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Updated: Sep 1, 2025

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
Published on: April 27, 2021
Connecting single-cell ATP dynamics to overflow metabolism, cell growth, and the cell cycle in Escherichia coli
Wei-Hsiang Lin1, Christine Jacobs-Wagner1
1Department of Biology, Stanford University, Palo Alto, CA 94305, USA; Chemistry, Engineering, Medicine for Human Health Institute, Stanford University, Palo Alto, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Palo Alto, CA 94305, USA.
Abstract:
Adenosine triphosphate (ATP) is an abundant and essential metabolite that cells consume and regenerate in large amounts to support growth. Although numerous studies have inferred the intracellular concentration of ATP in bacterial cultures, what happens in individual bacterial cells under stable growth conditions is less clear. Here, we use the QUEEN-2m biosensor to quantify ATP dynamics in single Escherichia coli cells in relation to their growth rate, metabolism, cell cycle, and cell lineage. We find that ATP dynamics are more complex than expected from population studies and are associated with growth-rate variability. Under stable nutrient-rich condition, cells can display large fluctuations in ATP level that are partially coordinated with the cell cycle. Abrogation of aerobic acetate fermentation (overflow metabolism) through genetic deletion considerably reduces both the amplitude of ATP level fluctuations and the cell-cycle trend. Similarly, growth in media in which acetate fermentation is lower or absent results in the reduction of ATP level fluctuation and cell-cycle trend. This suggests that overflow metabolism exhibits temporal dynamics, which contributes to fluctuating ATP levels during growth. Remarkably, at the single-cell level, growth rate negatively correlates with the amplitude of ATP fluctuation for each tested condition, linking ATP dynamics to growth-rate heterogeneity in clonal populations. Our work highlights the importance of single-cell analysis in studying metabolism and its implication to phenotypic diversity and cell growth.
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