Lehmann Paul Viktor
Cellular Technology Ltd., Cleveland, OH, USA.
Methods Mol Biol. 2005;302:117-32. doi: 10.1385/1-59259-903-6:117.
The recent renaissance of enzyme-linked immunospot (ELISPOT) assays largely is the result of advances in image analysis. Information on the frequency of antigen-specific T-cells and also on the secretion rate of the individual cells is captured in spots generated using this technique. Although the overall assessment of ELISPOT results can be conducted visually, this is inevitably subjective, inaccurate, and cumbersome. In contrast, objective, and accurate measurements are fundamental to good science. Validated image analysis algorithms and procedures, therefore, have become critical for elevating the quality of ELISPOT assays results. As cytokine and granzyme B ELISPOT assays become the gold standard for monitoring antigen-specific T-cell immunity in clinical trials, the pressure increases to make ELISPOT analysis transparent, reproducible and tamperproof, complying with Good Laboratory Practice and Code for Federal Regulations Part 11 guidelines. In addition, ELISPOT assays in clinical and basic science settings frequently require high degrees of throughput, thus further raising the need for advanced data management and statistical analysis. The ImmunoSpot software portfolio has been specifically designed to meet all these needs, using the techniques described in this chapter.
酶联免疫斑点(ELISPOT)检测法最近的复兴很大程度上是图像分析技术进步的结果。使用该技术产生的斑点中捕获了有关抗原特异性T细胞频率以及单个细胞分泌率的信息。尽管ELISPOT结果的总体评估可以通过肉眼进行,但这不可避免地具有主观性、不准确且繁琐。相比之下,客观准确的测量对于优秀的科学研究至关重要。因此,经过验证的图像分析算法和程序对于提高ELISPOT检测结果的质量变得至关重要。随着细胞因子和颗粒酶B ELISPOT检测法成为临床试验中监测抗原特异性T细胞免疫的金标准,使ELISPOT分析具有透明度、可重复性和防篡改能力的压力不断增加,这需要符合良好实验室规范和联邦法规第11部分指南。此外,临床和基础科学环境中的ELISPOT检测通常需要高度的通量,从而进一步增加了对先进数据管理和统计分析的需求。ImmunoSpot软件组合经过专门设计,利用本章所述技术满足所有这些需求。