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Robert G. Egbert

Bio: Robert G. Egbert is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Biology & Synthetic biology. The author has an hindex of 7, co-authored 17 publications receiving 324 citations. Previous affiliations of Robert G. Egbert include Lawrence Berkeley National Laboratory & University of Washington.

Papers
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Journal ArticleDOI
TL;DR: A simple and general approach to rapidly tune gene networks in Escherichia coli using hypermutable simple sequence repeats embedded in the spacer region of the ribosome binding site is introduced, suggesting a new approach to optimizing gene networks via directed evolution.
Abstract: The parameters in a complex synthetic gene network must be extensively tuned before the network functions as designed. Here, we introduce a simple and general approach to rapidly tune gene networks in Escherichia coli using hypermutable simple sequence repeats embedded in the spacer region of the ribosome binding site. By varying repeat length, we generated expression libraries that incrementally and predictably sample gene expression levels over a 1,000-fold range. We demonstrate the utility of the approach by creating a bistable switch library that programmatically samples the expression space to balance the two states of the switch, and we illustrate the need for tuning by showing that the switch’s behavior is sensitive to host context. Further, we show that mutation rates of the repeats are controllable in vivo for stability or for targeted mutagenesis—suggesting a new approach to optimizing gene networks via directed evolution. This tuning methodology should accelerate the process of engineering functionally complex gene networks.

98 citations

Journal ArticleDOI
TL;DR: This work introduces a framework for the specification and simulation of multicelled behaviors that combines a simple simulation of microcolony growth and molecular signaling with a new specification language called gro and allows the researcher to explore the collective behaviors induced by high level descriptions of individual cell behaviors.
Abstract: Recent advances in the design and construction of synthetic multicelled systems in E. coli and S. cerevisiae suggest that it may be possible to implement sophisticated distributed algorithms with these relatively simple organisms. However, existing design frameworks for synthetic biology do not account for the unique morphologies of growing microcolonies, the interaction of gene circuits with the spatial diffusion of molecular signals, or the relationship between multicelled systems and parallel algorithms. Here, we introduce a framework for the specification and simulation of multicelled behaviors that combines a simple simulation of microcolony growth and molecular signaling with a new specification language called gro. The framework allows the researcher to explore the collective behaviors induced by high level descriptions of individual cell behaviors. We describe example specifications of previously published systems and introduce two novel specifications: microcolony edge detection and programmed microcolony morphogenesis. Finally, we illustrate through example how specifications written in gro can be refined to include increasing levels of detail about their bimolecular implementations.

82 citations

Journal ArticleDOI
TL;DR: The production of even chain length alkanes represents initial steps toward the expansion of this recently discovered microbial alkane production pathway to synthesize complex fuels.
Abstract: Microbially produced alkanes are a new class of biofuels that closely match the chemical composition of petroleum-based fuels. Alkanes can be generated from the fatty acid biosynthetic pathway by the reduction of acyl-ACPs followed by decarbonylation of the resulting aldehydes. A current limitation of this pathway is the restricted product profile, which consists of n-alkanes of 13, 15, and 17 carbons in length. To expand the product profile, we incorporated a new part, FabH2 from Bacillus subtilis , an enzyme known to have a broader specificity profile for fatty acid initiation than the native FabH of Escherichia coli . When provided with the appropriate substrate, the addition of FabH2 resulted in an altered alkane product profile in which significant levels of n-alkanes of 14 and 16 carbons in length are produced. The production of even chain length alkanes represents initial steps toward the expansion of this recently discovered microbial alkane production pathway to synthesize complex fuels. This work was conceived and performed as part of the 2011 University of Washington international Genetically Engineered Machines (iGEM) project.

70 citations

Journal ArticleDOI
TL;DR: The results indicate that while most parts and constructs work similarly in the two organisms, some deviate significantly and will aid in developing more robust synthetic biology principles and approaches for this non-model chassis.
Abstract: The fast-growing nonmodel marine bacterium Vibrio natriegens has recently garnered attention as a host for molecular biology and biotechnology applications. In order to further its capabilities as a synthetic biology chassis, we have characterized a wide range of genetic parts and tools for use in V. natriegens. These parts include many commonly used resistance markers, promoters, ribosomal binding sites, reporters, terminators, degradation tags, origin of replication sequences, and plasmid backbones. We have characterized the behavior of these parts in different combinations and have compared their functionality in V. natriegens and Escherichia coli. Plasmid stability over time, plasmid copy numbers, and production load on the cells were also evaluated. Additionally, we tested constructs for chemical and optogenetic induction and characterized basic engineered circuit behavior in V. natriegens. The results indicate that, while most parts and constructs work similarly in the two organisms, some deviate significantly. Overall, these results will serve as a primer for anyone interested in engineering V. natriegens and will aid in developing more robust synthetic biology principles and approaches for this nonmodel chassis.

48 citations

Journal ArticleDOI
TL;DR: It is argued that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments.

