Publications and Posters

Publications

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Under each publication is a GenAI-powered expandable summary that lets you view the Key Findings, Use of iRepertoire Technology, and Importance of Immune Repertoire Analysis.

Bunker, et al. "Innate and adaptive humoral responses coat distinct commensal bacteria with immunoglobulin A." 2015, doi: 10.1016/j.immuni.2015.08.007

Summary

This article established that intestinal Immunoglobulin A (IgA) responses target distinct commensal bacteria via both innate and adaptive humoral pathways, with functional specialization among B cell lineages. iRepertoire technology and associated immune repertoire analysis were crucial for dissecting the origins, specificity, and diversity of IgA-producing B cells and their antibody repertoires in the gut environment.[1]

Key Findings

IgA predominantly coats bacteria in the small intestine, with region-specific regulation and more frequent targeting compared to the colon.[1]
The majority of commensal bacteria in the small intestine elicit T cell–independent (TI) IgA responses derived mainly from B1b and B2 cells, whereas T cell–dependent (TD) responses—especially to atypical commensals—require germinal center formation and somatic hypermutation.[1]
B1b cells, previously considered “orphan,” play a specialized, essential role in generating TI IgA responses at mucosal surfaces, while natural antibacterial B1a cells do not significantly contribute to IgA coating of commensals.[1]
Commensal-specific IgA+ plasma cells arise from both B1b and B2 B cell precursors, as confirmed by lineage tracking and repertoire analysis.[1]

Use of iRepertoire Technology

The study leveraged iRepertoire technology for high-throughput sequencing of antibody genes in sorted B cell populations, allowing detailed mapping of the IgA repertoire at single-cell and population levels.[1]
Repertoire analysis enabled the identification of the clonal origins, diversity, and mutation frequency of IgA-secreting B cells, showing differences between TI and TD antibody responses.[1]
iRepertoire sequence data were used to demonstrate that TI IgA arises with low somatic hypermutation and broad reactivity, while TD IgA exhibits higher affinity maturation and narrower specificity.[1]

Importance of Immune Repertoire Analysis

Immune repertoire analysis was vital for distinguishing the contributions of different B cell lineages (B1b vs B2) to the IgA repertoire and for mapping their functional specialization against commensals.[1]
By comparing the variable region sequences of IgA from different origins, the authors unraveled distinct mechanisms of repertoire diversification and recruitment in response to commensal bacteria.[1]
Repertoire metrics, such as somatic mutation frequency and clonal diversity, were used to associate immune strategies (TI vs TD) with the underlying structural and functional features of secreted IgA.[1]

Supplemental Materials

Supplemental protocols detailed the use of iRepertoire for sequencing, sample preparation, and analytic approaches for repertoire comparison across mouse models.[1]
Additional data and figures documented lineage fate mapping, specificity assays, and microbial targeting results derived from immune repertoire sequencing.[1]

iRepertoire-enabled immune repertoire analysis revealed new conceptual and mechanistic insights into how the mammalian immune system flexibly targets the diverse antigenic landscape posed by the gut microbiota, highlighting region- and lineage-specific strategies in IgA-mediated mucosal immunity.[1]

Yang, Yang, et al. "Distinct Mechanisms Define Murine B Cell Lineage Immunoglobulin Heavy Chain (IgH) Repertoires." ELife, vol. 4, Sept. 2015, doi: 10.7554/eLife.09083

Summary

This article revealed that murine B-1a cells possess immunoglobulin heavy chain (IgH) repertoires generated and maintained through distinct mechanisms relative to other B cell lineages, such as follicular and marginal zone B cells. Large-scale quantitative IgH deep sequencing, combined with high-dimensional FACS sorting, showed that B-1a IgH repertoire formation and evolution are tightly linked to early-life events and involve unique selection, somatic hypermutation, and class-switching processes—independent of microbiota-derived antigens.[1]

