Single-cell protein dynamics reproduce universal fluctuations in cell populations

TL;DR

This study demonstrates that temporal protein fluctuations in single bacterial cells exhibit universal statistical features similar to population snapshots, revealing fundamental cellular properties governing protein variability over time.

Contribution

It introduces a compact stochastic model capturing protein dynamics in single cells that explains universal fluctuation patterns observed across different conditions and microorganisms.

Findings

Temporal fluctuations follow universal distribution shapes.

Mean and variance of protein levels obey quadratic relation.

Protein content increases exponentially within cell cycles.

Abstract

Protein variability in single cells has been studied extensively in populations, but little is known about temporal protein fluctuations in a single cell over extended times. We present here traces of protein copy number measured in individual bacteria over multiple generations and investigate their statistical properties, comparing them to previously measured population snapshots. We find that temporal fluctuations in individual traces exhibit the same universal features as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the same universal distribution shape as found in populations measured under a wide range of conditions and in two distinct microorganisms. Additionally, the mean and variance of the traces over time obey the same quadratic relation. Analyzing the temporal features of the protein traces in individual cells, reveals that within a cell cycle protein content increases as an exponential function with a rate that varies from cycle to cycle. This leads to a compact description of the protein trace as a 3-variable stochastic process - the exponential rate, the cell-cycle duration and the value at the cycle start - sampled once each cell cycle. This compact description is sufficient to preserve the universal statistical properties of the protein fluctuations, namely, the protein distribution shape and the quadratic relationship between variance and mean. Our results show that the protein distribution shape is insensitive to sub-cycle intracellular microscopic details and reflects global cellular properties that fluctuate between generations.