Genetic Design via Combinatorial Constraint Specification

Characterization of Programmable Transcription Activators in the Model Monocot Setaria viridis Via Protoplast Transfection

Recent advances in DNA synthesis and assembly allow for genetic constructs to be designed and constructed in high throughput. Characterizing large numbers of variant genetic designs is not feasible with low-throughput and time-consuming plant transformation workflows. Protoplast transformation offers a rapid, high-throughput compatible alternative for testing genetic constructs in plant-relevant molecular environments. Here, we describe a protocol for protoplast transformation using a recent experiment in genetic optimization of dCas9-based programmable transcription activators as an example.

A synthetic distributed genetic multi-bit counter

A design for genetically encoded counters is proposed via repressor-based circuits. An N-bit counter reads sequences of input pulses and displays the total number of pulses, modulo 2N. The design is based on distributed computation with specialized cell types allocated to specific tasks. This allows scalability and bypasses constraints on the maximal number of circuit genes per cell due to toxicity or failures due to resource limitations. The design starts with a single-bit counter. The N-bit counter is then obtained by interconnecting (using diffusible chemicals) a set of N single-bit counters and connector modules. An optimization framework is used to determine appropriate gate parameters and to compute bounds on admissible pulse widths and relaxation (inter-pulse) times, as well as to guide the construction of novel gates. This work can be viewed as a step toward obtaining circuits that are capable of finite automaton computation in analogy to digital central processing units.

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A single-bit counter is designed for a repressor-based genetic circuit

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A scalable multi-bit counter is enabled by distributing the design across cells

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A computational optimization framework is proposed to guide the design

Cell-Free Protein Synthesis as a Prototyping Platform for Mammalian Synthetic Biology

The field of mammalian synthetic biology is expanding quickly, and technologies for engineering large synthetic gene circuits are increasingly accessible. However, for mammalian cell engineering, traditional tissue culture methods are slow and cumbersome, and are not suited for high-throughput characterization measurements. Here we have utilized mammalian cell-free protein synthesis (CFPS) assays using HeLa cell extracts and liquid handling automation as an alternative to tissue culture and flow cytometry-based measurements. Our CFPS assays take a few hours, and we have established optimized protocols for small-volume reactions using automated acoustic liquid handling technology. As a proof-of-concept, we characterized diverse types of genetic regulation in CFPS, including T7 constitutive promoter variants, internal ribosomal entry sites (IRES) constitutive translation-initiation sequence variants, CRISPR/dCas9-mediated transcription repression, and L7Ae-mediated translation repression. Our data shows simple regulatory elements for use in mammalian cells can be quickly prototyped in a CFPS model system.

Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL)

As improvements in DNA synthesis technology and assembly methods make combinatorial assembly of genetic constructs increasingly accessible, methods for representing genetic constructs likewise need to improve to handle the exponential growth of combinatorial design space. To this end, we present a community accepted extension of the SBOL data standard that allows for the efficient and flexible encoding of combinatorial designs. This extension includes data structures for representing genetic designs with "variable" components that can be implemented by choosing one of many linked designs for existing genetic parts or constructs. We demonstrate the representational power of the SBOL combinatorial design extension through case studies on metabolic pathway design and genetic circuit design, and we report the expansion of the SBOLDesigner software tool to support users in creating and modifying combinatorial designs in SBOL.

Cell-Free Synthetic Biology Platform for Engineering Synthetic Biological Circuits and Systems

Synthetic biology brings engineering disciplines to create novel biological systems for biomedical and technological applications. The substantial growth of the synthetic biology field in the past decade is poised to transform biotechnology and medicine. To streamline design processes and facilitate debugging of complex synthetic circuits, cell-free synthetic biology approaches has reached broad research communities both in academia and industry. By recapitulating gene expression systems in vitro, cell-free expression systems offer flexibility to explore beyond the confines of living cells and allow networking of synthetic and natural systems. Here, we review the capabilities of the current cell-free platforms, focusing on nucleic acid-based molecular programs and circuit construction. We survey the recent developments including cell-free transcription-translation platforms, DNA nanostructures and circuits, and novel classes of riboregulators. The links to mathematical models and the prospects of cell-free synthetic biology platforms will also be discussed.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Deep learning to predict the lab-of-origin of engineered DNA

Genetic engineering projects are rapidly growing in scale and complexity, driven by new tools to design and construct DNA. There is increasing concern that widened access to these technologies could lead to attempts to construct cells for malicious intent, illegal drug production, or to steal intellectual property. Determining the origin of a DNA sequence is difficult and time-consuming. Here deep learning is applied to predict the lab-of-origin of a DNA sequence. A convolutional neural network was trained on the Addgene plasmid dataset that contained 42,364 engineered DNA sequences from 2230 labs as of February 2016. The network correctly identifies the source lab 48% of the time and 70% it appears in the top 10 predicted labs. Often, there is not a single "smoking gun" that affiliates a DNA sequence with a lab. Rather, it is a combination of design choices that are individually common but collectively reveal the designer.

Who are the users of synthetic DNA? Using metaphors to activate microorganisms at the center of synthetic biology

Synthetic biology, a multidisciplinary field involving designing and building with DNA, often designs and builds in microorganisms. The role of these microorganisms tends to be understood through metaphors making the microbial cell like a machine and emphasizing its passivity: cells are described as platforms, chassis, and computers. Here, I point to the efficacy of such metaphors in enacting the microorganism as a particular kind of (non-)participant in the research process, and I suggest the utility of employing metaphors that make microorganisms a different kind of thing-active participants, contributors, and even collaborators in scientific research. This suggestion is worth making, I argue, because enabling the activity of the microorganism generates opportunities for learning from microorganisms in ways that may help explain currently unexplained phenomena in synthetic biology and suggest new experimental directions. Moreover, "activating the microorganism" reorients relationships between human scientists and nonhuman experimental participants away from control over nonhuman creatures and toward respect for and listening to them, generating conditions of possibility for exploring what responsible research means when humans try to be responsible toward and even with creatures across species boundaries.

Boosting Secondary Metabolite Production and Discovery through the Engineering of Novel Microbial Biosensors

Bacteria are a source of a large number of secondary metabolites with several biomedical and biotechnological applications. In recent years, there has been tremendous progress in the development of novel synthetic biology approaches both to increase the production rate of secondary metabolites of interest in native producers and to mine and reconstruct novel biosynthetic gene clusters in heterologous hosts. Here, we present the recent advances toward the engineering of novel microbial biosensors to detect the synthesis of secondary metabolites in bacteria and in the development of synthetic promoters and expression systems aiming at the construction of microbial cell factories for the production of these compounds. We place special focus on the potential of Gram-negative bacteria as a source of biosynthetic gene clusters and hosts for pathway assembly, on the construction and characterization of novel promoters for native hosts, and on the use of computer-aided design of novel pathways and expression systems for secondary metabolite production. Finally, we discuss some of the potentials and limitations of the approaches that are currently being developed and we highlight new directions that could be addressed in the field.

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available "design space" represented by "devices" created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction. Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols. The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation.