An automated approach to determine antibody endpoint titers for COVID-19 by an enzyme-linked immunosorbent assay.

Q4 Medicine
A D Ho, H Verkerke, J W Allen, B J Saeedi, D Boyer, J Owens, S Shin, M Horwath, K Patel, A Paul, S-C Wu, S Chonat, P Zerra, C Lough, J D Roback, A Neish, C D Josephson, C M Arthur, S R Stowell
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引用次数: 0

Abstract

While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33-43.

While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33–43.

通过酶联免疫吸附试验自动测定 COVID-19 抗体终点滴度的方法。
尽管 COVID-19 治疗的各种治疗方案不断涌现,但疗养血浆(CP)在大流行早期已被用作一种可能的治疗方案。然而,无论是在确定疗效还是在临床上实施这种方法时,CP疗法面临的最大挑战之一就是如何准确有效地表征这种异质性治疗方法。鉴于目前的局限性,我们的目标是利用 SARS 抗体检测平台和新开发的自动终点滴度分析程序,快速确定 CP 供体和住院患者的 SARS-CoV-2 抗体水平。新开发的抗体检测平台用于对免疫球蛋白 (Ig)G、IgM 和 IgA SARS-CoV-2 抗体进行连续稀释酶联免疫吸附试验 (ELISA)。然后使用市售软件 GraphPad Prism 或新开发的 Python 程序 TiterScape 分析数据,以分析终点滴度。然后比较两种分析方法的终点滴度计算和分析时间。对 SARS-CoV-2 抗体水平的序列稀释分析表明,个体之间的异质性很高。商业平台分析需要大量时间手动输入数据,当最后一次序列稀释高于终点临界值时就会推断出终点滴度值,偶尔会产生错误的高结果。相比之下,TiterScape 在大约 14 分钟内就处理了 1008 个样本的终点滴度结果,而商业软件程序分析则需要 8 个小时。同样重要的是,TiterScape 和 Prism 得出的结果非常相似,平均差异为 1.26 ± 0.2%(平均值 ± SD)。大流行给在短时间内准确检测大量个体的 SARS-CoV-2 抗体水平带来了前所未有的挑战。在寻求以高通量方式确定终点滴度时,能够进行序列稀释分析的 ELISA 平台以及高度灵活的软件界面可能会提供有用的工具。免疫血液学 2021;37:33-43.在 COVID-19 治疗中不断出现各种治疗方案的同时,康复血浆 (CP) 在大流行早期已被用作一种可能的治疗方案。然而,无论是在确定疗效还是在临床上实施治疗方法时,CP疗法面临的最大挑战之一就是如何准确、高效地描述这种异质性治疗方法。鉴于目前的局限性,我们的目标是利用 SARS 抗体检测平台和新开发的自动终点滴度分析程序,快速确定 CP 供体和住院患者的 SARS-CoV-2 抗体水平。新开发的抗体检测平台用于对免疫球蛋白 (Ig)G、IgM 和 IgA SARS-CoV-2 抗体进行连续稀释酶联免疫吸附试验 (ELISA)。然后使用市售软件 GraphPad Prism 或新开发的 Python 程序 TiterScape 分析数据,以分析终点滴度。然后比较两种分析方法的终点滴度计算和分析时间。对 SARS-CoV-2 抗体水平的序列稀释分析表明,个体之间的异质性很高。商业平台分析需要大量时间手动输入数据,当最后一次序列稀释高于终点临界值时就会推断出终点滴度值,偶尔会产生错误的高结果。相比之下,TiterScape 在大约 14 分钟内就处理了 1008 个样本的终点滴度结果,而商业软件程序分析则需要 8 个小时。同样重要的是,TiterScape 和 Prism 得出的结果非常相似,平均差异为 1.26 ± 0.2%(平均值 ± SD)。大流行给在短时间内准确检测大量个体的 SARS-CoV-2 抗体水平带来了前所未有的挑战。在寻求以高通量方式确定终点滴度时,能够进行序列稀释分析的 ELISA 平台以及高度灵活的软件界面可能会提供有用的工具。Immunohematology 2021;37:33–43.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Immunohematology
Immunohematology Medicine-Medicine (all)
CiteScore
1.30
自引率
0.00%
发文量
18
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