CRISPR‐Enhanced Hydrogel Microparticles for Multiplexed Detection of Nucleic Acids. Issue 10 (1st February 2023)

• Record Type: Journal Article
• Authors: Roh, Yoon Ho; Lee, Chang Yeol; Lee, Sujin; Kim, Hyunho; Ly, Amy; Castro, Cesar M.; Cheon, Jinwoo; Lee, Jae‐Hyun; Lee, Hakho
• Is Part Of: Advanced science. Volume 10:Issue 10(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-01
• Subjects: CRISPR/Cas -- human papillomavirus -- hydrogel microparticles -- isothermal amplification -- multiplexed assays; Science -- Periodicals; 505
• DOI: 10.1002/advs.202206872
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: CRISPR/Cas systems offer a powerful sensing mechanism to transduce sequence‐specific information into amplified analytical signals. However, performing multiplexed CRISPR/Cas assays remains challenging and often requires complex approaches for multiplexed assays. Here, a hydrogel‐based CRISPR/Cas12 system termed CLAMP ( C as‐ L oaded A nnotated M icro‐Particles) is described. The approach compartmentalizes the CRISPR/Cas reaction in spatially‐encoded hydrogel microparticles (HMPs). Each HMP is identifiable by its face code and becomes fluorescent when target DNA is present. The assay is further streamlined by capturing HMPs inside a microfluidic device; the captured particles are then automatically recognized by a machine‐learning algorithm. The CLAMP assay is fast, highly sensitive (attomolar detection limits with preamplification), and capable of multiplexing in a single‐pot assay. As a proof‐of‐concept clinical application, CLAMP is applied to detect nucleic acid targets of human papillomavirus in cervical brushing samples. Abstract : A new strategy is demonstrated for multiplexed CRISPR/Cas assays. In this approach, each Cas reaction takes place inside a spatially‐encoded hydrogel microparticle (HMP). A machine‐learning (ML) algorithm then identifies coded HMPs and quantifies their intended molecular targets. The method is scalable to detect many targets in a single‐pot format, facilitating high‐throughput diagnoses.