Synthetic biology has garnered significant global interest owing to its diverse applications in biobased production, biosensing, living therapeutics, and drug delivery. This heightened interest has increased the demand for novel protein synthesis methods and genome-scale assemblies. However, gene assembly from oligomers presents several challenges, including the risk of incorrect assembly between oligomers, self-annealing, and the potential for insertions or deletions resulting from misannealed oligomers. Dsembler (DNA Assembly Designer) is a web-based software application designed to assemble long DNA sequences. It provides a set of oligomers with optimal melting temperatures and GC overlap, which facilitates a commercially available oligomer pool service. By enhancing the accuracy of oligomer design, Dsembler has addressed critical challenges in synthetic biology and supported advancements in genetic engineering and molecular biology.

Cellular transport systems are key determinants of intracellular molecule concentrations and can be utilized to modulate the responsiveness of transcription factor (TF)-based biosensors. Efflux pumps facilitate the export of small molecules; therefore, their activity can directly compromise the accuracy of biosensor-based assays. We engineered a cellular export machinery to enhance the responsiveness and reduce crosstalk of a DmpR-based biosensor, which employs the phenol-responsive TF DmpR to detect intracellular phenolic ligands but is affected by ligand diffusion between cells. To overcome this limitation, efflux pump genes were knocked out to minimize ligand diffusion and improve signal fidelity. Among the efflux pumps tested, deletion of mdtA was found to promote effective intracellular accumulation of phenolic compounds. This strategy not only increased biosensor sensitivity by up to 19-fold but also reduced false positives during enzyme screening by suppressing intercellular diffusion of enzymatic products. In the mock library experiment, the proportion of false positives relative to the total positive cells was 74

Engineering enzymes to degrade solid substrates, such as crystalline cellulose from paper sludge or microplastics in sewage sludge, presents challenges for high-throughput screening (HTS), as solid substrates are not readily accessible in cell-based biosensor systems. To address this challenge, we developed a cell-free cellobiose-detectable biosensor (CB-biosensor) for rapid characterization of cellobiohydrolase (CBH) activity, enabling direct detection of hydrolysis products without cellular constraints. The CB-biosensor demonstrates higher sensitivity than conventional assays and distinguishes between CBH subtypes (CBHI and CBHII) based on their modes of action. Integration with the Echo 525 liquid handler enables precise and reproducible sample processing, with fluorescence signals from automated preparations comparable to manual experiments. Furthermore, assay volumes can be reduced to just a few microlitres-impractical with manual methods. This cell-free CB-biosensor with Echo 525 minimizes reagent consumption, accelerates testing, and facilitates reliable large-scale screening. These findings highlight its potential to overcome current HTS limitations, advancing enzyme screening and accelerating the Design-Build-Test-Learn cycle for sustainable biomanufacturing.

The interdisciplinary nature of synthetic biology merges engineering principles with biology and provides innovative solutions for issues in the biomanufacturing industry. To develop industrially applicable biocatalysts and/or microbial cell factories, a design-build-test-learn cycle-based iterative process is necessary, which is often time-consuming and labor-intensive. The integration of microfluidic technologies into synthetic biology can accelerate these processes, particularly for achieving high-throughput phenotyping and screening. In this review, we examine the potential of microfluidic technologies to revolutionize synthetic biology. Although commercial microfluidics demonstrate superior throughput for single-cell assays, their application can be limited, for example, in cases where products are retained inside the cells. Droplet microfluidics, on the other hand, is a rather flexible platform and shows high diversity in single-cell, cell-to-cell interaction-based, and cell-free reaction-based analyses. By examining previous studies, we have summarized the potential of microfluidic technologies to foster sustainable biomanufacturing and advanced biological engineering.

Although gas chromatography is the gold standard for detecting the persistent organic pollutant dichlorodiphenyltrichloroethane (DDT), a quick and easy alternative is needed to detect this highly toxic pesticide in food and household products. Therefore, we developed a monoclonal antibody (mAb)-based assay for the sensitive detection of DDT. The mAb used in our assay demonstrated favourable binding affinity in the nanomolar range against 2,2-bis(4-chlorophenyl)acetic acid (DDA), a DDT analogue, which is considered higher than commercially developed antibodies. By optimizing the assay conditions, we were able to detect DDT and its closely related compounds, including dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyldichloroethane (DDD), and isomeric impurities. Our dot blotting assay demonstrated a detection limit of 0.9 ng/mL for DDT. Using computational modelling, we predicted the structure of the mAb and its interaction with DDT. Overall, this study provides insights for engineering mAb with improved sensitivity, facilitates point-of-care detection of toxic chemicals, including DDT, and offers a vital method for food safety monitoring and environmental protection.

