Multiplex Microscopy Assay for Assessment of Therapeutic and Serum Antibodies against Emerging Pathogens

Viruses Pub Date : 2024-09-17 DOI:10.3390/v16091473
Nuno Sartingen, Vanessa Stürmer, Matthias Kaltenböck, Thorsten G. Müller, Paul Schnitzler, Anna Kreshuk, Hans-Georg Kräusslich, Uta Merle, Frauke Mücksch, Barbara Müller, Constantin Pape, Vibor Laketa
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Abstract

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.
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用于评估针对新发病原体的治疗抗体和血清抗体的多重显微分析法
新型病原体的出现(如最近出现的严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2))凸显了对可快速部署和适应性强的诊断检测的需求,以评估其对人类健康的影响并指导未来大流行病的公共卫生应对措施。在这项研究中,我们开发了一种自动多重显微检测方法,并结合了基于机器学习的抗体检测分析。为了实现多重化和同时检测多种病毒抗原,我们设计了一种条形码策略,利用基于 HeLa 的细胞系面板。每种细胞系都表达了一种不同的病毒抗原,以及一种显示独特亚细胞定位模式的荧光蛋白,用于细胞分类。我们的稳健细胞分割和分类算法与自动图像采集相结合,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用于定量检测患者或接种者血清中针对不同变体的 SARS-CoV-2 棘突蛋白和核壳蛋白的免疫反应,以及研究单克隆抗体的选择性反应。重要的是,我们的系统可以迅速适应其他 SARS-CoV-2 变体以及任何新出现病原体的抗原,因此是大流行病防备方面的重要资源。
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