Quantitative analyses of T cell motion in tissue reveals factors driving T cell search in tissues
Abstract
T cells are required to clear infection, moving first in lymph nodes to interact with antigen bearing dendritic cells leading to activation. T cells then move to sites of infection to find and clear infection. T cell motion plays a role in how quickly a T cell finds its target, from initial natiıve T cell activation by a dendritic cell to interaction with target cells in infected tissue. To better understand how different tissue environments might affect T cell motility, we compared multiple features of T cell motion including speed, persistence, turning angle, directionality, and confinement of motion from T cells moving in multiple tissues using tracks collected with microscopy from murine tissues. We quantitatively analyzed natiıve T cell motility within the lymph node and compared motility parameters with activated CD8 T cells moving within the villi of small intestine and lung under different activation conditions. Our motility analysis found that while the speeds and the overall displacement of T cells vary within all tissues analyzed, T cells in all tissues tended to persist at the same speed, particularly if the previous speed is very slow (less than 2 μm/min) or very fast (greater than 8 μm/min) with the exception of T cells in the villi for speeds greater than 10 μm/min. Interestingly, we found that turning angles of T cells in the lung show a marked population of T cells turning at close to 180o, while T cells in lymph nodes and villi do not exhibit this 'reversing' movement. Additionally, T cells in the lung showed significantly decreased meandering ratios and increased confinement compared to T cells in lymph nodes and villi. The combination of these differences in motility patterns led to a decrease in the total volume scanned by T cells in lung compared to T cells in lymph node and villi. These results suggest that the tissue environment in which T cells move can impact the type of motility and ultimately, the efficiency of T cell search for target cells within specialized tissues such as the lung.
Data availability
Datasets are available as Supplementary Materials under the Biorxiv preprint BIORXIV/2022/516891 https://www.biorxiv.org/content/10.1101/2022.11.17.516891v2.supplementary-material. The code used for analysis can be downloaded at: https://github.com/davytorres/T-cell-analysis-tool .
Article and author information
Author details
Funding
National Institutes of Health (P20GM103451)
- David J Torres
University of New Mexico (NCI P30CA118100)
- Paulus Mrass
National Institutes of Health (P20GM121176)
- Paulus Mrass
University of New Mexico (School of Medicine)
- Paulus Mrass
National Institutes of Health (1R01AI097202)
- Judy L Cannon
National Institutes of Health (P50 GM085273)
- Judy L Cannon
National Institutes of Health (5P20GM103452)
- Judy L Cannon
National Institutes of Health (P20GM121176)
- Judy L Cannon
National Institutes of Health (5 T32 AI007538-19)
- Janie Byrum
University of New Mexico (School of Medicine)
- Judy L Cannon
University of New Mexico (DARPA/AFRL FA8650-18-C-6898)
- Judy L Cannon
University of New Mexico (NCI P30CA118100)
- Judy L Cannon
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Michael L Dustin, University of Oxford, United Kingdom
Ethics
Animal experimentation: All work was done in accordance with approved protocols per IACUC institutional approvals, IACUC Animal approval #: 21-201165-HS
Version history
- Received: November 15, 2022
- Preprint posted: November 17, 2022 (view preprint)
- Accepted: October 22, 2023
- Accepted Manuscript published: October 23, 2023 (version 1)
- Version of Record published: November 24, 2023 (version 2)
Copyright
© 2023, Torres et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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