title: Single-cell protein dynamics reproduce universal fluctuations in cell populations.
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 cells exhibit the same properties as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the universal distribution shape measured in populations under a wide range of conditions and in two distinct microorganisms; the mean and variance of the traces over time obey the same quadratic relation. Analyzing the individual protein traces reveals that within a cell cycle protein content increases exponentially, with a rate that varies from cycle to cycle. This leads to a compact description of the trace as a 3-variable stochastic process -exponential rate, cell cycle duration and value at the cycle start- sampled once a cycle. This description is sufficient to reproduce both universal statistical properties of the protein fluctuations. 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.
authors.affiliation: Department of Chemical Engineering, Technion, 32000, Haifa, Israel. nbrenner@tx.technion.ac.il.|Laboratory of Network Biology, Technion, 32000, Haifa, Israel. nbrenner@tx.technion.ac.il.
authors.forename: Naama
authors.initials: N
authors.lastname: Brenner
authors.affiliation: Laboratory of Network Biology, Technion, 32000, Haifa, Israel.|Department of Physics, Technion, 32000, Haifa, Israel.
authors.forename: Erez
authors.initials: E
authors.lastname: Braun
authors.affiliation: Department of Physics and Astronomy, University of Pittsburgh, 15260, Pittsburgh, PA, USA.
authors.forename: Anna
authors.initials: A
authors.lastname: Yoney
authors.affiliation: Department of Mathematics, Technion, 32000, Haifa, Israel.
authors.forename: Lee
authors.initials: L
authors.lastname: Susman
authors.affiliation: Department of Physics and Astronomy, University of Pittsburgh, 15260, Pittsburgh, PA, USA.
authors.forename: James
authors.initials: J
authors.lastname: Rotella
authors.affiliation: Department of Physics and Astronomy, University of Pittsburgh, 15260, Pittsburgh, PA, USA. hsalman@pitt.edu.|Department of Computational and Systems Biology, University of Pittsburgh, 15260, Pittsburgh, PA, USA. hsalman@pitt.edu.
authors.forename: Hanna
authors.initials: H
authors.lastname: Salman
mesh_terms: D003198:Computer Simulation; D004926:Escherichia coli / Q000502:physiology*; D029968:Escherichia coli Proteins / Q000378:metabolism*; D018628:Gene Dosage / Q000502:physiology*; D008954:Models, Biological; D008956:Models, Chemical; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D029968:Escherichia coli Proteins
keywords: Living systems: Biological networks