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Torres DJ, Mrass P, Byrum J, Gonzales A, Martinez DN, Juarez E, Thompson E, Vezys V, Moses ME, Cannon JL. Quantitative analyses of T cell motion in tissue reveals factors driving T cell search in tissues. eLife 2023; 12:e84916. [PMID: 37870221 PMCID: PMC10672806 DOI: 10.7554/elife.84916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 10/22/2023] [Indexed: 10/24/2023] Open
Abstract
T cells are required to clear infection, and T cell motion plays a role in how quickly a T cell finds its target, from initial naive T cell activation by a dendritic cell to interaction with target cells in infected tissue. To better understand how different tissue environments affect T cell motility, we compared multiple features of T cell motion including speed, persistence, turning angle, directionality, and confinement of T cells moving in multiple murine tissues using microscopy. We quantitatively analyzed naive 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. Interestingly, we found that 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. T cells in the lung also showed significantly decreased meandering ratios and increased confinement compared to T cells in lymph nodes and villi. 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.
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Affiliation(s)
| | - Paulus Mrass
- Department of Molecular Genetics and Microbiology, University of New Mexico School of MedicineAlbuquerqueUnited States
| | - Janie Byrum
- Department of Molecular Genetics and Microbiology, University of New Mexico School of MedicineAlbuquerqueUnited States
| | | | | | | | - Emily Thompson
- Department of Microbiology and Immunology, University of Minnesota Medical SchoolMinneapolisUnited States
| | - Vaiva Vezys
- Department of Microbiology and Immunology, University of Minnesota Medical SchoolMinneapolisUnited States
| | - Melanie E Moses
- Department of Computer Science, University of New MexicoAlbuquerqueUnited States
| | - Judy L Cannon
- Department of Molecular Genetics and Microbiology, University of New Mexico School of MedicineAlbuquerqueUnited States
- Autophagy, Inflammation, and Metabolism Center of Biomedical Research Excellence, University of New Mexico School of MedicineAlbuquerqueUnited States
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Rajakaruna H, O'Connor JH, Cockburn IA, Ganusov VV. Liver Environment-Imposed Constraints Diversify Movement Strategies of Liver-Localized CD8 T Cells. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2022; 208:1292-1304. [PMID: 35131868 PMCID: PMC9250760 DOI: 10.4049/jimmunol.2100842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 12/17/2021] [Indexed: 05/11/2023]
Abstract
Pathogen-specific CD8 T cells face the problem of finding rare cells that present their cognate Ag either in the lymph node or in infected tissue. Although quantitative details of T cell movement strategies in some tissues such as lymph nodes or skin have been relatively well characterized, we still lack quantitative understanding of T cell movement in many other important tissues, such as the spleen, lung, liver, and gut. We developed a protocol to generate stable numbers of liver-located CD8 T cells, used intravital microscopy to record movement patterns of CD8 T cells in livers of live mice, and analyzed these and previously published data using well-established statistical and computational methods. We show that, in most of our experiments, Plasmodium-specific liver-localized CD8 T cells perform correlated random walks characterized by transiently superdiffusive displacement with persistence times of 10-15 min that exceed those observed for T cells in lymph nodes. Liver-localized CD8 T cells typically crawl on the luminal side of liver sinusoids (i.e., are in the blood); simulating T cell movement in digital structures derived from the liver sinusoids illustrates that liver structure alone is sufficient to explain the relatively long superdiffusive displacement of T cells. In experiments when CD8 T cells in the liver poorly attach to the sinusoids (e.g., 1 wk after immunization with radiation-attenuated Plasmodium sporozoites), T cells also undergo Lévy flights: large displacements occurring due to cells detaching from the endothelium, floating with the blood flow, and reattaching at another location. Our analysis thus provides quantitative details of movement patterns of liver-localized CD8 T cells and illustrates how structural and physiological details of the tissue may impact T cell movement patterns.
