Based on previously identified objects from the raw signal (Figure 1A-D), other cellular features can be inferred (Figure 1E) and several metrics dependent on the detected objects can be computed (Figure 1F).įigure 1 - A) Raw signal from the DAPI channel B) Nuclei object detection C) Raw signal from the Alexa488 channel D) Detection of objects representing $\beta$-tubulin staining E) Inferred cytoplasm objects based on the detection of B) and D) F) Color-coder cell objects based on the percentage of surface in contact with other cell objects (neighbours). This was performed by manually adjusting detection parameters (see Methods section). To obtain objects from the images captured in the screen, object detection using Cell Profiler was performed. I know citations are due here, I'm looking into to do that in the best way. Of particular interest is the ability of these screens to probe into the cell-to-cell variability of responses to perturbations, where the population context of cells can be a determinant condition to respond in variable ways when perturbed. It’s ability to have single-cell measurements is a quality which only very recently is starting to be acquired in other fields of molecular biology, and thus makes it by excellence a data-rich method. Although generally slower than other screening methods, the amount and variety of data acquired in high-throughput image-based screening is unsurpassed. Image-based screens are able to measure hundreds of cellular and sub-cellular features quantitatively and are therefore extremely powerful. In response to this, high-throughput screening of chemical compounds is a tool that is increasingly more used and in high demand due to its ability to investigate hundreds of thousands of compounds in a relatively short time. While there is increasing need for the discovery of new drugs, the number of new approved drugs per decade is in fast decline. In this small rotation project, I optimized the usage of existing computational tools for the analysis of image-based chemical screens at the single-cell level. Image-based screens, in particular, can measure hundreds of cellular features at the single-cell level and are therefore of great interest. A combination of increasing demand for new drugs and advances in automation have made high-throughput screening of chemical compounds a reality.
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