High throughput image screening using CellProfiler

Research at the cBITE group is characterized by both high-content and high-throughput image analysis. For this, we routinely utilize CellProfiler, a program designed by the Broad Institute of Harvard and MIT. CellProfiler enables us to design custom-made modules that allow us to extract both quantitative and qualitative features from our acquired images. Examples here include the segmentation of actin fibers, providing us with data concerning the orientation, localization and the number of fibers in different experimental settings.

Extracting morphological features of actin fibers. Top left: original image (U2OS cells on NanoTopoChip), top right: identified single fibers; bottom left: identified cell body and nuclei; bottom right: morphological features extracted from the shape of the fibers. 

Another example is the quantification of a protein of interest of cells cultured on multiple TopoChips. Here, we analyzed 29435 cells to extract cellular and nuclear morphological features and protein intensity levels through ICC. Subsequent data-analysis is performed in R and reveals a steady upregulation of the protein of interest when cells are cultured on micro-topographies. Further data analysis through machine-learning algorithms can reveal the association between morphological features and the upregulation of the protein of interest.

Quantitative image analysis of protein of interest. A) Segmentation of nuclear and cellular morphology B) ICC against the protein of interest located in the nucleus. C) Extraction of integrated intensity measurements of protein of interest reveals a steady upregulation when cells are cultured on micro-topographies. Black dots represent median integrated intensities of individual TopoUnits. Blue dot represents median integrated intensity values of cells cultured on the flat surface.

Further reading

Reimer et al., Sci Rep, 2016
Le et al., Tissue Eng Part A, 2017
Cell Profiler
Caicedo et al. Nature Methods, 2017