Half of the T‐cell repertoire combinatorial diversity is genetically determined in humans and humanized mice

Pham, Hang-Phuong; Manuel, Manuarii; Petit, Nicolas; Klatzmann, David; Cohen‐Kaminsky, Sylvia; Six, Adrien; Marodon, Gilles

doi:10.1002/eji.201141798

Cited by 14 publications

(10 citation statements)

References 36 publications

(59 reference statements)

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“…the HLA-background of a host and thymic selection [63]–[65], or the likelyhood of certain VDJ-recombinations [65]–[68]. Even though the T-cell pool might vary in every individual as a result of such influences, we found that T-cells have a preference for certain amino acids (see Supplemental Table S1, the immunogenicity model).…”

Section: Discussionmentioning

confidence: 73%

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

et al. 2013

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T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4–6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.

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Section: Discussionmentioning

confidence: 73%

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

et al. 2013

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“…Marodon et al reported that V-J combination distribution of human T cells is already present before TCR-MHC selection in the thymus of NSG mice [15]. In addition, Pham et al reported a similar distribution of human T cell receptor β chain families in the thymus of NSG mice and in human thymus, suggesting the selection of functional human T cells reconstituted in these mice [45]. In addition, some thymic selection of human T cells occurs on mouse MHC, as evidenced by a slightly increased weak proliferation of human T cells toward mismatched mouse dendritic cells as compared with that toward host ones [8].…”

Section: Discussionmentioning

confidence: 99%

Effective Elicitation of Human Effector CD8+ T Cells in HLA-B*51:01 Transgenic Humanized Mice after Infection with HIV-1

2012

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Humanized mice are expected to be useful as small animal models for in vivo studies on the pathogenesis of infectious diseases. However, it is well known that human CD8+ T cells cannot differentiate into effector cells in immunodeficient mice transplanted with only human CD34+ hematopoietic stem cells (HSCs), because human T cells are not educated by HLA in the mouse thymus. We here established HLA-B*51:01 transgenic humanized mice by transplanting human CD34+ HSCs into HLA-B*51:01 transgenic NOD/SCID/Jak3−/− mice (hNOK/B51Tg mice) and investigated whether human effector CD8+ T cells would be elicited in the mice or in those infected with HIV-1 NL4-3. There were no differences in the frequency of late effector memory and effector subsets (CD27lowCD28−CD45RA+/−CCR7− and CD27−CD28−CD45RA+/−CCR7−, respectively) among human CD8+ T cells and in that of human CD8+ T cells expressing CX3CR1 and/or CXCR1 between hNOK/B51Tg and hNOK mice. In contrast, the frequency of late effector memory and effector CD8+ T cell subsets and of those expressing CX3CR1 and/or CXCR1 was significantly higher in HIV-1-infected hNOK/B51Tg mice than in uninfected ones, whereas there was no difference in that of these subsets between HIV-1-infected and uninfected hNOK mice. These results suggest that hNOK/B51Tg mice had CD8+ T cells that were capable of differentiating into effector T cells after viral antigen stimulation and had a greater ability to elicit effector CD8+ T cells than hNOK ones.

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“…In collaboration with ImmunID, we have proposed a novel strategy for statistical modeling of T lymphocyte repertoire data obtained in humans and humanized mice. With this model, we revealed that half of the human TRB repertoire, in terms of proportion of TRBV-TRBJ combinations, is genetically determined, the other half occurring stochastically (182). In addition, the biotechnology company “Adaptive” and the “Repertoire 10K (R10K) Project” have been recently founded by researchers respectively from the Fred Hutchinson Cancer Research Center (Seattle and Washington) and the HudsonAlpha Institute (Huntsville).…”

Section: Statistical Analysis and Modeling Of Immune Repertoire Datamentioning

confidence: 99%

The Past, Present, and Future of Immune Repertoire Biology – The Rise of Next-Generation Repertoire Analysis

et al. 2013

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T and B cell repertoires are collections of lymphocytes, each characterized by its antigen-specific receptor. We review here classical technologies and analysis strategies developed to assess immunoglobulin (IG) and T cell receptor (TR) repertoire diversity, and describe recent advances in the field. First, we describe the broad range of available methodological tools developed in the past decades, each of which answering different questions and showing complementarity for progressive identification of the level of repertoire alterations: global overview of the diversity by flow cytometry, IG repertoire descriptions at the protein level for the identification of IG reactivities, IG/TR CDR3 spectratyping strategies, and related molecular quantification or dynamics of T/B cell differentiation. Additionally, we introduce the recent technological advances in molecular biology tools allowing deeper analysis of IG/TR diversity by next-generation sequencing (NGS), offering systematic and comprehensive sequencing of IG/TR transcripts in a short amount of time. NGS provides several angles of analysis such as clonotype frequency, CDR3 diversity, CDR3 sequence analysis, V allele identification with a quantitative dimension, therefore requiring high-throughput analysis tools development. In this line, we discuss the recent efforts made for nomenclature standardization and ontology development. We then present the variety of available statistical analysis and modeling approaches developed with regards to the various levels of diversity analysis, and reveal the increasing sophistication of those modeling approaches. To conclude, we provide some examples of recent mathematical modeling strategies and perspectives that illustrate the active rise of a “next-generation” of repertoire analysis.

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Half of the T‐cell repertoire combinatorial diversity is genetically determined in humans and humanized mice

Cited by 14 publications

References 36 publications

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

Effective Elicitation of Human Effector CD8+ T Cells in HLA-B*51:01 Transgenic Humanized Mice after Infection with HIV-1

The Past, Present, and Future of Immune Repertoire Biology – The Rise of Next-Generation Repertoire Analysis

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