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Van Eyndhoven LC, Chouri E, Matos CI, Pandit A, Radstake TRDJ, Broen JCA, Singh A, Tel J. Unraveling IFN-I response dynamics and TNF crosstalk in the pathophysiology of systemic lupus erythematosus. Front Immunol 2024; 15:1322814. [PMID: 38596672 PMCID: PMC11002168 DOI: 10.3389/fimmu.2024.1322814] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
Introduction The innate immune system serves the crucial first line of defense against a wide variety of potential threats, during which the production of pro-inflammatory cytokines IFN-I and TNFα are key. This astonishing power to fight invaders, however, comes at the cost of risking IFN-I-related pathologies, such as observed during autoimmune diseases, during which IFN-I and TNFα response dynamics are dysregulated. Therefore, these response dynamics must be tightly regulated, and precisely matched with the potential threat. This regulation is currently far from understood. Methods Using droplet-based microfluidics and ODE modeling, we studied the fundamentals of single-cell decision-making upon TLR signaling in human primary immune cells (n = 23). Next, using biologicals used for treating autoimmune diseases [i.e., anti-TNFα, and JAK inhibitors], we unraveled the crosstalk between IFN-I and TNFα signaling dynamics. Finally, we studied primary immune cells isolated from SLE patients (n = 8) to provide insights into SLE pathophysiology. Results single-cell IFN-I and TNFα response dynamics display remarkable differences, yet both being highly heterogeneous. Blocking TNFα signaling increases the percentage of IFN-I-producing cells, while blocking IFN-I signaling decreases the percentage of TNFα-producing cells. Single-cell decision-making in SLE patients is dysregulated, pointing towards a dysregulated crosstalk between IFN-I and TNFα response dynamics. Discussion We provide a solid droplet-based microfluidic platform to study inherent immune secretory behaviors, substantiated by ODE modeling, which can challenge the conceptualization within and between different immune signaling systems. These insights will build towards an improved fundamental understanding on single-cell decision-making in health and disease.
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Affiliation(s)
- Laura C. Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Eleni Chouri
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Catarina I. Matos
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Aridaman Pandit
- Center for Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Timothy R. D. J. Radstake
- Center for Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Jasper C. A. Broen
- Regional Rheumatology Center, Máxima Medical Center, Eindhoven and Veldhoven, Eindhoven, Netherlands
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, United States
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
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Schrom E, Kinzig A, Forrest S, Graham AL, Levin SA, Bergstrom CT, Castillo-Chavez C, Collins JP, de Boer RJ, Doupé A, Ensafi R, Feldman S, Grenfell BT, Halderman JA, Huijben S, Maley C, Moses M, Perelson AS, Perrings C, Plotkin J, Rexford J, Tiwari M. Challenges in cybersecurity: Lessons from biological defense systems. Math Biosci 2023:109024. [PMID: 37270102 DOI: 10.1016/j.mbs.2023.109024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 04/27/2023] [Accepted: 05/20/2023] [Indexed: 06/05/2023]
Abstract
Defending against novel, repeated, or unpredictable attacks, while avoiding attacks on the 'self', are the central problems of both mammalian immune systems and computer systems. Both systems have been studied in great detail, but with little exchange of information across the different disciplines. Here, we present a conceptual framework for structured comparisons across the fields of biological immunity and cybersecurity, by framing the context of defense, considering different (combinations of) defensive strategies, and evaluating defensive performance. Throughout this paper, we pose open questions for further exploration. We hope to spark the interdisciplinary discovery of general principles of optimal defense, which can be understood and applied in biological immunity, cybersecurity, and other defensive realms.
