Single Positive T Cells
Single Positive T Cells - Related Videos
06:08
Generating Single Positive CD8 T Cells from Induced Pluripotent Stem Cells
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2025
This video demonstrates an assay to generate tumor antigen-specific induced pluripotent stem cell (iPSC)-derived CD8αβ+ T Cells. Tumor antigen-specific iPSCs are grown on a stromal cell monolayer and differentiated into hematopoietic progenitor cells (HPCs). The HPCs are differentiated into CD4+ CD8+ double-positive T cells using a differentiation medium. These cells are then stimulated to generate single-positive T cells expressing CD8.
12:19
Analysis of Cell Cycle Position in Mammalian Cells
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Cited by 71 •
2012
Determining the cell cycle position of a population of cells, or understanding how signals affect proliferation, can be readily measured by flow cytometry using this protocol. We report a simple experimental approach to staining cells and quantifying their position in the cell cycle.
12:30
Structural Information from Single-molecule FRET Experiments Using the Fast Nano-positioning System
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Cited by 13 •
2017
We present the setup and experimental procedure to obtain smFRET data from large donor-acceptor networks with a TIRF microscope. The step-by-step analysis of these measurements with the Bayesian inference software Fast-NPS yields high-resolved structural information via the application of adapted dye models.
11:26
Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells
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Cited by 8 •
2017
Here, we present a combinatorial approach for classifying neuronal cell types prior to isolation and for the subsequent characterization of single-cell transcriptomes. This protocol optimizes the preparation of samples for successful RNA Sequencing (RNA-Seq) and describes a methodology designed specifically for the enhanced understanding of cellular diversity.
02:32
Position-effect Variegation
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2020
In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
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Selection tests whether thymocyte T-cell receptors recognize peptide–MHC complexes with useful and appropriately regulated specificity. Cells meeting these criteria survive, while unsuitable recognition does not support maturation. This filtering step produces populations capable of participating in adaptive immunity while helping establish central tolerance, which limits the development of strongly self-reactive T cells.
Lineage commitment follows the selection of double-positive thymocytes and is reflected by expression of either the CD4 or CD8 coreceptor. The resulting populations have different broad functional roles: CD4 cells support helper activities, whereas CD8 cells support cytotoxic activities. Measuring these populations therefore provides a way to examine developmental outcomes within the thymus.
Receptor specificity connects thymocyte development with the antigens that T cells may recognize after maturation. Central tolerance adds a control step by favoring appropriately regulated recognition rather than potentially harmful self-reactivity. Together, these features make mature CD4 and CD8 populations useful for investigating how immune protection and the risk of autoimmunity emerge during T-cell development.
Flow cytometry is commonly used to assess their frequency and phenotype, using the CD4 or CD8 coreceptor as key measured features. Investigators can also examine receptor specificity when supported by the assay design. Comparing these measurements across samples helps characterize thymocyte maturation and reveals changes relevant to immune development or disease research.
Frequency measurements show how prominently CD4 or CD8 populations are represented, while phenotype describes their detectable cellular features. Receptor specificity adds information about potential recognition patterns. Considered together, these readouts can indicate how T-cell development is progressing and can support comparisons between normal immune states and conditions involving altered immunity.
These populations are examined in studies of immunodeficiency, autoimmunity, infection, and immunotherapy. In each setting, researchers may compare their frequency, phenotype, or receptor specificity to investigate changes in T-cell development or adaptive immune function. Their developmental origin also makes them useful for connecting thymic selection and lineage decisions with later immune responses.