Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.National Institute of General Medical Sciences (U.S.) (Grant P50 GM098792)National Institute of General Medical Sciences (U.S.) (Grant R01 GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (EEC0540879)Life Technologies, Inc. (A114510)National Science Foundation (U.S.). Graduate Research FellowshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant 4500000552

Dynamical Models of biological networks

In der Molekularbiologie sind mathematische Modelle von regulatorischen und metabolischen Netzwerken essentiell, um von einer Betrachtung isolierter Komponenten und Interaktionen zu einer systemischen Betrachtungsweise zu kommen. Genregulatorische Systeme eignen sich besonders gut zur Modellierung, da sie experimentell leicht zugänglich und manipulierbar sind. In dieser Arbeit werden verschiedene genregulatorische Netzwerke unter Zuhilfenahme von mathematischen Modellen analysiert. Weiteres wird ein Modell einer in silico Zelle vorgestellt und diskutiert. Zunächst werden zwei zyklische genregulatorische Netzwerke - der klassische Repressilator und ein Repressilator mit zusätzlicher Autoaktivierung – im Detail mit analytischen Methoden untersucht. Um den Einfluß zufällig schwankender Molekülzahlen auf die Dynamik der beiden Systeme zu untersuchen, werden stochastische Modelle erstellt und die beiden oszillierenden Systeme verglichen. Weiteres werden mögliche Auswirkungen von Genduplikationen auf ein einfaches genregulatorisches Netzwerk untersucht. Dazu wird zunächst ein kleines Netzwerk von GATA Transkriptionsfaktoren, das eine zentrale Rolle in der Regulation des Stickstoffmetabolismus in Hefe spielt, modelliert und das Modell mit experimentellen Daten verglichen, um Parameterregionen einschränken zu können. Außerdem werden potentielle Topologien genregulatorischer Netzwerke von GATA Transkriptionsfaktoren in verwandten Fungi mittels sequenzbasierender Methoden gesucht und verglichen. Im letzten Teil der Arbeit wird MiniCellSim vorgestellt, ein Modell einer selbständigen in silico Zelle. Es erlaubt ein dynamisches System, das eine Protozelle mit einem genregulatorischen Netzwerk, einem einfachen Metabolismus und einer Zellmembran beschreibt, aus einer Sequenz abzuleiten. Nachdem alle Parameter, die zur Berechnung des dynamischen Systems benötigt werden, ohne zusätzliche Eingabe nur aus der Sequenzinformation abgeleitet werden, kann das Modell für Studien zur Evolution von genregulatorischen Netzwerken verwendet werden.In this thesis different types of gene regulatory networks are analysed using mathematical models. Further a computational framework of a novel, self-contained in silico cell model is described and discussed. At first the behaviour of two cyclic gene regulatory systems - the classical repressilator and a repressilator with additional auto-activation - are inspected in detail using analytical bifurcation analysis. To examine the behaviour under random fluctuations, stochastic versions of the systems are created. Using the analytical results sustained oscillations in the stochastic versions are obtained, and the two oscillating systems compared. In the second part of the thesis possible implications of gene duplication on a simple gene regulatory system are inspected. A model of a small network formed by GATA-type transcription factors, central in nitrogen catabolite repression in yeast, is created and validated against experimental data to obtain approximate parameter values. Further, topologies of potential gene regulatory networks and modules consisting of GATA-type transcription factors in other fungi are derived using sequence-based approaches and compared. The last part describes MiniCellSim, a model of a self-contained in silico cell. In this framework a dynamical system describing a protocell with a gene regulatory network, a simple metabolism, and a cell membrane is derived from a string representing a genome. All the relevant parameters required to compute the time evolution of the dynamical system are calculated from within the model, allowing the system to be used in studies of evolution of gene regulatory and metabolic networks

