Synthetic biology (SynBio) has attracted like no other recent development the attention not only of Life Science researchers and engineers but also of intellectuals, technology think-tanks, and private and public investors. This is largely due to its promise to propel biotechnology beyond its traditional realms in medicine, agriculture, and environment toward new territories historically dominated by the chemical and manufacturing industries─but now claimed to be amenable to complete biologization. For this to happen, it is crucial for the field to remain true to its foundational engineering drive, which relies on mathematics and quantitative tools to construct practical solutions to real-world problems. This article highlights several SynBio themes that, in our view, come with somewhat precarious promises that need to be tackled. First, SynBio must critically examine whether enough basic information is available to enable the design or redesign of life processes and turn biology from a descriptive science into a prescriptive one. Second, unlike circuit boards, cells are built with soft matter and possess inherent abilities to mutate and evolve, even without external cues. Third, the field cannot be presented as the one technical solution to many grave world problems and so must avoid exaggerated claims and hype. Finally, SynBio should pay heed to public sensitivities and involve social science in its development and growth, and thus change the technology narrative from sheer domination of the living world to conversation and win-win partnership.

ATP is the energy currency of the cell and new methods for ATP regeneration will benefit a range of emerging biotechnology applications including synthetic cells. We designed and assembled a membraneless ATP-regenerating enzymatic cascade by exploiting the substrate specificities of selected NAD(P)(H)-dependent oxidoreductases combined with substrate-specific kinases. The enzymes in the NAD(P)(H) cycle were selected to avoid cross-reactions, and the cascade was driven by irreversible fuel oxidation. As a proof-of-concept, formate oxidation was chosen as the fueling reaction. ATP regeneration was accomplished via the phosphorylation of NADH to NADPH and the subsequent transfer of the phosphate to ADP by a reversible NAD+ kinase. The cascade was able to regenerate ATP at a high rate (up to 0.74 mmol/L/h) for hours, and >90% conversion of ADP to ATP using monophosphate was also demonstrated. The cascade was used to regenerate ATP for use in cell free protein synthesis reactions, and the ATP production rate was further enhanced when powered by the multistep oxidation of methanol. The NAD(P)(H) cycle provides a simple cascade for the in vitro regeneration of ATP without the need for a pH-gradient or costly phosphate donors.

In synthetic biology, the precise control of gene expression is challenging due to the limited orthogonality of expression elements. Here, to address this issue and improve the reusability of genetic elements, we developed a bicistronic expression cassette in Corynebacterium glutamicum based on a leaderless promoter lacking a 5′UTR. The created leaderless bicistronic design (BCD) significantly improved the orthogonality of expression elements across different genes of interest. We also explored the importance of the fore-cistron and SD motif in maintaining the strength of leaderless BCDs. Additionally, we established a library containing 55,901 fore-cistrons and demonstrated that the regulatory range of gene expression in leaderless BCDs can be broader by modifying the fore-cistron sequence. This study provides a novel synthetic biology tool based on leaderless BCD for fine-tuning gene expression in C. glutamicum using fore-cistrons. Moreover, the strategy developed here can also be applied to improve the performance of other leaderless promoters in other bacteria.

It is impractical to develop a new parts collection for every potential host organism. It is well-established that gene expression parts, like genes, are qualitatively transferable, but there is little quantitative information defining transferability. Here, we systematically quantified the behavior of a parts set across multiple hosts. To do this, we developed a broad host range (BHR) plasmid system compatible with the large, modular CIDAR parts collection for E. coli, which we named openCIDAR. This enabled testing of a library of DNA constructs across the Pseudomonadota─Escherichia coli, Pseudomonas putida, Cupriavidus necator, and Komagataeibacter nataicola. Part performance was evaluated with a standardized characterization procedure that quantified expression in terms of molecules of equivalent fluorescein (MEFL), an objective unit of measure. The results showed that the CIDAR parts enable graded gene expression across all organisms─meaning that the same parts can be used to program E. coli, P. putida, C. necator, and K. nataicola. Most parts had a similar expression trend across hosts, although each organism had a different average gene expression level. The variability is enough that to achieve the same MEFL in a different organism, a lookup table is required to translate a design from one host to another. To identify truly divergent parts, we applied linear regression to a combinatorial set of promoters and ribosome binding sites, finding that the promoter J23100 behaves very differently in K. nataicola than in the other hosts. Thus, it is now possible to evaluate any CIDAR compatible part in three other hosts of interest, and the diversity of these hosts implies that the collection will also be compatible with many other Proteobacteria (Pseudomonadota). Furthermore, this work defines an approach to generalize modular synthetic biology parts sets beyond a single host, implying that only a few parts sets may be needed to span the tree of life. This will accelerate current efforts to engineer diverse species for environmental, biotechnological, and health applications.

