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Single cell profiling framework reveals metabolic subpopulations as drivers of bioproduction heterogeneity.


ABSTRACT: Heterogeneity within clonal cell populations remains a critical bottleneck within bioprocess engineering, notably by undermining bioproduction yields. Efforts to mitigate its impact have, however, been hampered by technological difficulties quantifying metabolism at the single-cell level. Here, we propose a framework based on single-cell biosensor analysis that enables robust characterisation of cell's metabolic states, leveraging it to detect and isolate isogeneic heterogeneity in response to environmental perturbations and within microbial cell factories. We identify acute and gradual glucose depletion to induce differentiation of metabolically distinct subpopulations and reveal these subpopulations to exhibit differential production capabilities, with lower intracellular pH subpopulations exhibiting enhanced product accumulation within violacein-producing strains but reduced yields within lycopene-producing strains. Lastly, we highlight galactose cultivation as a method to modulate subpopulation dynamics towards higher-producing lycopene phenotypes. Altogether, our research provides insights into subpopulation differentiation and establishes promising avenues for the engineering of more robust and higher-producing strains.

SUBMITTER: Savigny J 

PROVIDER: S-EPMC12816005 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature

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Single cell profiling framework reveals metabolic subpopulations as drivers of bioproduction heterogeneity.

Savigny Juline J   Shabestary Kiyan K   Portela Maria M   Klemm Cinzia C   Sum Yvette Y   Hapeta Piotr P   Storch Marko M   Rowlands Christopher C   Ledesma-Amaro Rodrigo R  

Nature communications 20251221 1


Heterogeneity within clonal cell populations remains a critical bottleneck within bioprocess engineering, notably by undermining bioproduction yields. Efforts to mitigate its impact have, however, been hampered by technological difficulties quantifying metabolism at the single-cell level. Here, we propose a framework based on single-cell biosensor analysis that enables robust characterisation of cell's metabolic states, leveraging it to detect and isolate isogeneic heterogeneity in response to e  ...[more]

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