Ratiometric control for differentiation of cell populations endowed with synthetic toggle switches

We consider the problem of regulating by means of external control inputs the ratio of two cell populations. Specifically, we assume that these two cellular populations are composed of cells belonging to the same strain which embeds some bistable memory mechanism, e.g. a genetic toggle switch, allowing them to switch role from one population to another in response to some inputs. We present three control strategies to regulate the populations' ratio to arbitrary desired values which take also into account realistic physical and technological constraints occurring in experimental microfluidic platforms. The designed controllers are then validated in-silico using stochastic agent-based simulations.Comment: Accepted to CDC'201

Synthetic biology: advancing biological frontiers by building synthetic systems

Advances in synthetic biology are contributing to diverse research areas, from basic biology to biomanufacturing and disease therapy. We discuss the theoretical foundation, applications, and potential of this emerging field

Engineering Cellular Communication Systems for Synthetic Biology

Synthetic biology is an emerging interdisciplinary field of biology that aims to system-atically design artificial biological systems. As synthetic biologists seek increasingly complex control over cellular processes to achieve robust and predictable systems. A new frontier in synthetic biology is engineering synthetic microbial consortia. This ap-proach employs the concept of division of labor, instead of introducing large genetic cir-cuitry to homogenous cell populations. In this approach, different cell types are assigned to execute a portion of the overall circuit. Each cell type communicates with their co-worker subpopulations to complete the circuit. The main advantage of this strategy is the reduced metabolic burden on each cell type. Thus, leading to more reliable and stable overall performance. In this work, to simplify cellular communication between the mem-bers of the consortium, we used the simple architecture of quorum sensing machinery. We constructed a toolbox that contains promoter, receptor and quorum sensing signal synthase genes along with fluorescent reporters. Using this toolbox, we constructed dif-ferent cell types that can be used in synthetic consortia forming various communication topologies. We characterized the constructed cell types individually and in co-cultures

Analysis and Control of Bacterial Populations in Synthetic Biology

Synthetic Biology is a new field of research that aims at engineering new functionalities in living beings. Analogously to electronic circuits, more advanced functionalities can be realised by putting together smaller functional modules that perform elementary tasks; however, the interaction of these basic pieces is somewhat complex and fragile. Therefore, to increase the robustness and reliability of the whole system, typical tools from Control Theory, such as feedback loops, can be employed. In the first part of this thesis we propose feedback control strategies to balance the gene expression of a bistable genetic circuit, known as genetic toggle switch, in an unstable region far away from its stable equilibria - a problem analogous to the stabilization of the inverted pendulum in mechanics. The effectiveness of the proposed control strategies is validated via realistic agent-based simulations of a bacterial population endowed with the genetic toggle switch. Later in the thesis we move towards the growth control of bacterial cells in bioreactors, introducing a novel open-source and versatile design of a turbidostat to host in vivo control experiments. In the last part, we want to control bioreactors to guarantee the coexistence of multiple species in the same environment. We analyse the dynamics of a simple one-chamber bioreactor, proposing control strategies to achieve the control goal. However, simple bioreactors have several drawback when the concentrations of multiple species are regulated at the same time; for these reason, we propose a novel layout for a bioreactor, with two growth chambers and a mixing one, to be used in multicellular in vivo control experiments

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tool