Protein dynamics in individual human cells: Experiment and theory

Ariel Aharon Cohen, Tomer Kalisky, Avi Mayo, Naama Geva-Zatorsky, Tamar Danon, Irina Issaeva, Ronen Benjamine Kopito, Natalie Perzov, Ron Milo, Alex Sigal, Uri Alon

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

A current challenge in biology is to understand the dynamics of protein circuits in living human cells. Can one define and test equations for the dynamics and variability of a protein over time? Here, we address this experimentally and theoretically, by means of accurate time-resolved measurements of endogenously tagged proteins in individual human cells. As a model system, we choose three stable proteins displaying cell-cycle-dependant dynamics. We find that protein accumulation with time per cell is quadratic for proteins with long mRNA life times and approximately linear for a protein with short mRNA lifetime. Both behaviors correspond to a classical model of transcription and translation. A stochastic model, in which genes slowly switch between ON and OFF states, captures measured cell-cell variability. The data suggests, in accordance with the model, that switching to the gene ON state is exponentially distributed and that the cell-cell distribution of protein levels can be approximated by a Gamma distribution throughout the cell cycle. These results suggest that relatively simple models may describe protein dynamics in individual human cells.

Original languageEnglish
Article numbere4901
JournalPLoS ONE
Volume4
Issue number4
DOIs
StatePublished - 17 Apr 2009
Externally publishedYes

Bibliographical note

Funding Information:
We thank the Kahn Family Foundation and the Israel Science Foundation for support. We thank Michael Elbaum and his lab for discussions and assistance with the calibration of fluorescence levels.

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