Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A Andronico
{"title":"VISION - 用于细胞生物物理学多维图像自动分析的开源软件。","authors":"Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A Andronico","doi":"10.1242/jcs.262166","DOIUrl":null,"url":null,"abstract":"<p><p>Environment-sensitive probes are frequently used in spectral and 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 easy adoption.</p>","PeriodicalId":15227,"journal":{"name":"Journal of cell science","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529879/pdf/","citationCount":"0","resultStr":"{\"title\":\"VISION - an open-source software for automated multi-dimensional image analysis of cellular biophysics.\",\"authors\":\"Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A Andronico\",\"doi\":\"10.1242/jcs.262166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Environment-sensitive probes are frequently used in spectral and 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 easy adoption.</p>\",\"PeriodicalId\":15227,\"journal\":{\"name\":\"Journal of cell science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529879/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of cell science\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1242/jcs.262166\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of cell science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1242/jcs.262166","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/23 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
VISION - an open-source software for automated multi-dimensional image analysis of cellular biophysics.
Environment-sensitive probes are frequently used in spectral and 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 easy adoption.