30 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Journal ArticleDOI
01 Apr 2016-Science
TL;DR: Electronic design automation principles from EDA are applied to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects, and it is demonstrated that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems.
Abstract: INTRODUCTION Cells respond to their environment, make decisions, build structures, and coordinate tasks. Underlying these processes are computational operations performed by networks of regulatory proteins that integrate signals and control the timing of gene expression. Harnessing this capability is critical for biotechnology projects that require decision-making, control, sensing, or spatial organization. It has been shown that cells can be programmed using synthetic genetic circuits composed of regulators organized to generate a desired operation. However, the construction of even simple circuits is time-intensive and unreliable. RATIONALE Electronic design automation (EDA) was developed to aid engineers in the design of semiconductor-based electronics. In an effort to accelerate genetic circuit design, we applied principles from EDA to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects. We used the hardware description language Verilog to enable a user to describe a circuit function. The user also specifies the sensors, actuators, and “user constraints file” (UCF), which defines the organism, gate technology, and valid operating conditions. Cello (www.cellocad.org) uses this information to automatically design a DNA sequence encoding the desired circuit. This is done via a set of algorithms that parse the Verilog text, create the circuit diagram, assign gates, balance constraints to build the DNA, and simulate performance. RESULTS Cello designs circuits by drawing upon a library of Boolean logic gates. Here, the gate technology consists of NOT/NOR logic based on repressors. Gate connection is simplified by defining the input and output signals as RNA polymerase (RNAP) fluxes. We found that the gates need to be insulated from their genetic context to function reliably in the context of different circuits. Each gate is isolated using strong terminators to block RNAP leakage, and input interchangeability is improved using ribozymes and promoter spacers. These parts are varied for each gate to avoid breakage due to recombination. Measuring the load of each gate and incorporating this into the optimization algorithms further reduces evolutionary pressure. Cello was applied to the design of 60 circuits for Escherichia coli , where the circuit function was specified using Verilog code and transformed to a DNA sequence. The DNA sequences were built as specified with no additional tuning, requiring 880,000 base pairs of DNA assembly. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts). Across all circuits, 92% of the 412 output states functioned as predicted. CONCLUSION Our work constitutes a hardware description language for programming living cells. This required the co-development of design algorithms with gates that are sufficiently simple and robust to be connected by automated algorithms. We demonstrate that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems. This approach leads to highly repetitive and modular genetics, in stark contrast to the encoding of natural regulatory networks. The use of a hardware-independent language and the creation of additional UCFs will allow a single design to be transformed into DNA for different organisms, genetic endpoints, operating conditions, and gate technologies.

813 citations

Journal ArticleDOI
TL;DR: A genetically encoded metabolic switch that enables dynamic regulation of fatty acids (FA) biosynthesis in Escherichia coli was reported, able to dynamically compensate the critical enzymes involved in the supply and consumption of malonyl-CoA and efficiently redirect carbon flux toward FA biosynthesis.
Abstract: Global energy demand and environmental concerns have stimulated increasing efforts to produce carbon-neutral fuels directly from renewable resources. Microbially derived aliphatic hydrocarbons, the petroleum-replica fuels, have emerged as promising alternatives to meet this goal. However, engineering metabolic pathways with high productivity and yield requires dynamic redistribution of cellular resources and optimal control of pathway expression. Here we report a genetically encoded metabolic switch that enables dynamic regulation of fatty acids (FA) biosynthesis in Escherichia coli. The engineered strains were able to dynamically compensate the critical enzymes involved in the supply and consumption of malonyl-CoA and efficiently redirect carbon flux toward FA biosynthesis. Implementation of this metabolic control resulted in an oscillatory malonyl-CoA pattern and a balanced metabolism between cell growth and product formation, yielding 15.7- and 2.1-fold improvement in FA titer compared with the wild-type strain and the strain carrying the uncontrolled metabolic pathway. This study provides a new paradigm in metabolic engineering to control and optimize metabolic pathways facilitating the high-yield production of other malonyl-CoA-derived compounds.

441 citations

Journal ArticleDOI
TL;DR: A biophysical model employing thermodynamic first principles and a four-parameter free energy model is developed and confirmed that the ribosome can readily bind distant standby site modules that support high translation rates, providing a physical mechanism for observed context effects and long-range post-transcriptional regulation.
Abstract: The ribosome’s interactions with mRNA govern its translation rate and the effects of post-transcriptional regulation. Long, structured 5 0 untranslated regions (5 0 UTRs) are commonly found in bacterial mRNAs, though the physical mechanisms that determine how the ribosome binds these upstream regions remain poorly defined. Here, we systematically investigate the ribosome’s interactions with structured standby sites, upstream of Shine– Dalgarno sequences, and show that these interactions can modulate translation initiation rates by over 100-fold. We find that an mRNA’s translation initiation rate is controlled by the amount of single-stranded surface area, the partial unfolding of RNA structures to minimize the ribosome’s binding free energy penalty, the absence of cooperative binding and the potential for ribosomal sliding. We develop a biophysical model employing thermodynamic first principles and a fourparameter free energy model to accurately predict the ribosome’s translation initiation rates for 136 synthetic 5 0 UTRs with large structures, diverse shapes and multiple standby site modules. The model predicts and experiments confirm that the ribosome can readily bind distant standby site modules that support high translation rates, providing a physical mechanism for observed context effects and long-range post-transcriptional regulation.

433 citations