ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data.

RNA-engineered systems offer simple and versatile control over gene expression in many organisms. In particular, the design and implementation of riboswitches presents a unique opportunity to manipulate any reporter device in cis, executing tight temporal and spatial control at low metabolic costs. Assembled to higher order genetic circuits, such riboswitch-regulated devices may efficiently process logical operations. Here, we propose a hierarchical stochastic modeling approach to characterize an in silico repressor gate based on neomycin- and tetracycline-sensitive riboswitches. The model was calibrated on rich, transient in vivo single-cell data to account for cell-to-cell variability. To capture the effect of this variability on gate performance we employed the well-known ROC-analysis and derived a novel performance indicator for logic gates. Introduction of such a performance measure is necessary, since we aimed to assess the correct functionality of the gate at the single-cell level-a prerequisite for its further adaption to a genetic circuitry. Our results may be applied to other genetic devices to analyze their efficiency and ensure their correct performance in the light of cell-to-cell variability.