Bacterial infections are a major cause of human morbidity and mortality on a global scale. Many bacterial pathogens, such as Escherichia coli, can cause diseases intracellularly via cell entry and avoidance of the host immune system. Antibiotic resistance has caused such infections to be problematic, which has necessitated the development of new antimicrobials. Bacteriophages are a potent alternative due to their specificity and ease of genetic modification. We have engineered phage K1F, which is specific to E. coli K1 to express an epidermal growth factor (EGF) and green fluorescent protein (GFP) fusion on the minor capsid protein. Here, we demonstrate that EGF-labeled phage K1F can be internalized more readily in human cell lines to eradicate E. coli K1 infection intracellularly. Further, we establish that K1F-GFP-EGF enters human cells primarily through endocytosis following EGF receptor (EGFR) induction, subverting the phagocytic mode of entry and permitting its accretion in the cytosol to seek out its bacterial host.

Knowledge about the substrate scope for a given enzyme is informative for elucidating biochemical pathways and also for expanding applications of the enzyme. However, no general methods are available to accurately predict the substrate specificity of an enzyme. Pyrrolysyl-tRNA synthetase (PylRS) is a powerful tool for incorporating various noncanonical amino acids (NCAAs) into proteins, which enabled us to probe, image, rationally engineer, and evolve protein structure and function. However, the incorporation of a new NCAA typically requires the selection of large libraries of PylRS with randomized mutations at active sites, and this process requires multiple rounds of selection for each new substrate. Therefore, a single aminoacyl-tRNA synthetase with broad substrate promiscuity is ideal to facilitate widespread applications of the genetic NCAA incorporation technique. Herein, machine learning models were developed to predict the substrate specificity of PylRS to accept novel NCAAs that could be incorporated into proteins by three PylRS mutants. The models were built from a training set of 285 unique enzyme–substrate pairs of three PylRS mutants including IFRS, BtaRS, and MFRS against 95 NCAAs. The best BaggingTree (BT) model was then used for virtually screening a NCAAs library containing 1474 phenylalanine, tyrosine, tryptophan, and alanine analogues, and 156 NCAAs were predicted to be accepted by at least one of the three PylRS mutants. Then, 27 NCAAs including 24 positive and 3 negative substrates were experimentally tested for their activities, and 20 of the 24 positive substrates showed weak or strong activity and were accepted by at least one PylRS mutant, among which 11 NCAAs were never reported to be incorporated into proteins before. Three negative substrates did not show any activity. Experimental results suggested that the BT model provides a three-class classification accuracy of 0.69 and a binary classification accuracy of 0.86. This study expanded the substrate scope of three PylRS variants and provided a framework for developing machine learning models to predict substrate specificity of other PylRS variants.

In recent years, a plethora of new synthetic biology tools for use in cyanobacteria have been published; however, their reported characterizations often cannot be reproduced, greatly limiting the comparability of results and hindering their applicability. In this interlaboratory study, the reproducibility of a standard microbiological experiment for the cyanobacterial model organism Synechocystis sp. PCC 6803 was assessed. Participants from eight different laboratories quantified the fluorescence intensity of mVENUS as a proxy for the transcription activity of the three promoters PJ23100, PrhaBAD, and PpetE over time. In addition, growth rates were measured to compare growth conditions between laboratories. By establishing strict and standardized laboratory protocols, reflecting frequently reported methods, we aimed to identify issues with state-of-the-art procedures and assess their effect on reproducibility. Significant differences in spectrophotometer measurements across laboratories from identical samples were found, suggesting that commonly used reporting practices of optical density values need to be supplemented by cell count or biomass measurements. Further, despite standardized light intensity in the incubators, significantly different growth rates between incubators used in this study were observed, highlighting the need for additional reporting requirements of growth conditions for phototrophic organisms beyond the light intensity and CO2 supply. Despite the use of a regulatory system orthogonal to Synechocystis sp. PCC 6803, PrhaBAD, and a high level of protocol standardization, ∼32% variation in promoter activity under induced conditions was found across laboratories, suggesting that the reproducibility of other data in the field of cyanobacteria might be affected similarly.

