Protein distributions measured under a broad set of conditions in bacteria and yeast exhibit a universal skewed shape, with variances depending quadratically on means. For bacteria these properties are reproduced by protein accumulation and division dynamics across generations. We present a stochastic growth-and-division model with feedback which captures these observed properties. The limiting copy number distribution is calculated exactly, and a single parameter is found to determine the distribution shape and the variance-to-mean relation. Estimating this parameter from bacterial temporal data reproduces the measured universal distribution shape with high accuracy, and leads to predictions for future experiments.
Protein distributions measured under a broad set of conditions in bacteria and yeast were shown to exhibit a common skewed shape, with variances depending quadratically on means. For bacteria these properties were reproduced by temporal measurements of protein content, showing accumulation and division across generations. Here we present a stochastic growth-and-division model with feedback which captures these observed properties. The limiting copy number distribution is calculated exactly, and a single parameter is found to determine the distribution shape and the variance-to-mean relation. Estimating this parameter from bacterial temporal data reproduces the measured distribution shape with high accuracy, and leads to predictions for future experiments.
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are reproduced by protein
were reproduced by temporal measurements of protein content, showing
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dynamics
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universal