 Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of SearchG Matthew Fricke, Kenneth A Letendre, Melanie E Moses and Judy L Cannon PLOS Computational Biology, 2016, vol. 12, issue 3, 1-23 Abstract: 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.Author Summary: The immune system is responsible for clearing disease-causing infections, and T cells are an important immune cell type that helps eliminate viruses and bacteria. To become activated, T cells must encounter another type of immune cell called dendritic cells in the lymph node. T cell search for dendritic cells is similar to animal search for food. Here we precisely analyze how T cells move using search patterns originally developed to describe animals. We find that T cell motion is a complex combination of multiple strategies including moving in a persistent direction and using different step sizes. This allows T cells to balance the need to search both extensively throughout the lymph node and also to search some regions thoroughly for possible infection. Furthermore, we use a computer model to demonstrate that T cells are more likely to be found in specific locations in lymph nodes. We call these locations “hotspots”. We find that T cells in hotspots move differently, apparently searching more thoroughly, suggesting that T cells can adapt to their environment, similar to animals foraging for food. These results show that T cells share fundamental search strategies with foraging animals, exhibiting both persistence and adaptation. Date: 2016 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1004818 DOI: 10.1371/journal.pcbi.1004818 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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