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Principles of metabolic pathway control by biomolecular condensates in cells

Abstract

Phase separation of biomolecules regulates a wide variety of intracellular functions. This process generates membraneless compartments called biomolecular condensates, which can enrich or exclude macromolecules. This property has been exploited to control metabolic pathways by selectively sequestering enzymes within condensates. Here we analyze the conditions under which biomolecular condensates can amplify the yield or selectivity of diverse metabolic pathways. For all these pathways, we show that the efficacy of phase separation can be approximately predicted by a single metric comprising two coarse-grained parameters: the fraction of the enzyme partitioning into the condensates and the change in the enzyme activity inside compared with outside the condensates. We validated the metric using genetically encoded engineered—synthetic—condensates in yeast to regulate acetoin biosynthesis. This metric can guide future experimental efforts in quantifying the relevant parameters to optimize metabolic flux in engineered condensates.

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Fig. 1: A metric to quantify the effects of condensate-induced compartmentalization on an enzymatic reaction.
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Fig. 2: Enzyme enrichment and the enzyme activity coefficient in condensates dictate the outcome of multiple-enzyme cascade reactions via condensates.
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Fig. 3: Condensates modulate a branching reaction pathway more effectively through ν.
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Fig. 4: Biosynthesis of acetoin in S. cerevisiae is optimized via enzyme enrichment in condensates.
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Fig. 5: Partitioning of the substrate increases product biosynthesis via condensate formation in a branched pathway.
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Data availability

All data generated or analyzed during this study are available within the Article and its Supplementary Information and via GitHub at https://github.com/youlab/Condensate_MetabolicEng. All plasmids and strains used in this study are available from the corresponding author upon request. Source data are provided with this paper.

Code availability

The simulation code used in this study is available via GitHub at https://github.com/youlab/Condensate_MetabolicEng.

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Acknowledgements

We thank M. Lalwani for sharing the unpublished yMAL20 strain and for additional advice and suggestions on the study of acetoin biosynthesis. This work was supported by the Air Force Office of Scientific Research (FA9550-20-1-0241 to C.P.B., A.C., J.L.A. and L.Y.) and by NIH (R35GM127042 to A.C.). M.T.W. is supported by the NSF GRFP (DGE-1656466).

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D.L. and L.Y. conceived the idea and performed the computational study. M.T.W., K.-H.S. and K.X. conducted the S. cerevisiae fermentation experiments. D.L., M.T.W., K.-H.S., Y.D., K.X., C.P.B., A.C., J.L.A. and L.Y. analyzed the data and contributed to the discussions and revisions.

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Correspondence to Lingchong You.

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C.P.B. is a founder of and consultant for Nereid Therapeutics. A patent describing the PpID system is currently pending (US 2023/0295638 A1). The other authors declare no competing interests.

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Lee, D., Walls, M.T., Siu, KH. et al. Principles of metabolic pathway control by biomolecular condensates in cells. Nat Chem Eng 2, 198–208 (2025). https://doi.org/10.1038/s44286-025-00193-y

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