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Affiliation(s)
| | - James H O'Connor
- Division of Immunology, Inflammation and Infectious Disease, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; and
- Australian National University Medical School, Acton, Australian Capital Territory, Australia
| | - Ian A Cockburn
- Division of Immunology, Inflammation and Infectious Disease, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; and
| | - Vitaly V Ganusov
- Department of Microbiology, University of Tennessee, Knoxville, TN;
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Frattolin J, Watson DJ, Bonneuil WV, Russell MJ, Fasanella Masci F, Bandara M, Brook BS, Nibbs RJB, Moore JE. The Critical Importance of Spatial and Temporal Scales in Designing and Interpreting Immune Cell Migration Assays. Cells 2021; 10:3439. [PMID: 34943947 PMCID: PMC8700135 DOI: 10.3390/cells10123439] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/01/2021] [Accepted: 12/03/2021] [Indexed: 02/08/2023] Open
Abstract
Intravital microscopy and other direct-imaging techniques have allowed for a characterisation of leukocyte migration that has revolutionised the field of immunology, resulting in an unprecedented understanding of the mechanisms of immune response and adaptive immunity. However, there is an assumption within the field that modern imaging techniques permit imaging parameters where the resulting cell track accurately captures a cell's motion. This notion is almost entirely untested, and the relationship between what could be observed at a given scale and the underlying cell behaviour is undefined. Insufficient spatial and temporal resolutions within migration assays can result in misrepresentation of important physiologic processes or cause subtle changes in critical cell behaviour to be missed. In this review, we contextualise how scale can affect the perceived migratory behaviour of cells, summarise the limited approaches to mitigate this effect, and establish the need for a widely implemented framework to account for scale and correct observations of cell motion. We then extend the concept of scale to new approaches that seek to bridge the current "black box" between single-cell behaviour and systemic response.
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Affiliation(s)
- Jennifer Frattolin
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK; (J.F.); (D.J.W.); (W.V.B.)
| | - Daniel J. Watson
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK; (J.F.); (D.J.W.); (W.V.B.)
| | - Willy V. Bonneuil
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK; (J.F.); (D.J.W.); (W.V.B.)
| | - Matthew J. Russell
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK; (M.J.R.); (B.S.B.)
| | - Francesca Fasanella Masci
- Institute of Infection, Immunity and Inflammation, College of Medicine, Veterinary Medicine and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK; (F.F.M.); (M.B.); (R.J.B.N.)
| | - Mikaila Bandara
- Institute of Infection, Immunity and Inflammation, College of Medicine, Veterinary Medicine and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK; (F.F.M.); (M.B.); (R.J.B.N.)
| | - Bindi S. Brook
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK; (M.J.R.); (B.S.B.)
| | - Robert J. B. Nibbs
- Institute of Infection, Immunity and Inflammation, College of Medicine, Veterinary Medicine and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK; (F.F.M.); (M.B.); (R.J.B.N.)
| | - James E. Moore
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK; (J.F.); (D.J.W.); (W.V.B.)
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Wortel IM, Liu AY, Dannenberg K, Berry JC, Miller MJ, Textor J. CelltrackR: An R package for fast and flexible analysis of immune cell migration data. IMMUNOINFORMATICS 2021; 1-2. [PMID: 37034276 PMCID: PMC10079262 DOI: 10.1016/j.immuno.2021.100003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present celltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration. CelltrackR supports the analysis of both 2D and 3D cell tracks. CelltrackR is an open-source package released under the GPL-2 license, and is freely available on both GitHub and CRAN. Although the package was designed specifically for immune cell migration data, many of its methods will also be of use in other research areas dealing with moving objects.
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Tasnim H, Fricke GM, Byrum JR, Sotiris JO, Cannon JL, Moses ME. Quantitative Measurement of Naïve T Cell Association With Dendritic Cells, FRCs, and Blood Vessels in Lymph Nodes. Front Immunol 2018; 9:1571. [PMID: 30093900 PMCID: PMC6070610 DOI: 10.3389/fimmu.2018.01571] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/25/2018] [Indexed: 12/25/2022] Open
Abstract
T cells play a vital role in eliminating pathogenic infections. To activate, naïve T cells search lymph nodes (LNs) for dendritic cells (DCs). Positioning and movement of T cells in LNs is influenced by chemokines including CCL21 as well as multiple cell types and structures in the LNs. Previous studies have suggested that T cell positioning facilitates DC colocalization leading to T:DC interaction. Despite the influence chemical signals, cells, and structures can have on naïve T cell positioning, relatively few studies have used quantitative measures to directly compare T cell interactions with key cell types. Here, we use Pearson correlation coefficient (PCC) and normalized mutual information (NMI) to quantify the extent to which naïve T cells spatially associate with DCs, fibroblastic reticular cells (FRCs), and blood vessels in LNs. We measure spatial associations in physiologically relevant regions. We find that T cells are more spatially associated with FRCs than with their ultimate targets, DCs. We also investigated the role of a key motility chemokine receptor, CCR7, on T cell colocalization with DCs. We find that CCR7 deficiency does not decrease naïve T cell association with DCs, in fact, CCR7-/- T cells show slightly higher DC association compared with wild type T cells. By revealing these associations, we gain insights into factors that drive T cell localization, potentially affecting the timing of productive T:DC interactions and T cell activation.
