A population-based microbial oscillator

Genetic oscillators are a major theme of interest in the emerging field of synthetic biology. Until recently, most work has been carried out using intra-cellular oscillators, but this approach restricts the broader applicability of such systems. Motivated by a desire to develop large-scale, spatially-distributed cell-based computational systems, we present an initial design for a population-level oscillator which uses three different bacterial strains. Our system is based on the client-server model familiar to computer science, and uses quorum sensing for communication between nodes. We present the results of extensive in silico simulation tests, which confirm that our design is both feasible and robust.Comment: Submitte

Design Principles of Biological Oscillators through Optimization: Forward and Reverse Analysis

26 páginas, 10 figuras, 1 tabla.-- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedFrom cyanobacteria to human, sustained oscillations coordinate important biological functions. Although much has been learned concerning the sophisticated molecular mechanisms underlying biological oscillators, design principles linking structure and functional behavior are not yet fully understood. Here we explore design principles of biological oscillators from a multiobjective optimization perspective, taking into account the trade-offs between conflicting performance goals or demands. We develop a comprehensive tool for automated design of oscillators, based on multicriteria global optimization that allows two modes: (i) the automatic design (forward problem) and (ii) the inference of design principles (reverse analysis problem). From the perspective of synthetic biology, the forward mode allows the solution of design problems that mimic some of the desirable properties appearing in natural oscillators. The reverse analysis mode facilitates a systematic exploration of the design space based on Pareto optimality concepts. The method is illustrated with two case studies: the automatic design of synthetic oscillators from a library of biological parts, and the exploration of design principles in 3-gene oscillatory systemsThis work was supported by MINECO (and the European Regional Development Fund) project ªSYNBIOFACTORYº (grant number DPI2014-55276-C5-2-R).Peer reviewe

Designing synthetic networks in silico : A generalised evolutionary algorithm approach

Background: Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). Results: The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. Conclusions: In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses

Design and implementation of a mammalian synthetic gene oscillator

The core goal of synthetic biology as a discipline is to design, develop and characterize biological parts in order to precisely control cellular behaviour. Much of the research in this field has been focused on the development of gene regulatory networks, namely switches and oscillators. The study of synthetic gene oscillators has attracted significant attention in the past decade due to their intriguing dynamics and relevance in controlling inflammatory, metabolic and circadian signalling pathways. Additionally, the precise expression dynamics and molecular mechanisms that underlie the mammalian circadian clock structure are not fully understood. The work presented herein regards the design and implementation of a tuneable mammalian synthetic gene oscillator with a novel biological structure. To this end, an approach based on a combination of in silico design and in vivo part validation, in conjunction with a comparative analysis of previously implemented synthetic gene oscillators, was taken when assembling the proposed system. The topology of the system relies on a delayed negative feedback loop, consisting of the coupled regulatory activities of the transcription regulators LacI, tTA, and Gal4. The numerical solution and stability analysis of an ODE-based model describing the dynamics of the system are indicative that the proposed system is capable of generating sustained oscillations across a wide range of parameter values. The biological parts that comprise the system have been monitored and validated in HEK293T cells through time-lapse fluorescence microscopy and image analysis. The in vivo performance of the proposed mammalian synthetic gene oscillator was also assessed in the HEK293T cell line, and monitored using time-lapse fluorescence microscopy. Damped fluorescence oscillations were observed: these could be tuned by a differential IPTG concentration gradient and abolished by doxycycline. The proposed mammalian synthetic gene oscillator provides valuable insight into the gene expression regulatory processes leading to oscillatory behaviour, and has the potential to foster progress in future synthetic biology-based therapies.Open Acces

A MicroRNA Based Genetic Clock

This thesis focuses on the design, construction and stable integration in mammalian cells of a natural microRNA-based genetic oscillator. This will help both in better understanding the rules underlying the periodic expression of genes observed in major biological processes, such as the circadian clock and cell-cycle, as well as, in generating new tools to probe and investigate the function of a gene in a cell, by allowing not only its over-expression or knock-down, but also its cyclic expression. The circuit involves a positive feedback loop, consisting of a transcription factor (TF) activating itself, and a negative feedback loop, using a natural micro RNA controlled by the TF, which induces degradation of the TF itself. The circuit was built in a modular way, and implemented it in two lentiviral vectors able to infect both dividing and non-dividing cells, hence suitable for many different applications. Since obtaining stable oscillations is non-trivial, a modified version of the oscillator was engineered, including an intermediate step between the TF and the microRNA, to increase the delay in the negative feedback loop. The oscillatory behavior was tested via in vivo time-lapse fluorescence microscopy in both versions of the oscillator, since both the TF(s) and the microRNA are expressed together with fluorescent reporters.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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