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Affiliation(s)
- Edward Schrom
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, United States of America
| | - Ann Kinzig
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States of America
| | - Stephanie Forrest
- Biodesign Center for Biocomputation, Security and Society, Arizona State University, Tempe, AZ 85287, United States of America; School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85287, United States of America; Santa Fe Institute, Santa Fe, NM 87501, United States of America
| | - Andrea L Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, United States of America; Santa Fe Institute, Santa Fe, NM 87501, United States of America
| | - Simon A Levin
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, United States of America.
| | - Carl T Bergstrom
- Department of Biology, University of Washington, Seattle, WA 98195, United States of America
| | - Carlos Castillo-Chavez
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, United States of America
| | - James P Collins
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States of America
| | - Rob J de Boer
- Theoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands
| | - Adam Doupé
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85287, United States of America; Center for Cybersecurity and Trusted Foundations, Global Security Initiative, Arizona State University, Tempe, AZ 85287, United States of America
| | - Roya Ensafi
- Department of Electrical Engineering and Computer Science, Computer Science and Engineering Division, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Stuart Feldman
- Schmidt Futures, New York, NY 10011, United States of America
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, United States of America; Princeton School of Public and International Affairs, Princeton University, Princeton, NJ 08544, United States of America
| | - J Alex Halderman
- Department of Electrical Engineering and Computer Science, Computer Science and Engineering Division, University of Michigan, Ann Arbor, MI 48109, United States of America; Center for Computer Security and Society, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Silvie Huijben
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States of America
| | - Carlo Maley
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, United States of America; Biodesign Center for Biocomputation, Security and Society, Arizona State University, Tempe, AZ 85287, United States of America
| | - Melanie Moses
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, United States of America; Department of Biology, University of New Mexico, Albuquerque, NM 87131, United States of America; Santa Fe Institute, Santa Fe, NM 87501, United States of America
| | - Alan S Perelson
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, United States of America; Santa Fe Institute, Santa Fe, NM 87501, United States of America
| | - Charles Perrings
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States of America
| | - Joshua Plotkin
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Jennifer Rexford
- Department of Computer Science, Princeton University, Princeton, NJ 08540, United States of America
| | - Mohit Tiwari
- Department of Electrical and Computer Engineering, University of Texas, Austin, TX 78712, United States of America
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Van Eyndhoven LC, Verberne VPG, Bouten CVC, Singh A, Tel J. Transiently heritable fates and quorum sensing drive early IFN-I response dynamics. eLife 2023; 12:83055. [PMID: 36629318 PMCID: PMC9910831 DOI: 10.7554/elife.83055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 01/10/2023] [Indexed: 01/12/2023] Open
Abstract
Type I interferon (IFN-I)-mediated antiviral responses are central to host defense against viral infections. Crucial is the tight and well-orchestrated control of cellular decision-making leading to the production of IFN-Is. Innovative single-cell approaches revealed that the initiation of IFN-I production is limited to only fractions of 1-3% of the total population, both found in vitro, in vivo, and across cell types, which were thought to be stochastically regulated. To challenge this dogma, we addressed the influence of various stochastic and deterministic host-intrinsic factors on dictating early IFN-I responses, using a murine fibroblast reporter model. Epigenetic drugs influenced the percentage of responding cells. Next, with the classical Luria-Delbrück fluctuation test, we provided evidence for transient heritability driving responder fates, which was verified with mathematical modeling. Finally, while studying varying cell densities, we substantiated an important role for cell density in dictating responsiveness, similar to the phenomenon of quorum sensing. Together, this systems immunology approach opens up new avenues to progress the fundamental understanding on cellular decision-making during early IFN-I responses, which can be translated to other (immune) signaling systems.
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Affiliation(s)
- Laura C Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Vincent PG Verberne
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Carlijn VC Bouten
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
- Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of DelawareNewarkUnited States
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
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Adaptive discrimination between harmful and harmless antigens in the immune system by predictive coding. iScience 2022; 26:105754. [PMID: 36594030 PMCID: PMC9804113 DOI: 10.1016/j.isci.2022.105754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 11/08/2022] [Accepted: 12/04/2022] [Indexed: 12/12/2022] Open
Abstract
The immune system discriminates between harmful and harmless antigens based on past experiences; however, the underlying mechanism is largely unknown. From the viewpoint of machine learning, the learning system predicts the observation and updates the prediction based on prediction error, a process known as "predictive coding." Here, we modeled the population dynamics of T cells by adopting the concept of predictive coding; conventional and regulatory T cells predict the antigen concentration and excessive immune response, respectively. Their prediction error signals, possibly via cytokines, induce their differentiation to memory T cells. Through numerical simulations, we found that the immune system identifies antigen risks depending on the concentration and input rapidness of the antigen. Further, our model reproduced history-dependent discrimination, as in allergy onset and subsequent therapy. Taken together, this study provided a novel framework to improve our understanding of how the immune system adaptively learns the risks of diverse antigens.
