Denani Caio B, Setatino Bruno P, Vieira Renan Oliveira, Schwarcz Waleska D
Laboratory of Immunomolecular Analysis - LANIM, Institute of Technology in Immunobiologicals (Bio-Manguinhos), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.
Methods Mol Biol. 2025;2913:177-182. doi: 10.1007/978-1-0716-4458-4_15.
In the yellow fever studies, methods to quantify neutralizing antibodies are crucial and contribute to the development and evaluation of new antiviral vaccines effectiveness. The assay most commonly used for this purpose is the Plaque-Reduction Neutralization Test (PRNT), but this assay is time-consuming, not amenable to a large number of samples, and difficult to adapt to a high throughput routine. PRNT variations like FRNT and microFRNT were designed to mitigate these bottlenecks, but also tend to have large variations among different analysts due to visual plaque recognition and manual counting errors. Therefore, providing faster and more accurate methods for image acquiring and plaque/focus counting to the neutralizing antibodies assays could minimize human inherent variations. Innovations such as automation at critical steps can increase throughput, reduce rework, and generate more accurate results. Companies specialized in microscopy, robotics, and information technology developed robust systems able to standardize the image acquisition and analysis for neutralization assays, which could aid the public health response to emerging viral diseases. In this context, these automated systems aim to obtain images and to identify morphological patterns, setting the best ranges for some parameters from structures of interest, such as circularity, size, color intensity, etc. In this session, we describe the use of automated image acquisition and quantification procedures to increase serum neutralization assays throughput and improving their results accuracy.
在黄热病研究中，量化中和抗体的方法至关重要，有助于新抗病毒疫苗有效性的研发和评估。为此目的最常用的检测方法是蚀斑减少中和试验（PRNT），但该检测方法耗时，不适用于大量样本，且难以适应高通量常规检测。像FRNT和microFRNT这样的PRNT变体旨在缓解这些瓶颈，但由于视觉蚀斑识别和人工计数误差，不同分析人员之间也往往存在较大差异。因此，为中和抗体检测提供更快、更准确的图像采集和蚀斑/病灶计数方法可以最大限度地减少人为固有差异。关键步骤的自动化等创新可以提高通量、减少返工并产生更准确的结果。专门从事显微镜、机器人技术和信息技术的公司开发了强大的系统，能够对中和试验的图像采集和分析进行标准化，这有助于公共卫生应对新出现的病毒性疾病。在这种背景下，这些自动化系统旨在获取图像并识别形态模式，从感兴趣的结构（如圆形度、大小、颜色强度等）中设置一些参数的最佳范围。在本次会议中，我们描述了使用自动化图像采集和定量程序来提高血清中和试验的通量并提高其结果准确性。
