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bioRxiv · 10.1101/2024.12.10.627849

CRISPR-based environmental biosurveillance assisted via artificial intelligence design of guide-RNAs

Duran-Vinet, B.·Stanton, J.-A. L.·Jeunen, G.-J.·von Ammon, U.·Treece, J.·Pochon, X.·Zaiko, A.·Gemmell, N.
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Abstract

Environmental biosecurity challenges are worsening for aquatic ecosystems as climate change and increased anthropogenic pressures facilitate the spread of invasive species, thereby broadly impacting ecosystem composition, functioning, and services. Environmental DNA (eDNA) has transformed traditional biomonitoring through detection of trace DNA fragments left by organisms in their surroundings, primarily by application of the quantitative polymerase chain reaction (qPCR). 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 alternatives. We report here the development of CORSAIR (CRISPR-based envirOnmental biosuRveillance aSsisted via Artificial Intelligence guide-RNAs), that harnesses the programmability of the CRISPR-Cas technology, RPA and the artificial intelligence (AI)-based tool Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT) to deploy a swift RPA-CRISPR-Cas13a-based method that detects eDNA from two invasive species as proof of concept: Sabella spallanzanii and Undaria pinnatifida. CORSAIR showcased a robust, streamlined method augmented by ADAPT, reaching a high specificity when tested against co-occurring species and a 100% agreement with 12 PCR-benchmarked eDNA samples, reaching a sensitivity of 0.34 copies uL-1 in 1 hour with a cost of 3.5 USD per sample; thus highlighting CORSAIR as a powerful environmental biosurveillance platform for environmental nucleic acid detection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/627849v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@b60942org.highwire.dtl.DTLVardef@119e924org.highwire.dtl.DTLVardef@1956bforg.highwire.dtl.DTLVardef@18e18b9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

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Duran-Vinet, B., Stanton, J.-A. L., Jeunen, G.-J., von Ammon, U., Treece, J., Pochon, X., Zaiko, A., Gemmell, N.. 2024-12-11. CRISPR-based environmental biosurveillance assisted via artificial intelligence design of guide-RNAs. https://doi.org/10.1101/2024.12.10.627849

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