Life at low copy number: A single molecule adventure in live cell gene expression

In a living cell, gene expression, the transcription of DNA to mRNA followed by translation to protein, occurs stochastically, as a consequence of the small copy numbers of DNA and mRNA molecules involved. These stochastic events of protein production are difficult to observe directly with measurements on large ensemble of cells due to lack of synchronization among cells. Measurements to date on single cells, however, lack the sensitivity to resolve individual events of protein production.; We demonstrate a microfluidics based assay that allows real-time observation of the expression of beta-galactosidase in living Escherichia coli cells with single molecule sensitivity. We observe that protein production occurs in bursts, with exponentially distributed burst sizes. Application of this assay to probe gene expression in individual budding yeast and mouse embryonic stem cells demonstrate its generality.; We note that many proteins involved in important cellular decisions, such as cell fate and differentiation, are expressed at low levels. We utilize single molecule detection to study the role of low copy numbers lac permease in committing E. coli to bistable metabolic states. We show conclusively that one molecule of permease is insufficient to trigger induction and elucidate the molecular mechanism for decision making in the lac operon.; From the experimentally observed burst statistics, we develop an analytic model showing that the copy number distribution of a protein in a population of cells is Gamma distributed. This model allows us to establish that the two kinetic parameters of protein expression, the burst size and frequency, can be extracted directly from the "noise" in a steady state population measurement and is equivalent to those measured in the real time experiments.; By generalizing the Gamma model to include mRNA as well as protein bursts, we show that it describes accurately population distribution well beyond the low copy number regime, extending into high expression level. We show further that the modulations in protein burst size and frequency, extracted from the model, are correlated to molecular mechanisms regulating the duration and rate of transcriptional bursts, demonstrating the model's utility as an analytical tool for identifying regulation mechanisms on the genome scale.