Synthetic biology approaches for engineering diverse bacterial species

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, June 2016.Cataloged from PDF version of thesis. "May 2016."Includes bibliographical references (pages 113-134).When engineers control gene expression, cells can be re-programmed to create living therapeutics or materials by initiating expression of biosynthetic pathways in response to specific signals. In this thesis, two new genetic tools were developed to aid the construction of genetic circuits and facilitate their delivery to bacteria isolated from diverse environments. First, antisense transcription was explored as a new tool for tuning gene expression in Escherichia coli. Antisense transcription was found to reliably repress gene expression and was applied tune simple genetic circuits. Second, an integrative conjugative element from Bacillus subtilis, ICEBsJ, was engineered to deliver exogenous DNA to diverse strains of undomesticated Gram-positive bacteria. Engineered ICEBsI conjugation was demonstrated in twenty different bacterial strains, spanning sixteen species and five genera. To demonstrate ICE's utility in creating new probiotics, the element was used to deliver functional nitrogen fixation pathways (nif clusters) to bacteria isolated from agricultural soils. Collectively, the tools presented here in provide a platform for programing bacteria from diverse environments for advanced applications.by Jennifer Ann Noelani Brophy.Ph. D

Computational design of orthogonal microRNAs for synthetic biology

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Upcoming applications of synthetic biology will require access to a wide array of robust genetic components (parts). The logic of a genetic system is encoded with regulatory elements such as pairs of transcription factors:promoters, miRNAs:target sites, or ribozymes:aptamers among others. Due to a relatively simple form and mode of operation of miRNAs, it is possible to design their synthetic variants. Out of all possible miRNA sequences the ones chosen should perform efficiently and should avoid cross-talk with both the host system circuits and within the imported synthetic ones. In this work, a computational method involving a series of heuristics is developed that can be used to design ensembles of such sequences depending on the host transcriptome. As an example, an ensemble of eight such miRNA sequences is produced using this method for use in a human host. Those have then been validated experimentally against the above-mentioned requirements by transfection into HEK 293 cells and flow cytometry measurements of fluorescent markers. The produced sequences are available for use from pENTR vectors of the Gateway cloning system. The required computations were facilitated by a modern cluster computing system—Kaichu—especially developed for this project, but fit for general purpose use and available under an open-source license.EPSR

Program and abstracts from the 2008 Neurospora conference

Program and abstracts from the 2008 Neurospora Conference, March 27-30, Pacific Grove, C

From Endogenous to Synthetic microRNA-Mediated Regulatory Circuits: An Overview

MicroRNAs are short non-coding RNAs that are evolutionarily conserved and are pivotal post-transcriptional mediators of gene regulation. Together with transcription factors and epigenetic regulators, they form a highly interconnected network whose building blocks can be classified depending on the number of molecular species involved and the type of interactions amongst them. Depending on their topology, these molecular circuits may carry out specific functions that years of studies have related to the processing of gene expression noise. In this review, we first present the different over-represented network motifs involving microRNAs and their specific role in implementing relevant biological functions, reviewing both theoretical and experimental studies. We then illustrate the recent advances in synthetic biology, such as the construction of artificially synthesised circuits, which provide a controlled tool to test experimentally the possible microRNA regulatory tasks and constitute a starting point for clinical applications

Programming microbes to treat superbug infection

Superbug infection is one of the greatest public health threat with grave implications across all levels of society. Towards a new solution to combat infection by multi-drug resistant bacteria, this thesis presents an engineering framework and genetic tools applied to repurpose commensal bacteria into “micro-robots” for the treatment of superbug infection. Specifically, a prototype of designer probiotic was developed using the human commensal bacteria Escherichia coli. The engineered commensal was reprogrammed with user-specified functions to sense superbug, produced pathogen-specific killing molecules and released the killing molecules via a lytic mechanism. The engineered commensal was effective in suppressing ~99% of planktonic Pseudomonas and preventing ~ 90% of biofilm formation. To enhance the sensing capabilities of engineered commensal, genetic interfaces comprising orthogonal AND & OR logic devices were developed to mediate the integration and interpretation of binary input signals. Finally, AND, OR and NOT logic gates were networked to generate a myriad of cellular logic operations including half adder and half subtractor. The creation of half adder logic represents a significant advancement of engineering human commensal to be biological equivalent of microprocessor chips in programmable computer with the ability to process input signals into diversified actions. Importantly, this thesis provides exemplary case studies to the attenuation of cellular and genetic context dependent effects through principles elucidated herein, thereby advancing our capability to engineer commensal bacteria.Open Acces

