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 communitydriven, 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.Synthetic biology treats biological organisms as a new technological medium with a unique set of characteristics, such as the ability to self-repair, evolve and replicate. These characteristics create their own engineering challenges, but offer a rich and largely untapped source of potential applications across a broad range of sectors 1,2 . Applications such as biomolecular computing 3 , metabolic engineering 4 , or reconstruction and exploration of natural cell biology 5,6 commonly require the design of new genetically encoded systems. As engineers, synthetic biologists most often base their designs on previously described 'DNA segments' (see Supplementary Table 1 for definitions of selected terms) to meet their design requirements. Reuse of the DNA sequence for these segments involves their exchange between laboratories and their hierarchical composition to form devices and systems with higher level function.Every engineering field relies on a set of 'standards' 7 that practitioners follow to enable the exchange and reuse of designs for 'systems' , 'devices' and 'components' . Similarly, the representation of synthetic biology designs using computer-readable 'data standards' has the potential to facilitate the forward engineering of novel biological systems from previously characterized devices and components. For example, such standards could enable synthetic biology companies to offer catalogs of devices and components by means of computerreadable data sheets, just as modern semiconductor companies do for electronics. Such standards could also enable a synthetic biologist to develop portions of a design using one software tool, refine the design using another tool, and finally transmit it electronically to a colleague or commercial fabrication company.In order for synthetic biology designs to scale up in complexity, researchers will need to make greater use of specialized design tools and parts repositories. Seamless inter-tool communication would, for example, allow the separation of gene...

Cell-free protein synthesis (CFPS) platforms, once primarily a research tool to produce difficult to express proteins, are increasingly being pursued by the synthetic biology community for applications including biomanufacturing, rapid screening systems, and field-ready sensors. While consistency within individual studies is apparent in the literature, challenges with reproducing results between laboratories, or even between individuals within a laboratory, are discussed openly by practitioners. As the field continues to grow and move toward applications, a quantitative understanding of expected variability for CFPS and the relative contribution of underlying sources will become increasingly important. Here we offer the first quantitative assessment of interlaboratory variability in CFPS. Three laboratories implemented a single CFPS protocol and performed a series of exchanges, both of material and personnel, designed to quantify relative contributions to variability associated with the site, operator, cell extract preparation, and supplemental reagent preparation. We found that materials prepared at each laboratory, exchanged pairwise, and tested at each site resulted in 40.3% coefficient of variation compared to 7.64% for a single operator across days using a single set of materials. Reagent preparations contributed significantly to observed variability; extract preparations, however, surprisingly did not explain any of the observed variability, even when prepared in different laboratories by different operators. Subsequent exchanges showed that both the site and the operator each contributed to observed interlaboratory variability. In addition to providing the first quantitative assessment of interlaboratory variability in CFPS, these results establish a baseline for individual operator variability across days that can be used as an initial benchmark for community-driven standardization efforts. We anticipate that our results will narrow future avenues of investigation to develop best practices that will ultimately drive down interlaboratory variability, accelerating research progress and informing the suitability of CFPS for real-world applications.

Cell-free systems that mimic essential cell functions, such as gene expression, have dramatically expanded in recent years, both in terms of applications and widespread adoption. Here we provide a review of cell-extract methods, with a specific focus on prokaryotic systems. Firstly, we describe the diversity of Escherichia coli genetic strains available and their corresponding utility. We then trace the history of cell-extract methodology over the past 20 years, showing key improvements that lower the entry level for new researchers. Next, we survey the rise of new prokaryotic cell-free systems, with associated methods, and the opportunities provided. Finally, we use this historical perspective to comment on the role of methodology improvements and highlight where further improvements may be possible.

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Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology.