Immune Repertoire

Immune Repertoire

The immune repertoire refers to the complete collection of antigen receptors—T cell receptors (TCRs) and B cell receptors (BCRs)—present in an individual at any given time. Understanding the repertoire provides insights into immune status, disease states, and responses to infection or vaccination.

Overview

The adaptive immune system’s power lies in its ability to recognize virtually any antigen through an enormous diversity of receptors. Each lymphocyte expresses a unique receptor generated by V(D)J recombination, and the collective population of these receptors constitutes the immune repertoire.

What Defines the Repertoire?

Scale of Diversity

Theoretical vs. Realized Diversity

The realized repertoire is vastly smaller than theoretical diversity because:

• Limited number of lymphocytes
• Selection processes eliminate many specificities
• Some receptors cannot fold or function properly

The Repertoire as an Immunological Fingerprint

Each individual’s repertoire is unique, shaped by:

Repertoire Organization

Defining a Clonotype

A clonotype is typically defined by:

1. V gene segment used
2. J gene segment used
3. CDR3 nucleotide or amino acid sequence
4. (For BCR) D gene segment and mutation status
5. (For paired analysis) Both chains together

Example TCR Clonotype Notation:

TRBV7-2*01 | CASSLGQAYEQYF | TRBJ2-7*01
   (V gene)    (CDR3 amino acids)   (J gene)

Example BCR Clonotype Notation:

IGHV3-23*01 | CARDRGYSSSWFDPW | IGHJ4*02 | 8.5% mutated
   (V gene)     (HCDR3 amino acids)  (J gene)    (SHM level)

Clone Size Distribution

The repertoire follows a characteristic power-law distribution:

Clone Size Distribution:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Rare clones        │████████████████████  80% of unique sequences
Medium clones      │████  15%
Expanded clones    │█  5%
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Most diversity resides in rare clones, but expanded clones contribute significantly to function.

Repertoire Compartments

Different lymphocyte populations have distinct repertoire characteristics:

Measuring the Repertoire

The Sampling Challenge

The iceberg problem: Any sample captures only a fraction of the total repertoire.

Strategies to Address:

• Adequate input cell numbers
• Sufficient sequencing depth
• Statistical estimators for unseen diversity
• Rarefaction analysis

Diversity Metrics

Richness (Clone Counting)

Definition: Total number of unique clonotypes observed

Limitation: Heavily dependent on sampling depth—deeper sequencing always finds more rare clones.

Diversity Indices

Where pᵢ = proportion of clone i in the sample.

Clonality

Definition: Measure of how dominated the repertoire is by expanded clones

Clonality = 1 - (Shannon entropy / log₂(richness))

Sequencing Approaches

Repertoire Dynamics

During Immune Responses

Acute Infection Timeline:

Vaccination:

• Similar expansion/contraction pattern
• Detectable memory repertoire shift for years
• Booster doses recall and further expand specific clones

Age-Related Changes

Immunosenescence involves:

• Thymic involution → fewer new naive T cells
• Accumulated memory → oligoclonal expansions
• Reduced diversity → impaired responses to new antigens
• Inflammaging → chronic low-grade activation

Tissue-Specific Repertoires

Clinical Applications

Diagnostic Uses

Clonality Assessment

Clinical Application: Distinguishing malignancy from reactive lymphocytosis.

Minimal Residual Disease (MRD)

• Track tumor-specific clonotype after treatment
• Detect relapse before clinical symptoms
• Sensitivity: 1 in 10⁵ - 10⁶ cells
• Guide therapy decisions (continue vs. stop treatment)

Autoimmune Disease Signatures

Application: Biomarkers for diagnosis, monitoring, patient stratification.

Transplant Monitoring

Research Applications

Public vs. Private Repertoire

Public Sequences

Some TCR/BCR sequences are found across multiple individuals:

Significance: Public sequences can serve as biomarkers across populations.

Private Sequences

Most sequences are unique to an individual:

Repertoire Analysis Workflow

Typical Pipeline

1. Sample Collection
   └── Blood, tissue, or sorted cells

2. Library Preparation
   ├── RNA extraction
   ├── Reverse transcription
   ├── PCR amplification (multiplex or 5'RACE)
   ├── UMI incorporation (for quantification)
   └── Adapter ligation

3. Sequencing
   └── Illumina, PacBio, or other platform

4. Bioinformatics
   ├── Quality filtering
   ├── UMI deduplication
   ├── V(D)J assignment (IMGT reference)
   ├── CDR3 extraction
   ├── Error correction
   └── Clonotype quantification

5. Analysis
   ├── Diversity metrics
   ├── Clone tracking
   ├── Motif analysis
   ├── Lineage clustering (BCR)
   └── Statistical comparisons

Key Considerations

Common Analysis Tools

Key Concepts

1. The immune repertoire is the complete collection of antigen receptors, characterized by clonotype identity and abundance

2. Diversity metrics (Shannon entropy, Simpson index, clonality) quantify repertoire complexity beyond simple clone counts

3. Sampling depth critically affects detection—rare clones require deep sequencing

4. Repertoire dynamics reflect immune history—acute responses cause expansion, memory maintains selected clones

5. Clinical applications range from MRD detection to autoimmune diagnosis to transplant monitoring

6. Public sequences shared across individuals may serve as population-level biomarkers

7. Paired chain information is essential for definitive antigen specificity and many diagnostic applications

Related Articles

• T Cell Receptor Structure — TCR architecture
• V(D)J Recombination — How diversity is generated
• Somatic Hypermutation — BCR diversification
• T Cell Development — Thymic selection shapes the T cell repertoire
• B Cell Development — Bone marrow checkpoints shape B cell repertoire

References

1. Robins H. (2013). Immunosequencing: applications of immune repertoire deep sequencing. Current Opinion in Immunology, 25:646-652.

2. Six A, et al. (2013). The past, present and future of immune repertoire biology. Frontiers in Immunology, 4:413.

3. Greiff V, et al. (2017). Systems analysis reveals high genetic and antigen-driven predetermination of antibody repertoires throughout B cell development. Cell Reports, 19:1467-1478.

4. Emerson RO, et al. (2017). Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire. Nature Genetics, 49:659-665.