DOI 10.1021/acs.analchem.0c05278
Critical Comparison between Large and Mini Vertical Flow Immunoassay Platforms for Yersinia Pestis Detection.
Аннотация
Yersinia pestis is a Gram-negative bacterium that is the causative agent of plague and is widely recognized as a potential biological weapon. Due to the high fatality rate of plague when diagnosis is delayed, the development of rapid, sensitive, specific, and cost-effective methods is needed for its diagnosis. The Y. pestis low calcium response V (LcrV) protein has been identified as a potential microbial biomarker for the diagnosis of plague. In this paper, we present a highly sensitive, paper-based, vertical flow immunoassay (VFI) prototype for the detection of LcrV and the diagnosis of plague. An antigen-capture assay using monoclonal antibodies is employed to capture and detect the LcrV protein, using a colorimetric approach. In addition, the effect of miniaturizing the VFI device is explored based on two different sizes of VFI platforms, denoted as "large VFI" and "mini VFI." Also, a comparative analysis is performed between the VFI platform and a lateral flow immunoassay (LFI) platform to exhibit the improved assay sensitivity suitable for point-of-care (POC) diagnostics. The analytical sensitivity or limit of detection (LOD) in the mini VFI is approximately 0.025 ng/mL, that is, 10 times better than that of the large VFI platform or 80 times over a standard lateral flow configuration. The low LOD of the LcrV VFI appears to be highly suitable for testing clinical samples and potentially diagnosing plague at earlier time points. In addition, optimization of the gold nanoparticle (AuNP) concentration, nanomaterial plasmonic properties, and flow velocity analysis could improve the performance of the VFI. Furthermore, we developed automated image analysis software that shows potential for integrating the diagnostic system into a smartphone. These methods and findings demonstrate that the VFI platform is a highly sensitive device for detecting the LcrV and potentially many other biomarkers.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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