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
Access to computing facilities for numerical work.
Employment Contract
Pay and benefits will comply with the Dutch Collective labor agreement for PhD candidates.
Period of Doctorate and Funding
Doctorates at VU take 4 years. Unspent local CAFE-BIO funds and VU funds may be used to support the Doctoral Candidate in year 4 as required.
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)