The CD8 immgenT framework as a universal reference of mouse CD8αβ T cell differentiation states

Area of Science:

• Immunology
• Cell Biology
• Bioinformatics

Background:

• CD8 T cell differentiation is complex, with existing models lacking a comprehensive framework for diverse immunological contexts.
• Understanding the full spectrum of CD8 T cell states is crucial for addressing infections, cancer, and autoimmune diseases.

Purpose of the Study:

• To present the CD8 immgenT framework, a unified system integrating vast single-cell data for CD8 T cell analysis.
• To establish a comprehensive map of CD8 T cell states and their relationships across various physiological and pathological conditions.

Main Methods:

• Integration of over 200,000 single-cell transcriptomes and 128-plex surface proteomes from 734 diverse samples.
• Unbiased computational analysis to identify and define distinct CD8 T cell states and their molecular signatures.

Main Results:

• Identification of 21 distinct CD8 T cell states, including naive, effector, memory, and exhausted populations.
• Demonstration of molecular convergence, where similar transcriptional programs underlie protective or dysfunctional CD8 T cell outcomes.
• Validation of combinatorial markers and gating strategies for reproducible CD8 T cell annotation.

Conclusions:

• The CD8 immgenT framework provides a universal coordinate system for harmonizing CD8 T cell research across different immune challenges.
• This framework clarifies the heterogeneity within classic CD8 T cell archetypes and their relationships in health and disease.
• It enables reproducible annotation of new datasets, advancing our understanding of CD8 T cell differentiation and function.