Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay

Digital nucleic acid assays, known for their high sensitivity and specificity, typically rely on fluorescent readouts and expensive and complex nanowell manufacturing, which constrain their broader use in point-of-care (POC) application. Here, we introduce an alternative digital molecular diagnostics, termed dCRISTOR, by seamlessly integrating deactivated Cas9 (dCas9)-engineered micromotors, extraction-free loop-mediated isothermal amplification (LAMP), low-cost bright field microscopy, and deep learning-enabled image processing. The micromotor, composed of a polystyrene sphere attached to a magnetic bead, incorporates a dCas9 ribonucleoprotein complex. The presence of human immunodeficiency virus-1 (HIV-1) RNA in a sample results in the formation of large-sized amplicons that can be specifically captured by the micromotors, reducing their velocity induced by an external magnetic field. The micromotor is propelled by an external magnetic field, which eliminates the need for chemical fuels, reducing system complexity, and allowing for precise control over micromotor movement, enhancing accuracy and reliability. A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format ("1" or "0") for simplified result interpretation without user bias. Incorporating an extraction-free LAMP assay streamlines the dCRISTOR workflow, enabling qualitative HIV-1 detection in spiked plasma (n = 21) that demonstrates 100% sensitivity and specificity and achieves a limit of detection (LOD) of 0.96 copies/μL. The assay also achieved 100% correlation with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in clinical patient samples (n = 9). The dCRISTOR assay, a label-free digital nucleic acid testing system that eliminates the need for fluorescence readouts, absorbance measurements, or expensive manufacturing processes, represents a substantial advancement in digital viral RNA diagnostics.