Protein dynamics in individual human cells: experiment and theory.
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.
Cohen
Ariel Aharon
AA
Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.
Kalisky
Tomer
T
Mayo
Avi
A
Geva-Zatorsky
Naama
N
Danon
Tamar
T
Issaeva
Irina
I
Kopito
Ronen Benjamine
RB
Perzov
Natalie
N
Milo
Ron
R
Sigal
Alex
A
Alon
Uri
U
D002138:Calibration; D002453:Cell Cycle; D006801:Humans; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D012333:RNA, Messenger / Q000235:genetics; D013050:Spectrometry, Fluorescence
D011506:Proteins; D012333:RNA, Messenger