化学
诺如病毒
拉伤
表位
分子印迹聚合物
食品科学
病毒学
抗体
生物化学
病毒
选择性
遗传学
医学
内科学
生物
催化作用
作者
Amy Dann,Pankaj Singla,Jake McClements,Minji Kim,Sloane Stoufer,Robert D. Crapnell,Craig Edward Banks,Shayan Seyedin,Mark Geoghegan,Christopher F. Blanford,Matthew D. Moore,Marloes Peeters
标识
DOI:10.1016/j.aca.2025.344331
摘要
BACKGROUND: Norovirus is the leading cause of viral gastroenteritis worldwide, contributing to widespread disease and financial burdens. However, current testing methods are unsuitable for on-site analysis, as they typically use biological receptors, require specialized reagents, and skilled technicians. Proactive on-site testing of high-risk food samples is essential to prevent outbreaks, requiring the development of innovative sensor systems. RESULTS: We have developed a thermal sensor capable of selectively detecting two recurrent norovirus genotypes, GI.1 and GII.4, within a model food matrix. The sensor uses epitope-imprinted polymer nanoparticles (nanoMIPs) designed from a 10-amino-acid sequence derived from the conserved P1 region of the GI.1 viral capsid. The nanoMIPs demonstrated favorable detection capability to norovirus GI.1 and GII.4 virus-like particles in buffer solutions, achieving detection limits of 1.53 and 2.28 pg/mL, respectively. The selectivity of the nanoMIPs was evaluated against a panel of similar viruses, including murine norovirus, Tulane virus, and bacteriophage MS2, each of which showed a reduced signal. Notably, the sensor achieved rapid detection (30 min) of norovirus GI.1 and GII.4 virus-like particles in contamination prone spinach samples while maintaining comparable detection limits (2.19 pg/mL and 2.69 pg/mL) to spiked buffer solutions. SIGNIFICANCE: The combination of rapid detection time, dual strain recognition, and simple sample preparation makes this thermal sensor a promising tool for on-site testing in food safety and public health settings. Furthermore, the ability to detect multiple strains using a single ligand represents a significant advantage, enabling the development of straightforward systems capable of detecting various strains in complex environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI