Biology subjects

Marvel, J.

Publications and source records attributed to Marvel, J..

4 recordsLinked to original sources

bioRxiv2024

Memory-Phenotype Ly49+ CD8 T emerging from the thymus develop into two subsets with distinct immune functions

Ly49+ CD8 T cells are memory-phenotype (MP) cells expressing Ly49 family inhibitory receptors, that control autoimmune diseases development through the regulation of follicular CD4 T cells. During viral infection, their number increases, suggesting an involvement in antiviral responses. These cells do not derive from naive cells and are thought to develop in the thymus. This study identified two subsets of Ly49+ CD8 T cells, based on CD8{beta} expression, in mice and humans. Lineage tracing and reliance on the transcription factor Zeb1 indicate a thymic origin via agonist selection. scRNAseq analysis revealed that a small fraction of CD8{beta}-Ly49+ cells acquired an effector profile during vaccinia virus infection. Moreover, the majority of Ly49+ CD8 T cells seems to respond to cytokine-driven bystander signals. In vitro, these signals promoted the expression of effector molecules such as IFN{gamma} and granzyme B, as well as the homing chemokine receptor CXCR5, potentially driving their recruitment to germinal centers. SummaryThis study shows that Ly49+ CD8 T cells comprises two subsets that develop in the thymus through agonist selection. In viral infection, both subsets respond to bystander stimuli that could drive their regulatory activity. Furthermore, some CD8{beta}-expressing Ly49+ cells exert TCR-mediated antiviral response.

immunology↗

bioRxiv2022

CD8 memory precursor cells generation is a continuous process

In this work, we studied the generation of memory precursor cells following an acute infection by analyzing single-cell RNA-seq data that contained CD8 T cells collected during the postinfection expansion phase. We used different tools to reconstruct the developmental trajectory that CD8 T cells followed after activation. Cells that exhibited a memory precursor signature were identified and positioned on this trajectory. We found that memory precursors are generated continuously with increasing numbers being generated over time. Similarly, expression of genes associated with effector functions was also found to be raised in memory precursors at later time points. The ability of cells to enter quiescence to differentiate into memory cells was confirmed by BrdU pulse-chase experiment in vivo. Analysis of cell counts indicates that the vast majority of memory cells are generated at later time points from cells that have extensively divided.

immunology↗

bioRxiv2019

Investigation of Inter-Individual Variability in CD8 T Cell Responses with Nonlinear Mixed Effects Models

To develop vaccines it is mandatory yet challenging to account for inter-individual variability during immune responses. Even in laboratory mice, T cell responses of single individuals exhibit a high heterogeneity that may come from genetic backgrounds, intra-specific processes (e.g. antigen-processing and presentation) and immunization protocols. To account for inter-individual variability in CD8 T cell responses in mice, we propose a dynamical model coupled to a statistical, nonlinear mixed effects model. Average and individual dynamics during a CD8 T cell response are characterized in different immunization contexts (vaccinia virus and tumor). On one hand, we identify biological processes that generate inter-individual variability (activation rate of naive cells, the mortality rate of effector cells, and dynamics of the immunogen). On the other hand, introducing categorical covariates to analyze two different immunization regimens, we highlight the steps of the response impacted by immunogens (priming, differentiation of naive cells, expansion of effector cells and generation of memory cells). The robustness of the model is assessed by confrontation to new experimental data. Our approach allows to investigate immune responses in various immunization contexts, when measurements are scarce or missing, and contributes to a better understanding of inter-individual variability in CD8 T cell immune responses.

immunology↗

bioRxiv2018

Model-based assessment of the Role of Uneven Partitioning of Molecular Content on Heterogeneity and Regulation of Differentiation in CD8 T-cell Immune Responses

Activation of naive CD8 T-cells can lead to the generation of multiple effector and memory subsets. Multiple parameters associated with activation conditions are involved in generating this diversity that is associated with heterogeneous molecular contents of activated cells. Naive cell polarisation upon antigenic stimulation and the asymmetric division that results are known to be a major source of heterogeneity and cell fate regulation. The consequences of stochastic uneven partitioning of molecular content upon subsequent divisions remain unclear. Here we aim at studying the impact of uneven partitioning on molecular-content heterogeneity and then on the immune response dynamics at the cellular level. To do so, we introduce a multiscale mathematical model of the CD8 T-cell immune response in the lymph node. In the model, cells are described as agents evolving and interacting in a 2D environment while a set of differential equations, embedded in each cell, models the regulation of intra and extracellular proteins involved in cell differentiation. Based on the analysis of in silico data at the single cell level, we show that immune response dynamics can be explained by the molecular-content heterogeneity generated by uneven partitioning at cell division. In particular, uneven partitioning acts as a regulator of cell differentiation and induces the emergence of two coexisting subpopulations of cells exhibiting antagonistic fates. We show that the degree of unevenness of molecular partitioning, along all cell divisions, affects the outcome of the immune response and can promote the generation of memory cells.

immunology↗