Tuneable Synthetic Genetic Devices

  • Vittorio Bartoli

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


Synthetic genetic circuits are gene regulatory networks used to engineer biological systems to carry out useful functions. Moving circuits between environments or host cells alters their function in ways we can’t predict, leading to circuit failures that can only be fixed by laboriously rebuilding them. Here, we propose a novel regulatory motif that controls transcription and translation of a gene. We implemented the motif to design a device - a tuneable expression system (TES) that used a riboregulator to activate translation of a gene in response to cognate small RNAs (sRNA). Transcription of the gene and sRNA were independently regulated by two sensors that were activated in response to different inducers, allowing us to dynamically tune the device’s response function. The TES’s outputs at high and low inputs could be shifted 4.5 and 28-fold, respectively. We tested the TES in a range of glucose concentrations to emulate how these conditions would affect device performance in industry and found that it produced protein >2-times faster in higher glucose concentrations. We showed that the TES can be regulated so protein production rate remains constant in different glucose concentrations. We then used the TES to build a tuneable repressor protein based NOT gate, whose transition between on and off states can be tuned over a >6-fold range. However, in all devices, tuning the device reduced its fold-change and separation between populations of cells with high and low inputs. Using deterministic and thermodynamic models we found we could improve the device’s performance by increasing the rate of sRNA transcription and removing a self-cleaving ribozyme insulator that interfered with riboregulator function. Circuits built using the TES could be tuned and fixed dynamically, removing the need to reassemble them from new parts and accelerating genetic circuit development. Furthermore, TESs provide the basis for novel adaptive circuits, systems that self-regulate their behaviour to be optimal in all condition.
Date of Award29 Sep 2020
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorMario Di Bernardo (Supervisor) & Thomas E Gorochowski (Supervisor)


  • Synthetic Biology
  • Systems Biology
  • Gene regulation
  • Gene expression
  • Genetic circuit engineering

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