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Updated: Oct 2, 2026

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing
Published on: January 12, 2021
Single-cell immune repertoire atlas maps coordinated circulating adaptive immune states in inflammatory bowel disease
Abstract:
Single-cell studies have defined immune states in inflammatory bowel disease (IBD), but how adaptive receptor histories organize circulating immunity remains unclear. We generated a single-cell transcriptomic atlas of peripheral blood from 249 participants with Crohn's disease, ulcerative colitis, or non-IBD control status, including 182 with productive TCR and BCR recovery. Expanded TCR clonotypes marked inflammatory-memory and cytotoxic states, while distinct but similar paired TCRs shared inflammatory programs across participants. BCR lineage maturation linked IgA-associated mucosal and plasma B cell programs to somatic mutation and class switching, distinguishing maturation-associated biology from clonal expansion. Helper, regulatory, and cytotoxic T-cell programs covaried with B-cell states, and inferred interactions nominated reciprocal antigen-presentation and helper pathways. Repertoire-based machine learning distinguished diagnosis, inflammation, and contemporaneous six-month treatment-response status. Together, this atlas connects receptor architecture to coordinated systemic immune remodeling, establishes a foundation for repertoire-informed patient stratification, and prioritizes candidate mechanisms of IBD pathogenesis.
Highlights:
Paired single-cell receptors map circulating adaptive immune states across IBDTCR expansion and paired-chain convergence identify inflammatory programsBCR lineage maturation links plasma programs to mutation and class switchingRepertoire features benchmark diagnosis and clinical-state classification.
In Brief:
Gubatan et al. present a peripheral blood single-cell transcriptome and paired immune-receptor atlas across IBD and controls. Clone-aware analyses connect TCR expansion and sequence similarity to inflammatory programs, distinguish B-cell phenotype from lineage maturation, and link participant-level T-B covariation to an inferred ligand- receptor interactome. Machine learning models with repertoire features classify diagnosis, inflammatory status, and contemporaneous six-month treatment-response status.
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Inflammatory Bowel Disease III: Crohn's Disease
Inflammatory Bowel Disease I: Introduction
Inflammatory Bowel Disease II: Ulcerative Colitis
Inflammatory Bowel Disease IV: Clinical Manifestations