The genus Bacteroides, a predominant group in the human gut microbiome, presents significant potential for microbiome engineering and the development of live biotherapeutics aimed at treating gut diseases. Despite its promising capabilities, tools for effectively engineering Bacteroides species have been limited. In our study, we have made a breakthrough by identifying novel signal peptides in Bacteroides thetaiotaomicron and Akkermansia muciniphila. These peptides facilitate efficient protein transport across cellular membranes in Bacteroides, a critical step for therapeutic applications. Additionally, we have developed an advanced episomal plasmid system. This system demonstrates superior protein secretion capabilities compared to traditional chromosomal integration plasmids, making it a vital tool for enhancing the delivery of therapeutic proteins in Bacteroides species. Initially, the stability of this episomal plasmid posed a challenge; however, we have overcome this by incorporating an essential gene-based selection system. This novel strategy not only ensures plasmid stability but also aligns with the growing need for antibiotic-free selection methods in clinical settings. Our work, therefore, not only provides a more robust secretion system for Bacteroides but also sets a new standard for the development of live biotherapeutics.

Being able to perform modular design of artificial transcription factors is useful in bioengineering and synthetic biology, particularly in the development of biosensors and therapeutics. This study aimed to develop a two-fragment transcription factor system by splitting a lactose repressor (LacI). To fragment LacI, we screened potential split positions from transposon-based insertional libraries that we generated to identify those positions that did not disturb the intrinsic activity of LacI. The interaction of protein tags fused with fragments induces the reassembly of LacI and recovers the isopropyl-β-D-thiogalactoside-dependent regulatory function. The split LacI-based biosensor was implemented on an in vitro platform using a cell-free protein expression system to facilitate accurate analytical studies with high reproducibility. This versatile platform holds great potential to realize the rapid and simple detection of protein–protein interactions in cell-free systems; thus, it can be further extended to disease diagnosis, particularly at the point-of-care.

Isoprene has numerous industrial applications, including rubber polymer and potential biofuel. Microbial methane-based isoprene production could be a cost-effective and environmentally benign process, owing to a reduced carbon footprint and economical utilization of methane. In this study, Methylococcus capsulatus Bath was engineered to produce isoprene from methane by introducing the exogenous mevalonate (MVA) pathway. Overexpression of MVA pathway enzymes and isoprene synthase from Populus trichocarpa under the control of a phenol-inducible promoter substantially improved isoprene production. M. capsulatus Bath was further engineered using a CRISPR-base editor to disrupt the expression of soluble methane monooxygenase (sMMO), which oxidizes isoprene to cause toxicity. Additionally, optimization of the metabolic flux in the MVA pathway and culture conditions increased isoprene production to 228.1 mg/L, the highest known titer for methanotroph-based isoprene production. The developed methanotroph could facilitate the efficient conversion of methane to isoprene, resulting in the sustainable production of value-added chemicals.

Levulinic acid (LA) is a valuable chemical used in fuel additives, fragrances, and polymers. In this study, we proposed possible biosynthetic pathways for LA production from lignin and poly(ethylene terephthalate). We also created a genetically encoded biosensor responsive to LA, which can be used for screening and evolving the LA biosynthesis pathway genes, by employing an LvaR transcriptional regulator of Pseudomonas putida KT2440 to express a fluorescent reporter gene. The LvaR regulator senses LA as a cognate ligand. The LA biosensor was first examined in an Escherichia coli strain and was found to be non-functional. When the host of the LA biosensor was switched from E. coli to P. putida KT2440, the LA biosensor showed a linear correlation between fluorescence intensity and LA concentration in the range of 0.156-10 mM LA. In addition, we determined that 0.156 mM LA was the limit of LA detection in P. putida KT2440 harboring an LA-responsive biosensor. The maximal fluorescence increase was 12.3-fold in the presence of 10 mM LA compared to that in the absence of LA. The individual cell responses to LA concentrations reflected the population-averaged responses, which enabled high-throughput screening of enzymes and metabolic pathways involved in LA biosynthesis and sustainable production of LA in engineered microbes.