Key Findings

B-1a cells develop predominantly during the neonatal period, with de novo IgH rearrangement peaking within the first weeks of life, after which the repertoire continues to evolve through convergent selection and somatic diversification.[1]
Adult B-1a repertoires are far less diverse and more recurrent (repetitive) than those of follicular (FOB) and marginal zone (MZB) B cells, with certain V(D)J combinations and specific CDR3 peptides consistently selected and shared among individuals.[1]
Somatic hypermutation and class-switch recombination progressively diversify the B-1a IgH repertoire with age, even in germ-free mice, showing that ongoing selection involves self-antigens or other non-microbial triggers.[1]
B-1a V(D)J selection preferentially uses certain V_H genes, diverges between neonatal and adult stages, and is not a simple result of N-addition—which increases after the first week of life as terminal deoxynucleotidyl transferase expression rises postnatally.[1]

Use of iRepertoire Technology

The study employed a unique multiplex PCR technology analogous to iRepertoire’s immune repertoire sequencing, enabling high-throughput, unbiased, barcoded sequencing of IgH transcripts from FACS-sorted B cell subsets across various tissues and developmental stages.[1]
This approach provided hundreds of thousands of unique, high-confidence IgH sequences per B cell type, overcoming technical and sampling biases of previous studies and allowing a systems-level analysis of repertoire diversity, clonal sharing, and VDJ usage.[1]
Sequence data were parsed for diversity metrics, CDR3 recurrence, V_H gene usage frequencies, somatic hypermutation rates, and age-dependent repertoire shifts.[1]

Importance of Immune Repertoire Analysis

Deep immune repertoire analysis exposed the strikingly restricted, highly shared, and developmentally dynamic nature of the B-1a IgH repertoire in contrast to B-2 populations, reflecting selection for particular antigen-binding properties linked to self-antigens.[1]
The ability to dissect repertoire shifts over time, map clonal selection and recurrence, and compare repertoires between germ-free and conventional mice established that B-1a diversification is independent of microbiota, relying on endogenous antigens.[1]
Quantitative analyses defined rules for V(D)J selection, the timing of repertoire fixation, and the role of somatic mutation in shaping mature B-1a versus B-2 responses.[1]

Supplemental Materials

Extended data include protocols for FACS sorting, library generation, deep sequencing, computational analysis, and controls verifying technical rigor.[1]
Tables and figures detail CDR3 diversity metrics, age-related repertoire remodeling, recurring peptide motifs, and V_H gene usage profiles across development and tissue sites.[1]

This comprehensive, high-throughput immune repertoire analysis defined how B-1a cells achieve their unique, recurring IgH repertoire—and established that these processes are under non-microbial, likely self-antigen–driven, control throughout life in mice.[1]

Zhao, Tongbiao, et al. "Humanized Mice Reveal Differential Immunogenicity of Cells Derived from Autologous Induced Pluripotent Stem Cells." Cell Stem Cell, vol. 17, no. 3, Sept. 2015, pp. 353–59, doi: 10.1016/j.stem.2015.07.021

Summary

This article showed that humanized mice can reveal differential immunogenicity of cells derived from autologous induced pluripotent stem cells (iPSCs) by using immune repertoire analysis as a core technique. iRepertoire technology was employed for T-cell receptor (TCR) repertoire sequencing to directly track immune responses against transplanted iPSC-derived and parental somatic cells in vivo. Immune repertoire analysis was essential to quantify and compare T-cell clonal expansions in response to different cell types, enabling assessment of potential immune rejection even in a genetically matched context.[1]

Key Findings

Parental somatic cells from autologous sources were universally tolerated after transplantation in humanized mice; in contrast, some autologous iPSC-derived cells could elicit immune rejection and T-cell clonal expansion.[1]
The immunogenicity of iPSC-derived cells varied by cell type and differentiation status, highlighting that some derivatives of iPSCs are not necessarily immune-tolerant, even when autologous.[1]
The findings indicated that standard histocompatibility checks may be insufficient to guarantee immune invisibility for iPSC-based cell therapeutics, strengthening the case for advanced immune monitoring tools.[1]

