Abstract
Background: Conventional PRRSV diagnostic approaches have limitations, including complex laboratory requirements, inability to distinguish active from past infections, and susceptibility to viral mutations. Objectives: This study aimed to develop a rapid and specific porcine reproductive and respiratory syndrome virus (PRRSV) detection method using DNA aptamers selected through Cell-SELEX targeting virus-infected cells. Results: MARC-145 cells infected with PRRSV strain VR-2332 served as positive targets, whereas uninfected cells were used as negative controls for Cell-SELEX selection using a randomized single-stranded DNA (ssDNA) library. The selected aptamer candidates underwent post-SELEX binding-affinity screening via NanoDrop quantification, secondary structure prediction using M-fold analysis, and specificity validation through an aptamer-based sandwich assay (ABSA) employing swine influenza virus (SIV)-infected cells as heterologous controls. Cell-SELEX yielded 22 distinct aptamer candidates, with three aptamers (PRRSV_apta17, PRRSV_apta18, and PRRSV_apta21) demonstrating superior binding affinity for PRRSV-infected cells. PRRSV_apta17 exhibited optimal thermodynamic stability and highest binding performance. ABSA validation confirmed high specificity for PRRSV-infected cells with minimal cross-reactivity to SIV-infected controls. Conclusion: Cell-SELEX successfully generated highly specific DNA aptamers capable of detecting PRRSV-infected cells by recognizing infection-induced extracellular surface modifications. This aptamer-based approach offers promising alternatives for rapid, cost-effective diagnosis of PRRSV with potentially enhanced resistance to viral mutations by targeting conserved host cellular responses, enabling improved point-of-care testing applications.
| Original language | English |
|---|---|
| Journal | Molecular and Cellular Toxicology |
| DOIs | |
| State | Accepted/In press - 2025 |
Keywords
- Cell-SELEX
- DNA aptamer
- Infected cell detection
- PRRSV
- Swine disease
- Viral detection
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