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T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

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Related Experiment Video

Updated: Dec 26, 2025

Examination of Thymic Positive and Negative Selection by Flow Cytometry

Examination of Thymic Positive and Negative Selection by Flow Cytometry

Published on: October 8, 2012

Is T Cell Negative Selection a Learning Algorithm?

Inge M N Wortel¹, Can Keşmir², Rob J de Boer²

¹Department of Tumor Immunology, Radboud Institute for Molecular Life Sciences, Geert Grooteplein 26-28, 6525 GA Nijmegen, The Netherlands.

|March 15, 2020

Summary

This summary is machine-generated.

The immune system prevents autoimmunity by training T cells in the thymus. A machine learning model shows that T cell cross-reactivity helps distinguish foreign peptides from self-peptides not encountered during training.

Keywords:

T cell repertoires artificial immune system central tolerance learning by example negative selection self-nonself discrimination

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Last Updated: Dec 26, 2025

Examination of Thymic Positive and Negative Selection by Flow Cytometry

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Published on: August 6, 2016

Mouse Naïve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets

Mouse Naïve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets

Published on: April 16, 2015

Area of Science:

Immunology
Computational Biology
Machine Learning

Background:

The immune system must distinguish self from foreign to prevent autoimmunity.
Negative selection in the thymus trains T cells to tolerate self-peptides.
Some self-reactive T cells escape thymic selection, indicating incomplete self-peptide exposure.

Purpose of the Study:

To investigate how T cells discriminate unseen self-peptides from foreign peptides.
To explore the role of T cell cross-reactivity in shaping the T cell repertoire after negative selection.
To model the impact of thymic negative selection on T cell recognition of novel self-peptides.

Main Methods:

Development of an "artificial immune system" using machine learning.
Modeling the T cell repertoire and its response to self and foreign peptides.
Simulating negative selection with a defined set of self-peptides.

Main Results:

Moderate T cell cross-reactivity skews the repertoire towards peptides systematically differing from self.
Distinguishing self-like foreign peptides is possible if thymic peptides are sufficiently diverse.
Negative selection on a curated self-peptide set enhances tolerance to "unseen" self-peptides.

Conclusions:

T cell cross-reactivity plays a crucial role in generalizing tolerance to novel self-peptides.
The model predicts that strategic negative selection can improve self-tolerance.
Findings suggest a learning-like generalization process in adaptive immunity.