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Naoun AA, Raphael I, Forsthuber TG. Immunoregulation via Cell Density and Quorum Sensing-like Mechanisms: An Underexplored Emerging Field with Potential Translational Implications. Cells 2022; 11:cells11152442. [PMID: 35954285 PMCID: PMC9368058 DOI: 10.3390/cells11152442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/27/2022] [Accepted: 08/01/2022] [Indexed: 11/16/2022] Open
Abstract
Quorum sensing (QS) was historically described as a mechanism by which bacteria detect and optimize their population density via gene regulation based on dynamic environmental cues. Recently, it was proposed that QS or similar mechanisms may have broader applications across different species and cell types. Indeed, emerging evidence shows that the mammalian immune system can also elicit coordinated responses on a population level to regulate cell density and function, thus suggesting that QS-like mechanisms may also be a beneficial trait of the immune system. In this review, we explore and discuss potential QS-like mechanisms deployed by the immune system to coordinate cellular-level responses, such as T cell responses mediated via the common gamma chain (γc) receptor cytokines and the aryl hydrocarbon receptors (AhRs). We present evidence regarding a novel role of QS as a multifunctional mechanism coordinating CD4+ and CD8+ T cell behavior during steady state and in response to infection, inflammatory diseases, and cancer. Successful clinical therapies such as adoptive cell transfer for cancer treatment may be re-evaluated to harness the effects of the QS mechanism(s) and enhance treatment responsiveness. Moreover, we discuss how signaling threshold perturbations through QS-like mediators may result in disturbances of the complex crosstalk between immune cell populations, undesired T cell responses, and induction of autoimmune pathology. Finally, we discuss the potential therapeutic role of modulating immune-system-related QS as a promising avenue to treat human diseases.
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Affiliation(s)
- Adrian A. Naoun
- Department of Molecular Microbiology and Immunology, University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Itay Raphael
- Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15217, USA
- Correspondence: (I.R.); (T.G.F.)
| | - Thomas G. Forsthuber
- Department of Molecular Microbiology and Immunology, University of Texas at San Antonio, San Antonio, TX 78249, USA
- Correspondence: (I.R.); (T.G.F.)
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Elkington P, Polak ME, Reichmann MT, Leslie A. Understanding the tuberculosis granuloma: the matrix revolutions. Trends Mol Med 2022; 28:143-154. [PMID: 34922835 PMCID: PMC8673590 DOI: 10.1016/j.molmed.2021.11.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/18/2021] [Accepted: 11/22/2021] [Indexed: 02/06/2023]
Abstract
Mycobacterium tuberculosis (Mtb) causes the human disease tuberculosis (TB) and remains the top global infectious pandemic after coronavirus disease 2019 (COVID-19). Furthermore, TB has killed many more humans than any other pathogen, after prolonged coevolution to optimise its pathogenic strategies. Full understanding of fundamental disease processes in humans is necessary to successfully combat this highly successful pathogen. While the importance of immunodeficiency has been long recognised, biologic therapies and unbiased approaches are providing unprecedented insights into the intricacy of the host-pathogen interaction. The nature of a protective response is more complex than previously hypothesised. Here, we integrate recent evidence from human studies and unbiased approaches to consider how Mtb causes human TB and highlight the recurring theme of extracellular matrix (ECM) turnover.
