Ron Milo
Harvard Medical School
Quantitative understanding of protein networks requires the measurement of endogenous protein dynamics in living cells. We developed a method to measure concentration and localization dynamics of proteins expressed from their endogenous chromosomal locations in individual human cells. A library of over 200 cell clones, each with a different gene tagged with yellow fluorescent protein (YFP), was constructed. Each clone expressed a full length protein tagged with retrovirally delivered YFP as an internal exon. The fluorescently tagged proteins were tracked over several cell cycles in individual cells by time-lapse microscopy and image analysis tools. Synchronization of the cells was achieved in-silico by aligning the dynamics of each cell between consecutive divisions. We observe widespread (40%) cell-cycle dependence of nuclear protein levels. We also quantified cell-cell variability, otherwise masked by assays that average over cell populations. We found cell-cell variability with a standard deviation that ranged, for different proteins, between 15% and 30% of the mean. Protein levels mixing time was found to be longer than 2 generations (over 40 hours) for many proteins. Such persistent memory in protein fluctuations may underlie individuality in cell behavior and set a timescale needed for signals to fully affect every member of a cell population. The present approach opens the possibility of studying, on the proteomic scale, the spatio-temporal behavior and variability of proteins in individual human cells.