J. Christopher Anderson

Environmental signal integration by a modular AND gate

Microorganisms use genetic circuits to integrate environmental information. We have constructed a synthetic AND gate in the bacterium Escherichia coli that integrates information from two promoters as inputs and activates a promoter output only when both input promoters are transcriptionally active. The integration occurs via an interaction between an mRNA and tRNA. The first promoter controls the transcription of a T7 RNA polymerase gene with two internal amber stop codons blocking translation. The second promoter controls the amber suppressor tRNA supD. When both components are transcribed, T7 RNA polymerase is synthesized and this in turn activates a T7 promoter. Because inputs and outputs are promoters, the design is modular; that is, it can be reconnected to integrate different input signals and the output can be used to drive different cellular responses. We demonstrate this modularity by wiring the gate to integrate natural promoters (responding to Mg2+ and AI‐1) and using it to implement a phenotypic output (invasion of mammalian cells). A mathematical model of the transfer function is derived and parameterized using experimental data.

Expanding the genetic code: selection of efficient suppressors of four-base codons and identification of "shifty" four-base codons with a library approach in Escherichia coli.

Abstract Naturally occurring tRNA mutants are known that suppress +1 frameshift mutations by means of an extended anticodon loop, and a few have been used in protein mutagenesis. In an effort to expand the number of possible ways to uniquely and efficiently encode unnatural amino acids, we have devised a general strategy to select tRNAs with the ability to suppress four-base codons from a library of tRNAs with randomized 8 or 9 nt anticodon loops. Our selectants included both known and novel suppressible four-base codons and resulted in a set of very efficient, non-cross-reactive tRNA/four-base codon pairs for AGGA, UAGA, CCCU and CUAG. The most efficient four-base codon suppressors had Watson-Crick complementary anticodons, and the sequences of the anticodon loops outside of the anticodons varied with the anticodon. Additionally, four-base codon reporter libraries were used to identify “shifty” sites at which +1 frameshifting is most favorable in the absence of suppressor tRNAs in Escherichia coli. We intend to use these tRNAs to explore the limits of unnatural polypeptide biosynthesis, both in vitro and eventually in vivo. In addition, this selection strategy is being extended to identify novel five- and six-base codon suppressors.

The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology

The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.

Exploring the Limits of Codon and Anticodon Size

We previously employed a combinatorial approach to identify the most efficient suppressors of four-base codons in E. coli. We have now examined the suppression of two-, three-, four-, five-, and six-base codons with tRNAs containing 6-10 nt in their anticodon loops. We found that the E. coli translational machinery tolerates codons of 3-5 bases and that tRNAs with 6-10 nt anticodon loops can suppress these codons. However, N-length codons were found to prefer N + 4-length anticodon loops. Additionally, sequence preferences, including the requirement of Watson-Crick complementarity to the codon, were evident in the loops. These selections have yielded efficient suppressors of four-base and five-base codons for our ongoing efforts to expand the genetic code. They also highlight some of the parameters that underlie the fidelity of frame maintenance.

Gene synthesis demystified

DNA fabrication of genetic cassettes at base-level precision is transforming genetic engineering from a laborious art to an information-driven discipline. Although substantial advances have been made in the development of DNA fabrication, the methods employed vary widely based on the length of the DNA. All of these methods are available commercially, but can also be performed at the molecular biology bench using typical reagents and procedures. Because the technology is not mature and is still evolving rapidly, it is helpful to gain some understanding of the different steps in this process and the associated technical challenges to successfully take advantage of DNA fabrication in a research project.

Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems

Background Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. Results We illustrate Eugenes capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugenes ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. Conclusions Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly.

Algorithms for automated DNA assembly

Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and formal approaches are needed for exploring these vast design spaces. By automating the design of DNA fabrication schemes using computational algorithms, we can eliminate human error while reducing redundant operations, thus minimizing the time and cost required for conducting biological engineering experiments. Here, we provide algorithms that optimize the simultaneous assembly of a collection of related DNA sequences. We compare our algorithms to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with random search approaches on two real-world datasets show that our algorithms can also quickly find lower-cost solutions for large datasets.

Successes and failures in modular genetic engineering

Synthetic biology relies on engineering concepts such as abstraction, standardization, and decoupling to develop systems that address environmental, clinical, and industrial needs. Recent advances in applying modular design to system development have enabled creation of increasingly complex systems. However, several challenges to module and system development remain, including syntactic errors, semantic errors, parameter mismatches, contextual sensitivity, noise and evolution, and load and stress. To combat these challenges, researchers should develop a framework for describing and reasoning about biological information, design systems with modularity in mind, and investigate how to predictively describe the diverse sources and consequences of metabolic load and stress.

Essential information for synthetic DNA sequences

Jean Peccoud1, J Christopher Anderson2, Deepak Chandran3, Douglas Densmore4, Michal Galdzicki5, Matthew W Lux1, Cesar A Rodriguez6, Guy-Bart Stan7 & Herbert M Sauro3 1Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA. 2Department of Bioengineering, QB3: California Institute for Quantitative Biological Research, University of California, Berkeley, California, USA. 3Department of Bioengineering, University of Washington, Seattle, Washington, USA. 4Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts, USA.5Biomedical and Health Informatics, University of Washington, Seattle, Washington, USA. 6BIOFAB, Emeryville, California, USA. 7Department of Bioengineering and Centre for Synthetic Biology and Innovation, Imperial College London, London, UK. e-mail: peccoud@vt.edu

Automated Assembly of Standard Biological Parts

The primary bottleneck in synthetic biology research today is the construction of physical DNAs, a process that is often expensive, time-consuming, and riddled with cloning difficulties associated with the uniqueness of each DNA sequence. We have developed a series of biological and computational tools that lower existing barriers to automation and scaling to enable affordable, fast, and accurate construction of large DNA sets. Here we provide detailed protocols for high-throughput, automated assembly of BglBrick standard biological parts using iterative 2ab reactions. We have implemented these protocols on a minimal hardware platform consisting of a Biomek 3000 liquid handling robot, a benchtop centrifuge and a plate thermocycler, with additional support from a software tool called AssemblyManager. This methodology enables parallel assembly of several hundred large error-free DNAs with a 96+% success rate.