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Longitudinal single-cell chemical imaging of engineered strains reveals heterogeneity in fatty acid production

Nathan Tague, Haonan Lin, Jean-Baptiste Lugagne, Owen M. O’Connor, Deeya Burman, Wilson W. Wong, Ji-Xin Cheng, View ORCID ProfileMary J. Dunlop
doi: https://doi.org/10.1101/2021.07.26.453865
Nathan Tague
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
bBiological Design Center, Boston University, Boston, MA, USA 02215
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Haonan Lin
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
cPhotonics Center, Boston University, Boston, MA, USA 02215
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Jean-Baptiste Lugagne
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
bBiological Design Center, Boston University, Boston, MA, USA 02215
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Owen M. O’Connor
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
bBiological Design Center, Boston University, Boston, MA, USA 02215
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Deeya Burman
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
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Wilson W. Wong
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
bBiological Design Center, Boston University, Boston, MA, USA 02215
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Ji-Xin Cheng
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
cPhotonics Center, Boston University, Boston, MA, USA 02215
dDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, USA 02215
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  • For correspondence: mjdunlop@bu.edu jxcheng@bu.edu
Mary J. Dunlop
aDepartment of Biomedical Engineering, Boston University, Boston, MA, USA 02215
bBiological Design Center, Boston University, Boston, MA, USA 02215
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  • ORCID record for Mary J. Dunlop
  • For correspondence: mjdunlop@bu.edu jxcheng@bu.edu
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Abstract

Understanding metabolic heterogeneity is critical for optimizing microbial production of valuable chemicals, but requires tools that can quantify metabolites at the single-cell level over time. Here, we develop longitudinal hyperspectral stimulated Raman scattering (SRS) chemical imaging to directly visualize free fatty acids in engineered Escherichia coli over many cell cycles. We also develop compositional analysis to determine the chain length and unsaturation of the fatty acids in living cells. Our method reveals substantial heterogeneity in fatty acid production among and within colonies that emerges over the course of many generations. Interestingly, the strains display distinct types of production heterogeneity in an enzyme-dependent manner. By pairing time-lapse and SRS imaging, we examine the relationship between growth and production at the single-cell level. Single-cell quantification does not show a significant growth-production tradeoff in a strain that exhibits high production heterogeneity. Our results demonstrate that cell-to-cell production heterogeneity is pervasive and provide a means to link single-cell and population-level production.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵1 Co-first authors

  • Substantial new experimental data, extensively revised text

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted September 25, 2022.
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Longitudinal single-cell chemical imaging of engineered strains reveals heterogeneity in fatty acid production
Nathan Tague, Haonan Lin, Jean-Baptiste Lugagne, Owen M. O’Connor, Deeya Burman, Wilson W. Wong, Ji-Xin Cheng, Mary J. Dunlop
bioRxiv 2021.07.26.453865; doi: https://doi.org/10.1101/2021.07.26.453865
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Longitudinal single-cell chemical imaging of engineered strains reveals heterogeneity in fatty acid production
Nathan Tague, Haonan Lin, Jean-Baptiste Lugagne, Owen M. O’Connor, Deeya Burman, Wilson W. Wong, Ji-Xin Cheng, Mary J. Dunlop
bioRxiv 2021.07.26.453865; doi: https://doi.org/10.1101/2021.07.26.453865

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