Dataset for “Plasma membrane order maps functional diversity in immune cells”
Abstract
It contains data sets from the publication Andronico et al, 2026 (DOI: TBD). with the details for citation provided in the README file.Please cite this item as:Luca A. Andronico, Cenk O. Gurdap, Abishek Arora, Franziska Ragaller, Patrick A. Sandoz, Yidan Jiang, Sarantis Giatrellis, Leonard L. de Boer, Valentina Carannante, Sofiia Iskrak, Jaromir Mikes, Marcus Buggert, Anders Österborg, Björn Önfelt, Andrey Klymchenko, Petter Brodin, Erdinc SezginDOI: 10.17044/scilifelab.31882975It contains microscopy images and excel sheets of the data.AbstractCell membranes undergo biophysical remodelling as an adaptation to the surroundings and to perform specific biological functions. However, the extent and relevance of such changes in human immune cells remain unknown, largely due to the lack of single-cell and multidimensional methodologies. Here, we apply a cytometry-based method to fill this gap by combining biophysical profiling with simultaneous analysis of immune cell markers. This platform reveals notable cell type-dependent plasma membrane order heterogeneity in immune cells. By sorting immune cells according to their membrane order and performing transcriptome and spatial surface proteome analyses together with functional tests, we show that plasma membrane order can be used to identify subsets of immune cells with distinct phenotypes and functional behaviours. Our findings demonstrate a broad heterogeneity of plasma membrane order in immune cells that will provide a more precise definition of immune cell states based on their biophysical properties in health and disease.Data usageResearchers are welcome to use the data contained in the dataset for any projects. Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License.Data ContentExcel files for graphslsm files for raw microscopy images Software to open files.csv - Microsoft excel.lsm - Fiji (https://imagej.net/Fiji.html#Downloads)
Publication details
- Journal / source
- SciLifeLab Data Repository
- Publication date
- 3 August 2026
- Document type
- Dataset