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Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search
Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4798282/ https://www.ncbi.nlm.nih.gov/pubmed/26990103 http://dx.doi.org/10.1371/journal.pcbi.1004818 |
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author | Fricke, G. Matthew Letendre, Kenneth A. Moses, Melanie E. Cannon, Judy L. |
author_facet | Fricke, G. Matthew Letendre, Kenneth A. Moses, Melanie E. Cannon, Judy L. |
author_sort | Fricke, G. Matthew |
collection | PubMed |
description | Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call “hotspots” within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search. |
format | Online Article Text |
id | pubmed-4798282 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-47982822016-03-23 Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search Fricke, G. Matthew Letendre, Kenneth A. Moses, Melanie E. Cannon, Judy L. PLoS Comput Biol Research Article Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call “hotspots” within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search. Public Library of Science 2016-03-18 /pmc/articles/PMC4798282/ /pubmed/26990103 http://dx.doi.org/10.1371/journal.pcbi.1004818 Text en © 2016 Fricke et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Fricke, G. Matthew Letendre, Kenneth A. Moses, Melanie E. Cannon, Judy L. Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title | Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title_full | Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title_fullStr | Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title_full_unstemmed | Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title_short | Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search |
title_sort | persistence and adaptation in immunity: t cells balance the extent and thoroughness of search |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4798282/ https://www.ncbi.nlm.nih.gov/pubmed/26990103 http://dx.doi.org/10.1371/journal.pcbi.1004818 |
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