CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Examining cells by microscopy has long been a primary method for studying cellular function. When cells are stained appropriately, visual analysis can reveal biological mechanisms. Advanced microscopes can now, in a single day, easily collect thousands of high resolution images of cells from time-lapse experiments and from large-scale screens using chemical compounds, RNA interference (RNAi) reagents, or expression plasmids [1-5]. However, a bottleneck exists at the image analysis stage. Several pioneering large screens have been scored through visual inspection by expert biologists [6,7], whose interpretive ability will not soon be replicated by a computer. Still, for most applications, image cytometry (automated cell image analysis) is strongly preferable to analysis by eye. In fact, in some cases image cytometry is absolutely required to extract the full spectrum of information present in biological images, for reasons we discuss here.First, while human observers typically score one or at most a few cellular features, image cytometry simultaneously yields many informative measures of cells, including the intensity and localization of each fluorescently labeled cellular component (for example, DNA or protein) within each subcellular compartment, as well as the number, size, and shape of those subcellular compartments. Image-based analysis is thus versatile, inherently multiplexed, and high in information content. Like flow cytometry, image cytometry measures the per-cell amount of protein and DNA, but can more conveniently handle hundreds of thousands of distinct samples and is also compatible with adherent cell types, time-lapse samples, and intact tissues. In addition, image cytometry can accurately measure protein texture and localization as well as cell shape and size.Second, human-scored image analysis is qualitative, usually categorizing samples as 'hits' (where normal physiology is grossly disturbed) or 'non-hits'. By contrast, automated analysis rapidly pr