Synthetic Biology is gaining an increasingly important role in the scientific community and dedicated research centers are rising all over the world. This discipline introduced the engineering principles of abstraction, modularity and standardization in the biology world; the application of these principles is allowing the design of complex biological systems to program living cells, realizing all sorts of desired function in many fields. These systems consist of DNA sequences, rationally combined to program the genetic instructions for cell behavior customization. Each part should behave as a biological brick for the design of complex genetic programs through functional building blocks; each module undergoes an extensive characterization to provide documentation on its functioning, enabling the rational design of complex circuits. Mathematical modeling accompanies all the design procedure as a tool to describe the behavior of each single genetic module, in a bottom-up fashion that should allow the prediction of more complex systems obtained by the interconnection of pre-characterized parts. However, many unpredictability sources hamper the ideally rational design of those synthetic genetic devices, mainly due to the tangled context-dependency behavior of those parts once placed into an intrinsically complex biological living system. Among others, the finite amount of translational resources in prokaryotic cells leads to an effect called metabolic burden, as a result of which hidden interactions between protein synthesis rates arise, leading to unexpected counterintuitive behaviors. To face this issue, two actions have been proposed in this study: firstly, a recently proposed mathematical modeling solution that included a description of the metabolic load exerted by the expression of recombinant genes have been applied on a case study, highlighting its worth of use and working boundaries; second, a CRISPR interference-based architecture have been developed to be used as an alternative to high resource usage transcriptional protein regulators, studying the underlying mechanism in several circuital configurations and optimizing each forming part in order to achieve the desired specifications. In Chapter 1, an introduction on synthetic biology is presented; in the second part, a brief overview on CRISPR technology and the overall aim of the study are reported. In Chapter 2, a case study evaluating the use of mathematical modeling to properly include metabolic burden in rational design of a set of transcriptional regulator cascades is reported. Firstly, the circuits and expected behavior are introduced, along with the discussion about experimental data, dissenting from what initially predicted. Secondly, the comparison between the use of a classical Hill equation-based model and an improved version that explicitly consider the translational load exerted by the expression of recombinant genes is reported. In Chapter 3, the design and deep characterization of a BioBrick$^{TM}$-compatible CRISPR interference-based repression set of modules is shown; expression optimization of the molecular players is reported and its usability as a low-burden alternative is demonstrated with experimental data and mathematical modeling. Working boundaries, peculiar aspects and rooms for improvements are then highlighted. In Chapter 4, preliminary studies aimed to improve the CRISPR interference system are reported and some of its context-dependencies are highlighted. Effects on repression efficiency due to alteration in the sequence of the RNA molecules addressing the CRISPR machinery to the desired target are discussed; evaluation of problems and opportunities related to the expression of more of this RNA guides are then highlighted. Lastly, an example of behavior of the system in presence of a competitor transcriptional regulator is reported. In Chapter 5 the overall conclusions of this thesis work are drawn.
Overcoming Metabolic Burden in Synthetic Biology: a CRISPR interference approach
BELLATO, MASSIMO
2019-01-30
Abstract
Synthetic Biology is gaining an increasingly important role in the scientific community and dedicated research centers are rising all over the world. This discipline introduced the engineering principles of abstraction, modularity and standardization in the biology world; the application of these principles is allowing the design of complex biological systems to program living cells, realizing all sorts of desired function in many fields. These systems consist of DNA sequences, rationally combined to program the genetic instructions for cell behavior customization. Each part should behave as a biological brick for the design of complex genetic programs through functional building blocks; each module undergoes an extensive characterization to provide documentation on its functioning, enabling the rational design of complex circuits. Mathematical modeling accompanies all the design procedure as a tool to describe the behavior of each single genetic module, in a bottom-up fashion that should allow the prediction of more complex systems obtained by the interconnection of pre-characterized parts. However, many unpredictability sources hamper the ideally rational design of those synthetic genetic devices, mainly due to the tangled context-dependency behavior of those parts once placed into an intrinsically complex biological living system. Among others, the finite amount of translational resources in prokaryotic cells leads to an effect called metabolic burden, as a result of which hidden interactions between protein synthesis rates arise, leading to unexpected counterintuitive behaviors. To face this issue, two actions have been proposed in this study: firstly, a recently proposed mathematical modeling solution that included a description of the metabolic load exerted by the expression of recombinant genes have been applied on a case study, highlighting its worth of use and working boundaries; second, a CRISPR interference-based architecture have been developed to be used as an alternative to high resource usage transcriptional protein regulators, studying the underlying mechanism in several circuital configurations and optimizing each forming part in order to achieve the desired specifications. In Chapter 1, an introduction on synthetic biology is presented; in the second part, a brief overview on CRISPR technology and the overall aim of the study are reported. In Chapter 2, a case study evaluating the use of mathematical modeling to properly include metabolic burden in rational design of a set of transcriptional regulator cascades is reported. Firstly, the circuits and expected behavior are introduced, along with the discussion about experimental data, dissenting from what initially predicted. Secondly, the comparison between the use of a classical Hill equation-based model and an improved version that explicitly consider the translational load exerted by the expression of recombinant genes is reported. In Chapter 3, the design and deep characterization of a BioBrick$^{TM}$-compatible CRISPR interference-based repression set of modules is shown; expression optimization of the molecular players is reported and its usability as a low-burden alternative is demonstrated with experimental data and mathematical modeling. Working boundaries, peculiar aspects and rooms for improvements are then highlighted. In Chapter 4, preliminary studies aimed to improve the CRISPR interference system are reported and some of its context-dependencies are highlighted. Effects on repression efficiency due to alteration in the sequence of the RNA molecules addressing the CRISPR machinery to the desired target are discussed; evaluation of problems and opportunities related to the expression of more of this RNA guides are then highlighted. Lastly, an example of behavior of the system in presence of a competitor transcriptional regulator is reported. In Chapter 5 the overall conclusions of this thesis work are drawn.File | Dimensione | Formato | |
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