State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, School of Public Health, School of Life Sciences, Xiamen University, 361102 Xiamen, Fujian, PR China.
Emergency Department, The First Affiliated Hospital of Xiamen University, 361003 Xiamen, Fujian, PR China.
J Virol Methods. 2022 Nov;309:114597. doi: 10.1016/j.jviromet.2022.114597. Epub 2022 Aug 3.
Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has become disaster for human society. As the pandemic becomes more regular, we should develop more rapid and accurate detection methods to achieve early diagnosis and treatment. Antigen detection methods based on spike protein has great potential, however, it has not been effectively developed, probably due to the torturing conformational complexity. By utilizing cross-blocking data, we clustered SARS-CoV-2 receptor binding domain (RBD)-specific monoclonal antibodies (mAbs) into 6 clusters. Subsequently, the antigenic sites for representative mAbs were identified by RBDs with designed residue substitutions. The sensitivity and specificity of selected antibody pairs was demonstrated using serial diluted samples of SARS-CoV-2 S protein and SARS-CoV S protein. Furthermore, pseudovirus system was constructed to determine the detection capability against SARS-CoV-2 and SARS-CoV. 6 RBD-specific mAbs, recognizing different antigenic sites, were identified as potential candidates for optimal antibody pairs for detection of SARS-CoV-2 S protein. By considering relative spatial position, accessibility and conservation of corresponding antigenic sites, affinity and the presence of competitive antibodies in clinical samples, 6H7-6G3 was rationally identified as optimal antibody pair for detection of both SARS-CoV-2 and SARS-CoV. Furthermore, our results showed that 6H7 and 6G3 effectively bind to SARS-CoV-2 variants of concern (VOCs). Taken together, we identified 6H7-6G3 antibody pair as a promising rapid antigen diagnostic tool in containing COVID-19 pandemic caused by multiple VOCs. Moreover, our results also provide an important reference in screening of antibody pairs detecting antigens with complex conformation.
由严重急性呼吸系统综合征冠状病毒 2 型（SARS-CoV-2）引起的 2019 年冠状病毒病（COVID-19）已成为人类社会的灾难。随着大流行变得更加规律，我们应该开发更快速、更准确的检测方法，以实现早期诊断和治疗。基于刺突蛋白的抗原检测方法具有很大的潜力，但尚未得到有效开发，这可能是由于其复杂的构象。我们利用交叉阻断数据，将 SARS-CoV-2 受体结合域（RBD）特异性单克隆抗体（mAbs）聚类为 6 个簇。随后，通过设计残基取代 RBD 来确定代表性 mAbs 的抗原表位。通过对 SARS-CoV-2 S 蛋白和 SARS-CoV S 蛋白的系列稀释样本进行检测，验证了选定抗体对的灵敏度和特异性。此外，还构建了假病毒系统来确定对 SARS-CoV-2 和 SARS-CoV 的检测能力。鉴定了 6 种识别不同抗原表位的 RBD 特异性 mAbs，它们是用于检测 SARS-CoV-2 S 蛋白的最佳抗体对的潜在候选物。通过考虑相应抗原表位的相对空间位置、可及性和保守性、亲和力以及临床样本中竞争抗体的存在，我们合理地确定了 6H7-6G3 作为检测 SARS-CoV-2 和 SARS-CoV 的最佳抗体对。此外，我们的结果表明 6H7 和 6G3 可有效地与 SARS-CoV-2 关注变体（VOC）结合。总之，我们确定了 6H7-6G3 抗体对作为一种有前途的快速抗原诊断工具，可用于控制由多种 VOC 引起的 COVID-19 大流行。此外，我们的结果还为筛选用于检测复杂构象抗原的抗体对提供了重要参考。
