Workshop 3: Synthetic Biology: Titles & Abstracts
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- Titles & Abstracts
Recent results in synthetic biology showed that it is possible to design and build a variety of gene circuits and implement them in bacterial and mammalian cells. Example include toggle switches, oscillators, counters, concentration range detectors, and logical gates. By drawing inspiration from electrical circuits, such biological circuits can be combined to achieve more complex and useful behavior. However, as in electrical circuits, the usefulness and dependability of an ensemble depends on the reliability of the components. Can we build "reliable" synthetic gene circuits? Can we guarantee their qualitative behavior (e.g., AND gate) under parameter uncertainty? In this talk, I will present some preliminary answers to these questions. I will show that, by using techniques such as abstractions and model checking from formal verification, realistic and widely used mathematical models of gene networks can be synthesized, analyzed, and controlled from rich, qualitative specifications. I will show how these results can be applied to "tune" the parameters of a transcriptional cascade and to analyze and control a mathematical model of a toggle switch.
Live cells process information using purely digital systems, such as the genetic code, and analog reaction networks that at times behave as digital circuits, such as signal transduction. We are developing approaches to build "designer" reaction networks in a systematic fashion in order to control and modify cellular behavior. As a first step we have constructed networks that control gene expression based on logic combinations of specified biomolecular inputs, including mRNAs, microRNAs and transcription factors. Our approach uses RNA interference as a logic processor and a variety of sensor "devices" to read out individual inputs. We are also addressing questions pertaining to robustness and reliability of these networks, and to this end demonstrated how an "incoherent feed-forward" network motif can limit fluctuations due to gene copy number variability.
Gene regulatory networks are at the heart of cellular function and help to determine cell fate and phenotype. A coherent mathematical understanding of how these networks operate will be necessary not only to elucidate the true function of cellular machinery, but also to guide the design of engineered networks for use in practical applications. In this talk, I will discuss the creation of a fast, robust and tunable synthetic gene oscillator in Escherichia coli. This oscillator, based on previous theoretical work, revealed fundamental flaws in our ability to computationally model dynamical gene regulation and cellular signaling. Discrepancies between the experimentally observed dynamics and the mathematically predicted behavior led us to new insights into the importance of fast reactions and dynamical delay in gene regulatory networks.
Given the success in engineering synthetic phenotypes in microbes and mammalian cells, constructing non-native pathways in mammals has become increasingly attractive for understanding and identifying potential targets for treating metabolic disorders. Here we introduced the glyoxylate shunt into mouse liver to investigate mammalian fatty acid metabolism. Mice expressing the shunt showed resistance to diet-induced obesity on a high fat diet despite similar food consumption. This was accompanied by a decrease in total fat mass, circulating leptin levels, plasma triglyceride concentration, and a signaling metabolite in liver, malonyl-CoA, that inhibits fatty acid degradation. Contrary to plants and bacteria, in which the glyoxylate shunt prevents the complete oxidation of fatty acids, this pathway when introduced in mice increases fatty acid oxidation such that resistance to diet-induced obesity develops. This work suggests that using non-native pathways in higher organisms to explore and modulate metabolism may be a useful approach.
Key features of Synthetic Biology include a focus on design and design principles, as well as the development of well-characterized and re-usable Parts. The field intersects with Metabolic Engineering in areas such as the design of novel pathways for product generation, in which enzymes may be considered as interchangeable Parts, and the improvement of those pathways for increased productivity. We have constructed a synthetic pathway for the production of glucaric acid, deemed a "top-value added chemical" from biomass, from glucose in Escherichia coli. Co-expression of the genes encoding myo-inositol-1-phosphate synthase (Ino1) from Saccharomyces cerevisiae, myo-inositol oxygenase (MIOX) from mouse, and uronate dehydrogenase (Udh) from Pseudomonas syringae led to production of glucaric acid. Flux towards glucaric acid is ultimately limited by MIOX, whose activity is dependent upon the concentration of myo-inositol, its substrate. To improve glucaric acid production, we have explored several options for increasing flux through the pathway, including the use of other enzyme Parts and the creation of synthetic scaffolds (Devices) to co-localize Ino1 and MIOX, thereby increasing the local concentration of myo-inositol. We will present results on the application of these scaffolds in various configurations to improve MIOX activity and glucaric acid productivity.
Work performed in collaboration with John Dueber, currently Assistant Professor of Bioengineering at the University of California, Berkeley.
