CRISPR-Cas13a–Powered Electrochemical Biosensor for Label-Free Detection of Chikungunya Virus RNA Using a Ceria-Modified Screen-Printed Carbon Electrode

This study aims to develop a label-free electrochemical biosensor for the detection of chikungunya virus (CHIKV) RNA, based on CRISPR-Cas13a integrated with a cerium oxide (ceria)-modified screen-printed carbon electrode (SPCE). The ceria film was deposited through cathodic electrodeposition, forming a uniform, needle-like film, as observed by SEM, and a crystalline fluorite structure was confirmed by XRD with characteristic (111), (200), and (220) reflections. The results showed that Raman spectroscopy demonstrated a dominant F2g band at ∼463 cm −1, indicative of cubic ceria, while XPS analysis displayed the presence of 13.65% Ce 3+, contributing to favorable surface reactivity for biomolecule immobilization. This interface enhanced the attachment of a biotinylated RNA probe through streptavidin binding. Furthermore, a guide RNA (gRNA) was rationally designed to target the conserved region of the CHIKV E1 gene, with high specificity confirmed through in silico arrangement against related viruses. Upon target recognition, the activated Cas13a enzyme triggered collateral cleavage of the immobilized probe, leading to a measurable reduction in the guanine oxidation signal, detected by differential pulse voltammetry (DPV). This detection strategy was entirely label-free and amplification-free, simplifying both sensor fabrication and operation. The biosensor achieved a detection limit of 1.325 ppt, had a linear response in the range of 1–10,000 ppt, and showed excellent selectivity against DENV and SARS-CoV-2. It also retained signal stability over 45 days and yielded a recovery rate of 94.98% in spiked human serum. In conclusion, this study represents a modular and programmable sensing platform for direct RNA detection that integrates RNA-guided molecular recognition and signal transduction without the need for labeled substrates or amplification, simplifying CRISPR-based diagnostics supporting good health and well-being through field-deployable applications.