analysis of the eDNA samples. SENTINEL displayed no off-target activity when challenged against 23 gDNA samples from co-occurring species. Thus, our study showcases SENTINEL's potential as a robust platform for eDNA screening applications.