Protein overabundance is driven by growth robustness
ORAL
Abstract
Protein expression levels optimize cell fitness: Too low an expression level of essential proteins will slow growth by compromising essential processes; whereas overexpression slows growth by increasing the metabolic load. This trade-off naively predicts that cells maximize their fitness by sufficiency, expressing just enough of each essential protein for function. We test this prediction in the naturally-competent bacterium Acinetobacter baylyi by characterizing the proliferation dynamics of essential-gene knockouts at a single-cell scale (by imaging) as well as at a genome-wide scale (by TFNseq). In these experiments, cells proliferate for multiple generations as target protein levels are diluted from their endogenous levels. This approach facilitates a proteome-scale analysis of protein overabundance. As predicted by the Robustness-Load Trade-Off (RLTO) model, we find that roughly 70% of essential proteins are overabundant and that overabundance increases as the expression level decreases, the signature prediction of the model. These results reveal that robustness plays a fundamental role in determining the expression levels of essential genes and that overabundance is a key mechanism for ensuring robust growth.
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Publication: Lo TW, Choi HJ, Huang D, Wiggins PA (2024) Noise robustness and metabolic load determine the principles of central dogma regulation. Science Advances 10(34)
Choi HJ, Lo TW, Cutler KJ, Huang D, Will WR, Wiggins PA (2024) Protein overabundance is driven by growth robustness. (Submitted to PNAS)
Presenters
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James Choi
University of Washington
Authors
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James Choi
University of Washington
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Teresa W Lo
University of Washington
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Ryan Will
University of Washington
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Kevin Cutler
University of Washington
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Dean Huang
University of Washington
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Paul Wiggins
University of Washington