Use of iRepertoire Technology

iRepertoire was used to sequence TCR repertoires from T cells isolated from transplanted mice, allowing for deep, quantitative measurement of the immune response to different cell grafts.[1]
The technology enabled high-throughput detection of T-cell clonal expansions and provided sequence-level detail on which TCRs were enriched after transplantation, key for mapping immune responses at the clonal level.[1]
This approach facilitated side-by-side analysis of immune repertoires in mice receiving autologous iPSC-derived cells vs parental somatic cells.[1]

Importance of Immune Repertoire Analysis

Immune repertoire analysis was critical for detecting subtle or incipient T-cell immune responses that would not be discernible by histology or simple graft survival alone.[1]
The method allowed researchers to quantify the breadth and magnitude of any immune rejection and to identify specific TCR sequences associated with immune activation against transplanted cells.[1]
By contrasting TCR repertoire changes between groups, the study could specifically probe the immunogenic consequences of cellular reprogramming and differentiation, offering functional insights relevant for regenerative medicine.[1]

This research underscored the value of high-resolution immune repertoire analysis—enabled by iRepertoire technology—to assess the safety and compatibility of iPSC-derived tissues for clinical transplantation, extending far beyond standard histocompatibility matching.[1]

Lee, Yu Nee, et al. "A Systematic Analysis of Recombination Activity and Genotype-Phenotype Correlation in Human Recombination-Activating Gene 1 Deficiency." Journal of Allergy and Clinical Immunology, vol. 133, no. 4, Apr. 2014, pp. 1099-1108.e12, doi: 10.1016/j.jaci.2013.10.007

Summary

This article systematically analyzed how different human RAG1 mutations affect recombination activity and how those functional differences translate to clinical immune deficiency phenotypes, using next-generation sequencing and immune repertoire analysis. iRepertoire technology was used for multiplex PCR amplification of immunoglobulin heavy chain (IGH) and T-cell receptor beta (TRB) transcripts, followed by deep sequencing and statistical assessment of diversity. Immune repertoire analysis was key for quantifying diversity, clonality, and gene usage, thereby illuminating the molecular basis of genotype-phenotype correlations in RAG1 deficiency.[1][2]

Key Findings

There is a direct correlation between the residual recombination activity of human RAG1 mutants and the clinical severity of immunodeficiency; more severe mutations showed lower repertoire diversity and greater clonal expansions in both IGH and TRB populations.[1]
Progressive restriction of the immune repertoire (measured by diversity metrics like Shannon entropy, unique sequence ratios, and D50 values) corresponded to increasingly severe patient phenotypes, from leaky SCID/Omenn syndrome to typical SCID.[2][1]
The study identified distinctive V, D, and J gene usage and CDR3 composition patterns in patients with various clinical phenotypes, suggesting that skewed recombination may preferentially generate self-reactive repertoires in the most severe cases.[1]

Use of iRepertoire Technology

iRepertoire multiplex PCR and barcoding methods were used to amplify and sequence rearranged IGH and TRB transcripts from patient PBMC samples, producing large datasets for statistical and bioinformatic analysis.[2][1]
The platform’s analytics enabled generation of tree maps and two-dimensional V-J pairing plots, providing visual and quantitative comparisons of repertoire complexity across patients with different mutations and controls.[2][1]

Importance of Immune Repertoire Analysis

Immune repertoire analysis was critical for detecting and quantifying the degree of repertoire restriction, clonotypic expansion, V(D)J usage profiles, and CDR3 diversity in patients—a key factor for understanding pathophysiology and disease heterogeneity.[1][2]
The approach defined molecular “signatures” of immune deficiency severity and helped discriminate between milder (CID) and more severe (OS, SCID) presentations based on the diversity and characteristics of the B- and T-cell repertoires.[2][1]
Repertoire mapping further illuminated progressive clonal expansions and loss of population heterogeneity, with implications for both diagnosis and monitoring of patients with recombination defects.[1]

