Modular cloning systems streamline laboratory workflows by consolidating genetic ‘parts’ into reusable and modular collections, enabling researchers to fast-track strain construction. The GoldenBraid 2.0 modular cloning system utilizes the cutting property of type IIS restriction enzymes to create defined genetic ‘grammars’, which facilitate the reuse of standardized genetic parts and assembly of genetic parts in the right order. Here, we present a GoldenBraid 2.0 toolkit of genetic parts designed to accelerate cloning in the model bacterium Escherichia coli. This toolkit features 478 pre-made parts for gene expression and protein tagging as well as strains to expedite cloning and strain construction, enabling researchers to quickly generate functional plasmid-borne or chromosome-integrated expression constructs. In addition, we provide a complete laboratory manual with overviews of common reagent recipes, E. coli protocols, and community resources to promote toolkit utilization. By streamlining the assembly process, this resource will reduce the financial and temporal burdens of cloning and strain building in many laboratory settings.

Natural products are a valuable source of pharmaceuticals, providing a majority of the small-molecule drugs in use today. However, their production through organic synthesis or in heterologous hosts can be difficult and time-consuming. Therefore, to allow for easier screening and production of natural products, we demonstrated the use of a cell-free protein synthesis system to partially assemble natural products in vitro using S-Adenosyl Methionine (SAM)-dependent methyltransferase enzyme reactions. The tea caffeine synthase, TCS1, was utilized to synthesize caffeine within a cell-free protein synthesis system. Cell-free systems also provide the benefit of allowing the use of substrates that would normally be toxic in a cellular environment to synthesize novel products. However, TCS1 is unable to utilize a compound like S-adenosyl ethionine as a cofactor to create ethylated caffeine analogs. The automation and reduced metabolic engineering requirements of cell-free protein synthesis systems, in combination with other synthesis methods, may enable the more efficient generation of new compounds.Graphical

Reusability has been a key issue since the origins of the parts-based approach to synthetic biology. Starting with the BioBrick™ standard part, multiple efforts have aimed to make biology more exchangeable. The reusability of parts and other deoxyribonucleic acid-based data has proven over time to be challenging, however. Drawing on a series of qualitative interviews and an international workshop, this article explores the challenges of reusability in real laboratory practice. It shows particular ways that standards are experienced as presenting shortcomings for capturing the kinds of contextual information crucial for scientists to be able to reuse biological parts and data. I argue that researchers in specific laboratories develop a sense of how much circumstantial detail they need to share for others to be able to make sense of their data and possibly reuse it. When choosing particular reporting formats, recharacterizing data to gain closer knowledge or requesting additional information, researchers enact an ‘economy of details’. The farther apart two laboratories are in disciplinary, epistemological, technical and geographical terms, the more detailed information needs to be captured for data to be reusable across contexts. In synthetic biology, disciplinary distance between computing science and engineering researchers and experimentalist biologists is reflected in diverging views on standards: what kind of information should be included to enable reusability, what kind of information can be captured by standards at all and how they may serve to produce and circulate knowledge. I argue that such interdisciplinary tensions lie at the core of difficulties in setting standards in synthetic biology.

In this study, we provide a universal approach to Gene Expression Engineering (GeneEE) for creating artificial expression systems. GeneEE leads to the generation of artificial 5ʹ regulatory sequences (ARES) consisting of promoters and 5ʹ untranslated regions. The ARES lead to the successful recruitment of RNA polymerase, related sigma factors and ribosomal proteins that result in a wide range of expression levels. We also demonstrate that by engaging native transcription regulators, GeneEE can be used to generate inducible promoters. To showcase the universality of the approach, we demonstrate that 200-nucleotide (nt)-long DNA with random composition can be used to generate functional expression systems in six bacterial species, Escherichia coli, Pseudomonas putida, Corynebacterium glutamicum, Thermus thermophilus, Streptomyces albus and Streptomyces lividans, and the eukaryote yeast Saccharomyces cerevisiae.

<br/>Mix the ingredients, pour them into a tin, and ‘bake’ at ambi- ent temperature for 5 days. What sounds like instructions for a ready-made baking mix could soon become a way to grow your own home—or emergency shelter needed after a natural disaster (1).

Recombineering is an important tool in gene editing, enabling fast, precise and highly specific in vivo modification of microbial genomes. Oligonucleotide-mediated recombineering via the in vivo production of single-stranded DNA can overcome the limitations of traditional recombineering methods that rely on the exogenous delivery of editing templates. By modifying a previously reported plasmid-based system for fully in vivo single-stranded DNA recombineering, we demonstrate iterative editing of independent loci by utilizing a temperature-sensitive origin of replication for easy curing of the editing plasmid from recombinant cells. Optimization of the promoters driving the expression of the system’s functional components, combined with targeted counterselection against unedited cells with Cas9 nuclease, enabled editing efficiencies of 90–100%. The addition of a dominant-negative mutL allele to the system allowed single-nucleotide edits that were otherwise unachievable due to mismatch repair. Finally, we tested alternative recombinases and found that efficiency significantly increased for some targets. Requiring only a single cloning step for retargeting, our system provides an easy-to-use method for rapid, efficient construction of desired mutants. Graphical

Practical delivery of Findable, Accessible, Reusable and Interoperable principles for research data management requires expertise, time resource, (meta)data standards and formats, software tools and public repositories. The Synthetic Biology Open Language (SBOL2) metadata standard enables FAIR sharing of the designs of synthetic biology constructs, notably in the repository of the SynBioHub platform. Large libraries of such constructs are increasingly easy to produce in practice, for example, in DNA foundries. However, manual curation of the equivalent libraries of designs remains cumbersome for a typical lab researcher, creating a barrier to data sharing. Here, we present a simple tool SynBio2Easy, which streamlines and automates operations on multiple Synthetic Biology Open Language (SBOL) designs using Microsoft Excel® tables as metadata inputs. The tool provides several utilities for manipulation of SBOL documents and interaction with SynBioHub: for example, generation of a library of plasmids based on an original design template, bulk deposition into SynBioHub, or annotation of existing SBOL component definitions with notes and authorship information. The tool was used to generate and deposit a collection of 3661 cyanobacterium Synechocystis plasmids into the public SynBioHub repository. In the process of developing the software and uploading these data, we evaluated some aspects of the SynBioHub platform and SBOL ecosystem, and we discuss proposals for improvement that could benefit the user community. With software such as SynBio2Easy, we aim to deliver a user-driven tooling to make FAIR a reality at all stages of the project lifecycle in synthetic biology research.Graphical

Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework’s efficiency.