One horizon in synthetic biology seeks alternative forms of DNA that store, transcribe, and support the evolution of biological information. Here, hydrogen bond donor and acceptor groups are rearranged within a Watson–Crick geometry to get 12 nucleotides that form 6 independently replicating pairs. Such artificially expanded genetic information systems (AEGIS) support Darwinian evolution in vitro. To move AEGIS into living cells, metabolic pathways are next required to make AEGIS triphosphates economically from their nucleosides, eliminating the need to feed these expensive compounds in growth media. We report that “polyphosphate kinases” can be recruited for such pathways, working with natural diphosphate kinases and engineered nucleoside kinases. This pathway in vitro makes AEGIS triphosphates, including third-generation triphosphates having improved ability to survive in living bacterial cells. In α-32P-labeled forms, produced here for the first time, they were used to study DNA polymerases, finding cases where third-generation AEGIS triphosphates perform better with natural enzymes than second-generation AEGIS triphosphates.

Systematic, genome-scale genetic screens have been instrumental for elucidating genotype–phenotype relationships, but approaches for probing genetic interactions have been limited to at most ∼100 pre-selected gene combinations in mammalian cells. Here, we introduce a theory for high-throughput genetic interaction screens. The theory extends our recently developed Multiplexing using Spectral Imaging and Combinatorics (MuSIC) approach to propose ∼105 spectrally unique, genetically encoded MuSIC barcodes from 18 currently available fluorescent proteins. Simulation studies based on constraints imposed by spectral flow cytometry equipment suggest that genetic interaction screens at the human genome-scale may be possible if MuSIC barcodes can be paired to guide RNAs. While experimental testing of this theory awaits, it offers transformative potential for genetic perturbation technology and knowledge of genetic function. More broadly, the availability of a genome-scale spectral barcode library for non-destructive identification of single cells could find more widespread applications such as traditional genetic screening and high-dimensional lineage tracing.

As the impacts of engineering biology grow, it is important to introduce the field early and in an accessible way. However, teaching engineering biology poses challenges, such as limited representation of the field in widely used scientific textbooks or curricula, and the interdisciplinary nature of the subject. We have created an adaptable curriculum module that can be used by anyone to teach the basic principles and applications of engineering biology. The module consists of a versatile, concept-based slide deck designed by experts across engineering biology to cover key topic areas. Starting with the design, build, test, and learn cycle, the slide deck covers the framework, core tools, and applications of the field at an undergraduate level. The module is available for free on a public website and can be used in a stand-alone fashion or incorporated into existing curricular materials. Our aim is that this modular, accessible slide deck will improve the ease of teaching current engineering biology topics and increase public engagement with the field.

Context independent gene expression is required for genetic circuits to maintain consistent and predicable behavior. Previous efforts to develop context independent translation have leveraged the helicase activity of translating ribosomes via bicistronic design translational control elements (BCDs) located within an efficiently translated leader peptide. We have developed a series of bicistronic translational control elements with strengths that span several orders of magnitude, maintain consistent expression levels across diverse sequence contexts, and are agnostic to common ligation sequences used in modular cloning systems. We have used this series of BCDs to investigate several features of this design, including the spacing of the start and stop codons, the nucleotide identity upstream of the start codon, and factors affecting translation of the leader peptide. To demonstrate the flexibility of this architecture and their value as a generic modular expression control cassette for synthetic biology, we have developed a set of robust BCDs for use in several Rhodococcus species.

Glycosylation is an important method of modifying natural products and is usually catalyzed by uridine 5′-diphosphate (UDP)-glycosyltransferase. UDP-β-l-arabinose (UDP-Ara) confers specific functions to natural products such as pentacyclic triterpenoids. However, UDP-arabinosyltransferase with high regioselectivity toward pentacyclic triterpenoids has rarely been reported. In addition, UDP-Ara is mainly biosynthesized from UDP-α-d-glucose (UDP-Glc) through several reaction steps, resulting in the high cost of UDP-Ara. Herein, UGT99D1 was systematically characterized for specifically transferring one moiety of arabinose to the C-3 position of typical pentacyclic triterpenoids. Subsequently, 15 enzymes from plants, mammals, and microorganisms were characterized, and a four-enzyme cascade comprising sucrose synthase, UDP-Glc dehydrogenase, UDP-α-d-glucuronic acid decarboxylase, and UDP-Glc 4-epimerase was constructed to transform sucrose into UDP-Ara with UDP recycling. This system was demonstrated to efficiently produce the arabinosylated derivative (Ara-BA) of typical pentacyclic triterpenoid betulinic acid (BA). Finally, the in vitro cytotoxicity tests indicated that Ara-BA showed much higher anticancer activities than BA. The established arabinosylation platform shows the potential to enhance the pharmacological activity of natural products.

