Browsing by Author "Iadevaia, Sergio"

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    Design of artificial genetic networks to regulate the biosynthesis of polyhydroxyalkanoate copolymers with desirable structures
    (2008) Iadevaia, Sergio; Zygourakis, Kyriacos
    The design of artificial genetic networks constitutes a powerful tool to regulate cellular physiology. Simple regulatory structures comprised of a few interacting genes can be assembled to engineer desirable phenotypes and control the biosynthesis of end products of biomedical and/or biotechnological interest. This doctoral thesis has focused on the in silico design of artificial genetic networks to drive the biosynthesis of a specific product of biotechnological interest, namely, PHA copolymer chains with desirable structures. In order to understand this complex process, a mathematical model was developed to describe the coupling between the dynamics of polymer and monomer formation and those of the genetic networks. The modeling studies have focused on the utilization of two synthetic networks, known as the genetic toggle and repressilator. The results indicate that the bistable toggle allows regulating the monomer composition of PHA copolymers. The use of the repressilator offers a higher level of control, as it enables the synthesis of PHA block copolymers with different length and composition of each of the blocks that comprise the chains. Additional computational studies have revealed the possibility to achieve superior performance than that of the repressilator, through the design of a novel genetic network that exhibits oscillatory dynamics with minimal overlap amongst gene expression levels. The oscillations were also found to be robust to stochastic fluctuations. Finally, an existing mathematical model was modified to explain the discrepancy of the original repressilator model with experimental data. The modeling studies support the hypothesis that non-specific interactions may also be present in addition to the original three promoter-repressor interactions, which the repressilator was designed to include.
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    Mapping Network Motif Tunability and Robustness in the Design of Synthetic Signaling Circuits
    (Public Library of Science, 2014) Iadevaia, Sergio; Nakhleh, Luay K.; Azencott, Robert; Ram, Prahlad T.
    Cellular networks are highly dynamic in their function, yet evolutionarily conserved in their core network motifs or topologies. Understanding functional tunability and robustness of network motifs to small perturbations in function and structure is vital to our ability to synthesize controllable circuits. In establishing core sets of network motifs, we selected topologies that are overrepresented in mammalian networks, including the linear, feedback, feed-forward, and bifan circuits. Static and dynamic tunability of network motifs were defined as the motif ability to respectively attain steady-state or transient outputs in response to pre-defined input stimuli. Detailed computational analysis suggested that static tunability is insensitive to the circuit topology, since all of the motifs displayed similar ability to attain predefined steady state outputs in response to constant inputs. Dynamic tunability, in contrast, was tightly dependent on circuit topology, with some motifs performing superiorly in achieving observed time-course outputs. Finally, we mapped dynamic tenability onto motif topologies to determine robustness of motif structures to changes in topology and identify design principles for the rational assembly of robust synthetic networks.