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A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses
The initiation of T-cell responses in lymph nodes requires T cells to integrate signals delivered by dendritic cells (DCs) during long-lasting contacts (synapses) or more transient interactions (kinapses). However, it remains extremely challenging to understand how a specific sequence of contacts es...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4980574/ https://www.ncbi.nlm.nih.gov/pubmed/27089942 http://dx.doi.org/10.1038/icb.2016.36 |
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author | Moreau, Hélène D Bogle, Gib Bousso, Philippe |
author_facet | Moreau, Hélène D Bogle, Gib Bousso, Philippe |
author_sort | Moreau, Hélène D |
collection | PubMed |
description | The initiation of T-cell responses in lymph nodes requires T cells to integrate signals delivered by dendritic cells (DCs) during long-lasting contacts (synapses) or more transient interactions (kinapses). However, it remains extremely challenging to understand how a specific sequence of contacts established by T cells ultimately dictates T-cell fate. Here, we have coupled a computational model of T-cell migration and interactions with DCs with a real-time, flow cytometry-like representation of T-cell activation. In this model, low-affinity peptides trigger T-cell proliferation through kinapses but we show that this process is only effective under conditions of high DC densities and prolonged antigen availability. By contrast, high-affinity peptides favor synapse formation and a vigorous proliferation under a wide range of antigen presentation conditions. In line with the predictions, decreasing the DC density in vivo selectively abolished proliferation induced by the low-affinity peptide. Finally, our results suggest that T cells possess a biochemical memory of previous stimulations of at least 1–2 days. We propose that the stability of T-cell–DC interactions, apart from their signaling potency, profoundly influences the robustness of T-cell activation. By offering the ability to control parameters that are difficult to manipulate experimentally, the virtual lymph node model provides new possibilities to tackle the fundamental mechanisms that regulate T-cell responses elicited by infections or vaccines. |
format | Online Article Text |
id | pubmed-4980574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49805742016-08-24 A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses Moreau, Hélène D Bogle, Gib Bousso, Philippe Immunol Cell Biol Original Article The initiation of T-cell responses in lymph nodes requires T cells to integrate signals delivered by dendritic cells (DCs) during long-lasting contacts (synapses) or more transient interactions (kinapses). However, it remains extremely challenging to understand how a specific sequence of contacts established by T cells ultimately dictates T-cell fate. Here, we have coupled a computational model of T-cell migration and interactions with DCs with a real-time, flow cytometry-like representation of T-cell activation. In this model, low-affinity peptides trigger T-cell proliferation through kinapses but we show that this process is only effective under conditions of high DC densities and prolonged antigen availability. By contrast, high-affinity peptides favor synapse formation and a vigorous proliferation under a wide range of antigen presentation conditions. In line with the predictions, decreasing the DC density in vivo selectively abolished proliferation induced by the low-affinity peptide. Finally, our results suggest that T cells possess a biochemical memory of previous stimulations of at least 1–2 days. We propose that the stability of T-cell–DC interactions, apart from their signaling potency, profoundly influences the robustness of T-cell activation. By offering the ability to control parameters that are difficult to manipulate experimentally, the virtual lymph node model provides new possibilities to tackle the fundamental mechanisms that regulate T-cell responses elicited by infections or vaccines. Nature Publishing Group 2016-08 2016-05-10 /pmc/articles/PMC4980574/ /pubmed/27089942 http://dx.doi.org/10.1038/icb.2016.36 Text en Copyright © 2016 Australasian Society for Immunology Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | Original Article Moreau, Hélène D Bogle, Gib Bousso, Philippe A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title | A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title_full | A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title_fullStr | A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title_full_unstemmed | A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title_short | A virtual lymph node model to dissect the requirements for T-cell activation by synapses and kinapses |
title_sort | virtual lymph node model to dissect the requirements for t-cell activation by synapses and kinapses |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4980574/ https://www.ncbi.nlm.nih.gov/pubmed/27089942 http://dx.doi.org/10.1038/icb.2016.36 |
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