Abstract
ELISPOT results used to be evaluated visually which, however, is inevitably subjective, inaccurate, and cumbersome. Even when applying automated image analysis to this end, the results are highly variable if the counting parameters are set subjectively. Since objective, accurate, and reproducible measurements are fundamental to science, major efforts have been undertaken over the last decade at CTL to understand the scientific principles behind ELISPOT data and to develop “intelligent” image analysis algorithms based on these principles. Thus, a spot recognition and gating algorithm was developed to automatically recognize the signatures of defined cell populations, such as T cells, discerning them from irrelevant cell types and noise. In this way, the science of ELISPOT data analysis has been introduced, permitting exact frequency measurement against background. As ELISPOT assays become a gold standard for monitoring antigen-specific T-cell immunity in clinical trials, the need has surfaced to make ELISPOT data transparent, reproducible, and tamper-proof, complying with Good Laboratory Practice (GLP) and Code for Federal Regulations (CFR) Part 11 guidelines. Flow cytometry-based and other immune monitoring assay platforms face the same challenge. In this chapter, we provide an overview of how CTL’s ImmunoSpot® platform for ELISPOT data analysis, management, and documentation meets these challenges.
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Acknowledgments
We would like to thank all those who worked at Cellular Technology Ltd., and at Case Western Reserve University under the direction of Prof. Paul V. Lehmann on establishing the scientific foundations of cytokine ELISPOT assays. At the postdoctoral level, these are (in alphabetical order): Drs. Don Anthony, Beate Berner, Thomas Forsthuber, Peter Heeger, Alexey Karulin Damian Kovalovsky, Stephanie Kuerten, Patrick Ott, Clara Pelfrey, Frauke Rininsland, Stephan Schwander, Tobias Schlingman, Oleg Targoni, and Magdalena Tary-Lehmann. Several graduate students at Case have also made major contributions in our ELISPOT efforts: Wolf Bartholomae, Jan Baus, Kamruz Darabi, Marcus Dittrich, Julia Eisenberg, Kristina Feldmann, Judith Gottwein, Robert Guerkov, Thomas Helms, Bernhard Herzog, Maike Hesse, Harald Hofstetter, Thomas Kleen, Christian Kreher, Haydar Kuekrek, Anke Lonsdorf, Kai Loevenbrueck, Stephan Quast, Tarvo Rajasalu, Britta Stern, and Hualin Yip. We are indebted to the hardware and software development efforts of Johannes Albrecht, Tameem Ansari, Istvan Becza, Dwaine Bensen, Andras Bakos, Georg Bezzeg, Richard Caspell, Carsten Lohrmann, Zoltan Megyesi, Brian Skinner, Akos Subucz, Dean Velasco, and Szabo Zsolt.
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Zhang, W., Lehmann, P.V. (2012). Objective, User-Independent ELISPOT Data Analysis Based on Scientifically Validated Principles. In: Kalyuzhny, A. (eds) Handbook of ELISPOT. Methods in Molecular Biology, vol 792. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-325-7_13
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DOI: https://doi.org/10.1007/978-1-61779-325-7_13
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