Learning non-reciprocal interactions between migrating cells
Objectives
Owing to their active nature, interactions between migrating cells can be non-reciprocal. However, the extent to which cells control their collective behaviour through non-reciprocal interactions remains unclear. Existing modelling avenues typically make a priori assumptions on the types of interactions between individual cells [1]. Here, our objective is to develop a data-driven theoretical approach [2] to detect and quantify non-reciprocal interactions directly from time-resolved microscopy data of cell migration experiments.
Activities of the Doctoral Candidate
Building on the expertise of Broedersz on data-driven theory of cell migration [3-5], we will develop a Stochastic Inference approach [2,3] (T11) to determine an effective physical description of a multicellular system with non-reciprocal interactions (L3). We will apply this approach directly to time-resolved microscopy data from cell migration experiments of variety of cell types (including non-cancerous MCF10A and cancerous MDA-231 cells) on 1d micropatterns, made available to us by Joachim Rädler (LMU Munich). This will allow us to learn a stochastic equation of motion describing a particle-based model (T1) and infer dynamical cell-cell interaction terms directly from experimental cell trajectories of the cell nuclei. This new approach can thus reveal the exact nature of the non-reciprocal interactions from experiments for various cell types. With Golestanian, who brings expertise on statistical physics of non-equilibrium systems with non-reciprocal interactions, we will investigate using both particle-based models (T1) and stochastic field theories (T3) how non-reciprocal interactions between cells can control the emergent collective multicellular migration behaviours.
Facilities Provided
TBC.
Employment Contract
TBC.
Period of Doctorate and Funding
TBC.
References
[1] Alert, R, & Trepat, X. (2020) Annu Rev Condens Matter Phys 11:77 [2] Brückner, DB, & Broedersz, CP. (2024) Rep Prog Phys 87:056601 [3] Brückner, DB, et al. (2020) Phys Rev Lett 125:058103 [4] Brückner, DB, et al. (2019) Nat Phys 15:595 [5] Brückner, DB, et al. (2021) Proc Natl Acad Sci 118:2016602118 (2021)