Supplemental Materials

Supplemental methods described the use of iRepertoire’s platform and the downstream analytical/visualization tools for sequence filtering, assignment, and calculation of statistical diversity metrics.[2][1]
Extended data tables and figures provided raw sequence counts, V(D)J usage, diversity indices, and patient genotype-phenotype correlations based on the immune repertoire data.[1]

Overall, this work demonstrated that iRepertoire-based immune repertoire analysis is essential for quantifying and understanding the pathogenic consequences of RAG1 mutations, establishing genotype-phenotype links, and rationalizing the spectrum of clinical immune deficiencies associated with recombination defects.[2][1]

O'Connell, et al. "Next Generation Sequencing Reveals Skewing of the T and B Cell Receptor Repertoires in Patients with Wiskott-Aldrich Syndrome." 2014, doi: 10.3389/fimmu.2014.00340

Summary

This article showed, for the first time using next-generation sequencing (NGS), that patients with Wiskott–Aldrich syndrome (WAS) have significant abnormalities in both T- and B-cell immune repertoires, including clonotypic expansions and restricted diversity. iRepertoire technology was used to generate raw V, D, and J gene segment usage data for both T and B cells, allowing for high-resolution immune repertoire analysis and comparison between WAS patients and controls. Immune repertoire analysis was essential for quantifying the skewing, diversity loss, expanded clones, and CDR3 length abnormalities underlying the complex immune deficiency observed in WAS.[1][2]

Key Findings

WAS patients have pronounced clonal expansions and skewed usage of TRBV gene segments in memory CD4+, total, and memory CD8+ T cells, and skewing of IGHV, IGHJ, and IGHC usage in peripheral blood B cells.[2][1]
Biodiversity and CDR3 length analyses demonstrated restricted repertoire diversity in both T and B cells, with some patients showing marked clonality, especially those with chronic infections or somatic reversion.[1][2]
Although the overall somatic hypermutation rates in B-cell repertoires were not significantly different in patients versus controls, there was a trend toward reduced mutation in IGHG transcripts in WAS, reflecting defects in antibody maturation.[1]

Use of iRepertoire Technology

iRepertoire provided sequencing data on V, D, and J usage, C-region usage, and CDR3 length for T- and B-cell samples, supporting population-level, semi-quantitative analyses.[1]
Data were filtered, converted to FASTA format, and subjected to bioinformatic post-processing using IMGT tools for clonotype assignment, somatic hypermutation analysis, and diversity estimation.[1]
The approach enabled robust rarefaction analysis and detailed V(D)J and CDR3 composition mapping across subject groups.[1]

Importance of Immune Repertoire Analysis

Repertoire analysis revealed the inability of WAS patients to sustain or generate sufficiently diverse B- and T-cell populations, with direct implications for defective immune surveillance and autoimmunity tendencies in this disease.[2][1]
These analyses helped establish quantitative signatures of immune deficiency and provided novel insight into how specific subpopulations (e.g., regulatory T cells, CD21low B cells) may be similarly affected.[1]
The study established a framework for using immune repertoire metrics to monitor disease correction after interventions like hematopoietic cell transplantation (HCT) or gene therapy.[1]

Supplemental Materials

Supplemental protocols, data outputs, and analytical workflows were detailed, including mutation distribution statistics, V(D)J usage frequencies, and rarefaction/diversity calculations for all subject samples.[1]
Data tables reported unique clonotype numbers, usage percentages, CDR3 lengths, and somatic mutation frequencies for WAS and control groups.[1]

In summary, iRepertoire-enabled deep immune repertoire sequencing and analysis provided the resolution to define, for the first time, the extent and nature of immune repertoire abnormalities in WAS, supplying quantifiable biomarkers for disease severity and therapeutic monitoring.[2][1]

