Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging

• Published in: Nature communications Vol. 10; no. 1; p. 848
• Main Authors: Vasdekis, A. E., Alanazi, H., Silverman, A. M., Williams, C. J., Canul, A. J., Cliff, J. B., Dohnalkova, A. C., Stephanopoulos, G.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19-02-2019; Nature Publishing Group; Nature Portfolio
• Subjects: 132/124; 14/63; 631/553/2707; 631/61/318; 639/766/747; BASIC BIOLOGICAL SCIENCES; Biodegradation; Cytosol - metabolism; Heterogeneity; Humanities and Social Sciences; Image enhancement; Image processing; Image Processing, Computer-Assisted - methods; Lipid Droplets - metabolism; lipids; Macromolecules; Mass spectrometry; Mass spectroscopy; Metabolic engineering; Metabolism; Microscopy; Microscopy - methods; multidisciplinary; Noise; Optical Imaging - methods; Optimization; Productivity; Proteins; Resource allocation; Science; Science (multidisciplinary); Secondary ion mass spectrometry; Single-Cell Analysis - methods; Spectrometry, Mass, Secondary Ion - methods; Strategy; Subpopulations; Tradeoffs; triacylglycerol; Triglycerides; Triglycerides - metabolism; Yarrowia - growth & development; Yarrowia - metabolism; Yarrowia lipolytica; Yeast
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-019-08717-w

Optimal metabolic trade-offs between growth and productivity are key constraints in strain optimization by metabolic engineering; however, how cellular noise impacts these trade-offs and drives the emergence of subpopulations with distinct resource allocation strategies, remains largely unknown. Here, we introduce a single-cell strategy for quantifying the trade-offs between triacylglycerol production and growth in the oleaginous microorganism
Yarrowia lipolytica
. The strategy relies on high-throughput quantitative-phase imaging and, enabled by nanoscale secondary ion mass spectrometry analyses and dedicated image processing, allows us to image how resources are partitioned between growth and productivity. Enhanced precision over population-averaging biotechnologies and conventional microscopy demonstrates how cellular noise impacts growth and productivity differently. As such, subpopulations with distinct metabolic trade-offs emerge, with notable impacts on strain performance and robustness. By quantifying the self-degradation of cytosolic macromolecules under nutrient-limiting conditions, we discover the cell-to-cell heterogeneity in protein and fatty-acid recycling, unmasking a potential bet-hedging strategy under starvation.
How cellular noise impacts metabolic trade-offs remains unknown. Here, the authors use a quantitative single-cell mass imaging strategy to reveal that cellular noise impacts cellular biomass and triacylglycerol accumulation, as well as protein and fatty-acid recycling under starvation, differently.