Defining the quantitative limits of intravital two-photon lymphocyte tracking
Two-photon microscopy has substantially advanced our understanding of cellular dynamics in the immune system. Cell migration can now be imaged in real time in the living animal. Strikingly, the migration of naive lymphocytes in secondary lymphoid tissue appears predominantly random. It is unclear, h...
Saved in:
Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 108; no. 30; pp. 12401 - 12406 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
National Academy of Sciences
26.07.2011
National Acad Sciences |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Two-photon microscopy has substantially advanced our understanding of cellular dynamics in the immune system. Cell migration can now be imaged in real time in the living animal. Strikingly, the migration of naive lymphocytes in secondary lymphoid tissue appears predominantly random. It is unclear, however, whether directed migration may escape detection in this random background. Using a combination of mathematical modeling and experimental data, we investigate the extent to which modern two-photon imaging can rule out biologically relevant directed migration. For naive T cells migrating in uninfected lymph nodes (LNs) at average 3D speeds of around 18 μm/min, we rule out uniform directed migration of more than 1.7 μm/min at the 95% confidence level, confirming that T cell migration is indeed mostly random on a timescale of minutes. To investigate whether this finding still holds for longer timescales, we use a 3D simulation of the naive T cell LN transit. A pure random walk predicts a transit time of around 16 h, which is in good agreement with experimental results. A directional bias of only 0.5 μm/min--less than 3% of the cell speed--would already accelerate the transit twofold. These results jointly strengthen the random walk analogy for naive T cell migration in LNs, but they also emphasize that very small deviations from random migration can still be important. Our methods are applicable to cells of any type and can be used to reanalyze existing datasets. |
---|---|
Bibliography: | http://dx.doi.org/10.1073/pnas.1102288108 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 Edited by Ronald N. Germain, National Institutes of Health, Bethesda, MD, and accepted by the Editorial Board June 10, 2011 (received for review February 11, 2011) Author contributions: J.T., A.P., S.E.H., U.H.v.A., and J.W. designed research; J.T., A.P., and M.S. performed research; J.T., A.P., and M.S. analyzed data; and J.T., S.E.H., and M.S. wrote the paper. |
ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.1102288108 |