Qinyue Jiang, Ciska Lindelauf, Vincent van Unen, Andrea E van der Meulen-de Jong, Frits Koning, M Fernanda Pascutti
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A 37-Color Spectral Flow Cytometric Panel to Assess Transcription Factors and Chemokine Receptors in Human Intestinal Lymphoid Cells.
We have developed a 37-color spectral flow cytometry panel to assess the phenotypical differentiation of innate and adaptive immune lymphoid subsets within human intestinal tissue. In addition to lineage markers for identifying innate lymphoid cells (ILC), TCRγδ, MAIT (mucosal-associated invariant T), natural killer (NK), CD4+ and CD8+ T cells, we incorporated markers of differentiation and activation (CD45RA, CD45RO, CD25, CD27, CD38, CD39, CD69, CD103, CD127, CD161, HLA-DR, CTLA-4 [CD152]), alongside transcription factors (Bcl-6, FoxP3, GATA-3, Helios, T-bet, PU.1 and RORγt) and chemokine receptors (CCR4, CCR6, CCR7, CXCR3, and CXCR5). Additionally, Granzyme B and Ki-67 were included to assess cytotoxicity and proliferation potential of the different subsets. This panel is currently used for in-depth immunophenotyping in endoscopic biopsies and peripheral blood mononuclear cells (PBMC) from inflammatory bowel disease (IBD) patients. Distinguished from other OMIP papers, the comprehensive detection of both transcription factors and chemokine receptors facilitates the efficient assessment of several subsets, particularly CD4+ T helper cells, and its potential application extends to both tissue and circulation.
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.