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MARPLE demonstrates improved antibody detection in complex biological samples, suggesting advancements in immunodiagnostic approaches.
Monitoring and quantifying clinically relevant antibodies—as biomarkers of disease states or responses to therapeutic and prophylactic regimens—is essential for informed and effective clinical decision-making. While established immunoassays such as ELISA offer reliable antibody quantification, they often rely on multistep workflows and are limited in point-of-care applications. Innovative approaches coupling antibody recognition with signal amplification mechanisms are therefore highly desirable. The CRISPR-Cas13 system, known for its powerful collateral cleavage activity, has emerged as a leading diagnostic tool for ultrasensitive detection of nucleic acid targets. However, extending its diagnostic capabilities to protein biomarkers, such as antibodies, remains largely unexplored. Here, we present MARPLE (Modular Antibody Recognition via Proximity-triggered Linker Exchange), a modular CRISPR-Cas13–based diagnostic platform for ultrasensitive antibody detection. MARPLE exploits antibody-induced proximity effects to trigger a strand displacement reaction that releases a sequestered RNA target, which in turn activates Cas13-mediated collateral cleavage of fluorescent RNA hairpin reporters. This programmable mechanism initiates a signal amplification cascade, enabling detection of antibodies at femtomolar concentrations. We demonstrate MARPLE’s versatility and adaptability across a range of antibody targets—including anti-digoxigenin, anti-cholesterol, anti-HA, trastuzumab, and anti-MUC1— highlighting its applicability in infectious disease monitoring, cancer diagnostics, and therapeutic drug monitoring. The assay operates under isothermal, one-pot conditions and retains robust performance in complex biological matrices such as human serum. These features establish MARPLE as a promising and broadly applicable tool for immunodiagnostics, expanding the scope of CRISPR-based sensing to protein biomarker detection.
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Spezzani et al. (2025) studied this question.
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