Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Abstract Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure...

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Main Authors: Francisca Monteiro, Georg Hubmann, Vakil Takhaveev, Silke R Vedelaar, Justin Norder, Johan Hekelaar, Joana Saldida, Athanasios Litsios, Hein J Wijma, Alexander Schmidt, Matthias Heinemann
Format: Article
Language:English
Published: Springer Nature 2019-12-01
Series:Molecular Systems Biology
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Online Access:https://doi.org/10.15252/msb.20199071
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Summary:Abstract Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single‐cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell‐intrinsic correlation between glycolytic flux and levels of fructose‐1,6‐bisphosphate (FBP), we transplanted the B. subtilis FBP‐binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.
ISSN:1744-4292