Control of cell state transitions

Oleksii S. Rukhlenko, Melinda Halasz, Nora Rauch, Vadim Zhernovkov, Thomas Prince, Kieran Wynne, Stephanie Maher, Eugene Kashdan, Kenneth MacLeod, Neil O. Carragher, Walter Kolch and Boris N. Kholodenko ()
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Oleksii S. Rukhlenko: University College Dublin
Melinda Halasz: University College Dublin
Nora Rauch: University College Dublin
Vadim Zhernovkov: University College Dublin
Thomas Prince: University College Dublin
Kieran Wynne: University College Dublin
Stephanie Maher: University College Dublin
Eugene Kashdan: University College Dublin
Kenneth MacLeod: The University of Edinburgh
Neil O. Carragher: The University of Edinburgh
Walter Kolch: University College Dublin
Boris N. Kholodenko: University College Dublin

Nature, 2022, vol. 609, issue 7929, 975-985

Abstract: Abstract Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology. Here we present cell state transition assessment and regulation (cSTAR), an approach for mapping cell states, modelling transitions between them and predicting targeted interventions to convert cell fate decisions. cSTAR uses omics data as input, classifies cell states, and develops a workflow that transforms the input data into mechanistic models that identify a core signalling network, which controls cell fate transitions by influencing whole-cell networks. By integrating signalling and phenotypic data, cSTAR models how cells manoeuvre in Waddington’s landscape1 and make decisions about which cell fate to adopt. Notably, cSTAR devises interventions to control the movement of cells in Waddington’s landscape. Testing cSTAR in a cellular model of differentiation and proliferation shows a high correlation between quantitative predictions and experimental data. Applying cSTAR to different types of perturbation and omics datasets, including single-cell data, demonstrates its flexibility and scalability and provides new biological insights. The ability of cSTAR to identify targeted perturbations that interconvert cell fates will enable designer approaches for manipulating cellular development pathways and mechanistically underpinned therapeutic interventions.

Date: 2022
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DOI: 10.1038/s41586-022-05194-y

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