Wouter Rappel
VerifiedUniversity of California, San Diego · Astronomy and Astrophysics
Active 1988–2024
Research topics
- Computer Science
- Biology
- Neuroscience
- Biological system
- Mathematics
- Physics
- Psychology
- Genetics
- Telecommunications
- Optoelectronics
- Mathematical analysis
Selected publications
Cellular memory in eukaryotic chemotaxis depends on the background chemoattractant concentration
Physical review. E · 2021 · 27 citations
Senior authorCorresponding- Computer Science
- Biology
- Physics
Cells of the social amoeba Dictyostelium discoideum migrate to a source of periodic traveling waves of chemoattractant as part of a self-organized aggregation process. An important part of this process is cellular memory, which enables cells to respond to the front of the wave and ignore the downward gradient in the back of the wave. During this aggregation, the background concentration of the chemoattractant gradually rises. In our microfluidic experiments, we exogenously applied periodic waves of chemoattractant with various background levels. We find that increasing background does not make detection of the wave more difficult, as would be naively expected. Instead, we see that the chemotactic efficiency significantly increases for intermediate values of the background concentration but decreases to almost zero for large values in a switch-like manner. These results are consistent with a computational model that contains a bistable memory module, along with a nonadaptive component. Within this model, an intermediate background level helps preserve directed migration by keeping the memory activated, but when the background level is higher, the directional stimulus from the wave is no longer sufficient to activate the bistable memory, suppressing directed migration. These results suggest that raising levels of chemoattractant background may facilitate the self-organized aggregation in Dictyostelium colonies.
Recent grants
A Combined Theoretical and Experimental Approach to Study Collective Cell Migration
NSF · $540k · 2018–2023
Patient-Directed Computational Analysis of Atrial Fibrillation
NIH · $5.3M · 2015–2028
Integrating Four-Dimensional Cell Migration Modeling with Quantitative Experiments
NSF · $438k · 2020–2024
Deciphering Coarsening Dynamics and Cluster Migration using Experiments and Models
NSF · $600k · 2023–2027
NIH · $236k · 2019–2021
Frequent coauthors
- 158 shared
Herbert Levine
Northeastern University
- 138 shared
Sanjiv M. Narayan
Stanford University
- 65 shared
David E. Krummen
University of California, San Diego
- 60 shared
Albert J. Rogers
Stanford University
- 46 shared
Tina Baykaner
Stanford University
- 44 shared
Paul J. Wang
Stanford University
- 39 shared
Neal K. Bhatia
Emory University Hospital
- 29 shared
Eberhard Bodenschatz
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