The engineered Methylococcus capsulatus Bath presents a promising approach for converting methane, a potent greenhouse gas, into valuable chemicals. High cell-density culture (HCDC) is necessary for high-titer growth-associated bioproducts, but it often requires time-consuming and labor-intensive optimization processes. In this study, we aimed to achieve efficient HCDC of M. capsulatus Bath by measuring the residual nutrient levels during bioreactor operations and analyzing the specific uptake of each medium component. By controlling the concentrations of nutrients, particularly calcium and phosphorus via intermittent feeding, we achieved a high cell density of 28.2 g DCW/L and a significantly elevated production of mevalonate at a concentration of 1.8 g/L from methane. Our findings demonstrate that the methanotroph HCDC approach presented herein offers a promising strategy for promoting sustainable development, with an exceptional g-scale production titer for value-added synthetic biochemicals.

Methanotrophs are promising and sustainable cell factory platforms owing to their ability to convert the most potent greenhouse gas, methane to valuable bioproducts. Genetic engineering toolkits for methanotrophs are extremely limited. Here, we present a phenol-inducible promoter for the high-level expression of exogenous genes in methanotrophs. The phenol-inducible gene expression system showed high dose-dependency and ho-mogeneity in methanotrophs. Using the phenol-inducible CRISPR-base editor (BE), we developed a highly effi-cient methanotroph genome editing system. The CRISPR-BE system efficiently introduced an early stop codon into the target gene, enabling one-step markerless genome editing in Methylococcus capsulatus Bath. We adopted this simple and efficient genome editing tool to produce mevalonate in the engineered M. capsulatus Bath. The native phosphoketolase pathway was reinforced in M. capsulatus Bath to increase the carbon flux via acetyl-CoA towards mevalonate. This engineered M. capsulatus Bath produced the maximum concentration of 2,090 mg/L mevalonate from methane, which is the highest amount of synthetic biochemicals produced from methane in methanotrophs. Here we present not only an efficient addition to the genetic engineering toolkit for methano-trophs but also a useful platform for the development of a methanotroph cell factory.

Enantiomerically pure d-amino acids are important intermediates as chiral building blocks for peptidomimetics and semisynthetic antibiotics. Here, a transcriptional factor-based screening strategy was used for the rapid screening of d-stereospecific amino acid amidase via an enzyme-specific amidophenol substrate. We used a d-threonine amidophenyl derivative to produce 2-aminophenol that serves as a putative enzyme indicator in the presence of d-threonine amidases. Comparative analyses of known bacterial species indicated that several Bacillus strains produce amidase and form putative indicators in culture media. The estimated amidase was cloned and subjected to rapid directed evolution through biosensor cells. Consequently, we characterized the F119A mutation that significantly improved the catalytic activity toward d-alanine, d-threonine, and d-glutamate. Its beneficial effects were confirmed by higher conversions and recurrent applications of the mutant enzyme, compared to the wild-type. This study showed that rapid directed evolution with biosensors coupled to designed substrates is useful to develop biocatalytic processes.

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

Antibiotics have been widely used for plasmid-mediated cell engineering. However, continued use of antibiotics increases the metabolic burden, horizontal gene transfer risks, and biomanufacturing costs. There are limited approaches to maintaining multiple plasmids without antibiotics. Herein, we developed an inverter cascade using CRISPRi by building a plasmid containing a single guide RNA (sgRNA) landing pad (pSLiP); this inhibited host cell growth by repressing an essential cellular gene. Anti-sgRNAs on separate plasmids restored cell growth by blocking the expression of growth-inhibitory sgRNAs in pSLiP. We maintained three plasmids in Escherichia coli with a single antibiotic selective marker. To completely avoid antibiotic use and maintain the CRISPRi-based logic inverter cascade, we created a novel d-glutamate auxotrophic E. coli. This enabled the stable maintenance of the plasmid without antibiotics, enhanced the production of the terpenoid, (-)-α-bisabolol, and generation of an antibiotic-resistance gene-free plasmid. CRISPRi is therefore widely applicable in genetic circuits and may allow for antibiotic-free biomanufacturing.

Genetic circuits have been developed for quantitative measurement of enzyme activity, metabolic engineering of strain development, and dynamic regulation of microbial cells. A genetic circuit consists of several bio-elements, including enzymes and regulatory cassettes, that can generate the desired output signal, which is then used as a precise criterion for enzyme screening and engineering. Antagonists and inhibitors are small molecules with inhibitory effects on regulators and enzymes, respectively. In this study, an antagonist and an inhibitor were applied to a genetic circuit for a dynamic detection range. We developed a genetic circuit relying on regulators and enzymes, allowing for straightforward control of its output signal without additional genetic modification. We used para -nitrophenol and alanine as an antagonist of DmpR and inhibitor of tyrosine phenol-lyase, respectively. We show that the antagonist resets the detection range of the genetic circuit similarly to a resistor in an electrical logic circuit. These biological resistors in genetic circuits can be used as a rapid and precise controller of variable outputs with minimal circuit configuration.

