ACS Synthetic Biology最新文献

Metabolite-responsive, protein-based biosensors are powerful tools for monitoring cellular metabolite dynamics in vivo and accelerating strain engineering workflows in microorganisms. In this study, we introduced a previously developed protein-based biosensor, computationally designed to detect farnesyl diphosphate (FPP), in the marine diatom Phaeodactylum tricornutum. We expressed two versions of the biosensor constitutively, under a strong promoter-terminator pair using extrachromosomal episomes, and we parametrized the capacity of both designs in detecting intracellular metabolite levels. Initial assays revealed that the two versions of the biosensor we investigated, S3-2D and S3-3A, had specificity not only for FPP but also for other exogenously supplied prenyl phosphates such as geranyl diphosphate (GPP) and geranylgeranyl diphosphate (GGPP) in a dose-dependent manner, showcasing broader specificity for multiple prenyl phosphates. We further demonstrated the capacity of S3-3A to track perturbations in the endogenous prenyl phosphate pools by testing it in the presence of pharmacological inhibition of the mevalonate pathway. Moreover, S3-3A generated dot-like, fluorescent signal "hotspots" in the cytosol of diatoms, suggesting a complex subcellular organization of the isoprenoid biosynthesis in P. tricornutum. These findings lay the groundwork for developing metabolite-responsive biosensors as useful tools for monitoring and investigating prenyl phosphate dynamics in diatoms, providing a foundation for advanced metabolic engineering of microalgae.

R6K plasmids are commonly used for a wide range of genome engineering applications due to their ability to support transient delivery of genetic cargos in many hosts. The maintenance of R6K plasmids requires specific strains. Unfortunately, many of these have obscure backgrounds, limited availability and were not built for efficient cloning. To address this issue, we present the construction and characterization of a series of Pir E. coli strains called SHARK that are built from the DH10B derivative, Marionette-Clo. All SHARK strains have a genome encoded pir gene for stable R6K plasmid maintenance and a λCI gene for tight unconditional repression of specific genes on plasmids. We show that SHARK strains are >100-fold more efficient than a commercial Pir strain when transformed with large and complex cloning reactions. SHARK is intended to help facilitate the cloning of R6K plasmids for challenging genome engineering projects, with all strains and genetic tools for their assembly being made publicly available.

Advances in synthetic biology continue to potentiate bacterial cancer therapy. Here, we constructed biosensor-driven encapsulation systems for autonomous control of capsular polysaccharides of Escherichia coli Nissle 1917 to improve pharmacokinetic profiles. The engineered bacteria were programmed to express capsular polysaccharides for immune evasion upon intravenous administration to reach tumors and then turn off gene expression upon colonizing the tumors based on quorum-sensing or acid-sensing to prevent dissemination of bacteria into the systemic circulation. Because a classical pharmacokinetic model could not capture the dynamic nature of living therapeutics, a two-state pharmacokinetic model was developed to simulate the autonomous control of capsular polysaccharides in different biological compartments and their impact on biodistribution. Using this model, we identified parameters in gene circuit dynamics and immune clearance that influence tumor colonization and systemic bacterial persistence. In a "humanized" pharmacokinetic model with an increased rate of complement-mediated lysis of bacteria, biosensor-driven systems achieved tumor seeding densities comparable to wild-type bacteria while reducing bacterial loads in blood and liver by several orders of magnitude, highlighting their potential for safe systemic delivery. The biosensor-driven systems represent a more effective strategy to control living drugs than inducible systems, and the two-state pharmacokinetic model is a first step to capture the autonomous nature of this new class of therapeutics for clinical translation.

Biosensors have been widely applied for high-throughput strain screening and dynamic regulation of metabolic networks. However, existing tryptophan sensors based on transcription factors or riboswitches often suffer from a narrow dynamic range and limited response threshold. In this study, we developed a series of tryptophan-responsive biosensors in Escherichia coli using the tryptophan-activated RNA-binding attenuation protein (TRAP) as the sensing module. First, we validated TRAP functionality and engineered a functional biosensor by fine-tuning its expression. Subsequently, screening of TRAP variants and optimization of TRAP-leader sequence interactions yielded two biosensors that exhibited distinct dynamic ranges (up to 22.1-fold) and response thresholds of 0-2.2 g/L, respectively. Using these biosensors, we screened two beneficial variants of key rate-limiting enzymes in the tryptophan biosynthetic pathway and further investigated their catalytic mechanisms through molecular dynamics simulations. Collectively, this study provides tools for engineering high tryptophan-producing strains and new strategies for biosensor design.

Hyperlysinemia is a life-threatening metabolic disorder that requires the continuous clearance of lysine. Engineered probiotics capable of degrading lysine in the gut represent a promising therapeutic strategy. However, the introduction of heterologous metabolic pathways can impose a substantial fitness burden on the bacterial host, potentially compromising the therapeutic efficacy. Current screening methods fail to adequately assess this pathway-induced stress. Therefore, optimizing methods to evaluate bacterial fitness after pathway modification is essential for developing effective bacterial therapies. Here, we present a label-free phenotypic screening approach using Fourier transform infrared (FTIR) spectroscopy to evaluate the physiological burden imposed by two distinct lysine catabolism pathways engineered Escherichia coli Nissle 1917 (EcN): the plant-derived bifunctional enzyme LKR-SDR and the yeast-derived two-enzyme cascade Lys2-Lys5. Employing FTIR under lysine stress mimicking pathological concentrations, decoded pathway-specific stress signatures, and molecular resilience. Probiotics expressing LKR-SDR exhibited severe multisystem damage, including proteotoxicity, lipid peroxidation, and significant nucleic acid stress. In contrast, the Lys2-Lys5 strain demonstrated superior resilience, maintained structural integrity, and exhibited adaptive metabolic changes, primarily through lipid membrane remodeling. This study establishes FTIR spectroscopy as a rapid screening platform that identifies the Lys2-Lys5 pathway as optimal for probiotic therapies. By directly linking spectroscopic signatures to cellular fitness, FTIR spectroscopy accelerates the rational development of durable microbial therapeutics for inborn metabolic disorders.

