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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: Jun 14, 2025

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

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Published on: February 6, 2017

A functionally validated TCR-pMHC database for TCR specificity model development.

Marius Messemaker^1,2, Bjørn P Y Kwee^1,2, Živa Moravec¹

¹Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

Biorxiv : the Preprint Server for Biology

|June 4, 2025

Summary

This summary is machine-generated.

High-throughput validation reveals only 50% of T-cell receptor (TCR) and peptide-MHC (pMHC) interactions in existing databases are functional. This study introduces a validated TCR database (TCRvdb) to improve TCR specificity prediction models.

Keywords:

T cell receptor functional genetic screening major histocompatibility antigen peptide predictive models

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High-Efficiency Generation of Antigen-Specific Primary Mouse Cytotoxic T Cells for Functional Testing in an Autoimmune Diabetes Model

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Published on: August 16, 2019

Area of Science:

Immunology
Computational Biology
Bioinformatics

Background:

Predicting T-cell receptor (TCR) specificity is crucial in immunology.
Current TCR-pMHC prediction models rely on historical data of variable quality.
Large language models and computational structure prediction offer potential solutions.

Purpose of the Study:

To develop and employ a high-throughput synthetic platform for validating TCR-pMHC interactions.
To assess the functional accuracy of entries in the VDJdb database.
To generate a high-quality, validated TCR database (TCRvdb) for community use.

Main Methods:

Established a high-throughput synthetic platform for TCR assembly and functional evaluation.
Assessed a large subset of VDJdb-deposited TCR-pMHC entries using standardized functional readouts.
Utilized TCRbridge to analyze AlphaFold3 confidence metrics for TCR-pMHC predictions.

Main Results:

Confirmed functional TCR reactivity for only 50% of the evaluated VDJdb entries.
Demonstrated AlphaFold3 confidence metrics can distinguish functionally validating from non-validating TCRs, despite not being trained for this task.
Generated the validated TCRvdb database.

Conclusions:

A significant portion of existing TCR-pMHC data lacks functional validation.
The validated TCRvdb database and AlphaFold3 confidence metrics show promise for improving TCR specificity prediction.
This resource will aid in training and evaluating more accurate predictive TCR specificity models.