Balancing sensitivity and specificity in distinguishing TCR groups by CDR sequence similarity

Area of Science:

• Immunology
• Bioinformatics
• Genomics

Background:

• T-cell receptor (TCR) repertoire sequencing offers deep insights into cellular immunity.
• Understanding TCR repertoire commonalities and differences across individuals and conditions is crucial.
• Complementarity determining regions (CDRs), especially CDR3, dictate antigen recognition.

Purpose of the Study:

• To systematically evaluate the predictive power of T-cell receptor (TCR) CDR3 sequences.
• To establish methods for assessing CDR sequence similarity, clustering, and classification.
• To determine the optimal balance between sensitivity and specificity in TCR repertoire analysis.

Main Methods:

• Utilized representative methods for evaluating CDR sequence similarity.
• Employed clustering and classification based on sequence similarity.
• Analyzed CDR3 sequences of known structure to calibrate diversity limits.
• Applied sequence similarity analysis to distinguish twins, classify antigen specificities, and identify pathologies.

Main Results:

• Structural similarity clustering of CDR3s helped define sequence diversity limits for common epitope interactions.
• A specific range of sequence similarity achieved a favorable specificity/sensitivity balance.
• CDR3 repertoire analysis successfully distinguished twins from non-twins.
• Classification of CDR3 repertoires by antigen specificity and pathology was demonstrated.

Conclusions:

• A broad range of CDR3 sequence similarity suggests shared antigen specificities.
• CDR3 sequence analysis is a powerful tool for understanding immune recognition and variation.