Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity

Kiyan Shabestary (), Cinzia Klemm, Benedict Carling, James Marshall, Juline Savigny, Marko Storch and Rodrigo Ledesma-Amaro ()
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Kiyan Shabestary: Imperial College London
Cinzia Klemm: Imperial College London
Benedict Carling: Imperial College London
James Marshall: Imperial College London
Juline Savigny: Imperial College London
Marko Storch: Imperial College Translation & Innovation Hub
Rodrigo Ledesma-Amaro: Imperial College London

Nature Communications, 2024, vol. 15, issue 1, 1-16

Abstract: Abstract In their natural environments, microorganisms mainly operate at suboptimal growth conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is subject to conflicting tasks: growth or survival maximisation. Here, we study this adaptation by systematically measuring the impact of a nitrogen downshift to 24 nitrogen sources on cellular metabolism at the single-cell level. Saccharomyces lineages grown in rich media and exposed to a nitrogen downshift gradually differentiate to form two subpopulations of different cell sizes where one favours growth while the other favours viability with an extended chronological lifespan. This differentiation is asymmetrical with daughter cells representing the new differentiated state with increased viability. We characterise the metabolic response of the subpopulations using RNA sequencing, metabolic biosensors and a transcription factor-tagged GFP library coupled to high-throughput microscopy, imaging more than 800,000 cells. We find that the subpopulation with increased viability is associated with a dormant quiescent state displaying differences in MAPK signalling. Depending on the identity of the nitrogen source present, differentiation into the quiescent state can be actively maintained, attenuated, or aborted. These results establish amino acids as important signalling molecules for the formation of genetically identical subpopulations, involved in chronological lifespan and growth rate determination.

Date: 2024
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DOI: 10.1038/s41467-024-50602-8

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