Co-design in synthetic biology: a system-level analysis of the development of an environmental sensing device.
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The concept of co-design is common in engineering, where it is necessary, for example, to determine the optimal partitioning between hardware and software of the implementation of a system features. Here we propose to adapt co-design methodologies for synthetic biology. As a test case, we have designed an environmental sensing device that detects the presence of three chemicals, and returns an output only if at least two of the three chemicals are present. We show that the logical operations can be implemented in three different design domains: (1) the transcriptional domain using synthetically designed hybrid promoters, (2) the protein domain using bi-molecular fluorescence complementation, and (3) the fluorescence domain using spectral unmixing and relying on electronic processing. We discuss how these heterogeneous design strategies could be formalized to develop co-design algorithms capable of identifying optimal designs meeting user specifications. (+info)
A computational model of gene expression in an inducible synthetic circuit.
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Synthetic biology aims to the rational design of gene circuits with predictable behaviours. Great efforts have been done so far to introduce in the field mathematical models that could facilitate the design of synthetic networks. Here we present a mathematical model of a synthetic gene-circuit with a negative feedback. The closed loop configuration allows the control of transcription by an inducer molecule (IPTG). Escherichia coli bacterial cells were transformed and expression of a fluorescent reporter (GFP) was measured for different inducer levels. Computer model simulations well reproduced the experimental induction data, using a single fitting parameter. Independent genetic components were used to assemble the synthetic circuit. The mathematical model here presented could be useful to predict how changes in these genetic components affect the behaviour of the synthetic circuit. (+info)
Retrovirus HTLV-1 gene circuit: a potential oscillator for eukaryotes.
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Retrovirus HTLV-1 gene circuit is characterized by positive and negative feedback phenomena, thus candidating it as a potential relaxation oscillator deliverable into eukaryotes. Here we describe a model of HTLV-1 which, by providing predictions of genes and proteins kinetics, can be helpful for designing gene circuits for eukaryotes, or for optimizing gene therapy approaches which are currently carried out by means of lentiviral vectors or re-engineered adenoviruses. Oscillatory patterns of HTLV-1 gene circuit are predicted when positive feedback is faster than negative feedback. Techniques to mutate the retroviral genome in order to implement practically the above conditions are discussed. Finally, the effect of stochasticity on the system behavior is tested by means of Gillespie algorithm. Simulations show the difficulties to preserve synchronization in viral expression for a multiplicity of cells, while the long tail of the density probability function of the master regulator gene tax/rex, due to its steady state fluctuations, suggests an activation mechanism of HTLV-1 similar to that recently proposed for HIV(1): the virus tends to latency but under certain circumstances, the master regulator gene reaches high values of expression, whose persistence induces the viral replication. (+info)
Emulsion based selection of T7 promoters of varying activity.
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The ability to build and control complex biological systems is greatly enhanced by the generation of related parts with varying strengths. In this way, various parts can be strung together and the connectivity and expression levels can be matched for the desired system performance. Engineered gene circuits, both in vivo and in vitro, often utilize the T7 RNA polymerase in tandem with the T7 promoter for transcription. In this work, we describe the selection of T7 promoter variants of varying strength by emulsifying in vitro transcription with subsequent fluorescence activated cell sorting (FACS) to enrich for active promoters. Such variant promoters should be of use to synthetic biologists for both in vivo and in vitro applications. (+info)
Writing and compiling code into biochemistry.
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This paper presents a methodology for translating iterative arithmetic computation, specified as high-level programming constructs, into biochemical reactions. From an input/output specification, we generate biochemical reactions that produce output quantities of proteins as a function of input quantities performing operations such as addition, subtraction, and scalar multiplication. Iterative constructs such as "while" loops and "for" loops are implemented by transferring quantities between protein types, based on a clocking mechanism. Synthesis first is performed at a conceptual level, in terms of abstract biochemical reactions - a task analogous to high-level program compilation. Then the results are mapped onto specific biochemical reactions selected from libraries - a task analogous to machine language compilation. We demonstrate our approach through the compilation of a variety of standard iterative functions: multiplication, exponentiation, discrete logarithms, raising to a power, and linear transforms on time series. The designs are validated through transient stochastic simulation of the chemical kinetics. We are exploring DNA-based computation via strand displacement as a possible experimental chassis. (+info)
Synthesis of pharmacokinetic pathways through knowledge acquisition and automated reasoning.
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Biological pathways are seen as highly critical in our understanding of the mechanism of biological functions. To collect information about pathways, manual curation has been the most popular method. However, pathway annotation is regarded as heavily time-consuming, as it requires expert curators to identify and collect information from different sources. Even with the pieces of biological facts and interactions collected from various sources, curators have to apply their biological knowledge to arrange the acquired interactions in such a way that together they perform a common biological function as a pathway. In this paper, we propose a novel approach for automated pathway synthesis that acquires facts from hand-curated knowledge bases. To comprehend the incompleteness of the knowledge bases, our approach also obtains facts through automated extraction from Medline abstracts. An essential component of our approach is to apply logical reasoning to the acquired facts based on the biological knowledge about pathways. By representing such biological knowledge, the reasoning component is capable of assigning ordering to the acquired facts and interactions that is necessary for pathway synthesis. We demonstrate the feasibility of our approach with the development of a system that synthesizes pharmacokinetic pathways. We evaluate our approach by reconstructing the existing pharmacokinetic pathways available in PharmGKB. Our results show that not only that our approach is capable of synthesizing these pathways but also uncovering information that is not available in the manually annotated pathways. (+info)
In silico biology.
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Rather than studying existent living systems, we can increasingly produce computer models that capture the salient aspects of life. This provides us with unprecedented opportunities to examine, manipulate, and explore biological phenomena, allowing us to investigate some of the deepest issues in biology. (+info)
A comparative analysis of synthetic genetic oscillators.
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