A common topology found in many bistable genetic systems is two interacting positive feedback loops, or a positive feedback loop interacting with a double-negative feedback loop. Here, we explore how this topology can allow bistability over a large range of cellular conditions. Based on theoretical arguments, we predict that nonlinear interactions between two positive feedback loops, or between a positive feedback loop and a double-negative feedback loop, can produce an ultrasensitive response which increases the range of cellular conditions at which bistability is observed. This prediction was experimentally tested by constructing a synthetic genetic circuit in Escherichia coli in which a well-characterized positive feedback loop was linked to a well-characterized double-negative feedback loop in a coherent fashion. The concerted action of both feedback loops resulted in bistable behavior over a broad range of inducer concentrations; when either of the feedback loops was inactivated the range of inducer concentrations at which the system exhibited bistability was decreased by an order of magnitude. Furthermore bistability of the system could be tuned by altering growth conditions that regulate the contribution of one of the feedback loops. Our theoretical and experimental work shows how linked feedback loops may produce the robust bistable responses required in cellular networks that regulate development, the cell cycle, and many other cellular responses.
Work done in collaboration with Dong-Eun Chang, Shelly Leung, Aaron Reifler, Mariette R. Atkinson, and Daniel Forger.
Biotechnology plays an increasingly central part in the manufacturing of compounds in the pharmaceutical, chemical, and fuel industry. The underlying biological research has moved beyond the molecular reductionist dogma to a systems view, and novel system-wide analytic tools allow unprecedented insight into the relevant processes in cells. At the same time, metagenomics increases drastically the gene pool from which to recruit catalysts. The ETH Bioprocess Laboratory develops tools that are crucial on the way from designing biocatalysts from a systems perspective to implementing production processes. We concentrate on the rational engineering of in vitro multi-enzyme reaction networks, in particular for the production of natural and unnatural sugars and ultimately oligosaccharides. Crucial questions are how to insulate efficient pathways from highly interconnected networks, such as the central carbon metabolism, and how to optimize these pathways in terms of dynamic behavior. We will illustrate possible strategies using our efforts in multi-enzyme production of building blocks for C-C-bond forming enzymes and real-time analysis of in vitro metabolic networks.
Determining quality of performance for a biological system is critical to identifying and elucidation its design principles. This important task is greatly facilitated by enumeration of regions within the system's design space that exhibit qualitatively distinct phenotypes. I will present an approach to the generic construction of the design space for biochemical systems. This approach is grounded in the power-law equations that characterize traditional chemical kinetics and, by transformation, the rational functions that characterize biochemical kinetics. In steady state, the analysis of these equations can be reduced to that of linear algebraic equations. These methods will be illustrated with applications to common classes of biochemical system motifs.
Chemical synthesis of viral genomes is independent of a natural template and, thus, it allows modifying the structure and function of a virus' genetic information to an extent not possible before. We have used this new strategy to further our understanding of an organism’s properties, particularly its pathogenic armory if it causes disease in humans, and to make use of this new information to protect from or treat human viral disease. Specifically, we have recoded the genome of poliovirus, altering the capsid-coding region by introducing 600 to 1,000 nucleotide changes. Specifically, we altered favored to unfavored codon pairs, thereby changing the codon pair bias within the polyprotein without changing codon bias or the sequence of the viral proteins. Such large-scale changes yielded surprising phenotypes, particularly those related to the specific infectivity of virus variants and to the attenuation of virus pathogenicity in CD155 tg mice. The strategy has been tested with influenza virus yielding highly attenuated influenza virus strains.
Also of interest is a poliovirus variant in which sequences of the polyprotein were "scrambled" by maximizing the number of nucleotide changes while preserving both codon bias and amino acid sequences. The scrambled sequences were used to replace the domains P1 (structural proteins), P2, or P3 (non-structural proteins) of the P1-P2-P3 polyprotein. Surprisingly, the scrambled sequence of P1 (934 changes out of 2,643 P1 nucleotides) in a P1scrambled-P2-P3 virus did not alter the virus' growth properties. We have used scrambled sequences in the non-structural region of the poliovirus polyprotein (P2+P3) to search for RNA signals essential for vial replication. As expected, a P1-P2scrambled-P3 virus was dead because the known essential cre element (an RNA hairpin) in P2 was destroyed; repairing the defect by inserting a wt cre into the 5' non-translated region restored the wt replication phenotype. We, therefore, can conclude that, other than cre, P2 does not contain essential RNA replication signals, a method currently applied to the P3 region. Interestingly, the P1-P2scrambled-P3 virus fails to recombine with a human C-cluster coxsackie virus (C-CAV20) in vivo because the sequence region where cross over occurs was scrambled. PV/C-CAV recombinants that are highly neurovirulent evolve in different parts of the world from oral poliovirus vaccines and C-CAVs, causing small epidemics of poliomyelitis.
To realize the promising practical applications of synthetic biology, bioengineers must interface the engineered genetic circuits in living cells with the environment. Although cells mostly rely on proteins such as receptors and transcription factors to transduce the chemical information into genetic signals, adapting such proteins to sense and respond to novel molecules is a daunting task. Despite its chemical simplicity, RNAs offer several attractive properties and engineering tools which make them an attractive platform for engineering chemical interfaces for applications in synthetic biology. We combine rational and combinatorial approaches to harness the diverse capacities of RNAs (molecular recognition, chemical catalysis, gene regulation) to construct synthetic chemical interfaces that operate in bacteria and in mammlian cells.
