CellStress - open source image analysis program for single-cell analysis

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.