ELISA rescue protocol: recovery of sample concentrations from an assay with an unsuccessful standard curve.

ELISA rescue protocol: recovery of sample concentrations from an assay with an unsuccessful standard curve.
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DOI:
10.1016/j.ymeth.2012.08.013
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发表时间:
2013-05-15
期刊:
Methods (San Diego, Calif.)
影响因子:
--
通讯作者:
Remick DG
Remick DG
中科院分区:
其他
文献类型:
--
作者:
Natarajan S;Remick DG

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酶联免疫吸附测定(ELISA)是一种常用于测量各种生物基质中蛋白质的方法,因为其易于执行且成本相对较低。为了生成定量数据,必须为每次测定制备参考标准曲线;然而,由于研究者错误或标准蛋白降解,否则代表性实验样品数据将变得无用。在此,我们描述了一种方案,通过该方案可以从标准曲线失效的测定中回收样品浓度。实验样品的ΔOD值用于生成新的标准曲线,该标准曲线应用于原始平板。为了验证该方法,将使用可接受的标准曲线获得的实验样品浓度与使用该新方法计算的浓度进行对比。使用线性回归分析,我们显示样品浓度之间的相关性接近1:1,r2值在0.98 - 0.99之间,斜率在0.97 - 1.10之间。该方法证明,产生不可用标准曲线的测定不需要对所有样品进行重新测定。相反,可以检索实验样品浓度,从而节省研究人员重新鉴定样品或重复整个实验所需的时间和资源。
The Enzyme-linked Immunosorbant Assay (ELISA) is a method commonly used to measure proteins in various biological matrices, due to its ease of performance and relatively low cost. In order for quantitative data to be generated, a reference standard curve must be prepared for each assay; however, due to investigator error or standard protein degradation, otherwise representative experimental sample data are rendered useless. Herein, we describe a protocol by which sample concentrations can be recovered from assays in which the standard curve fails. The ΔOD values of the experimental samples are used to generate a new standard curve, which is applied back to the original plate. For validation of this method, experimental sample concentrations obtained using acceptable standard curves were potted against those calculated using this new method. Using linear regression analysis, we show a near 1:1 correlation between sample concentrations, with r2 values between 0.98 – 0.99 and slopes between 0.97 – 1.10. This method demonstrates that assays resulting in unusable standard curves do not require re-assay of all samples. Instead, the experimental sample concentrations can be retrieved saving the investigator the time and resources required to rerun samples or repeat entire experiments.
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