Saccharomyces cerevisiae has been extensively used as a convenient synthetic biology chassis to reconstitute fungal polyketide biosynthetic pathways. Despite progress in refactoring these pathways for expression and optimization of the yeast production host by metabolic engineering, product yields often remain unsatisfactory. Such problems are especially acute when synthetic biological production is used for bioprospecting via genome mining or when chimeric fungal polyketide synthases (PKSs) are employed to produce novel bioactive compounds. In this work, we demonstrate that empirically balancing the expression levels of the two collaborating PKS subunits that afford benzenediol lactone (BDL)-type fungal polyketides is a facile strategy to improve the product yields. This is accomplished by systematically and independently altering the copy numbers of the two plasmids that express these PKS subunits. We applied this plasmid copy number engineering strategy to two orphan PKSs from genome mining where the yields of the presumed BDL products in S. cerevisiae were far too low for product isolation. This optimization resulted in product yield improvements of up to 10-fold, allowing for the successful isolation and structure elucidation of new BDL analogues. Heterocombinations of these PKS subunits from genome mining with those from previously identified BDL pathways led to the combinatorial biosynthesis of several additional novel BDL-type polyketides.

Transcriptional factors-based biosensors are commonly used in metabolic engineering for inducible control of gene expression and related applications such as high-throughput screening and dynamic pathway regulations. Mining for novel transcriptional factors is essential for expanding the usability of these toolsets. Here, we report the identification, characterization, and engineering of a phenolic acid responsive regulator PadR from Bacillus amyloliquefaciens (BaPadR). This BaPadR-based biosensor system showed a unique ligand preference and exhibited a high output strength comparable to that of commonly used inducible expression systems. Through engineering the DNA binding region of BaPadR, we further enhanced the dynamic range of the biosensor system. The DNA sequences that are responsible for BaPadR recognition were located by promoter truncation and hybrid promoter building. To further explore the tunability of the sensor system, base substitutions were performed on the BaPadR binding region of the phenolic acid decarboxylase promoter (PpadC) and the hybrid promoter. This novel biosensor system can serve as a valuable tool in future synthetic biology applications.

In metazoans, living cells achieve capabilities beyond individual cell functionality by assembling into multicellular tissue structures. These higher-order structures represent dynamic, heterogeneous, and responsive systems that have evolved to regenerate and coordinate their actions over large distances. Recent advances in constructing micrometer-sized vesicles, or synthetic cells, now point to a future where construction of synthetic tissue can be pursued, a boon to pressing material needs in biomedical implants, drug delivery systems, adhesives, filters, and storage devices, among others. To fully realize the potential of synthetic tissue, inspiration has been and will continue to be drawn from new molecular findings on its natural counterpart. In this review, we describe advances in introducing tissue-scale features into synthetic cell assemblies. Beyond mere complexation, synthetic cells have been fashioned with a variety of natural and engineered molecular components that serve as initial steps toward morphological control and patterning, intercellular communication, replication, and responsiveness in synthetic tissue. Particular attention has been paid to the dynamics, spatial constraints, and mechanical strengths of interactions that drive the synthesis of this next-generation material, describing how multiple synthetic cells can act as one.

Xeno-nucleic acid (XNA) aptamers based on evolvable non-natural genetic polymers hold enormous potential as future diagnostic and therapeutic agents. However, time-consuming and costly procedures requiring the purification of individual XNA sequences produced by large-scale polymerase-mediated primer extension reactions pose a major bottleneck to the discovery of highly active XNA motifs for biomedical applications. Here, we describe a straightforward approach for rapidly surveying the binding properties of XNA aptamers identified by in vitro selection. Our strategy involves preparing XNA aptamer particles in which many copies of the same aptamer sequence are distributed throughout the gel matrix of a polyacrylamide-encapsulated magnetic particle. Aptamer particles are then screened by flow cytometry to assess target binding affinity and deduce structure–activity relationships. This generalizable and highly parallel assay dramatically accelerates the pace of secondary screening by allowing a single researcher to evaluate 48–96 sequences per day.

