Controlling cell migration is important in tissue engineering and medicine. Cell motility depends on factors such as nutrient concentration gradients and soluble factor signaling. In particular, cell-cell signaling can depend on cell-cell separation distance and can influence cellular arrangements in bulk cultures. Here, we seek a physicalbased approach, which identifies a potential governed by cell-cell signaling that induces a directed cell-cell motion. A single-cell barcode chip (SCBC) was used to experimentally interrogate secreted proteins in hundreds of isolated glioblastoma brain cancer cell pairs and to monitor their relative motions over time. We used these trajectories to identify a range of cell-cell separation distances where the signaling was most stable. We then used a thermodynamicsmotivated analysis of secreted protein levels to characterize freeenergy changes for different cell-cell distances. We show that glioblastoma cell-cell movement can be described as Brownian motion biased by cell-cell potential. To demonstrate that the free-energy potential as determined by the signaling is the driver of motion, we inhibited two proteins most involved in maintaining the free-energy gradient. Following inhibition, cell pairs showed an essentially random Brownian motion, similar to the case for untreated, isolated single cells.
|Number of pages
|Proceedings of the National Academy of Sciences of the United States of America
|Published - 17 May 2016
Bibliographical noteFunding Information:
This work was funded by National Cancer Institute Grant 1U54CA199090-01 [to J.R.H., principal investigator (PI)], the Ben and Catherine Ivy Foundation (J.R.H.), the Jean Perkins Foundation (J.R.H., PI), the Korean-American Scientists and Engineers Association (Y.S.S., PI), the Phelps Family Foundation (Y.S.S.), and European Commission FP7 Future and Emerging Technologies-Open Project BAMBI 618024 (to R.D.L.). N.K.-B. was supported by an EMBO postdoctoral fellowship.
- Brownian dynamics
- Cell motility
- Cell-cell force
- Langevin equation
- Surprisal analysis