Analytical results on the Beauchemin model of lymphocyte migration

The Beauchemin model is a simple particle-based description of stochastic lymphocyte migration in tissue, which has been successfully applied to studying immunological questions. In addition to being easy to implement, the model is also to a large extent mathematically tractable. This article provides a comprehensive overview of both existing and new analytical results on the Beauchemin model within a common mathematical framework. Specifically, we derive the motility coefficient, the mean square displacement, and the confinement ratio, and discuss four different methods for simulating biased migration of pre-defined speed. The results provide new insight into published studies and a reference point for future research based on this simple and popular lymphocyte migration model.

[1]  H. Berg Random Walks in Biology , 2018 .

[2]  Mark J. Miller,et al.  T cell repertoire scanning is promoted by dynamic dendritic cell behavior and random T cell motility in the lymph node. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[3]  G. Marsaglia Choosing a Point from the Surface of a Sphere , 1972 .

[4]  Mark J. Miller,et al.  Autonomous T cell trafficking examined in vivo with intravital two-photon microscopy , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Grant Lythe,et al.  T-cell movement on the reticular network. , 2012, Journal of theoretical biology.

[6]  Henrik Flyvbjerg,et al.  Cell motility as persistent random motion: theories from experiments. , 2005, Biophysical journal.

[7]  Jason G. Cyster,et al.  Lymph node cortical sinus organization and relationship to lymphocyte egress dynamics and antigen exposure , 2010, Proceedings of the National Academy of Sciences.

[8]  Alan S. Perelson,et al.  Characterizing T Cell Movement within Lymph Nodes in the Absence of Antigen1 , 2007, The Journal of Immunology.

[9]  U. V. von Andrian,et al.  Defining the quantitative limits of intravital two-photon lymphocyte tracking , 2011, Proceedings of the National Academy of Sciences.

[10]  James D. Murray Mathematical Biology: I. An Introduction , 2007 .

[11]  P. Billingsley,et al.  Convergence of Probability Measures , 1969 .

[12]  R. Pepperkok,et al.  Birth and life of tissue macrophages and their migration in embryogenesis and inflammation in medaka , 2007, Journal of leukocyte biology.

[13]  P. Gennes Chemotaxis: the role of internal delays , 2004, European Biophysics Journal.

[14]  Grégoire Altan-Bonnet,et al.  Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T cell–dendritic cell interaction , 2006, Nature.

[15]  Joost B. Beltman,et al.  Analysing immune cell migration , 2009, Nature Reviews Immunology.

[16]  Edward A. Codling,et al.  Random walk models in biology , 2008, Journal of The Royal Society Interface.

[17]  Mark J. Miller,et al.  Two-Photon Imaging of Lymphocyte Motility and Antigen Response in Intact Lymph Node , 2002, Science.

[18]  Joost B. Beltman,et al.  B cells within germinal centers migrate preferentially from dark to light zone , 2011, Proceedings of the National Academy of Sciences.

[19]  Ian Parker,et al.  Choreography of Cell Motility and Interaction Dynamics Imaged by Two-photon Microscopy in Lymphoid Organs , 2007 .

[20]  S. Henrickson,et al.  T-cell priming by dendritic cells in lymph nodes occurs in three distinct phases , 2004, Nature.

[21]  BMC Bioinformatics , 2005 .

[22]  O. Kallenberg Foundations of Modern Probability , 2021, Probability Theory and Stochastic Modelling.

[23]  G. M.,et al.  Partial Differential Equations I , 2023, Applied Mathematical Sciences.

[24]  Joost B. Beltman,et al.  Lymph node topology dictates T cell migration behavior , 2007, The Journal of experimental medicine.

[25]  Ronald N Germain,et al.  Stromal cell networks regulate lymphocyte entry, migration, and territoriality in lymph nodes. , 2006, Immunity.

[26]  G. Oster,et al.  Digital Object Identifier (DOI): , 2000 .