Marie-Theres Thieme-Ehlert, Thomas Jacobs, Johannes Brandi, Maria Sophia Mackroth
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OMIP-114: A 36-Color Spectral Flow Cytometry Panel for Detailed Analysis of T Cell Activation and Regulation in Small Human Blood Volumes.
This 36-color flow cytometry panel is designed to characterize multiple lymphocyte compartments, with a focus on T cells, their memory subpopulations, and immune checkpoints in human whole blood samples. In clinical settings, the amount of blood available from patients for scientific research is often limited. This restriction may be further exacerbated when working with samples from small children or in resource-poor settings-both scenarios commonly encountered in malaria and infectious disease research. Accordingly, this panel is designed to maximize the information that can be obtained from as little as 200 μL whole blood using flow cytometry. This panel allows a phenotypic characterization of the main subpopulations within T cells, as well as B cells and NK cells. It includes markers for the analysis of memory subpopulations, regulatory T cell subsets, and T follicular helper cells. Furthermore, surface and intracellular markers for activation and differentiation, effector functions, exhaustion, and immune checkpoints are included, allowing detailed characterization of the main lymphocyte subsets, in particular T cells. This panel was optimized for the analysis of fresh human blood samples obtained from malaria patients, but it may be adapted to the analysis of isolated PBMC or tissue samples, as well as samples from patients with other infectious or inflammatory diseases.
期刊介绍:
Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques.
The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome:
Biomedical Instrumentation Engineering
Biophotonics
Bioinformatics
Cell Biology
Computational Biology
Data Science
Immunology
Parasitology
Microbiology
Neuroscience
Cancer
Stem Cells
Tissue Regeneration.