Cell population heterogeneity in expression of a gene-switching network with fluorescent markers of different half-lives

We studied the distribution of expression levels amongst the cells of an Escherichia coli population carrying a gene-switching network, known as the genetic toggle. We employed two green fluorescent protein (GFP) reporter proteins with different half-lives and characterized the effect of isopropyl-β-d-thiogalactopyranoside (IPTG) inducer concentration on fluorescence distribution characteristics. Our flow cytometric measurements indicated that there is a spread of fluorescence phenotypes of one to three orders of magnitude, due to the highly heterogeneous nature of the cell populations under investigation. Moreover, the shape of the distribution at a specific quasi-time-invariant reference state, defined for comparison purposes, strongly depended on inducer concentration. For very low and very high inducer concentrations, the distributions at the reference state are unimodal. On the contrary, for intermediate IPTG concentrations, two distinct subpopulations were formed below and above a single-cell threshold, resulting in distributions with a bimodal shape. The region of inducer concentrations where bimodality is observed is the same and independent of GFP half-life. Bimodal number density functions are not only obtained at the reference state. Transient studies revealed that even in cases where the distribution at the reference state is unimodal, the distribution becomes bimodal for a period of time required for the population to pass through the single-cell induction threshold. However, this feature was only captured by the system with the reduced half-life GFP. A simple single-cell model was used to shed light into the effect of inducer concentration and GFP half-life on the shape of the experimentally measured number density functions. The wide range of fluorescent phenotypes and the inability of the average population properties to fully characterize network behavior, indicate the importance of taking into account cell population heterogeneity when designing such a gene-switching network for biotechnological and biomedical applications.