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Affiliation(s)
- Humayra Tasnim
- Moses Biological Computation Laboratory, Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
| | - G. Matthew Fricke
- Moses Biological Computation Laboratory, Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
- UNM Center for Advanced Research Computing (CARC), The University of New Mexico, Albuquerque, NM, United States
| | - Janie R. Byrum
- The Cannon Laboratory, Molecular Genetics & Microbiology, The University of New Mexico, Albuquerque, NM, United States
| | - Justyna O. Sotiris
- Moses Biological Computation Laboratory, Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
| | - Judy L. Cannon
- The Cannon Laboratory, Molecular Genetics & Microbiology, The University of New Mexico, Albuquerque, NM, United States
- Department of Pathology, The University of New Mexico, Albuquerque, NM, United States
- Autophagy, Inflammation, and Metabolism Center of Biomedical Research Excellence, The University of New Mexico, Albuquerque, NM, United States
| | - Melanie E. Moses
- Moses Biological Computation Laboratory, Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
- Biology Department, The University of New Mexico, Albuquerque, NM, United States
- Santa Fe Institute, Santa Fe, NM, United States
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Abstract
Mathematical and statistical methods enable multidisciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. We collect a representative sample of studies in T-cell biology that illustrate the benefits of modelling–experimental collaborations and that have proven valuable or even groundbreaking. We conclude that it is possible to find excellent examples of synergy between mathematical modelling and experiment in immunology, which have brought significant insight that would not be available without these collaborations, but that much remains to be discovered.
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Affiliation(s)
- Mario Castro
- Universidad Pontificia Comillas , E28015 Madrid , Spain
| | - Grant Lythe
- Department of Applied Mathematics, School of Mathematics , University of Leeds , Leeds LS2 9JT , UK
| | - Carmen Molina-París
- Department of Applied Mathematics, School of Mathematics , University of Leeds , Leeds LS2 9JT , UK
| | - Ruy M Ribeiro
- Los Alamos National Laboratory , Theoretical Biology and Biophysics , Los Alamos, NM 87545 , USA
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Fricke GM, Letendre KA, Moses ME, Cannon JL. Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search. PLoS Comput Biol 2016; 12:e1004818. [PMID: 26990103 PMCID: PMC4798282 DOI: 10.1371/journal.pcbi.1004818] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Accepted: 02/17/2016] [Indexed: 11/19/2022] Open
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.
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Affiliation(s)
- G. Matthew Fricke
- Department of Computer Science, The University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Kenneth A. Letendre
- Department of Biology, The University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Melanie E. Moses
- Department of Computer Science, The University of New Mexico, Albuquerque, New Mexico, United States of America
- Department of Biology, The University of New Mexico, Albuquerque, New Mexico, United States of America
- External Faculty, Santa Fe Institute, Santa Fe, New Mexico, United States of America
| | - Judy L. Cannon
- Department of Molecular Genetics and Microbiology, The University of New Mexico School of Medicine, Albuquerque, New Mexico, United States of America
- Department of Pathology, The University of New Mexico School of Medicine, Albuquerque, New Mexico, United States of America
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Abstract
T cell migration is essential for T cell responses; it allows for the detection of cognate antigen at the surface of antigen-presenting cells and for interactions with other cells involved in the immune response. Although appearing random, growing evidence suggests that T cell motility patterns are strategic and governed by mechanisms that are optimized for both the activation stage of the cell and for environment-specific cues. In this Opinion article, we discuss how the combined effects of T cell-intrinsic and -extrinsic forces influence T cell motility patterns in the context of highly complex tissues that are filled with other cells involved in parallel motility. In particular, we examine how insights from 'search theory' can be used to describe T cell movement across an 'exploitation-exploration trade-off' in the context of activation versus effector function and lymph nodes versus peripheral tissues.
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