Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Mycobacterial Research Laboratories, Colorado State University, Fort Collins, CO, United States.
Front Immunol. 2024 Oct 2;15:1427526. doi: 10.3389/fimmu.2024.1427526. eCollection 2024.
Enzyme-linked immunosorbent assay (ELISA) is a technique to detect the presence of an antigen or antibody in a sample. ELISA is a simple and cost-effective method that has been used for evaluating vaccine efficacy by detecting the presence of antibodies against viral/bacterial antigens and diagnosis of disease stages. Traditional ELISA data analysis utilizes a standard curve of known analyte, and the concentration of the unknown sample is determined by comparing its observed optical density against the standard curve. However, in the case of vaccine research for complicated bacteria such as (Mtb), there is no prior information regarding the antigen against which high-affinity antibodies are generated and therefore plotting a standard curve is not feasible. Consequently, the analysis of ELISA data in this instance is based on a comparison between vaccinated and unvaccinated groups. However, to the best of our knowledge, no robust data analysis method exists for "non-standard curve" ELISA. In this paper, we provide a straightforward R-based ELISA data analysis method with open access that incorporates end-point titer determination and curve-fitting models. Our modified method allows for direct measurement data input from the instrument, cleaning and arranging the dataset in the required format, and preparing the final report with calculations while leaving the raw data file unchanged. As an illustration of our method, we provide an example from our published data in which we successfully used our method to compare anti-Mtb antibodies in vaccinated vs non-vaccinated mice.
酶联免疫吸附测定（ELISA）是一种用于检测样品中抗原或抗体存在的技术。ELISA 是一种简单且具有成本效益的方法，已被用于通过检测针对病毒/细菌抗原的抗体存在来评估疫苗效力，并诊断疾病阶段。传统的 ELISA 数据分析利用已知分析物的标准曲线，通过将未知样品的观察光密度与标准曲线进行比较来确定其浓度。然而，在针对复杂细菌（如 Mtb）的疫苗研究中，对于产生高亲和力抗体的抗原没有先验信息，因此绘制标准曲线是不可行的。因此，在这种情况下，ELISA 数据的分析是基于接种组和未接种组之间的比较。然而，据我们所知，对于“非标准曲线”ELISA，还没有可靠的数据分析方法。在本文中，我们提供了一种简单的基于 R 的 ELISA 数据分析方法，具有开放访问权限，其中包括终点滴度测定和曲线拟合模型。我们的改进方法允许直接从仪器输入测量数据，清洁和整理所需格式的数据，并准备带有计算的最终报告，而原始数据文件保持不变。作为我们方法的说明，我们提供了一个来自我们已发表数据的示例，其中我们成功地使用我们的方法比较了接种组和未接种组小鼠中的抗 Mtb 抗体。
