| Autor: |
Perrino G; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy., Napolitano S; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy.; Department of Chemical, Materials and Industrial Production Engineering, University of Naples Federico II, Naples, Italy., Galdi F; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy., La Regina A; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy., Fiore D; Department of Mathematics and Applications 'R. Caccioppoli', University of Naples Federico II, Naples, Italy., Giuliano T; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy., di Bernardo M; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.; SSM - School for Advanced Studies, Naples, Italy., di Bernardo D; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy. dibernardo@tigem.it.; Department of Chemical, Materials and Industrial Production Engineering, University of Naples Federico II, Naples, Italy. dibernardo@tigem.it. |
| Abstrakt: |
The cell cycle is the process by which eukaryotic cells replicate. Yeast cells cycle asynchronously with each cell in the population budding at a different time. Although there are several experimental approaches to synchronise cells, these usually work only in the short-term. Here, we build a cyber-genetic system to achieve long-term synchronisation of the cell population, by interfacing genetically modified yeast cells with a computer by means of microfluidics to dynamically change medium, and a microscope to estimate cell cycle phases of individual cells. The computer implements a controller algorithm to decide when, and for how long, to change the growth medium to synchronise the cell-cycle across the population. Our work builds upon solid theoretical foundations provided by Control Engineering. In addition to providing an avenue for yeast cell cycle synchronisation, our work shows that control engineering can be used to automatically steer complex biological processes towards desired behaviours similarly to what is currently done with robots and autonomous vehicles. |
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