Synthetic biology (Oxford, England)最新文献

The ribosome is a two-subunit, macromolecular machine composed of RNA and proteins that carries out the polymerization of α-amino acids into polypeptides. Efforts to engineer ribosomal RNA (rRNA) deepen our understanding of molecular translation and provide opportunities to expand the chemistry of life by creating ribosomes with altered properties. Toward these efforts, reverse transcription PCR (RT-PCR) of the entire 16S and 23S rRNAs, which make up the 30S small subunit and 50S large subunit, respectively, is important for isolating desired phenotypes. However, reverse transcription of rRNA is challenging due to extensive secondary structure and post-transcriptional modifications. One key challenge is that existing commercial kits for RT-PCR rely on reverse transcriptases that lack the extreme thermostability and processivity found in many commercial DNA polymerases, which can result in subpar performance on challenging templates. Here, we develop methods employing a synthetic thermostable reverse transcriptase (RTX) to enable and optimize RT-PCR of the complete Escherichia coli 16S and 23S rRNAs. We also characterize the error rate of RTX when traversing the various post-transcriptional modifications of the 23S rRNA. We anticipate that this work will facilitate efforts to study and characterize many naturally occurring long RNAs and to engineer the translation apparatus for synthetic biology.

The rapid design and assembly of synthetic DNA constructs have become a crucial component of biological engineering projects via iterative design-build-test-learn cycles. In this perspective, we provide an overview of the workflows used to generate the thousands of constructs and libraries produced each year at the U.S. Department of Energy Joint Genome Institute. Particular attention is paid to describing pipelines, tools used, types of scientific projects enabled by the platform and challenges faced in further scaling output.

Successful industrial biotechnological solutions to biofuels and other chemicals production rely on effective competition with existing lower-cost natural sources and synthetic chemistry approaches enabled by adopting low-cost bioreactors and processes. This is achievable by mobilizing Halomonas as a next generation industrial chassis, which can be cultivated under non-sterile conditions. To increase the cost effectiveness of an existing sustainable low carbon bio-propane production strategy, we designed and screened a constitutive promoter library based on the known strong porin promoter from Halomonas. Comparative studies were performed between Escherichia coli and Halomonas using the reporter gene red fluorescent protein (RFP). Later studies with a fatty acid photodecarboxylase-RFP fusion protein demonstrated tuneable propane production in Halomonas and E. coli, with an ∼8-fold improvement in yield over comparable isopropyl-β-D-thiogalactoside-inducible systems. This novel set of promoters is a useful addition to the synthetic biology toolbox for future engineering of Halomonas to make chemicals and fuels.

The RNA-guided endonuclease system CRISPR-Cas9 has been extensively modified since its discovery, allowing its capabilities to extend far beyond double-stranded cleavage to high fidelity insertions, deletions and single base edits. Such innovations have been possible due to the modular architecture of CRISPR-Cas9 and the robustness of its component parts to modifications and the fusion of new functional elements. Here, we review the broad toolkit of CRISPR-Cas9-based systems now available for diverse genome-editing tasks. We provide an overview of their core molecular structure and mechanism and distil the design principles used to engineer their diverse functionalities. We end by looking beyond the biochemistry and toward the societal and ethical challenges that these CRISPR-Cas9 systems face if their transformative capabilities are to be deployed in a safe and acceptable manner.

The increasing demand for bio-based compounds produced from waste or sustainable sources is driving biofoundries to deliver a new generation of prototyping biomanufacturing platforms. Integration and automation of the design, build, test and learn (DBTL) steps in centers like SYNBIOCHEM in Manchester and across the globe (Global Biofoundries Alliance) are helping to reduce the delivery time from initial strain screening and prototyping towards industrial production. Notably, a portfolio of producer strains for a suite of material monomers was recently developed, some approaching industrial titers, in a tour de force by the Manchester Centre that was achieved in less than 90 days. New in silico design tools are providing significant contributions to the front end of the DBTL pipelines. At the same time, the far-reaching initiatives of modern biofoundries are generating a large amount of high-dimensional data and knowledge that can be integrated through automated learning to expedite the DBTL cycle. In this Perspective, the new design tools and the role of the learning component as an enabling technology for the next generation of automated biofoundries are discussed. Future biofoundries will operate under completely automated DBTL cycles driven by in silico optimal experimental planning, full biomanufacturing devices connectivity, virtualization platforms and cloud-based design. The automated generation of robotic build worklists and the integration of machine-learning algorithms will collectively allow high levels of adaptability and rapid design changes toward fully automated smart biomanufacturing.

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms-organisms that are easy to use like Escherichia coli-often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute's DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

Archaea produce unique membrane lipids, which possess two fully saturated isoprenoid chains linked to the glycerol moiety via ether bonds. The isoprenoid chain length of archaeal membrane lipids is believed to be important for some archaea to thrive in extreme environments because the hyperthermophilic archaeon Aeropyrum pernix and some halophilic archaea synthesize extended C25,C25-archaeal diether-type membrane lipids, which have isoprenoid chains that are longer than those of typical C20,C20-diether lipids. Natural archaeal diether lipids possessing longer C30 or C35 isoprenoid chains, however, have yet to be isolated. In the present study, we attempted to synthesize such hyperextended archaeal membrane lipids. We investigated the substrate preference of the enzyme sn-2,3-(digeranylfarnesyl)glycerol-1-phosphate synthase from A. pernix, which catalyzes the transfer of the second C25 isoprenoid chain to the glycerol moiety in the biosynthetic pathway of C25,C25-archaeal membrane lipids. The enzyme was shown to accept sn-3-hexaprenylglycerol-1-phosphate, which has a C30 isoprenoid chain, as a prenyl acceptor substrate to synthesize sn-2-geranylfarnesyl-3-hexaprenylglycerol-1-phosphate, a supposed precursor for hyperextended C25,C30-archaeal membrane lipids. Furthermore, we constructed an artificial biosynthetic pathway by introducing 4 archaeal genes and 1 gene from Bacillus subtilis in the cells of Escherichia coli, which enabled the E. coli strain to produce hyperextended C25,C30-archaeal membrane lipids, which have never been reported so far.

Synthetic receptors are powerful tools for engineering mammalian cell-based devices. These biosensors enable cell-based therapies to perform complex tasks such as regulating therapeutic gene expression in response to sensing physiological cues. Although multiple synthetic receptor systems now exist, many aspects of receptor performance are poorly understood. In general, it would be useful to understand how receptor design choices influence performance characteristics. In this study, we examined the modular extracellular sensor architecture (MESA) and systematically evaluated previously unexamined design choices, yielding substantially improved receptors. A key finding that might extend to other receptor systems is that the choice of transmembrane domain (TMD) is important for generating high-performing receptors. To provide mechanistic insights, we adopted and employed a Förster resonance energy transfer-based assay to elucidate how TMDs affect receptor complex formation and connected these observations to functional performance. To build further insight into these phenomena, we developed a library of new MESA receptors that sense an expanded set of ligands. Based upon these explorations, we conclude that TMDs affect signaling primarily by modulating intracellular domain geometry. Finally, to guide the design of future receptors, we propose general principles for linking design choices to biophysical mechanisms and performance characteristics.