ACS Synthetic Biology最新文献

Noncanonical amino acid (ncAA) incorporation at the protein N-terminus enables defined protein functionalization. However, initiation-based ncAA incorporation systems generally suppress the native methionine pathway, limiting their use for proteins containing internal methionine residues. Here, we developed an orthogonal initiation system for N-terminal ncAA incorporation in cell-free translation systems while retaining native methionine incorporation. We profiled background initiation from all 64 codons in cell-free translation systems and identified low-background artificial initiation codons. Engineered initiator tRNAs were designed to introduce ncAA at the protein N-terminus using artificial initiation codons. This system enabled efficient incorporation of N-biotinyl-l-phenylalanine into protein, reaching over 90% incorporation. This system was further extended to p-azido-l-phenylalanine and to an Escherichia coli extract-based cell-free translation system. Finally, N-biotinylated proteins synthesized in this system were utilized for purification-free biolayer interferometry analysis. This work establishes an orthogonal initiation strategy for N-terminal protein functionalization while preserving the native methionine incorporation.

Wickerhamomyces ciferrii is a non-model diploid yeast that naturally produces tetraacetyl phytosphingosine (TAPS), a sphingoid base used in cosmetic and dermatological applications. However, its strong preference for non-homologous end joining (NHEJ) over homologous recombination (HR) limits conventional genome editing, while disruption of LIG4, a core NHEJ gene, compromises cellular fitness. Here, we repurposed native NHEJ activity to develop a homology-independent multicopy genome integration platform for W. ciferrii. The platform combines three optimized donor-design features: telomeric end-shielding with two tandem copies of an 11 bp repeat to improve linear donor persistence, a defective URA5 auxotrophic marker to enrich multicopy integrants, and 5′-phosphorylated donor termini to enhance transformant recovery and integration output. These features were consolidated into the platform vector pTdmVU5. As a metabolic engineering demonstration, multicopy integration of LCB1 and LCB2, encoding the two subunits of serine palmitoyltransferase, increased TAPS titer by 2.7-fold. This work converts the native NHEJ bias of W. ciferrii from a barrier to precise genome editing into a practical tool for pathway amplification and establishes a framework for engineering NHEJ-dominant non-model yeasts.

Traditional protein design is fundamentally constrained by known sequences and folds. To break free from these limitations, we introduce a new alternative: designing proteins directly from plain-language specifications. To achieve this, we trained MP4, a transformer-based model that maps natural language prompts to protein sequences, on a dataset of 3.2 billion points and 138k tokens. In a benchmark of 96 prompts representing a wide array of functions and contexts, MP4 excelled by simultaneously improving on three key metrics: sequence realism, predicted fold quality, and alignment to the requested function. This high performance is particularly significant as it was achieved using only text as input which is a major departure from other models. Experimental validation confirmed our computational predictions: two de novo designs were experimentally shown to be both expressible and thermostable, with high-resolution crystallography (1.30 Å and 1.77 Å) ultimately revealing one to possess a paradigm-shifting novel fold. Functionally, the designs were also active, demonstrating both ATP binding and hydrolysis in vitro. This work demonstrates the realization of natural-language intent as functional proteins that express, crystallize, and catalyze. Although the underlying approach is still in early development with incomplete coverage and controllability, MP4 delivers a profound impact: it lowers the barrier to protein design and vastly expands the space for creative exploration in molecular programming.

The interaction between the receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S1) and human ACE2 receptor is essential for viral entry into host epithelial cells and a key target for drug discovery. Here, we describe the evolution of a threomer, a base-modified version of threose nucleic acid (TNA), that binds to the S1 protein and inhibits its interaction with ACE2. The aptamer was isolated by in vitro selection using a DNA display strategy that linked each TNA molecule to its encoding double-stranded DNA template. Following iterative cycles of selection and amplification, lead candidates were identified by parallelized screening of individual variants in hydrogel particles. The top-performing hit exhibits low nanomolar affinity to the S1 protein and inhibits formation of the S1−ACE2 complex. Together, this work establishes threomers as an emerging platform for inhibiting protein−protein interactions in therapeutic targets.

