Supporting data for: "Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles" by Ewa Sitarska, Silvia Dias Almeida, Marianne Sandvold Beckwith, Julian Stopp, Jakub Czuchnowski, Marc Siggel, Rita Roessner, Aline Tschanz, Christer Ejsing, Yannick Schwab, Jan Kosinski, Michael Sixt, Anna Kreshuk, Anna Erzberger and Alba Diz-Muñoz

This repository contains the supporting data for the paper: 

"Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles"

by Ewa Sitarska, Silvia Dias Almeida, Marianne Sandvold Beckwith,  Julian Stopp, Jakub Czuchnowski, Marc Siggel, Rita Roessner, Aline  Tschanz, Christer Ejsing, Yannick Schwab, Jan Kosinski, Michael Sixt,  Anna Kreshuk, Anna Erzberger and Alba Diz-Muñoz

1) Data for Coarse-Grained MD Simulations

This repository contains scripts, jupyter notebooks and files to  reproduce the simulation results presented in this work and to generate  the accompanying figures.

!! Important note: these files are provided as is! scripts and top files include original file names and need to be adapted by the user to their system!!

!! tpr files should work for gromacs 2021 out of the box !!

TPR files for each step in the setup from minimization -> equilibation -> production

_pp.tpr is without water for processing and visualization purposes.

the .tpr files can be run to reproduce the trajectories from the paper.

Note that due to numerical inaccuracies over long periods of time results might diverge from the exact results in the paper.

However, the time averages will be the same.

Files with _275 are presented in the main text and have less curvature than files with _575 with higher curvature (SI figure).

the itp files are renamed to be used with the scaled martini force field (alpha=0.7) (see methods of paper)

the setup can be followed in setup_curvature.sh and setup.system.ipynb

analysis code as reported in the methods can be found in postprocessing_curvature.ipynb and postprocessing_contacts.ipynb

2) Scripts for TIRFM Images analysis

(in zip file)

 time_area_space.py is a simple script that performs some shape and intensity calculations on images

You will need:

1) time framed movies of moving cells, where correspondent membrane proteins are also seen

2) Cell segmentation masks

3) Protein segmentation masks

It reads the cells' segmentation (channel 3) and binary erodes the segmentation.

Then, subtracts from the original membrane mask, in order to have a border area of the perimeter of the cell.

Then, calculates the percentage of proteins in that area (proteins area / border area) and the ratio of number of proteins in the border versus the total number of proteins

Finally, performs a number of calculations regarding the shape (elongation, eccentricity, etc)