ACS Synthetic Biology最新文献

Marmesin, a plant dihydrofuranocoumarin, is an important intermediate in the synthesis of linear furanocoumarins and exhibits a variety of pharmacological activities. However, due to the lack of efficient prenyltransferases, the incompatibility of redox partners for P450 enzymes, and the insufficient supply of precursor (DMAPP), the microbial synthesis of marmesin remained at an extremely low level. Here, we report the efficient biosynthesis of marmesin in Escherichia coli by screening the robust 6-prenyltransferase PpPT1 and marmesin synthase PpDCΔ_2-29 from Peucedanum praeruptorum. Next, the activities of PpPT1 and PpDCΔ_2-29 were enhanced using fusion protein tags and redox partner engineering, respectively. In addition, the synthesis of marmesin was further improved by strengthening the methylerythritol phosphate (MEP) pathway to increase the availability of DMAPP and by optimizing the modular pathway in the engineered strain. Finally, the titer of marmesin reached 203.69 mg L^-1 in the fed-batch fermentation with a molar conversion rate of umbelliferone of 81.4%, which is the highest titer for marmesin production using engineered microorganisms. The applied strategy and marmesin-producing strain constructed in this study lay the foundation for the green production of valuable complex furanocoumarins.

We developed two Pseudomonas aeruginosa biosensors to detect trans-translation inhibitors in this medically relevant pathogen. These biosensors leverage the red fluorescence produced by the accumulation of protoporphyrin IX, the substrate of ferrochelatase. The first biosensor monitors tmRNA-SmpB-mediated tagging and degradation of ferrochelatase, while the second serves as a control by tracking ClpP1-mediated proteolysis and porphyrin biosynthesis. Both biosensors were tested in wild-type and mutant backgrounds, and red fluorescence was measured relative to absorbance at 600 nm in microtiter plates. The results confirmed a link between fluorescence and trans-translation or proteolysis activity. These biosensors offer a promising tool for high-throughput screening of trans-translation inhibitors in P. aeruginosa.

Chemo-enzymatic pathway design aims to combine the strengths of enzymatic with chemical synthesis to traverse biomolecular design space more efficiently. While chemical reactions often struggle with regioselectivity and stereoselectivity, enzymatic conversions often encounter limitations of low enzyme activity or availability. Optimally integrating both approaches provides an opportunity to identify efficient pathways beyond the capabilities of either modality. Recently, studies have shown the advantage of leveraging enzymatic steps into industrial-scale chemical processes, such as for the blood sugar regulator Sitagliptin (Merck) and the HIV protease inhibitor Darunavir (Prozomix). Designing optimal chemo-enzymatic pathways is a complex task. It requires navigating a high-dimensional search space of potential reactions that combine individual chemical and biochemical steps while at the same time minimizing transitions between chemical catalysis and bioreactions. Here, we introduce an algorithmic approach, minChemBio, that relies on solving a mixed-integer linear programming (MILP) problem by optimally searching through known chemical and enzymatic steps extracted from the United States Patent Office (USPTO) and MetaNetX databases, respectively. minChemBio allows for the minimization of transitions between chemical and biological reactions in the pathway, thus reducing the need for costly separation and purification steps required. minChemBio was benchmarked on three case studies involving the synthesis of 2-5-furandicarboxylic acid, terephthalate, and 3-hydroxybutyrate. Identified designs included both established literature pathways as well as unexplored ones which were compared against pathways identified by existing retrosynthetic tools. minChemBio fills a current gap in the space of pathway retrosynthesis tools by controlling and minimizing the transitions between chemical catalysis and biocatalytic steps. It is accessible to users through open-source code (https://github.com/maranasgroup/chemo-enz).

Plants produce a large array of natural products of biotechnological interest. In many cases, these compounds are naturally produced at low titers and involve complex biosynthetic pathways, which often include cytochrome P450 enzymes. P450s are known to be difficult to express in traditional heterotrophic chassis. However, cyanobacteria have shown promise as a sustainable alternative for the heterologous expression of P450s and light-driven product biosynthesis. In this study, we explore strategies for improving plant P450 stability and membrane insertion in cyanobacteria. The widely used model cyanobacterium Synechocystis sp. PCC 6803 was chosen as the host, and the well-studied P450 CYP79A1 from the dhurrin pathway of Sorghum bicolor was chosen as the model enzyme. Combinations of the P450 fused with individual elements (e.g., signal peptide, transmembrane domain) or the full length cyanobacterial, thylakoid-localized, protein PetC1 were designed. All generated CYP79A1 variants led to oxime production. Our data show that strains producing CYP79A1 variants with elements of PetC1 improved thylakoid targeting. In addition, chlorophyll-normalized oxime levels increased, on average, up to 18 times compared to the unmodified CYP79A1. These findings offer promising strategies to improve heterologous P450 expression in cyanobacteria and can ultimately contribute to advancing light-driven biocatalysis in cyanobacterial chassis.

Dynamic control of biosynthetic pathways improves the bioproduction efficiency. One common approach is to use genetic sensors that control pathway expression in response to a nutrient molecule in the target feedstock. However, programming the cellular response requires the engineering of numerous genetic parts, which poses a significant barrier to explore the use of different nutrients as cellular signals. Here we created a dynamic control platform based on a set of modular transcriptional regulators; these regulators control the same promoter for driving gene expression, but each of them responds to a unique signal. We demonstrated that by replacing only the regulator, a different nutrient molecule can then be used for induction of the same genetic circuit. To show host versatility, we implemented this platform in both Escherichia coli and Pseudomonas putida. This platform was then used to program the induction of ethanol production by three nutrients, fructose, cellobiose, and galactose, of which each molecule can be present in a different set of crops. These results suggest that our platform facilitates the use of different agricultural products for the dynamic control of biosynthesis.

Integral feedback control strategies have proven effective in regulating protein expression in unpredictable cellular environments. These strategies, grounded in model-based designs and control theory, have advanced synthetic biology applications. Autocatalytic integral feedback controllers, utilizing positive autoregulation for integral action, are one class of simplest architectures to design integrators. This class of controllers offers unique features, such as robustness against dilution effects and cellular growth, as well as the potential for synthetic realizations across different biological scales, owing to their similarity to self-regenerative behaviors widely observed in nature. Despite this, their potential has not yet been fully exploited. One key reason, we discuss, is that their effectiveness is often hindered by resource competition and context-dependent couplings. This study addresses these challenges using a multilayer feedback strategy. Our designs enabled population-level integral feedback and multicellular integrators, where the control function emerges as a property of coordinated interactions distributed across different cell populations coexisting in a multicellular consortium. We provide a generalized mathematical framework for modeling resource competition in complex genetic networks, supporting the design of intracellular control circuits. The use of our proposed multilayer autocatalytic controllers is examined in two typical control tasks that pose significant relevance to synthetic biology applications: concentration regulation and ratiometric control. We define a ratiometric control task and solve it using a variant of our controller. The effectiveness of our controller motifs is demonstrated through a range of application examples, from precise regulation of gene expression and gene ratios in embedded designs to population growth and coculture composition control in multicellular designs within engineered microbial ecosystems. These findings offer a versatile approach to achieving robust adaptation and homeostasis from subcellular to multicellular scales.

Inarguably, the green fluorescent protein (GFP) family is an exemplary model for protein engineering, accessing a range of unparalleled functions and utility in biology. The first variant to recognize and provide an optical output of chloride in living cells was serendipitously uncovered more than 25 years ago. Since then, researchers have actively expanded the potential of GFP indicators for chloride through site-directed and combinatorial site-saturation mutagenesis, along with chimeragenesis. However, to date, the power of directed evolution has yet to be unleashed. As a proof-of-concept, here, we use random mutagenesis paired with anion walking to engineer a chloride-insensitive fluorescent protein named OFPxm into a functional indicator named ChlorOFF. The sampled mutational landscape unveils an evolutionary convergent solution at one position in the anion binding pocket and nine other mutations across eight positions, of which only one has been previously linked to chloride sensing potential in the GFP family.

Inarguably, the green fluorescent protein (GFP) family is an exemplary model for protein engineering, accessing a range of unparalleled functions and utility in biology. The first variant to recognize and provide an optical output of chloride in living cells was serendipitously uncovered more than 25 years ago. Since then, researchers have actively expanded the potential of GFP indicators for chloride through site-directed and combinatorial site-saturation mutagenesis, along with chimeragenesis. However, to date, the power of directed evolution has yet to be unleashed. As a proof-of-concept, here, we use random mutagenesis paired with anion walking to engineer a chloride-insensitive fluorescent protein named OFPxm into a functional indicator named ChlorOFF. The sampled mutational landscape unveils an evolutionary convergent solution at one position in the anion binding pocket and nine other mutations across eight positions, of which only one has been previously linked to chloride sensing potential in the GFP family.

The supply of artemisinin, the primary antimalarial drug recommended by the World Health Organization (WHO), is limited due to synthesis cost and supply constraints. This study explores novel chemo-enzymatic pathways for the efficient synthesis of dihydroartemisinic acid (DHAA), the penultimate precursor to artemisinin. The key concept here is to leverage the seamless integration of chemical and enzymatic steps for more thoroughly exploring synthesis alternatives. Using novoStoic, a biosynthetic pathway design tool, we identified previously unexplored carbon- and energy-balanced pathways for converting amorpha-4,11-diene (AMPD) to DHAA. For some of the enzymatically catalyzed steps lacking efficient enzymes, chemical catalysis alternatives were proposed and implemented, leading to a hybrid chemo-enzymatic pathway design. The proposed pathway converts AMPD directly to DHAA without going through artemisinic acid (AA), making it a shorter pathway compared with the existing synthesis routes for artemisinin. This effort paves the way for the systematic design of chemo-enzymatic pathways and provides insight into decision strategies between chemical synthesis and enzymatic synthesis steps. It serves as an example of how synthesis pathway design tools can be integrated with human intuition for accelerating retrosynthesis and how AI-based tools can identify and replace human intuitions to automate the decision processes. This can help reduce human-machine interventions and improve the development of future tools for synthesis planning.

The ATP-dependent ClpXP-SspB protease complex is responsible for the degradation of intracellular proteins and is maintained at low levels in Escherichia coli to avoid nonspecific degradation. The rate-limiting step in the protease complex leads to proteolytic queueing, where the proteins form waiting lines, and their overall degradation rate is slowed. Synthetic biologists have leveraged proteolytic queueing to design robust synthetic circuits by tagging proteins with the SsrA tag, an 11-amino acid sequence recognized by the complex. Previous work has demonstrated the binding site of each component of the ClpXP-SspB complex to the SsrA tag. However, the precise component responsible for queueing was unknown. To identify the bottleneck in the complex, we designed different SsrA tag variants depending on the chaperone binding sequences. We further overexpressed each protein in the ClpXP-SspB complex in vivo to determine how an increased amount of each component affects the tagged protein levels. Based on the degradation of the SsrA variants, upon overexpression of each component of the ClpXP-SspB system, evidence supports that ClpX (the ATP-dependent chaperone) is responsible for queueing but not ClpP (the protease) or SspB (the adapter, ATP-independent chaperone). In the process, we identified LAA-LAA, a 6-amino acid ClpX-dependent tag that degraded in vivo faster than the original SsrA tag, AANDENYALAA. We speculated that this high degradation tag could be useful in a dynamic-synthetic circuit, so we modified the well-characterized dual-feedback oscillator by replacing its original SsrA tag with the LAA-LAA tag to form the LAA-LAA-Osc oscillator. Both population and single-cell level experiments show that the new and old oscillators have distinct frequencies. Like the original oscillator, thousands of cells containing the new oscillator could be synchronized by entrainment using an external signal. Thus, the new LAA-LAA-Osc oscillator retains the original oscillator’s best characteristics (robustness to fluctuations, a steady oscillation period, and entrainment across 1000s of cells to an external signal) but oscillates at a different frequency.