Removing Negative Impacts from Inevitable Nonreproducible and Nonspecific Antibody–Probe Interactions in Viral Serology

血清学 化学 计算生物学 病毒学 抗体 免疫学 生物
作者
Wenwen Xu,Hao Chen,Yiting Li,Hu Cheng,Yi Deng,Peiyan Zheng,Jingzhi Li,Lan Yang,Shiping He,Dongli Ma,Qiang Zhu,Dayong Gu,Jun Han,Baoqing Sun,Hongwei Ma
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (3): 1867-1879 被引量:1
标识
DOI:10.1021/acs.analchem.2c03637
摘要

Serological assays are indispensable tools in public health. Presently deployed serological assays, however, largely overlook research progress made in the last two decades that jeopardizes the conceptual foundation of these assays, i.e., antibody (Ab) specificity. Challenges to traditional understanding of Ab specificity include Ab polyspecificity and most recently nonreproducible Ab-probe interactions (NRIs). Here, using SARS-CoV-2 and four common livestock viruses as a test bed, we developed a new serological platform that integrates recent understanding about Ab specificity. We first demonstrate that the response rate (RR) from a large-sized serum pool (∼100) is not affected by NRIs or by nonspecific Ab-probe interactions (NSIs), so RR can be incorporated into the diagnostic probe selection process. We subsequently used multiple probes (configured as a "protein peptide hybrid microarray", PPHM) to generate a digital microarray index (DMI) and finally demonstrated that DMI-based analysis yields an extremely robust probabilistic trend that enables accurate diagnosis of viral infection that overcomes multiple negative impacts exerted by NSI/NRI. Thus, our study with SARS-CoV-2 confirms that the PPHM-RR-DMI platform enables very rapid development of serological assays that outperform traditional assays (for both sensitivity and specificity) and supports that the platform is extendable to other viruses.
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