This record contains all data, artwork, and code used to create figures and tables in the article Schrangl et al. (2025): “CD4+ T-cells create a stable mechanical environment for force-sensitive TCR:pMHC interactions”.

Dataset structure

• schrangl2025_force_v1.zip contains source code for data file handling, high-level analysis, and figure generation
• data_force_raw.part1.zip and data_force_raw.part2.zip contain raw single-molecule fluorescence microscopy data from force sensor experiments
• data_force.zip contains per-experiment single-molecule FRET tracking datasets derived from the above using the fret-analysis software
• data_lifetime_raw.zip contains raw single-molecule fluorescence microscopy data from TCR:pMHC bond lifetime measurements
• data_lifetime.zip contains per-experiment single-molecule FRET tracking data derived from the above using the smfret-bondtime software
• data_supplementary_raw.zip contains raw data for supplementary figures
• data_supplementary.zip contains analysis data for supplementary figures

Installation

• Install the uv Python package and project manager. Note that many Linux distributions provide packages for easy installation. Version 0.7.13 was used to produce the published figures.

• Create a new folder and download the data archives (data_force.zip, data_force_raw.part1.zip, data_force_raw.part2.zip, data_lifetime.zip, data_lifetime_raw.zip, data_supplementary.zip, data_supplementary_raw.zip) into that folder.

• Download and unpack schrangl2025_force_v1.zip somewhere on your hard drive.

• Using a terminal, navigate into the unpacked folder and execute

  uv sync

  to obtain required Python packages.

• Execute

  uv run python data_utils/unpack.py --input-dir <download_folder> --output-dir data

  where <download_folder> is the folder into which the data archives were downloaded. Note that this will unpack all files with extension .zip, so make sure that only downloaded files are present in the folder.

  Alternatively, any application supporting zstd-compressed zip archives (such as 7z) can be used.

  After unpacking, the data folder should contain subfolders force, force_raw, lifetime, lifetime_raw, supplementary, and supplementary_raw consisting of the data files.

• Optionally delete the folder containing the downloaded data archives to free disk space.

Generation of figures and tables

The SCons software construction tool is used to execute Python scripts for data analysis and figure/table generation. SCons keeps track of dependencies and only reruns Python scripts if either the inputs or the scripts themselves change.

To build figures and tables, execute

uv run scons

This will

• generate a cache of single-molecule force data to speed up subsequent analysis
• analyze cached force data and lifetime data
• generate figures and tables from analysis results

All created files are placed in the output subfolder. On a current PC, this takes about 15 minutes to complete.

To clear the output subfolder, run

uv run scons --clean

For further information, consult the SCons documentation and inspect the SConscript file.

Licensing

Each file in schrangl2025_force_v1.zip and data_force.zip either contains a header or is accompinied by a file with additional extension .license providing licensing information according to the REUSE specfication. As a rule of thumb,

• code is subject to the BSD 3-Clause license,
• minor helper files are put into the public domain,
• other files (this README, illustrations, data) are subject to the Creative Commons Attribution 4.0 International license,

but there some exceptions, e.g. due to reuse of work created by third parties.

data_force_raw.part1.zip, data_force_raw.part2.zip, data_lifetime_raw.zip, data_lifetime.zip, data_supplementary.zip and data_supplementary_raw.zip contain

• Jupyter notebooks subject to the BSD 3-Clause license and
• other files (mainly data) subject to the Creative Commons Attribution 4.0 International license.

data_supplementary_raw.zip additionally contains ImageJ macros, which are BSD 3-Clause-licensed.

© 2017–2025 Lukas Schrangl <lukas.schrangl@boku.ac.at>, Florian Kellner <f.kellner@valdospan.com>, Vanessa Mühlgrabner <vanessa.muehlgrabner@meduniwien.ac.at>, Janett Göhring <janett.goehring@meduniwien.ac.at>