Abstract

The three-dimensional positions of immune cells can be tracked in live tissues precisely as a function of time using two-photon microscopy. However, standard methods of analysis used in the field and experimental artifacts can bias interpretations and obscure important aspects of cell migration such as directional migration and non-Brownian walk statistics. Therefore, methods were developed for minimizing drift artifacts, identifying directional and anisotropic (asymmetric) migration, and classifying cell migration statistics. These methods were applied to describe the migration statistics of CD8+ T cells in uninflamed lymph nodes. Contrary to current models, CD8+ T cell statistics are not well described by a straightforward persistent random walk model. Instead, a model in which one population of cells moves via Brownian-like motion and another population follows variable persistent random walks with noise reproduces multiple statistical measures of CD8+ T cell migration in the lymph node in the absence of inflammation.

Highlights

  • IntroductionA primary challenge of immunological imaging experimentation is to understand the nature of cell migration statistics, and the role that these statistics play in immune function

  • Migration is fundamental to immune cell function, and accurate quantitative methods are crucial for analyzing and interpreting migration statistics

  • A primary challenge of immunological imaging experimentation is to understand the nature of cell migration statistics, and the role that these statistics play in immune function

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Summary

Introduction

A primary challenge of immunological imaging experimentation is to understand the nature of cell migration statistics, and the role that these statistics play in immune function. Two-photon microscopy has transformed the understanding of the role of cell migration in the immune response [1,2,3]. Migration tracks can be directional or random and can be characterized by a bewildering array of models. This poses the question of how best to analyze migration tracks in an unbiased fashion, given experimental data that is often gathered in a limited field of view over a short period of time

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