Bacteroides thetaiotaomicron (Bt), a dominant bacterial species in the human gut, is a promising chassis for engineering in situ therapeutic delivery systems. Previously, we developed a secretion toolkit composed of endogenous lipoprotein signal peptides (SPs) and full-length secretory proteins from Bt. However, due to variations in length, structure, and amino-acid sequence, these SPs exhibited inconsistent secretion efficiencies across different cargo proteins. Because the activity of individual SP-cargo pairs is not readily predictable, screening and optimization are often required to achieve target secretion titers. To enhance the utility of our toolbox, we studied the impact of different SP sequence components on protein secretion and then applied this knowledge to develop a standardized toolkit to enable predictable and tunable protein secretion across diverse SP-cargo pairs. To achieve this, we first identified the lipoprotein export sequence (LES) as the key determinant of efficient secretion of heterologous proteins by lipoprotein SPs. We next performed mutagenesis on the LES region of a representative lipoprotein SP to generate a pool of mutants featuring a standardized SP backbone with diversified LES regions. Screening and characterization of this mutant pool revealed a charge-dependent regulation of both secretion and surface display of heterologous cargo proteins. From these findings, we established a toolkit with improved tunability, enhanced predictability, and surface display capabilities that minimizes the need for iterative screening when developing protein secreting gene circuits for Bt and other Bacteroides species. By enhancing both the flexibility and control of therapeutic protein output, these results expand the potential of engineered living therapeutic applications, particularly those requiring tunable dosing or surface presentation of proteins.

The strong cytotoxicity of wild-type CcdB limits its use as a counter-selection marker, as leaky expression can cause unintended cell death. Here, we report the rational engineering of a tunable CcdB variant with minimal basal toxicity while retaining inducible lethality. Using a structure-aware deep learning-guided strategy, we prioritized mutations predicted to alter CcdB−DNA gyrase binding energetics and experimentally identified variants with reduced basal toxicity and retained inducible killing. Targeted validation identified CcdB_L96P, which significantly reduces basal toxicity while preserving effective killing upon induction. This variant exhibits minimal leakage and robust inducible lethality across multiple Escherichia coli strains without requiring specialized hosts. It enables antibiotic-free CRISPR gRNA plasmid construction with high accuracy and efficient enrichment of correctly assembled clones. In a succinic acid-producing chassis, CcdB_L96P imposes no detectable metabolic burden and supports effective removal of residual cells using low concentrations of anhydrotetracycline. Together, this work provides a generalizable protein-level strategy for tuning toxin activity in synthetic biology.

The emergence of life required the coupling of metabolism, structure, and heredity within self-organizing chemical systems. We show that thermal proteinoid microspheres, made from amino acids (Glu, Asp, Lys) at 170 °C, connect with the Belousov−Zhabotinsky (BZ) reaction. This creates stable, self-reproducing hybrid systems that display basic computational abilities. Scanning electron microscopy shows that BZ-proteinoid microspheres have unique spherical and polygonal morphologies (0.5−1.5 μm) and internal compartments. This is different from the spherical shape of pure proteinoids (1−5 μm). Electrochemical monitoring with multi-electrode arrays (Pt/Ir, 10 mm spacing) shows that adding proteinoids increases potential amplitude by ∼3.3 times, reaching maxima of 319.9 mV (vs 97.7 mV for pure BZ). It also stabilizes high-voltage states. This reduces Shannon entropy to H = 0.010 bits, a drop of 98.7% from pure BZ (H = 0.754 bits). Boolean logic analysis shows a strong AND-gate coincidence (ρ_AND = 0.783) between control and hybrid channels. Also, the state transition network topology shows a 29% drop in outgoing entropy (ΔH = −0.062 bits). This indicates that the pathways are becoming more stable. Cyclic voltammetry shows memristive behavior and a 16-fold increase in peak current (±25 μA vs ± 1.5 μA). It demonstrates conductance increase over 100 cycles, energy loss with hysteresis, and the ability to store multiple bits of data. Hybrid microspheres reproduce in two ways: asymmetric budding and binary fission. They pass on their membrane structure and oscillatory behavior to their daughter cells. This shows a form of proto-heredity. The system maintains electrochemical coherence at pH 1.72, consistent with acidic prebiotic environments. These findings show that BZ-proteinoid hybrids are basic models for protocellular computation. They combine oscillating chemistry with compartmentalized structures. This leads to lasting, heritable information processing without needing genetic templates. The work suggests that rhythmic, membrane-bounded systems may have preceded template-based replication in the origin of cellular life.

