Directed acyclic graph-based technology mapping of genetic circuit models

SynBioSuite: A Tool for Improving the Workflow for Genetic Design and Modeling

Synthetic biology research has led to the development of many software tools for designing, constructing, editing, simulating, and sharing genetic parts and circuits. Among these tools are SBOLCanvas, iBioSim, and SynBioHub, which can be used in conjunction to create a genetic circuit design following the design-build-test-learn process. However, although automation works within these tools, most of these software tools are not integrated, and the process of transferring information between them is a very manual, error-prone process. To address this problem, this work automates some of these processes and presents SynBioSuite, a cloud-based tool that eliminates many of the drawbacks of the current approach by automating the setup and reception of results for simulating a designed genetic circuit via an application programming interface.

Context-Aware Technology Mapping in Genetic Design Automation

Genetic design automation (GDA) tools hold promise to speed-up circuit design in synthetic biology. Their widespread adoption is hampered by their limited predictive power, resulting in frequent deviations between the in silico and in vivo performance of a genetic circuit. Context effects, i.e., the change in overall circuit functioning, due to the intracellular environment of the host and due to cross-talk among circuits components are believed to be a major source for the aforementioned deviations. Incorporating these effects in computational models of GDA tools is challenging but is expected to boost their predictive power and hence their deployment. Using fine-grained thermodynamic models of promoter activity, we show in this work how to account for two major components of cellular context effects: (i) crosstalk due to limited specificity of used regulators and (ii) titration of circuit regulators to off-target binding sites on the host genome. We show how we can compensate the incurred increase in computational complexity through dedicated branch-and-bound techniques during the technology mapping process. Using the synthesis of several combinational logic circuits based on Cello's device library as a case study, we analyze the effect of different intensities and distributions of crosstalk on circuit performance and on the usability of a given device library.

Excel-SBOL Converter: Creating SBOL from Excel Templates and Vice Versa

Standards support synthetic biology research by enabling the exchange of component information. However, using formal representations, such as the Synthetic Biology Open Language (SBOL), typically requires either a thorough understanding of these standards or a suite of tools developed in concurrence with the ontologies. Since these tools may be a barrier for use by many practitioners, the Excel-SBOL Converter was developed to facilitate the use of SBOL and integration into existing workflows. The converter consists of two Python libraries: one that converts Excel templates to SBOL and another that converts SBOL to an Excel workbook. Both libraries can be used either directly or via a SynBioHub plugin.

Biocircuits in plants and eukaryotic algae

As one of synthetic biology's foundations, biocircuits are a strategy of genetic parts assembling to recognize a signal and to produce a desirable output to interfere with a biological function. In this review, we revisited the progress in the biocircuits technology basis and its mandatory elements, such as the characterization and assembly of functional parts. Furthermore, for a successful implementation, the transcriptional control systems are a relevant point, and the computational tools help to predict the best combinations among the biological parts planned to be used to achieve the desirable phenotype. However, many challenges are involved in delivering and stabilizing the synthetic structures. Some research experiences, such as the golden crops, biosensors, and artificial photosynthetic structures, can indicate the positive and limiting aspects of the practice. Finally, we envision that the modulatory structural feature and the possibility of finer gene regulation through biocircuits can contribute to the complex design of synthetic chromosomes aiming to develop plants and algae with new or improved functions.

Engineering genetic circuits: advancements in genetic design automation tools and standards for synthetic biology

Synthetic biology (SynBio) is a field at the intersection of biology and engineering. Inspired by engineering principles, researchers use defined parts to build functionally defined biological circuits. Genetic design automation (GDA) allows scientists to design, model, and analyze their genetic circuits in silico before building them in the lab, saving time, and resources in the process. Establishing SynBio's future is dependent on GDA, since the computational approach opens the field to a broad, interdisciplinary community. However, challenges with part libraries, standards, and software tools are currently stalling progress in the field. This review first covers recent advancements in GDA, followed by an assessment of the challenges ahead, and a proposed automated genetic design workflow for the future.

Genetic circuit design automation with Cello 2.0

Cells interact with their environment, communicate among themselves, track time and make decisions through functions controlled by natural regulatory genetic circuits consisting of interacting biological components. Synthetic programmable circuits used in therapeutics and other applications can be automatically designed by computer-aided tools. The Cello software designs the DNA sequences for programmable circuits based on a high-level software description and a library of characterized DNA parts representing Boolean logic gates. This process allows for design specification reuse, modular DNA part library curation and formalized circuit transformations based on experimental data. This protocol describes Cello 2.0, a freely available cross-platform software written in Java. Cello 2.0 enables flexible descriptions of the logic gates' structure and their mathematical models representing dynamic behavior, new formal rules for describing the placement of gates in a genome, a new graphical user interface, support for Verilog 2005 syntax and a connection to the SynBioHub parts repository software environment. Collectively, these features expand Cello's capabilities beyond Escherichia coli plasmids to new organisms and broader genetic contexts, including the genome. Designing circuits with Cello 2.0 produces an abstract Boolean network from a Verilog file, assigns biological parts to each node in the Boolean network, constructs a DNA sequence and generates highly structured and annotated sequence representations suitable for downstream processing and fabrication, respectively. The result is a sequence implementing the specified Boolean function in the organism and predictions of circuit performance. Depending on the size of the design space and users' expertise, jobs may take minutes or hours to complete.