Lipoic acid (LA) is a sulfur-containing cofactor with significant antioxidant and metabolism-regulating functions, which is widely used in the pharmaceutical and nutraceutical industries. However, current microbial production of LA relies on exogenous octanoic acid and synthesizes the product in a protein-bound form, requiring a subsequent dissociation step to obtain free LA. In this study, we constructed an Escherichia coli strain capable of de novo synthesizing free LA by deleting the compensatory pathway gene lplA and introducing eflpA, a lipoamidase that hydrolyzes protein-bound LA. A high-efficiency LA synthase (sllipA) was subsequently screened from Serratia liquefaciens and optimized at the gene copy-number level, resulting in a 44% increase in LA production. Furthermore, by enhancing the carbon flux from acetyl-CoA to the precursor octanoic acid and improving the intracellular supply of the key cofactors S-adenosylmethionine (SAM) and [4Fe-4S] iron-sulfur clusters, the LA titer was further increased by 184%. Finally, under controlled microaerobic production conditions, the optimized strain achieved an LA titer of 138.32 mg/L, representing the highest level of microbial LA production reported to date.

The pathogenic bacterium Vibrio parahaemolyticus represents a substantial economic and public health concern; however, elucidating its virulence mechanisms has been significantly impeded by its inherent resistant to genetic manipulation, primarily attributed to sophisticated immune defense systems including restriction-modification (R-M) modules, CRISPR-Cas systems, standalone DNases, and DdmDE systems. Paradoxically, while genetic modification is essential for overcoming these barriers, the very barriers themselves obstruct DNA introduction. Our investigation focused on the V. parahaemolyticus X1 strain, where initial plasmid transformation attempts proved unsuccessful. However, low-efficiency conjugation allowed knockout of defense genes, thereby silencing the host's defense mechanisms. Our findings revealed a standalone DNase, Vpn, as the predominant obstacle to foreign DNA entry in the X1 strain, while a DdmDE system executes elimination of invaded plasmids. Leveraging these insights, we created the V. parahaemolyticus X2 strain via sequential depletion of the Vpn nuclease and the DdmDE system. Capitalizing on the bacterium's exceptional growth rate, characterized by a generation time of approximately 10.5 min, we established a highly efficient molecular cloning platform capable of creating a new plasmid construct within a single day. This work not only presents a strategic framework for genetic manipulation of previously recalcitrant bacterial species but also underscores the potential of fast-growing marine bacteria as promising candidates for next-generation biotechnological applications.

Heterochiral DNA strand displacement provides a powerful mechanism for converting nucleic acid input signals of one chirality to nucleic acid output signals of the opposite chirality. This is achieved by combining naturally occurring d-DNA with synthetic, chiral mirror-image l-DNA. Such systems have potential for practical applications, including autonomous biomedical diagnostics and therapeutic actuation, which could take advantage of the degradation resistance of l-nucleic acids to carry out diagnostic information processing using a robust l-DNA molecular circuit. One implementation of this approach uses a leakless molecular translator architecture to minimize off-target release of an l-nucleic acid output in the absence of a d-nucleic acid input. In nonpristine environments, however, degradation of the d-DNA components of a heterochiral system can lead to a slow leak that could cause off-target side effects in a biomedical application. Here, we report an investigation of degradation-induced leak in heterochiral DNA strand displacement systems that combines experimental measurements with the computational fitting of an abstract kinetic model. We explore both sequential and parallel leak hypotheses for the leak mechanism and conclude that initial degradation reactions provide otherwise leakless components with alternative means of activating the programmed reaction cascade in the absence of input. We validate this model by demonstrating that it predicts key behaviors of heterochiral translators when the d-DNA domains are hardened against degradation by using phosphorothioate backbone modifications. This work thus lays the groundwork for future exploration of degradation-induced leak that will enable the development and deployment of robust heterochiral DNA devices for biomedical applications.

Synthetic biology laboratories generate diverse forms of data and metadata throughout a project’s life cycle, such as sequences, models, protocols, images, and time-series measurements. Unfortunately, these assets are scattered across spreadsheets, proprietary exports, custom scripts, etc. found in varied locations such as shared drives. Inconsistent metadata and data formats hinder provenance, reuse, security, compliance, automation, and scale-up. The central gap is a coherent way to link data, metadata, and code so they remain findable, accessible, interoperable, and reusable (FAIR). This perspective considers current practices through semistructured interviews with synthetic biology researchers in laboratories across the United States, and the findings were used to provide guidance to create a framework for an integrated data management workflow. This framework maps common data types to community standards that allow machine-accessible metadata, version control, and standards-compliant repositories. This perspective also offers a catalog of potential software solutions and stepwise adoption guidelines that turn the proposed framework into a day-to-day practice, democratizing the generation of standardized data. The result is that users gain a template that raises data to FAIR status, strengthens traceability for regulatory or defense contexts, and provides a stronger foundation for training machine learning models.