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Abadie K, Clark EC, Valanparambil RM, Ukogu O, Yang W, Daza RM, Ng KKH, Fathima J, Wang AL, Lee J, Nasti TH, Bhandoola A, Nourmohammad A, Ahmed R, Shendure J, Cao J, Kueh HY. Reversible, tunable epigenetic silencing of TCF1 generates flexibility in the T cell memory decision. Immunity 2024; 57:271-286.e13. [PMID: 38301652 PMCID: PMC10922671 DOI: 10.1016/j.immuni.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 10/09/2023] [Accepted: 12/07/2023] [Indexed: 02/03/2024]
Abstract
The immune system encodes information about the severity of a pathogenic threat in the quantity and type of memory cells it forms. This encoding emerges from lymphocyte decisions to maintain or lose self-renewal and memory potential during a challenge. By tracking CD8+ T cells at the single-cell and clonal lineage level using time-resolved transcriptomics, quantitative live imaging, and an acute infection model, we find that T cells will maintain or lose memory potential early after antigen recognition. However, following pathogen clearance, T cells may regain memory potential if initially lost. Mechanistically, this flexibility is implemented by a stochastic cis-epigenetic switch that tunably and reversibly silences the memory regulator, TCF1, in response to stimulation. Mathematical modeling shows how this flexibility allows memory T cell numbers to scale robustly with pathogen virulence and immune response magnitudes. We propose that flexibility and stochasticity in cellular decisions ensure optimal immune responses against diverse threats.
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Affiliation(s)
- Kathleen Abadie
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Elisa C Clark
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Rajesh M Valanparambil
- Emory Vaccine Center and Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Obinna Ukogu
- Department of Applied Mathematics, University of Washington, Seattle, WA 98105, USA
| | - Wei Yang
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Kenneth K H Ng
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Jumana Fathima
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Allan L Wang
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Judong Lee
- Emory Vaccine Center and Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Tahseen H Nasti
- Emory Vaccine Center and Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Avinash Bhandoola
- T-Cell Biology and Development Unit, Laboratory of Genome Integrity, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA
| | - Armita Nourmohammad
- Department of Applied Mathematics, University of Washington, Seattle, WA 98105, USA; Department of Physics, University of Washington, Seattle, WA 98105, USA; Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Rafi Ahmed
- Emory Vaccine Center and Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA; Allen Discovery Center for Cell Lineage Tracing, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98195, USA; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA.
| | - Junyue Cao
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Laboratory of Single-Cell Genomics and Population Dynamics, The Rockefeller University, New York, NY 10065, USA.
| | - Hao Yuan Kueh
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA.
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Permanence via invasion graphs: incorporating community assembly into modern coexistence theory. J Math Biol 2022; 85:54. [PMID: 36255477 PMCID: PMC9579112 DOI: 10.1007/s00285-022-01815-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/30/2022] [Accepted: 09/06/2022] [Indexed: 11/18/2022]
Abstract
To understand the mechanisms underlying species coexistence, ecologists often study invasion growth rates of theoretical and data-driven models. These growth rates correspond to average per-capita growth rates of one species with respect to an ergodic measure supporting other species. In the ecological literature, coexistence often is equated with the invasion growth rates being positive. Intuitively, positive invasion growth rates ensure that species recover from being rare. To provide a mathematically rigorous framework for this approach, we prove theorems that answer two questions: (i) When do the signs of the invasion growth rates determine coexistence? (ii) When signs are sufficient, which invasion growth rates need to be positive? We focus on deterministic models and equate coexistence with permanence, i.e., a global attractor bounded away from extinction. For models satisfying certain technical assumptions, we introduce invasion graphs where vertices correspond to proper subsets of species (communities) supporting an ergodic measure and directed edges correspond to potential transitions between communities due to invasions by missing species. These directed edges are determined by the signs of invasion growth rates. When the invasion graph is acyclic (i.e. there is no sequence of invasions starting and ending at the same community), we show that permanence is determined by the signs of the invasion growth rates. In this case, permanence is characterized by the invasibility of all \documentclass[12pt]{minimal}
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\begin{document}$$-i$$\end{document}-i communities, i.e., communities without species i where all other missing species have negative invasion growth rates. To illustrate the applicability of the results, we show that dissipative Lotka-Volterra models generically satisfy our technical assumptions and computing their invasion graphs reduces to solving systems of linear equations. We also apply our results to models of competing species with pulsed resources or sharing a predator that exhibits switching behavior. Open problems for both deterministic and stochastic models are discussed. Our results highlight the importance of using concepts about community assembly to study coexistence.
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Maini PK, Chaplain MAJ, Lewis MA, Sherratt JA. Special Collection: Celebrating J.D. Murray's Contributions to Mathematical Biology. Bull Math Biol 2021; 84:13. [PMID: 34865189 DOI: 10.1007/s11538-021-00955-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Philip K Maini
- Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.
| | - Mark A J Chaplain
- School of Mathematics and Statistics, Mathematical Institute, University of St Andrews, St Andrews, KY16 9SS, UK
| | - Mark A Lewis
- Department of Mathematical and Statistical Sciences, CAB 545B, University of Alberta, Edmonton, AB, T6G 2G1, Canada
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