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Affiliation(s)
- Paul Elkington
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
| | - Marta E Polak
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Michaela T Reichmann
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Alasdair Leslie
- Department of Infection and Immunity, University College London, London, UK; Africa Health Research Institute, KwaZulu-Natal, South Africa
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Germain RN, Radtke AJ, Thakur N, Schrom EC, Hor JL, Ichise H, Arroyo-Mejias AJ, Chu CJ, Grant S. Understanding immunity in a tissue-centric context: Combining novel imaging methods and mathematics to extract new insights into function and dysfunction. Immunol Rev 2021; 306:8-24. [PMID: 34918351 DOI: 10.1111/imr.13052] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/20/2021] [Accepted: 11/24/2021] [Indexed: 02/02/2023]
Abstract
A central question in immunology is what features allow the immune system to respond in a timely manner to a variety of pathogens encountered at unanticipated times and diverse body sites. Two decades of advanced and static dynamic imaging methods have now revealed several major principles facilitating host defense. Suborgan spatial prepositioning of distinct cells promotes time-efficient interactions upon pathogen sensing. Such pre-organization also provides an effective barrier to movement of pathogens from parenchymal tissues into the blood circulation. Various molecular mechanisms maintain effective intercellular communication among otherwise rapidly moving cells. These and related discoveries have benefited from recent increases in the number of parameters that can be measured simultaneously in a single tissue section and the extension of such multiplex analyses to 3D tissue volumes. The application of new computational methods to such imaging data has provided a quantitative, in vivo context for cell trafficking and signaling pathways traditionally explored in vitro or with dissociated cell preparations. Here, we summarize our efforts to devise and employ diverse imaging tools to probe immune system organization and function, concluding with a commentary on future developments, which we believe will reveal even more about how the immune system operates in health and disease.
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Affiliation(s)
- Ronald N Germain
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA.,Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Andrea J Radtke
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA.,Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Nishant Thakur
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA.,Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Edward C Schrom
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Jyh Liang Hor
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Hiroshi Ichise
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Armando J Arroyo-Mejias
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
| | - Colin J Chu
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA.,Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Spencer Grant
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA.,Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, Maryland, USA
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Graham AL, Schrom EC, Metcalf CJE. The evolution of powerful yet perilous immune systems. Trends Immunol 2021; 43:117-131. [PMID: 34949534 PMCID: PMC8686020 DOI: 10.1016/j.it.2021.12.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/03/2021] [Accepted: 12/05/2021] [Indexed: 12/23/2022]
Abstract
The mammalian immune system packs serious punch against infection but can also cause harm: for example, coronavirus disease 2019 (COVID-19) made headline news of the simultaneous power and peril of human immune responses. In principle, natural selection leads to exquisite adaptation and therefore cytokine responsiveness that optimally balances the benefits of defense against its costs (e.g., immunopathology suffered and resources expended). Here, we illustrate how evolutionary biology can predict such optima and also help to explain when/why individuals exhibit apparently maladaptive immunopathological responses. Ultimately, we argue that the evolutionary legacies of multicellularity and life-history strategy, in addition to our coevolution with symbionts and our demographic history, together explain human susceptibility to overzealous, pathology-inducing cytokine responses. Evolutionary insight thereby complements molecular/cellular mechanistic insights into immunopathology.
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Metcalf CJE, Grenfell BT, Graham AL. Disentangling the dynamical underpinnings of differences in SARS-CoV-2 pathology using within-host ecological models. PLoS Pathog 2020; 16:e1009105. [PMID: 33306746 PMCID: PMC7732095 DOI: 10.1371/journal.ppat.1009105] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Health outcomes following infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) are remarkably variable. The way the virus spreads inside hosts, and how this spread interacts with host immunity and physiology, is likely to determine variation in health outcomes. Decades of data and dynamical analyses of how other viruses spread and interact with host cells could shed light on SARS-CoV-2 within-host trajectories. We review how common axes of variation in within-host dynamics and emergent pathology (such as age and sex) might be combined with ecological principles to understand the case of SARS-CoV-2. We highlight pitfalls in application of existing theoretical frameworks relevant to the complexity of the within-host context and frame the discussion in terms of growing knowledge of the biology of SARS-CoV-2. Viewing health outcomes for SARS-CoV-2 through the lens of ecological models underscores the value of repeated measures on individuals, especially since many lines of evidence suggest important contingence on trajectory.
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Affiliation(s)
- C. Jessica E. Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Princeton School of Public and International Affairs, Princeton University, New Jersey, United States of America
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Princeton School of Public and International Affairs, Princeton University, New Jersey, United States of America
| | - Andrea L. Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
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