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Wang S, Prieux M, de Bernard S, Dubois M, Laubreton D, Djebali S, Zala M, Arpin C, Genestier L, Leverrier Y, Gandrillon O, Crauste F, Jiang W, Marvel J. Exogenous IL-2 delays memory precursors generation and is essential for enhancing memory cells effector functions. iScience 2024; 27:109411. [PMID: 38510150 PMCID: PMC10952031 DOI: 10.1016/j.isci.2024.109411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/27/2023] [Accepted: 02/29/2024] [Indexed: 03/22/2024] Open
Abstract
To investigate the impact of paracrine IL-2 signals on memory precursor (MP) cell differentiation, we activated CD8 T cell in vitro in the presence or absence of exogenous IL-2 (ex-IL-2). We assessed memory differentiation by transferring these cells into virus-infected mice. Both conditions generated CD8 T cells that participate in the ongoing response and gave rise to similar memory cells. Nevertheless, when transferred into a naive host, T cells activated with ex-IL-2 generated a higher frequency of memory cells displaying increased functional memory traits. Single-cell RNA-seq analysis indicated that without ex-IL-2, cells rapidly acquire an MP signature, while in its presence they adopted an effector signature. This was confirmed at the protein level and in a functional assay. Overall, ex-IL-2 delays the transition into MP cells, allowing the acquisition of effector functions that become imprinted in their progeny. These findings may help to optimize the generation of therapeutic T cells.
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Affiliation(s)
- Shaoying Wang
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China
| | - Margaux Prieux
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
- Laboratoire de Biologie et de Modélisation de la Cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
| | | | - Maxence Dubois
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
| | - Daphne Laubreton
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
| | - Sophia Djebali
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
| | - Manon Zala
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
- Faculté de Médecine Lyon-Sud, Université de Lyon, Oullins, France
| | - Christophe Arpin
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
- Laboratoire de Biologie et de Modélisation de la Cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
| | - Laurent Genestier
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
- Faculté de Médecine Lyon-Sud, Université de Lyon, Oullins, France
| | - Yann Leverrier
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
| | - Olivier Gandrillon
- Inria, Villeurbanne, France
- Laboratoire de Biologie et de Modélisation de la Cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
| | - Fabien Crauste
- Laboratoire MAP5 (UMR CNRS 8145), Université Paris Cité, Paris, France
| | - Wenzheng Jiang
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China
| | - Jacqueline Marvel
- Centre International de Recherche en Infectiologie, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Université de Lyon, Lyon, France
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Todorov H, Prieux M, Laubreton D, Bouvier M, Wang S, de Bernard S, Arpin C, Cannoodt R, Saelens W, Bonnaffoux A, Gandrillon O, Crauste F, Saeys Y, Marvel J. CD8 memory precursor cell generation is a continuous process. iScience 2022; 25:104927. [PMID: 36065187 PMCID: PMC9440290 DOI: 10.1016/j.isci.2022.104927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/21/2022] [Accepted: 08/09/2022] [Indexed: 11/30/2022] Open
Abstract
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 these memory precursors are generated continuously with increasing numbers arising 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 and 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. Trajectory inference tools reconstruct the timing of memory precursors generation The trajectory is defined by both cell cycle and effector functions encoding genes Memory precursors numbers in lymphoid organs increase with time after priming In vivo BrdU labeling validate the in silico data
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Affiliation(s)
- Helena Todorov
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Margaux Prieux
- Centre International de recherche en Infectiologie, Université de Lyon, INSERM U1111, CNRS UMR 5308, Ecole Normale Superieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
- Laboratoire de Biologie et de Modélisation de la cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
| | - Daphne Laubreton
- Centre International de recherche en Infectiologie, Université de Lyon, INSERM U1111, CNRS UMR 5308, Ecole Normale Superieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
| | - Matteo Bouvier
- Laboratoire de Biologie et de Modélisation de la cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
- Vidium, Lyon, France
| | - Shaoying Wang
- Centre International de recherche en Infectiologie, Université de Lyon, INSERM U1111, CNRS UMR 5308, Ecole Normale Superieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
| | | | - Christophe Arpin
- Centre International de recherche en Infectiologie, Université de Lyon, INSERM U1111, CNRS UMR 5308, Ecole Normale Superieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
| | - Robrecht Cannoodt
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
- Data Intuitive, Lebbeke, Belgium
| | - Wouter Saelens
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | | | - Olivier Gandrillon
- Laboratoire de Biologie et de Modélisation de la cellule, Université de Lyon, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Lyon, France
- Inria, Villeurbanne, France
| | - Fabien Crauste
- Laboratoire MAP5 (UMR CNRS 8145), Université de Paris, Paris, France
| | - Yvan Saeys
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Jacqueline Marvel
- Centre International de recherche en Infectiologie, Université de Lyon, INSERM U1111, CNRS UMR 5308, Ecole Normale Superieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
- Corresponding author
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