Current methods to produce stem cell-derived tissues have very limited throughput. By semi-automating tissue differentiation, researchers from the Moscow Institute of Physics and Technology (Dolgoprudny, Russia) and Harvard Medical School (MA, USA) have made the process almost four-times faster for organoid growth, without compromising the quality.
The research, which has been published in Translational Vision Science & Technology, focused on the retina. To overcome the current issues surrounding in vitro retinal tissue growth (e.g., random neuron growth and the time it takes to produce artificial retinas), the investigators increased the number of cells produced and improved their quality.
The team compared the quality of robot- and human-grown cells by producing several thousand retinal tissue samples for automatic processing and the same amount for manual handling. Researchers then scanned the wells housing the tissue samples from the first group and analyzed the resulting images with a Python script that they wrote to perform that specific task.
The program is able to determine the areas in the photos where the fluorescent protein glow is the strongest. As this protein is only produced in developing retinal cells, this means that the high fluorescence intensity can pinpoint parts of the sample with the right tissue. This allows the software to determine the amount of developing retina in each organoid.
According to the investigators, the automation algorithm was able to optimize cell production by simultaneously testing many systems without any adverse effect on tissue quality. The approach reduced the time researchers needed for cell processing from 2 hours to 34 minutes.
“One of our goals in this research has been to scale-up cell differentiation to enable a high-throughput tissue production for drug tests and cell transplantation experiments. Automated sample handling makes it possible to reduce the effort on the part of the personnel and produce several times more cells in the same period of time. With some slight modifications, the algorithm would be applicable to other organoids, not just the retina,” concluded study author, Evgenii Kegeles (Moscow Institute of Physics and Technology).
https://www.regmednet.com/robot-grown-cells-help-to-achieve-faster-organoid-growth-and-selection/
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