Colorimetric Aptablot Assay for the Detection of Chikungunya Virus (CHIKV)

Yong Chun, Low and Magdline Sia, Henry Sum and Anna, Andrew (2024) Colorimetric Aptablot Assay for the Detection of Chikungunya Virus (CHIKV). In: Molecular Diagnostics & Biomarker Discovery 2024, 3rd - 4th October 2024.

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Abstract

Chikungunya virus (CHIKV) infection is responsible for causing febrile illness in humans and posed a public health concern especially since the largest outbreak in the Indian Ocean in 2004. Patients infected with CHIKV might suffer from persistent joint pain for months to years. Serological tests detecting CHIKV antigens, such as enzyme-linked immunosorbent assays, have several limitations, including high cost, the need for well-trained personnel, batch-to-batch variation, and less stable. Unlike antibodies, aptamers (single-stranded DNA or RNA molecules) offer high affinity and specificity for target molecules, can be produced in vitro and do not have batch-to-batch variation. In this study, an Aptablot assay was developed using an aptamer, replacing antibodies commonly used in conventional dot blot assays. The aptamers were selected via Systematic Evolution of Ligands by Exponential Enrichment and are specific against CHIKV. The aptamers were modified with Thiol group at 5’ end and conjugated with 20 nm maleimide activated gold nanoparticles (AuNP) using a conjugation kit. The Aptablot assay was verified by immobilizing a series of concentrated CHIKV on the nitrocellulose membrane and incubated with aptamer-conjugated AuNP after the membrane was blocked with Bovine Serum Albumin in Phosphate Buffer Saline with Tween-20. The limit of detection of the Aptablot assay was 104 PFU/ml, which is within the typical CHIKV load (104 to 108 PFU/ml) in patients' samples during the viremic stage of infection. The colorimetric Aptablot assay developed in this study is simple, fast, and user-friendly, and it can be done without the need for advanced equipment or skilled personnel. Our findings suggest that the Aptablot assay is a promising tool for the detection of CHIKV, especially in resource-limited settings where CHIKV is endemic.

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