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Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Henrion, Lucas; Martinez, Juan Andres; Vandenbroucke, Vincent; Delvenne, Mathéo; Telek, Samuel; Zicler, Andrew; Grünberger, Alexander ORCID iD icon 1; Delvigne, Frank
1 Institut für Bio- und Lebensmitteltechnik (BLT), Karlsruher Institut für Technologie (KIT)

Abstract:

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.


Verlagsausgabe §
DOI: 10.5445/IR/1000164411
Veröffentlicht am 15.11.2023
Originalveröffentlichung
DOI: 10.1038/s41467-023-41917-z
Scopus
Zitationen: 4
Web of Science
Zitationen: 4
Dimensions
Zitationen: 9
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Bio- und Lebensmitteltechnik (BLT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2041-1723
KITopen-ID: 1000164411
Erschienen in Nature Communications
Verlag Nature Research
Band 14
Heft 1
Seiten Art.-Nr.: 6128
Vorab online veröffentlicht am 02.10.2023
Schlagwörter Applied microbiology, Cellular noise, Metabolic engineering, Synthetic biology
Nachgewiesen in Web of Science
Dimensions
Scopus
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