  Noise in gene expression, either due to inherent stochasticity or to varying
inter- and intracellular environment, can generate significant cell-to-cell
variability of protein levels in clonal populations. We present a theoretical
framework, based on stochastic processes, to quantify the different sources of
gene expression noise taking cell division explicitly into account. Analytical,
time-dependent solutions for the noise contributions arising from the major
steps involved in protein synthesis are derived. The analysis shows that the
induction level of the activator or transcription factor is crucial for the
characteristic signature of the dominant source of gene expression noise and
thus bridges the gap between seemingly contradictory experimental results.
Furthermore, on the basis of experimentally measured cell distributions, our
simulations suggest that transcription factor binding and promoter activation
can be modelled independently of each other with sufficient accuracy.
