One aim of synthetic biology is to exert systematic control over cellular behavior, either for medical purposes or to "program" microorganisms. An engineering approach to the design of biological controllers demands a quantitative understanding of the dynamics of both the system to be controlled and the controllers themselves. Here we focus on a widely used method of exerting control in bacterial cells: plasmid vectors bearing gene-promoter pairs. We study two variants of the simplest such element, an unregulated promoter constitutively expressing its gene, against the varying genomic background of four Escherichia coli cell strains. Absolute protein numbers and rates of expression vary with both cell strain and plasmid type, as does the variability of expression across the population. Total variability is most strongly coupled to the cell division process, and after cell size is scaled away, plasmid copy number regulation emerges as a significant effect. We present simple models that capture the main features of the system behavior. Our results confirm that complex interactions between plasmids and their hosts can have significant effects on both expression and variability, even in deliberately simplified systems.

Plasmid-borne gene expression systems have found wide application in the emerging fields of systems biology and synthetic biology, where plasmids are used to implement simple network architectures, either to test systems biology hypotheses about issues such as gene expression noise or as a means of exerting artificial control over a cell's dynamics. In both these cases, fluorescent proteins are commonly applied as a means of monitoring the expression of genes in the living cell, and efforts have been made to quantify protein expression levels through fluorescence intensity calibration and by monitoring the partitioning of proteins among the two daughter cells after division; such quantification is important in formulating the predictive models desired in systems and synthetic biology research. A potential pitfall of using plasmid-based gene expression systems is that the high protein levels associated with expression from plasmids can lead to the formation of inclusion bodies, insoluble aggregates of misfolded, nonfunctional proteins that will not generate fluorescence output; proteins caught in these inclusion bodies are thus "dark" to fluorescence-based detection methods. If significant numbers of proteins are incorporated into inclusion bodies rather than becoming biologically active, quantitative results obtained by fluorescent measurements will be skewed; we investigate this phenomenon here. We have created two plasmid constructs with differing average copy numbers, both incorporating an unregulated promoter (P(LtetO-1) in the absence of TetR) expressing the GFP derivative enhanced green fluorescent protein (EGFP), and inserted them into Escherichia coli bacterial cells (a common model organism for work on the dynamics of prokaryotic gene expression). We extracted the inclusion bodies, denatured them, and refolded them to render them active, obtaining a measurement of the average number of EGFP per cell locked into these aggregates; at the same time, we used calibrated fluorescent intensity measurements to determine the average number of active EGFP present per cell. Both measurements were carried out as a function of cellular doubling time, over a range of 45-75 min. We found that the ratio of inclusion body EGFP to active EGFP varied strongly as a function of the cellular growth rate, and that the number of "dark" proteins in the aggregates could in fact be substantial, reaching ratios as high as approximately five proteins locked into inclusion bodies for every active protein (at the fastest growth rate), and dropping to ratios well below 1 (for the slowest growth rate). Our results suggest that efforts to compare computational models to protein numbers derived from fluorescence measurements should take inclusion body loss into account, especially when working with rapidly growing cells.