Methanotrophs with soluble methane monooxygenase (sMMO) show high potential for various ecological and biotechnological applications. Here, we developed a high throughput method to identify sMMO-producing microbes by integrating droplet microfluidics and a genetic circuit-based biosensor system. sMMO-producers and sensor cells were encapsulated in monodispersed droplets with benzene as the substrate and incubated for 5 h. The sensor cells were analyzed as the reporter for phenol-sensitive transcription activation of fluorescence. Various combinations of methanotrophs and biosensor cells were investigated to optimize the performance of our droplet-integrated transcriptional factor biosensor system. As a result, the conditions to ensure sMMO activity to convert the starting material, benzene, into phenol, were determined. The biosensor signals were sensitive and quantitative under optimal conditions, showing that phenol is metabolically stable within both cell species and accumulates in picoliter-sized droplets, and the biosensor cells are healthy enough to respond quantitatively to the phenol produced. These results show that our system would be useful for rapid evaluation of phenotypes of methanotrophs showing sMMO activity, while minimizing the necessity of time-consuming cultivation and enzyme preparation, which are required for conventional analysis of sMMO activity.

Bacteria initiate complicated signaling cascades from the detection of intracellular metabolites or exogenous substances by hundreds of transcription factors, which have been widely investigated as genetically-encoded biosensors for molecular recognition. However, the limited number of transcription factors and their broad substrate specificity result in ambiguity in small molecule identification. This study presents a new small molecule fingerprinting technique using evolutionary biosensor arrays with a machine learning technique that can capture highly specific substrate signals. Employing multiple mutant transcription factors derived from a single transcription factor has effectively circumvented the limited availability of transcription factors induced by a small molecule of our interest. This method achieved up to 95.3% true positive rate for identifying small molecules, and the high-resolution protein engineering technique improved the limit of detection 75-fold. The signal trade-offs with background noises caused by the complex cellular biochemistry of mutant transcription factors enable the biosensor arrays to be more informative in terms of statistical variance. The machine learning technology, coupled with the single transcription factor-driven evolutionary biosensor array, will open new avenues for molecular fingerprinting technologies.

Bioconversion of C1 chemicals such as methane and methanol into higher carbon-chain chemicals has been widely studied. Methanol oxidation catalyzed by methanol dehydrogenase (Mdh) is one of the key steps in methanol utilization in bacterial methylotrophy. In bacteria, few NAD+-dependent Mdhs have been reported that convert methanol to formaldehyde. In this study, an uncharacterized Mdh gene from Lysinibacillus xylanilyticus (Lxmdh) was cloned and expressed in Escherichia coli. The maximum alcohol oxidation activity of the recombinant enzyme was observed at pH 9.5 and 55°C in the presence of 10 mM Mg2+. To improve oxidation activity, rational approach-based, site-directed mutagenesis of 16 residues in the putative active site and NAD+-binding region was performed. The mutations S101V, T141S, and A164F improved the enzyme’s specific activity toward methanol compared to that of the wild-type enzyme. These mutants show a slightly higher turnover rate than that of wild-type, although their KM values were increased compared to that of wild-type. Consequently, according the kinetic results, S101, T141, and A164 positions may related to the catalytic activity in the active site for methanol dehydrogenation. It should be further studied other mutant variants with high activity for methanol. In conclusion, we characterized a new Lxmdh and its variants that may be potentially useful for the development of synthetic methylotrophy in the future.

Genetic circuit-based biosensors have emerged as an effective analytical tool in synthetic biology; these biosensors can be applied to high-throughput screening of new biocatalysts and metabolic pathways. Sigma 54 (σ 54 )-dependent transcription factor (TF) can be a valuable component of these biosensors owing to its intrinsic silent property compared to most of the housekeeping sigma 70 (σ 70 ) TFs. Here, we show that these unique characteristics of σ 54 -dependent TFs can be used to control the host cell state to be more appropriate for high-throughput screening. The acclimation of cell state was achieved by using guanosine (penta)tetraphosphate ((p)ppGpp)-related genes ( relA , spoT ) and nutrient conditions, to link the σ 54 TF-based reporter expression with the target enzyme activity. By controlling stringent programmed responses and optimizing assay conditions, catalytically improved tyrosine phenol lyase (TPL) enzymes were successfully obtained using a σ 54 -dependent DmpR as the TF component, demonstrating the practical feasibility of this biosensor. This combinatorial strategy of biosensors using σ factor-dependent TFs will allow for more effective high-throughput enzyme engineering with broad applicability.