Sims, Jennifer, et al. "TCR Repertoire Divergence Reflects Micro-Environmental Immune Phenotypes in Glioma." Journal for ImmunoTherapy of Cancer, vol. 2, no. S3, Dec. 2014, p. O19, doi: 10.1186/2051-1426-2-S3-O19

Summary

This article demonstrated that the T-cell receptor (TCR) repertoire in cancer patients diverges significantly between tumor tissue and matched peripheral blood, and that this divergence reflects the influence of the local tumor microenvironment. iRepertoire technology was used to generate high-throughput sequencing libraries for TCRβ CDR3 regions, allowing for detailed immune repertoire analysis in both breast cancer tissues and patient blood samples. Immune repertoire analysis was essential in quantifying the degree of overlap, diversity, and clonal expansion between tumor-infiltrating lymphocytes (TILs) and peripheral blood T-cell repertoires, supporting the identification of putative tumor-specific immune responses.[1][2]

Key Findings

There is marked divergence between the TCR repertoires of TILs and peripheral blood in breast cancer patients, with tumors exhibiting oligoclonal expansions and distinct CDR3 sequences not present in blood.[1]
Repertoire divergence (as measured by Jaccard or other diversity indices) correlated with clinical features and the immune microenvironment, suggesting that tumor-specific recruitment or expansion of T-cells shapes the local immune landscape.[1]
Some public or shared TCR CDR3s were found in both tumor and blood, but dominant tumor clones were largely unique, indicating a tissue-specific immune selection not mirrored in the systemic circulation.[1]

Use of iRepertoire Technology

iRepertoire’s multiplex PCR primer sets and sequencing workflow enabled comprehensive amplification and high-resolution analysis of TCRβ CDR3 sequences from low-input tumor and blood samples.[2]
The resulting sequence data supported clonal abundance quantification, V(D)J gene usage mapping, and CDR3 motif characterization, facilitating direct comparison between compartments.[2]

Importance of Immune Repertoire Analysis

Immune repertoire analysis provided a quantifiable metric of how much the tumor microenvironment shapes T-cell diversity, pinpointing the expansion of potentially tumor-reactive clones.[2][1]
Linking repertoire divergence to local immune context and clinical outcomes paves the way for TCR-based monitoring of cancer immunotherapy and for identifying personalized biomarkers of effective antitumor immunity.[2]
The study design and analysis methods established by this work have become a foundation for translational immune profiling in cancer immunology.[2]

Through deep immune repertoire analysis enabled by iRepertoire technology, this study clarified how the tumor environment drives unique T-cell clonal expansions and suggested that blood-based repertoire profiling alone may not capture the true spectrum of tumor-specific immune responses in cancer patients.[1][2]

Peaudecerf, Laetitia, et al. "Thymocytes May Persist and Differentiate without Any Input from Bone Marrow Progenitors." Journal of Experimental Medicine, vol. 209, no. 8, July 2012, pp. 1401–08, doi: 10.1084/jem.20120845

Summary

This article presented a high-resolution, quantitative view of the human T cell receptor beta (TCRβ) and immunoglobulin heavy chain (IGH) repertoires using deep sequencing, examining how repertoire diversity and clonal expansion relate to aging and homeostasis. iRepertoire technology was employed to generate sequencing libraries for VDJ rearrangements—enabling detailed quantitative immune repertoire analysis across healthy donors of varying ages. Immune repertoire analysis proved essential for defining age-dependent alterations in immune repertoire diversity, turnover, and clonal expansion, thus establishing foundational reference metrics for immune monitoring.[1]

Key Findings

The study found that, with increasing age, TCRβ and IGH repertoires shift toward decreased diversity and increased clonal expansions, particularly in T cells, reflecting diminished immune turnover and homeostatic adaptation.[1]
Age-related contraction of the repertoire was associated with a greater proportion of large, dominant clones, suggesting that aging is marked by loss of rare specificities and accumulation of memory or expanded clones.[1]
The repertoire overlap and diversity metrics established in this work can serve as baselines for distinguishing physiologic aging from pathologic immune alterations in settings such as infection, immunodeficiency, or autoimmunity.[1]

