Collective cell migration has distinct directionality and speed dynamics

  • Yan Zhang
  • Guoqing Xu
  • Rachel M. Lee
  • Zijie Zhu
  • Jiandong Wu
  • Simon Liao
  • Gong Zhang
  • Yaohui Sun
  • Alex Mogilner
  • Wolfgang Losert
  • Tingrui Pan
  • Francis Lin
  • Zhengping Xu
  • Min Zhao
Original Article

DOI: 10.1007/s00018-017-2553-6

Cite this article as:
Zhang, Y., Xu, G., Lee, R.M. et al. Cell. Mol. Life Sci. (2017). doi:10.1007/s00018-017-2553-6


When a constraint is removed, confluent cells migrate directionally into the available space. How the migration directionality and speed increase are initiated at the leading edge and propagate into neighboring cells are not well understood. Using a quantitative visualization technique—Particle Image Velocimetry (PIV)—we revealed that migration directionality and speed had strikingly different dynamics. Migration directionality increases as a wave propagating from the leading edge into the cell sheet, while the increase in cell migration speed is maintained only at the leading edge. The overall directionality steadily increases with time as cells migrate into the cell-free space, but migration speed remains largely the same. A particle-based compass (PBC) model suggests cellular interplay (which depends on cell–cell distance) and migration speed are sufficient to capture the dynamics of migration directionality revealed experimentally. Extracellular Ca2+ regulated both migration speed and directionality, but in a significantly different way, suggested by the correlation between directionality and speed only in some dynamic ranges. Our experimental and modeling results reveal distinct directionality and speed dynamics in collective migration, and these factors can be regulated by extracellular Ca2+ through cellular interplay. Quantitative visualization using PIV and our PBC model thus provide a powerful approach to dissect the mechanisms of collective cell migration.


Wound healing Cell contractility PDMS Corneal epithelial cell Cell communication Blebbistatin 



Particle-based compass




Particle image velocimetry

Supplementary material

18_2017_2553_MOESM1_ESM.docx (2.8 mb)
Supplementary material 1 (DOCX 2837 kb)
18_2017_2553_MOESM2_ESM.avi (1.1 mb)
Supplementary material 2 (AVI 1083 kb)
18_2017_2553_MOESM3_ESM.avi (3.1 mb)
Supplementary material 3 (AVI 3132 kb)
18_2017_2553_MOESM4_ESM.avi (4.7 mb)
Supplementary material 4 (AVI 4822 kb)
18_2017_2553_MOESM5_ESM.avi (6.3 mb)
Supplementary material 5 (AVI 6494 kb)
18_2017_2553_MOESM6_ESM.avi (1.2 mb)
Supplementary material 6 (AVI 1214 kb)
18_2017_2553_MOESM7_ESM.avi (1.4 mb)
Supplementary material 7 (AVI 1418 kb)
18_2017_2553_MOESM8_ESM.avi (2.5 mb)
Supplementary material 8 (AVI 2549 kb)

Funding information

Funder NameGrant NumberFunding Note
National Institutes of Health
  • NIH EY019101
  • GM 068952
Air Force Office of Scientific Research
  • AFOSR FA9550-16-1-0052
The Major Program Grant of Zhejiang Provincial Science and Technology
  • No. 2012C03007-6

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of DermatologyUniversity of CaliforniaDavisUSA
  2. 2.Institute of Environmental MedicineZhejiang University School of MedicineHangzhouChina
  3. 3.Micro-Nano Innovations (MiNI) Laboratory, Department of Biomedical EngineeringUniversity of CaliforniaDavisUSA
  4. 4.Department of Physics and AstronomyUniversity of ManitobaWinnipegCanada
  5. 5.Department of Applied Computer ScienceUniversity of WinnipegWinnipegCanada
  6. 6.Department of PhysicsUniversity of MarylandCollege ParkUSA
  7. 7.Seven Oaks Hospital Wellness InstituteWinnipegCanada
  8. 8.The First Affiliated Hospital of Henan University of Science and TechnologyLuoyangChina
  9. 9.Courant Institute and Department of BiologyNew York UniversityNew YorkUSA
  10. 10.Department of Ophthalmology and Vision ScienceUniversity of CaliforniaDavisUSA

Personalised recommendations