Engineering serine integrase-based synthetic gene circuits for cellular memory and counting

A cellular counting system based on synthetic gene circuits would enable complex biological programming and be used in many biotechnology applications. Although a variety of synthetic memory circuits have been constructed, basic modules that can be assembled into a counting system are lacking. This thesis focuses on engineering a binary counting module, which can alternate between two states in response to a single repeating input signal. The highly directional large serine bacteriophage integrases were utilised as the basis for the synthetic circuits constructed in this study. Integrases and their protein co-factors, the recombination directionality factor (RDF) can change the orientation of a specific DNA segment flanked by two recombination sites. Integrase alone switches the orientation in one direction, and this directionality is reversed by the addition of its corresponding RDF. The two orientations can be used to turn gene expression on and off, leading to distinct output states which can be thought of as representing a single binary digit (0 and 1) heritably stored in the DNA. In this study, three different serine integrase-based synthetic gene circuits for cellular memory and counting were engineered and characterised. A set-reset latch was first constructed. By expressing ϕC31 integrase and co-expressing integrase with RDF Gp3 from two independent inducible systems, the orientation of the invertible DNA in the set-reset latch was inverted and restored respectively. This device demonstrated that ϕC31 integrase can successfully encode information into plasmid DNA. Next, a state-based latch was constructed, in which the gp3 gene was placed inside the invertible DNA segment to couple its transcriptional regulation to the circuit state. Integrase expression triggered by one input signal resulted in inversion of the invertible DNA, placing the gp3 gene in the correct orientation for transcription. Gp3 expression can then be triggered by another input signal to reverse the directionality of integrase, restoring the DNA back to its original configuration. By optimising the stoichiometry and kinetics of integrase and Gp3 expression, efficient switching of both multi-copy plasmid and single copy chromosomal DNA was achieved. Finally, the state-based latch was developed into a binary counting module by introducing a delay mechanism, in which gp3 transcription was inhibited by a state-based repressor during recombination requiring the absence of Gp3. Placing expression of gp3 under the control of the invertible DNA, allowed a single input signal controlling only integrase expression to switch the module between OFF (0) and ON (1). This is the first integrase-based module that generates different outputs in response to the same input signal and a fundamental step towards building a genetic binary counter with large counting capacity

Engineering a genetic circuit for Turing patterns in E. coli with a Synthetic Biology approach

Genetic circuits that can form spatial patterns have been a major topic of interest within Synthetic Biology. Turing patterns are self-organising spatial wave, spot or labyrinthine patterns that are formed in some reaction-diffusion circuits. The simplest Turing circuit involves a slow-diffusing activator and a fast-diffusing inhibitor, interacting to regulate their own and each other’s rates of production. An unambiguous implementation of Turing patterns with a genetic circuit is still lacking because of their exquisitely fine-tuned nature. This study aims to address this shortcoming and sets out to engineer a genetic circuit for Turing patterning in E. coli from first principles. Two genetic circuits were studied. Firstly, a phage circuit was designed according to the minimal self-activation, lateral inhibition Turing topology and involves a slow-diffusing M13 filamentous phage and a fast-diffusing 3OC6HSL quorum sensing signal. This circuit was abandoned because of the many complexities of phage biology, which were working against its successful implementation as a Turing generator. The focus was shifted to circuit ‘3954’, which was designed according to a more robust three-node topology and implemented with two small molecule diffusors; this could be done because the circuit allows for equal diffusivity of the two diffusing signals. All the components of circuit ‘3954’ were tested in reduced subcircuits and were shown to be functioning as expected. Growing bacterial colonies bearing the circuit were then visualised for pattern formation using confocal microscopy. Even though no Turing patterns were detected, the colonies consistently showed a centre-surround expression pattern of the fluorescence reporters, where GFP was expressed at the colony centre, whereas mCherry was predominantly expressed at the periphery. The obtained reaction-diffusion patterns are a good foundation for further tuning and exploration.Open Acces