SYSTEMATIC PROMOTER TUNING IN NEGATIVE AUTOREGULATORY TRANSCRIPTION NETWORKS

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Pavel Zach, H. Kasl, V. Babuka, D. Georgiev

University of West Bohemia, Czech Republic

Precise and predictable gene expression is fundamental for creating new synthetic circuits inside cells. Since gene expression is mainly controlled by the promoter sequences, being able to quickly design promoters with minimal experimental workload is desired. Existing promoter libraries provide a design starting point but the final promoter sequence will vary with experimental conditions, additional binding sites, and other design elements. Here, we present a simple algorithm for tuning the negative autoregulatory transcription network motif using differential in vivo RNA- based computations. The algorithm comprises two stages: sensitivity to perturbations is minimized first and the steady state level of the gene product is set second. Tuning is achieved by adjusting spacings between the consensus sequences in the -10/-35 and transcription factor binding site promoter regions. Differential RNA- based computations are proposed to minimize measurement sensitivity to external noise. Computations are realized by hybridization reactions between modified 3′- UTRs and 5′-UTRs of mRNA transcribed from different promoter designs. Convergence of the algorithm to the desired design irrespective of the binding kinetics is shown analytically. Accuracy of the method in measuring differences in gene expression from different promoter sequences is shown in silico. The feasibility of the approach and the underlying sequential tuning protocol are demonstrated in vivo. Gene expression is measured using both the described RT-qPCR measurements and fluorescence measurements for comparison. Several time- saving protocol innovations are introduced.