Expression of recombinant proteins in mammalian cell factories relies on synthetic assemblies of genetic parts to optimally control flux through the product biosynthetic pathway. In comparison to other genetic part-types, there is a relative paucity of characterized signal peptide components, particularly for mammalian cell contexts. In this study, we describe a toolkit of signal peptide elements, created using bioinformatics-led and synthetic design approaches, that can be utilized to enhance production of biopharmaceutical proteins in Chinese hamster ovary cell factories. We demonstrate, for the first time in a mammalian cell context, that machine learning can be used to predict how discrete signal peptide elements will perform when utilized to drive endoplasmic reticulum (ER) translocation of specific single chain protein products. For more complex molecular formats, such as multichain monoclonal antibodies, we describe how a combination of in silico and targeted design rule-based in vitro testing can be employed to rapidly identify product-specific signal peptide solutions from minimal screening spaces. The utility of this technology is validated by deriving vector designs that increase product titers ≥1.8×, compared to standard industry systems, for a range of products, including a difficult-to-express monoclonal antibody. The availability of a vastly expanded toolbox of characterized signal peptide parts, combined with streamlined in silico/in vitro testing processes, will permit efficient expression vector re-design to maximize titers of both simple and complex protein products.

Marine red algal biomass is a promising feedstock for sustainable production of value-added chemicals. However, the major constituents of red algal biomass, such as agar and carrageenan, are not easily assimilated by most industrial metabolic chassis developed to date. Synthetic biology offers a solution by utilizing nonmodel organisms as metabolic chassis for consolidated biological processes. In this study, the marine heterotrophic bacterium Pseudoalteromonas atlantica T6c was harnessed as a metabolic chassis to produce value-added chemicals from the affordable red algal galactans or agaropectin, a byproduct of industrial agarose production. To construct a heterologous gene expression device in P. atlantica T6c, promoters related to agar metabolism were screened from the differentially expressed genes using RNA-Seq analysis. The expression device was built and tested with selected promoters fused to a reporter gene and tuned by incorporation of a cognate repressor predicted from the agar-specific polysaccharide utilization locus. The feasibility of the marine bacterial metabolic chassis was examined by introducing the biosynthetic gene clusters of β-carotene and violacein. Our results demonstrate that the metabolic chassis platform enables direct conversion of low-cost red algal galactans or industrial waste agaropectin into valuable bioactive pigments without any pretreatment of biomass. The developed marine bacterial chassis could potentially be used in a biorefinery framework to produce value-added chemicals from marine algal galactans.

Pseudomonas aeruginosa (P. aeruginosa) infection has become an intractable problem worldwide due to the decreasing efficacy of the mainstay therapy, antibiotic treatment. Hence, exploring new drugs and therapies to address this issue is crucial. Here, we construct a chimeric pyocin (ChPy) to specifically kill P. aeruginosa and engineer a near-infrared (NIR) light-responsive strain to produce and deliver this drug. Our engineered bacterial strain can continuously produce ChPy in the absence of light and release it to kill P. aeruginosa via remotely and precisely controlled bacterial lysis induced by NIR light. We demonstrate that our engineered bacterial strain is effective in P. aeruginosa-infected wound therapy in the mouse model, as it eradicated PAO1 in mouse wounds and shortened the wound healing time. Our work presents a potentially spatiotemporal and noninvasively controlled therapeutic strategy of engineered bacteria for the targeted treatment of P. aeruginosa infections.

DNA-encoded peptide/protein libraries are the starting point for protein evolutionary modification and functional peptide/antibody selection. Different display technologies, protein directed evolution, and deep mutational scanning (DMS) experiments employ DNA-encoded libraries to provide sequence variations for downstream affinity- or function-based selections. Mammalian cells promise the inherent post-translational modification and near-to-natural conformation of exogenously expressed mammalian proteins and thus are the best platform for studying transmembrane proteins or human disease-related proteins. However, due to the current technical bottlenecks of constructing mammalian cell-based large size DNA-encoded libraries, the advantages of mammalian cells as screening platforms have not been fully exploited. In this review, we summarize the current efforts in constructing DNA-encoded libraries in mammalian cells and the existing applications of these libraries in different fields.