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Updated: Jul 13, 2026

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression
Published on: April 18, 2021
Cell-to-cell heterogeneity in growth rate and gene expression in Methylobacterium extorquens AM1
Tim J Strovas1, Linda M Sauter, Xiaofeng Guo
1Department of Chemical Engineering, University of Washington, Box 352125, Seattle, WA 98195, USA.
Abstract:
Cell-to-cell heterogeneity in gene expression and growth parameters was assessed in the facultative methylotroph Methylobacterium extorquens AM1. A transcriptional fusion between a well-characterized methylotrophy promoter (P(mxaF)) and gfp(uv) (encoding a variant of green fluorescent protein [GFPuv]) was used to assess single-cell gene expression. Using a flowthrough culture system and laser scanning microscopy, data on fluorescence and cell size were obtained over time through several growth cycles for cells grown on succinate or methanol. Cells were grown continuously with no discernible lag between divisions, and high cell-to-cell variability was observed for cell size at division (2.5-fold range), division time, and growth rate. When individual cells were followed over multiple division cycles, no direct correlation was observed between the growth rate before a division and the subsequent growth rate or between the cell size at division and the subsequent growth rate. The cell-to-cell variability for GFPuv fluorescence from the P(mxaF) promoter was less, with a range on the order of 1.5-fold. Fluorescence and growth rate were also followed during a carbon shift experiment, in which cells growing on succinate were shifted to methanol. Variability of the response was observed, and the growth rate at the time of the shift from succinate to methanol was a predictor of the response. Higher growth rates at the time of the substrate shift resulted in greater decreases in growth rates immediately after the shift, but full induction of P(mxaF)-gfp(uv) was achieved faster. These results demonstrate that in M. extorquens, physiological heterogeneity at the single-cell level plays an important role in determining the population response to the metabolic shift examined.
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