Abrupt and Dynamic Changes
in Gene Expression Revealed
by Live Cell Arrays
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Abstract
A description of the noise associated with gene expression
is presented,
based on a simplified form of the combined multistep processes of
transcription and translation. These processes are influenced by numerous
factors, including the accessibility of promoter regions to the transcriptional
machinery, the kinetics of assembly of the transcription complexes,
and the synthesis and degradation of both mRNA and proteins, among
others. Ultimately, stochasticity in cellular processes results in
variation in protein levels. Here we constructed a rationally designed
RNA-based transcriptional activator to reduce these variables and
provide a cleaner, more detailed portrayal of cellular noise. Functioning
at a level comparable to natural transcription activation, this activator
is isolated to a <i>lacZ</i> reporter gene in yeast cells
to quantitatively describe the efficiency of the combined processes
of transcription and translation. By employing single-cell array techniques
to monitor individual cells simultaneously and in real time, a statistical
approach to investigate noise inherent in gene expression is possible.
Live cell arrays enabled cell populations to be characterized temporally
at the individual cell level. The array platform allowed for a relative
measure of protein production in real time and could characterize
protein bursts with variable size and random timing, such that bursts
occurred in a temporally indiscriminate fashion. The inherent variability
and randomness of these processes is characterized, with almost half
(47%) of cells experiencing bursting behavior at least once over the
course of the experiment. We demonstrate that cells identified on
the upper periphery of activity exhibit behaviors that are substantially
different from the majority of the population, and such variable activities
within a population will provide a more accurate characterization
of the population