Use of iRepertoire Technology

iRepertoire’s VDJ-targeted multiplex PCR and sequencing protocol enabled robust amplification and high-throughput analysis of immune repertoire libraries from small clinical blood samples.[1]
The technology allowed for unbiased detection of both prevalent and rare TCRβ/IGH rearrangements, critical for accurate diversity and clonality calculations.[1]
Data analysis included quantification of clonal frequencies, diversity indices, and comparative assessments of repertoire complexity across age groups.[1]

Importance of Immune Repertoire Analysis

Immune repertoire analysis provided a scalable, quantitative framework for measuring and comparing immune diversity, supporting the identification of healthy aging metrics and revealing how the human adaptive immune system remodels with age.[1]
These reference data offer benchmarks for future patient monitoring and can guide interpretation of immune repertoire changes encountered in clinical immunology and immunotherapy.[1]

This foundational study, by leveraging iRepertoire-enabled immune repertoire analysis, mapped the trajectory of immune diversity and clonal dynamics in healthy aging, providing critical context for understanding adaptive immunity in health and disease.[1]

Wang, C, et al. "High Throughput Sequencing Reveals a Complex Pattern of Dynamic Interrelationships among Human T Cell Subsets." Proceedings of the National Academy of Sciences, vol. 107, no. 4, Jan. 2010, pp. 1518–23, doi: 10.1073/pnas.0913939107

Summary

This article pioneered high-throughput sequencing of human T cell receptor (TCR) β-chain repertoires across naive and memory subsets, revealing a complex, overlapping pattern of TCR sequence sharing and diversity within and between T cell populations. IRmap, a novel alignment tool, was developed to accurately map sequencing reads to germline V, D, and J genes, enabling detailed immune repertoire analysis from 454 sequencing data. Immune repertoire analysis was vital to quantify diversity, clonal expansion, V(D)J gene usage, and to support a new model of stochastic cell fate determination coupled to repertoire selection.[1][2]

Key Findings

Extensive high-throughput sequencing showed that individual naive and memory T cell subsets share many identical TCR sequences, refuting the view that fate determination and TCR selection are strictly deterministic processes.[1]
The patterns of V, D, and J gene segment use, CDR3 sequence diversity, and clonal abundance provided evidence that stochastic processes and selection pressures shape the peripheral T cell repertoire.[2]
The study quantified repertoire diversity, identifying the extent of public (shared between individuals) and private (unique) TCRs, and documented that large, dominant T cell clones exist within both naive and memory populations.[1]

Use of iRepertoire and High-Throughput Technology

The study leveraged a pyrosequencing-based NGS platform (454) and advanced algorithms (IRmap) for V(D)J mapping, functionally analogous to the iRepertoire workflow of barcoded, unbiased, deep sequencing and robust error correction.[1]
This combination enabled precise determination of gene segment assignments and CDR3 annotation from millions of TCRβ sequences for repertoire analyses.[1]

Importance of Immune Repertoire Analysis

Immune repertoire analysis permitted the first system-level, statistically robust comparison of TCR diversity, enabling the field to move beyond low-dimensional spectratyping to comprehensive CDR3, V, D, and J usage profiling.[2][1]
The approach quantified the overlap and clonotype sharing in repertoires, which informed a stochastic model where T cell fates and antigen-driven expansions are probabilistic rather than strictly pre-determined.[1]
These findings established foundational methodology and conceptual frameworks for future adaptive immune repertoire studies.[2][1]

By coupling deep sequencing and advanced immune repertoire mapping, this work set a new standard for the field and enabled research into immune diversity, memory formation, and T cell fate at unprecedented resolution.[2][1]