Department of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.
European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Viruses. 2024 Sep 17;16(9):1473. doi: 10.3390/v16091473.
The emergence of novel pathogens, exemplified recently by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the need for rapidly deployable and adaptable diagnostic assays to assess their impact on human health and guide public health responses in future pandemics. In this study, we developed an automated multiplex microscopy assay coupled with machine learning-based analysis for antibody detection. To achieve multiplexing and simultaneous detection of multiple viral antigens, we devised a barcoding strategy utilizing a panel of HeLa-based cell lines. Each cell line expressed a distinct viral antigen, along with a fluorescent protein exhibiting a unique subcellular localization pattern for cell classification. Our robust, cell segmentation and classification algorithm, combined with automated image acquisition, ensured compatibility with a high-throughput approach. As a proof of concept, we successfully applied this approach for quantitation of immunoreactivity against different variants of SARS-CoV-2 spike and nucleocapsid proteins in sera of patients or vaccinees, as well as for the study of selective reactivity of monoclonal antibodies. Importantly, our system can be rapidly adapted to accommodate other SARS-CoV-2 variants as well as any antigen of a newly emerging pathogen, thereby representing an important resource in the context of pandemic preparedness.
新型病原体的出现,最近以严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)为例,突出了需要快速部署和适应性强的诊断检测方法,以评估它们对人类健康的影响,并在未来的大流行中指导公共卫生应对措施。在这项研究中,我们开发了一种自动化多重显微镜检测方法,并结合基于机器学习的分析来进行抗体检测。为了实现多种病毒抗原的多重检测和同时检测,我们设计了一种利用基于 HeLa 细胞系的面板的条形码策略。每个细胞系表达一种独特的病毒抗原,以及一种具有独特亚细胞定位模式的荧光蛋白,用于细胞分类。我们强大的细胞分割和分类算法,结合自动化图像采集,确保了与高通量方法的兼容性。作为概念验证,我们成功地将这种方法应用于定量检测患者或疫苗接种者血清中针对 SARS-CoV-2 刺突和核衣壳蛋白不同变体的免疫反应,以及研究单克隆抗体的选择性反应性。重要的是,我们的系统可以快速适应新出现的病原体的其他 SARS-CoV-2 变体以及任何抗原,从而在大流行准备方面代表了一个重要资源。