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Iskrak, S.

Publications and source records attributed to Iskrak, S..

2 recordsLinked to original sources

VISION -- an open-source software for automated multi-dimensional image analysis of cellular biophysics

Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Phyton for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption. We anticipate that VISION will find a broad range of applications in different fields of biology, spanning from molecular and tissue biology to immunology and biophysics. Summary statementVISION, an open-source software, enables high throughput and correlative analysis of cellular biophysical properties.

biophysics↗

High-throughput analysis of membrane fluidity unveils a hidden dimension in immune cell states

Cell 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.

biophysics↗