EMMA-CAD: Design Automation for Synthetic Mammalian Constructs

Computational design tools are the cornerstone of synthetic biology and have underpinned its rapid development over the past two decades. As the field has matured, the scale of biological investigation has expanded dramatically, and researchers often must rely on computational tools to operate in the high-throughput investigational space. This is especially apparent in the modular design of DNA expression circuits, where complexity is accumulated rapidly. Alongside our automated pipeline for the high-throughput construction of Extensible Modular Mammalian Assembly (EMMA) expression vectors, we recognized the need for an integrated software solution for EMMA vector design. Here we present EMMA-CAD (https://emma.cailab.org), a powerful web-based computer-aided design tool for the rapid design of bespoke mammalian expression vectors. EMMA-CAD features a variety of functionalities, including a user-friendly design interface, automated connector selection underpinned by rigorous computer optimization algorithms, customization of part libraries, and personalized design spaces. Capable of translating vector assembly designs into human- and machine-readable protocols for vector construction, EMMA-CAD integrates seamlessly into our automated EMMA pipeline, hence completing an end-to-end design to production workflow.

Automated Design of Robust Genetic Circuits: Structural Variants and Parameter Uncertainty

Genetic design automation methods for combinational circuits often rely on standard algorithms from electronic design automation in their circuit synthesis and technology mapping. However, those algorithms are domain-specific and are hence often not directly suitable for the biological context. In this work we identify aspects of those algorithms that require domain-adaptation. We first demonstrate that enumerating structural variants for a given Boolean specification allows us to find better performing circuits and that stochastic gate assignment methods need to be properly adjusted in order to find the best assignment. Second, we present a general circuit scoring scheme that accounts for the limited accuracy of biological device models including the variability across cells and show that circuits selected according to this score exhibit higher robustness with respect to parametric variations. If gate characteristics in a library are just given in terms of intervals, we provide means to efficiently propagate signals through such a circuit and compute corresponding scores. We demonstrate the novel design approach using the Cello gate library and 33 logic functions that were synthesized and implemented in vivo recently (Nielsen, A., et al., Science, 2016, 352 (6281), DOI: 10.1126/science.aac7341). Across this set of functions, 32 of them can be improved by simply considering structural variants yielding performance gains of up to 7.9-fold, whereas 22 of them can be improved with gains up to 26-fold when selecting circuits according to the novel robustness score. We furthermore report on the synergistic combination of the two proposed improvements.

iBioSim 3: A Tool for Model-Based Genetic Circuit Design

The iBioSim tool has been developed to facilitate the design of genetic circuits via a model-based design strategy. This paper illustrates the new features incorporated into the tool for DNA circuit design, design analysis, and design synthesis, all of which can be used in a workflow for the systematic construction of new genetic circuits.

A standard-enabled workflow for synthetic biology

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.

SYNBADm: a tool for optimization-based automated design of synthetic gene circuits

MOTIVATION

The design of de novo circuits with predefined performance specifications is a challenging problem in Synthetic Biology. Computational models and tools have proved to be crucial for a successful wet lab implementation. Natural gene circuits are complex, subject to evolutionary tradeoffs and playing multiple roles. However, most synthetic designs implemented to date are simple and perform a single task. As the field progresses, advanced computational tools are needed in order to handle greater levels of circuit complexity in a more flexible way and considering multiple design criteria.

RESULTS

This works presents SYNBADm (SYNthetic Biology Automated optimal Design in Matlab), a software toolbox for the automatic optimal design of gene circuits with targeted functions from libraries of components. This tool makes use of global optimization to simultaneously search the space of structures and kinetic parameters. SYNBADm can efficiently handle high levels of circuit complexity and can consider multiple design criteria through multiobjective optimization. Further, it provides flexible design capabilities, i.e. the user can define the modeling framework, library of components and target performance function(s).

AVAILABILITY AND IMPLEMENTATION

SYNBADm runs under the popular MATLAB computational environment, and is available under GPLv3 license at https://sites.google.com/site/synbadm CONTACT: ireneotero@iim.csic.es or julio@iim.csic.es.

Genetic circuit design automation

Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits forEscherichia coli(880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language

In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

Proposed data model for the next version of the synthetic biology open language

While the first version of the Synthetic Biology Open Language (SBOL) has been adopted by several academic and commercial genetic design automation (GDA) software tools, it only covers a limited number of the requirements for a standardized exchange format for synthetic biology. In particular, SBOL Version 1.1 is capable of representing DNA components and their hierarchical composition via sequence annotations. This proposal revises SBOL Version 1.1, enabling the representation of a wider range of components with and without sequences, including RNA components, protein components, small molecules, and molecular complexes. It also introduces modules to instantiate groups of components on the basis of their shared function and assert molecular interactions between components. By increasing the range of structural and functional descriptions in SBOL and allowing for their composition, the proposed improvements enable SBOL to represent and facilitate the exchange of a broader class of genetic designs.

Parts & pools: a framework for modular design of synthetic gene circuits

Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.