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Synthesis of Molecularly Imprinted Polymer Nanoparticles for SARS-CoV-2 Virus Detection Using Surface Plasmon Resonance
Chemosensors ; 10(11):459, 2022.
Article in English | MDPI | ID: covidwho-2099368
ABSTRACT
COVID-19 caused by a SARS-CoV-2 infection was first reported from Wuhan, China, and later recognized as a pandemic on March 11, 2020, by the World Health Organization (WHO). Gold standard nucleic acid and molecular-based testing have largely satisfied the requirements of early diagnosis and management of this infectious disease;however, these techniques are expensive and not readily available for point-of-care (POC) applications. The COVID-19 pandemic of the 21st century has emphasized that medicine is in dire need of advanced, rapid, and cheap diagnostic tools. Herein, we report on molecularly imprinted polymer nanoparticles (MIP-NPs/nanoMIPs) as plastic antibodies for the specific detection of SARS-CoV-2 by employing a surface plasmon resonance (SPR) sensor. High-affinity MIP-NPs directed against SARS-CoV-2 were manufactured using a solid-phase imprinting method. The MIP-NPs were then characterized using dynamic light scattering (DLS) and atomic force microscopy (AFM) prior to their incorporation into a label-free portable SPR device. Detection of SARS-CoV-2 was studied within a range of 104–106 PFU mL−1. The MIP-NPs demonstrated good binding affinity (KD = 0.12 pM) and selectivity toward SARS-CoV-2. The AFM, cyclic voltammetry, and square-wave voltammetry studies revealed the successful stepwise preparation of the sensor. A cross-reactivity test confirmed the specificity of the sensor. For the first time, this study demonstrates the potential of molecular imprinting technology in conjunction with miniaturized SPR devices for the detection of SARS-CoV-2 particles with high-affinity and specificity. Such sensors could help monitor and manage the risks related to virus contamination and infections also beyond the current pandemic.

Full text: Available Collection: Databases of international organizations Database: MDPI Language: English Journal: Chemosensors Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Language: English Journal: Chemosensors Year: 2022 Document Type: Article