High Content Biology is an automated fluorescence microscopy method, drawing on computer-based image analysis to permit rapid, highly parallel biological research and drug discovery.
Combining fluorescence microscopy, microtitre plates and powerful image analysis algorithms, it is possible to acquire a deeper knowledge of multiple biochemical pathways at a single-cell level.
The steps involved in performing a High Content Biology experiment are as follows:
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Design experiment
Prepare plate maps showing how cells in the microtitre plates will be treated. Transfer cell lines to
the required number of microtitre plates and treat when cells are between 50-80% confluency.
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Execute treatment phase of experiment.
Treat cells with various compounds as per the plate map.
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Fix and stain cells.
This step is similar to standard fluorescence microscopy with the cells usually being treated with a primary antibody to detect the protein of interest followed
by a fluorescently-labelled secondary antibody which detects primary antibody that has bound the target protein.
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Run plates on a HCB Platform (eg Cellomics Arrayscan)
Acquire fluorescence images.
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Analyse Images.
Cell images are analysed using specialised software either supplied with the particular instrument used to capture the images or else third party
analysis software is also available (eg Definiens).
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Associate Experimental Independent & Dependent Variables.
The analysis software will return numbers for each well within the plate. The next step is to relate these numbers (measured variables) back to the treatment
conditions of the original experiment (Independent Variables) using the platemaps developed in step 1. Note at Imagen Biotech we have automated this step by
developing an Excel Addin called the PlateMaker Wizard.
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Analyse Data
The flat data file can now be used to generate graphs and perform various statistical analyses to gain a deeper understanding of the rich data set that High Content Biology
platforms deliver.
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Delivery Data to Customer
We pride ourselves on returning data to the customer as it generated. That way you do not need to wait to the end of the study to see how your compound series is unfolding.