l-Ornithine is a versatile amino acid with broad applications in the pharmaceutical, nutraceutical, and food industries. However, its efficient microbial production is constrained by a critical trade-off: excessive blockage of the downstream l-arginine pathway severely impairs cell growth, while intracellular l-ornithine accumulation causes metabolic stress. Here, we report an integrated metabolic engineering strategy in Escherichia coli that resolves these challenges through three key innovations. First, instead of complete pathway disruption, a fine-tuned attenuation of l-arginine biosynthesis was implemented to balance cellular growth with l-ornithine production. Second, a bidirectional dynamic control system was established to simultaneously repress the competing l-proline pathway and facilitate l-ornithine export, thereby coordinating intracellular synthesis with extracellular secretion. Third, fed-batch fermentation identified N-acetyl-l-ornithine accumulation as a major metabolic bottleneck, which was effectively alleviated by introducing an alternative deacetylation route to bypass feedback inhibition. The final engineered strain produced 65.55 g/L l-ornithine with a yield of 0.40 g/g glucose in a 5 L fed-batch fermentation, the highest de novo l-ornithine titer reported in E. coli to date. This work provides a generalizable framework for balancing growth, metabolic flux, and product secretion in amino acid biomanufacturing.

The interleukin-1 receptor antagonist (IL-1Ra) is a key anti-inflammatory cytokine that inhibits interleukin-1 signaling by competitively binding to IL-1 receptors. However, recombinant IL-1Ra, currently produced in Escherichia coli, exhibits limited pharmacokinetics and requires frequent administration due to its short plasma half-life and absence of glycosylation. To overcome these limitations, we designed a novel IL-1Ra-Fc fusion protein consisting of human IL-1Ra fused to a human IgG1 Fc fragment via a flexible linker and transiently expressed in Nicotiana benthamiana to enhance protein yield, stability, and enable glycosylation. The recombinant protein accumulated to approximately 340 mg/kg fresh leaf biomass and achieved an overall DSP recovery of 45% protein yield, with a characteristic high α-helical secondary structure, as confirmed by CD spectroscopy. Receptor-binding analysis shows that rhIL-1Ra-Fc exhibited significantly enhanced IL-1 receptor binding activity, showing approximately 17% higher activity than that of commercial IL-1Ra. Overall, this is the first study to demonstrate the feasibility of producing functionally active IL-1Ra-Fc in plants for potential therapeutic applications in inflammatory diseases.

Improving the reconstituted translation system is a key requirement for bottom-up synthetic biology. Here, we developed a two-step in vitro evolutionary method that can be used for improving translational proteins. In this method, two distinct conditions were sequentially applied while maintaining genotype-phenotype linkage in water-in-oil droplets. Using this method, we performed in vitro evolution of four translation factors, IleRS, PheRS, EF-G, and EF-Tu, and identified mutations that modestly enhanced translation activity in in vitro expression assays. One of the EF-G mutations (P610S) increased activity per protein approximately 2-fold for the recombinant protein purified from E. coli. This selection method is useful for improving translational proteins for bottom-up synthetic biology.