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Review
. 2024 May 13;3(1):kyae006.
doi: 10.1093/discim/kyae006. eCollection 2024.

Spectrum of Treg and self-reactive T cells: single cell perspectives from old friend HTLV-1

Masahiro Ono  1   2 , Yorifumi Satou  2
Affiliations
Review

Spectrum of Treg and self-reactive T cells: single cell perspectives from old friend HTLV-1

Masahiro Ono et al. Discov Immunol. .

Abstract

Despite extensive regulatory T cell (Treg) research, fundamental questions on in vivo dynamics remain to be answered. The current study aims to dissect several interwoven concepts in Treg biology, highlighting the 'self-reactivity' of Treg and their counterparts, namely naturally-arising memory-phenotype T-cells, as a key mechanism to be exploited by a human retroviral infection. We propose the novel key concept, Periodic T cell receptor (TCR)-signalled T-cells, capturing self-reactivity in a quantifiable manner using the Nr4a3-Timer-of-cell-kinetics-and-activity (Tocky) technology. Periodic and brief TCR signals in self-reactive T-cells contrast with acute TCR signals during inflammation. Thus, we propose a new two-axis model for T-cell activation by the two types of TCR signals or antigen recognition, elucidating how Foxp3 expression and acute TCR signals actively regulate Periodic TCR-signalled T-cells. Next, we highlight an underappreciated branch of immunological research on Human T-cell Leukemia Virus type 1 (HTLV-1) that precedes Treg studies, illuminating the missing link between the viral infection, CD25, and Foxp3. Based on evidence by single-cell analysis, we show how the viral infection exploits the regulatory mechanisms for T-cell activation and suggests a potential role of periodic TCR signalling in infection and malignant transformation. In conclusion, the new perspectives and models in this study provide a working framework for investigating Treg within the self-reactive T-cell spectrum, expected to advance understanding of HTLV-1 infection, cancer, and immunotherapy strategies for these conditions.

Keywords: Foxp3; HTLV-1; Nr4a3; T cell receptor signalling; Tocky; memory-phenotype T-cells; regulatory T-cells; self-reactive T-cells.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Graphical Abstract
Graphical Abstract
Figure 1:
Figure 1:
the Tocky system for analysing T-cell dynamics. (A) A schematic figure for Fluorescent Timer reporter mice (Tocky mice). Nr4a3-Tocky allows analysis of T-cell dynamics following TCR signals and Foxp3-Tocky enables investigation of Treg dynamics. The maturation half-life of immature blue and BFP-like fluorescence is 4 h and the protein half-life of the mature mCherry-type red protein is 120 h. (B) The Tocky locus approach and trigonometric transformation of Timer fluorescence data. Timer expression is converted into Timer Angle and Timer Intensity. The first half of Timer Angle (0˚–45˚) shows the temporal sequence of events following new transcription, while the second half (45˚– 90˚) represents transcriptional frequency, with values nearing 45° indicating the highest frequency
Figure 2:
Figure 2:
analysis of self-reactivity in CD4 + T-cells using Nr4a3-Tocky. (A) Flow cytometric analysis showing timer blue and red fluorescence across three CD4+ T-cell subsets from Nr4a3-Tocky mouse lymph nodes: CD44low CD25− Foxp3− CD4+ T-cells (Foxp3− Naïve), Foxp3+ Treg, and CD44high CD25− Foxp3− CD4+ memory-phenotype T-cells (Foxp3− memory). (B–C) Graphical representation of (B) the percentage of Timer-positive cells in CD4 + T-cells and (C) the proportion of cells in the Arrested locus among those Timer-positive CD4 + T-cells. The medians, along with the first and third interquartile ranges, are depicted by the bars. Sample size (N) = 7. Data were originally reported in [5]
Figure 3:
Figure 3:
the two axes activation model for T-cell activation dynamics. This model introduces two dimensions of T-cell activation via T-cell receptor (TCR) signals: Acute and Periodic TCR signals, for CD4+ T cells, including naïve, memory-phenotype, and regulatory T cells (Treg). (1) Acute TCR signals: characterized by acute TCR signals accompanied by co-stimulation through CD28, facilitated by intense interactions with antigen-presenting cells (APCs), typically occurring during inflammation. These signals can activate all three T-cell populations, which are then identified as activated CD4 + T cells, activated effector T cells, and activated Treg (or effector Treg). (2) Periodic TCR signals: ‘self-reactive’ T cells, including Treg and naturally arising memory-phenotype T cells, periodically receive TCR signals through their ‘self-reactive’ TCRs, potentially recognizing self-antigens and innocuous antigens, such as those from microbiota. The interactions between T cells and APCs that induce periodic TCR signals are typically brief and transient. Note that some memory-phenotype T cells may initiate new Foxp3 expression and are then identified as Treg, while some Treg may lose Foxp3 expression and are then identified as memory-phenotype T cells
Figure 4:
Figure 4:
activation mechanisms in self-reactive CD4 + T-cells as potential targets of HTLV-1. CD4+ T-cells from both HTLV-1 infected individuals and healthy donors were analysed using single-cell RNA-seq. (A) Violin plots displaying activation signatures of single cells, analysed by canonical correspondence analysis (CCA) for T-cell activation (upper) and regulatory T-cell characteristics (Treg). HD denotes healthy donors, AC stands for asymptomatic carriers, and SML represents smouldering acute T-cell leukemia (ATL). (B) The cell distributions of the three categories, normal, HTLV-1 carrier (AC), and infected ATL, are shown along the trajectory for the progression of HTLV-1 infection and ATL leukemogenesis (pseudotime, upper). The lower panel shows a schematic representation of the dynamics of the CCA T-cell activation signature across the normal and infected individuals. Note that the activation dynamics across T-cells in normal individuals ("Normal T cell activation and Treg differentiation") are overlapped and followed by those in HTLV-1 infected individuals ("HTLV-1 induced excessive activation"), based on CCA activation analysis. This demonstrates that the excessive activation in HTLV-1 infected individuals can be extrapolated by the normal activation progression. The original data are presented in [51].
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References

    1. Sakaguchi S, Yamaguchi T, Nomura T, Ono M.. Regulatory T cells and immune tolerance. Cell 2008, 133, 775–87. doi:10.1016/j.cell.2008.05.009 - DOI - PubMed
    1. Josefowicz SZ, Lu LF, Rudensky AY.. Regulatory T cells: mechanisms of differentiation and function. Annu Rev Immunol 2012, 30, 531–64. doi:10.1146/annurev.immunol.25.022106.141623 - DOI - PMC - PubMed
    1. Caton AJ, Weissler KA.. Regulatory cells in health and disease. Immunol Rev 2014, 259, 5–10. doi:10.1111/imr.12178 - DOI - PMC - PubMed
    1. Klein L, Kyewski B, Allen PM, Hogquist KA.. Positive and negative selection of the T cell repertoire: what thymocytes see (and don’t see). Nat Rev Immunol 2014, 14, 377–91. doi:10.1038/nri3667 - DOI - PMC - PubMed
    1. Bending D, Martín PP, Paduraru A, Ducker C, Marzaganov E, Laviron M, et al.. A timer for analyzing temporally dynamic changes in transcription during differentiation in vivo. J Cell Biol 2018, 217, 2931–50. doi:10.1083/jcb.201711048 - DOI - PMC - PubMed

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