Sharing Structure and Function in Biological Design with SBOL 2.0

Roehner, Nicholas; Beal, Jacob; Clancy, Kevin; Bartley, Bryan; Mısırlı, Göksel; Grünberg, Raik; Oberortner, Ernst; Pocock, Matthew; Bissell, M.G.; Madsen, Curtis; Nguyen, Tramy; Zhang, Michael; Zhang, Zhen; Zundel, Zach; Densmore, Douglas; Gennari, John H.; Wipat, Anil; Sauro, Herbert M.; Myers, Chris J.

doi:10.1021/acssynbio.5b00215

Cited by 80 publications

(88 citation statements)

References 46 publications

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“…The input to the pool extraction algorithm is a library of constructs where parts are defined using the SBOL standard (54,55). Most often, it is desirable to organize the pools around transcription units and this is done automatically based on the SBOL part definitions.…”

Section: Resultsmentioning

confidence: 99%

Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration

et al. 2016

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Genetic designs can consist of dozens of genes and hundreds of genetic parts. After evaluating a design, it is desirable to implement changes without the cost and burden of starting the construction process from scratch. Here, we report a two-step process where a large design space is divided into deep pools of composite parts, from which individuals are retrieved and assembled to build a final construct. The pools are built via multiplexed assembly and sequenced using next-generation sequencing. Each pool consists of ∼20 Mb of up to 5000 unique and sequence-verified composite parts that are barcoded for retrieval by PCR. This approach is applied to a 16-gene nitrogen fixation pathway, which is broken into pools containing a total of 55 848 composite parts (71.0 Mb). The pools encompass an enormous design space (1043 possible 23 kb constructs), from which an algorithm-guided 192-member 4.5 Mb library is built. Next, all 1030 possible genetic circuits based on 10 repressors (NOR/NOT gates) are encoded in pools where each repressor is fused to all permutations of input promoters. These demonstrate that multiplexing can be applied to encompass entire design spaces from which individuals can be accessed and evaluated.

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Section: Resultsmentioning

confidence: 99%

Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration

et al. 2016

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“…The Synthetic Biology Open Language (SBOL) SBOL (Galdzicki et al 2014;Roehner et al 2016b) is an emerging data exchange standard for synthetic biology with growing support among BDA tools, including database tools such as ICE (Ham et al 2012) and the SBOL Stack (Madsen et al 2016). SBOL has been de- Modeling and simulation results of a genetic AND gate and dual-feedback oscillator.…”

Section: Data Exchange and Standardizationmentioning

confidence: 99%

Design Automation in Synthetic Biology

Appleton

Madsen

Roehner

et al. 2017

Cold Spring Harb Perspect Biol

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Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas-specify, design, build, test, and learn-and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks.S ynthetic biology as a discipline has concerned itself with "forward engineering" living systems. This is a purposefully grand goal and is faced with numerous scientific, engineering, political, and ethical challenges. These engineering challenges include the storage of biological information, the design of complex, interacting biological systems using that information, the physical creation of these systems, and the dissemination of foundational principles as abstractions on which the next technical advances can be made. What should be clear to even the most casual observer is that computers, and the computational capabilities they bring with them, are going to be required if the field is going to succeed going forward. Debates remain regarding the framing of the computational approaches (Andrianantoandro et al. 2006;Lux et al. 2012;Densmore and Bhatia 2014), but there are few who debate the important and increasingly prominent role of computation in the field.Synthetic biology and its associated promise have attracted a wide variety of participants. In particular, computer engineers and computer scientists began developing computational tools for engineering these genetic systems using techniques from their disciplines. Electronic design automation (EDA) showed a clear process by which design formalisms could be built, software tools created, and a larger, separate industry developed (see latticeautomation.com; teselagen.com; deskgen.com; benchling.com). This pursuit in the synthetic biology field has recently been coined bio-design automation (BDA) (Densmore 2012). BDA often uses a "divide and conquer" approach for solving small parts of a larger problem one piece at a time and allows for specialists to tackle specific narrow problems in which they have considerable ex-

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“…For synthetic biology the Synthetic Biology Open Language (SBOL) is very useful in this respect. SBOL has been developed to exchange information about biological designs and their components [17][18][19]. This language provides a standardised format for designs, which is ideal for passing data between processes in a workflow.…”

Section: Research Articlementioning

confidence: 99%

Constructing synthetic biology workflows in the cloud

Mısırlı

Madsen

Murieta

et al. 2017

Engineering Biology

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Abstract:The synthetic biology design process has traditionally been heavily dependent upon manual searching, acquisition and integration of existing biological data. A large amount of such data is already available from Internetbased resources, but data exchange between these resources is often undertaken manually. Automating the communication between different resources can be done by the generation of computational workflows to achieve complex tasks that cannot be carried out easily or efficiently by a single resource. Computational workflows involve the passage of data from one resource, or process, to another in a distributed computing environment. In a typical bioinformatics workflow, the predefined order in which processes are invoked in a synchronous fashion and are described in a workflow definition document. However, in synthetic biology the diversity of resources and manufacturing tasks required favour a more flexible model for process execution. Here, the authors present the Protocol for Linking External Nodes (POLEN), a Cloud-based system that facilitates synthetic biology design workflows that operate asynchronously. Messages are used to notify POLEN resources of events in real time, and to log historical events such as the availability of new data, enabling networks of cooperation. POLEN can be used to coordinate the integration of different synthetic biology resources, to ensure consistency of information across distributed repositories through added support for data standards, and ultimately to facilitate the synthetic biology life cycle for designing and implementing biological systems.

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Sharing Structure and Function in Biological Design with SBOL 2.0

Cited by 80 publications

References 46 publications

Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration

Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration

Design Automation in Synthetic Biology

Constructing synthetic biology workflows in the cloud

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