VISION - an open-source software for automated multi-dimensional image analysis of cellular biophysics.
Florian WeberSofiia IskrakFranziska RagallerJan SchlegelBirgit PlochbergerErdinc SezginLuca A AndronicoPublished in: Journal of cell science (2024)
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 Python 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.
Keyphrases
- single cell
- optical coherence tomography
- deep learning
- high throughput
- rna seq
- cell therapy
- convolutional neural network
- oxidative stress
- high resolution
- small molecule
- stem cells
- magnetic resonance
- computed tomography
- magnetic resonance imaging
- mesenchymal stem cells
- cell proliferation
- data analysis
- bone marrow
- high speed
- molecular dynamics
- metal organic framework
- mass spectrometry
- psychometric properties