Traction Microscopy Integrated with Microfluidics for Chemotactic Collective Migration

Hwanseok Jang, Jongseong Kim, Jennifer H. Shin, Jeffrey J. Fredberg, Chan Young Park, Yongdoo Park

Research output: Contribution to journalArticle

Abstract

Cells change migration patterns in response to chemical stimuli, including the gradients of the stimuli. Cellular migration in the direction of a chemical gradient, known as chemotaxis, plays an important role in development, the immune response, wound healing, and cancer metastasis. While chemotaxis modulates the migration of single cells as well as collections of cells in vivo, in vitro research focuses on single-cell chemotaxis, partly due to the lack of the proper experimental tools. To fill that gap, described here is a unique experimental system that combines microfluidics and micropatterning to demonstrate the effects of chemical gradients on collective cell migration. Furthermore, traction microscopy and monolayer stress microscopy are incorporated into the system to characterize changes in cellular force on the substrate as well as between neighboring cells. As proof-of-concept, the migration of micropatterned circular islands of Madin-Darby canine kidney (MDCK) cells is tested under a gradient of hepatocyte growth factor (HGF), a known scattering factor. It is found that cells located near the higher concentration of HGF migrate faster than those on the opposite side within a cell island. Within the same island, cellular traction is similar on both sides, but intercellular stress is much lower on the side of higher HGF concentration. This novel experimental system can provide new opportunities to studying the mechanics of chemotactic migration by cellular collectives.

Original languageEnglish
JournalJournal of visualized experiments : JoVE
Issue number152
DOIs
Publication statusPublished - 2019 Oct 13

ASJC Scopus subject areas

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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