最新刊期
- 摘要：With the rapid advancement of global industrialization and urbanization, large quantities of heavy metals, organic pollutants, and emerging contaminants are continuously released and accumulated in the environment, posing long-term threats to ecosystem stability and human health. Microbial degradation, characterized by its environmental friendliness, sustainability, and high metabolic plasticity, has therefore emerged as an important strategy for environmental pollution control. However, natural microorganisms still face several critical limitations in practical applications, including insufficient sensitivity toward low-concentration pollutants, inadequate degradation efficiency, poor adaptability to complex environments, low community stability, and potential biosafety risks. Recent advances in synthetic biology have provided novel engineering approaches for environmental microbial degradation. By constructing programmable genetic circuits, dynamic metabolic regulatory modules, and cooperative population systems, synthetic biology enables highly sensitive pollutant detection, precise metabolic flux regulation, synergistic degradation of multiple substrates, and controllable environmental behaviors of engineered microorganisms, thereby significantly enhancing bioremediation efficiency. This review systematically summarizes recent advances in synthetic biology for environmental remediation from the perspective of microbial regulatory system engineering. Specifically, we discuss low-concentration pollutant-responsive systems based on transcription factors and riboswitches; signal amplification systems employing cascade regulation and logic-gate circuits; dynamic metabolic flux regulation; strategies for redox cofactor and energy homeostasis regulation; complex environment-responsive regulatory networks; artificial microbial consortia and quorum sensing-mediated cooperative systems; as well as biosafety and controllability design strategies for engineered microorganisms. Furthermore, we highlight the current challenges in environmental synthetic biology, including complex environmental adaptability, system stability, cross-scale regulation, and practical application and translation, and provide perspectives on the future development of intelligent, adaptive, and ecologically compatible microbial systems. Overall, this review aims to systematically outline the core strategies and emerging trends in environmental microbial degradation from the viewpoint of regulatory system engineering, thereby providing theoretical guidance for the development of efficient, safe, and programmable environmental synthetic biology systems in the future.关键词：pollutants detection;microbial degradation and transformation;synthetic biology;regulatory systems;biosafety1|0|0更新时间：2026-08-11
- 摘要：The continuous and pervasive accumulation of recalcitrant pollutants in the natural environment poses a progressively severe threat to global ecological security and human health. Conventional remediation technologies often struggle to completely mineralize these complex compounds. To address this critical issue, Photocatalysis-Biohybrid Systems (PBS) have emerged as a promising, sustainable strategy. These systems enable the efficient degradation and structural transformation of persistent pollutants driven directly by solar energy by seamlessly coupling semiconductor photocatalytic materials with non-photosynthetic microorganisms. By bridging abiotic light-harvesting components with whole-cell biocatalysts, PBS cleverly harness the strengths of both fields. However, current PBS configurations for environmental pollutant degradation largely remain at the rudimentary, empirical assembly stage, heavily relying on the "material + natural single strain" paradigm. Consequently, they face several core bottlenecks, such as restricted cross-interface electron transfer efficiency between inorganic materials and biological membranes, the non-directional diversion of intracellular reducing power, and incomplete microbial degradation metabolic pathways. These intrinsic limitations severely restrict their overall performance enhancement, operational stability, and subsequent large-scale engineering applications. To overcome these barriers, this comprehensive review systematically outlines the fundamental synergistic mechanisms, structural design characteristics, and key environmental influencing factors of various PBS architectures. It critically summarizes recent application advances in the targeted degradation of typical environmental pollutants, including antibiotics, polycyclic aromatic hydrocarbons (PAHs), heavy metal ions, and emerging microplastics. Furthermore, the review provides an in-depth, mechanistic analysis of effective pathways for systematic enhancement. Particular focus is directed toward core optimization strategies, such as synthetic microbiome construction for multi-step degradation, targeted electron transport chain reconstruction to boost energy utilization, and material interface optimization to enhance biocompatibility and electron transfer rates. Finally, this paper discusses the core challenges currently facing PBS, including low cross-interface electron transfer efficiency, incomplete degradation pathways, and insufficient system stability. It further highlights future prospects for achieving rational design and engineering applications through advanced strategies, such as the construction of synthetic microbiomes, the targeted regulation of electron transport chains, and the synergistic adaptation of community-material interfaces. Ultimately, this review aims to drive the fundamental transition of PBS research from an experience-driven "simple functional assembly" to a predictable, robust, and controllable "rational system design". By doing so, it provides a crucial theoretical basis and technical reference for the future development of highly efficient, stable, and scientifically controllable pollutant degradation systems globally.关键词：non-photosynthetic microorganisms;photocatalysis-biohybrid systems;Pollutant Degradation;synthetic biology;electron transfer7|3|0更新时间：2026-08-04
- 摘要：Synthetic microbial communities (SynComs), serving as the core vehicle for the paradigm shift in synthetic biology from monoculture cell factories to multicellular consortia, represent a pivotal strategy for achieving complex functionalities. However, a significant robustness gap persists when transitioning SynComs from controlled laboratory settings to complex, heterogeneous open environments. This review first systematically deconstructs the multidimensional connotations of robustness of SynComs for application across four key dimensions: environmental fitness, functional stability, colonization persistence, and scale-up adaptability. To address the complexity of open environments and circumvent the inherent limitations of emergent properties in low-complexity SynComs (typically comprising fewer than 20 species), this review employs high-complexity, large-scale SynComs (comprising more than 20 species), designed for high-fidelity emulation of complex natural habitats, as research models. Through reverse engineering, we characterize the underlying ecological mechanisms that maintain robustness under fluctuating pressures. Our analysis reveals that the robustness of large-scale SynComs originates from emergent properties generated by nonlinear coupling. In the phylogenetic dimension, diversity redundancy among high-abundance species forms a rigorous niche barrier, significantly enhancing invasive defense. In the metabolic dimension, members of SynComs construct efficient negative feedback loops, where the metabolic sink function of key species effectively alleviates the toxic accumulation of hazardous intermediates. In the environmental response dimension, the consortia exhibit strong correlations with host regulation and habitat fluctuations. Crucially, existing studies have indicated a decoupling between colonization and function, demonstrating that the functional robustness of SynComs can manifest as transient and immediate effects, rather than relying on permanent niche occupation. Based on these insights, we propose four rational design principles for the application of SynComs: 1) Phylogenetic niche saturation, enhancing invasion resistance by maximizing lineage saturation in target scenarios; 2) Metabolic negative feedback regulation, utilizing key metabolic sink species to eliminate metabolic toxicity; 3) Host-environment coupling, achieving steady-state alignment between artificial consortia and indigenous environmental factors; and 4) Functional demand-driven effect trade-offs. Functioning as a top-level constraint, this principle advocates for the dynamic adjustment of design logic across the other principles based on specific application scenarios (e.g., immediate intervention vs. long-term maintenance). This review provides systematic methodological guidance for the application of SynComs to overcome scale barriers when transitioning from the laboratory to open environments. Furthermore, it offers robust theoretical support for strengthening the underlying constraints of the "Design-Build-Test-Learn" (DBTL) cycle and for the rational construction of high-performance, stable SynComs.关键词：synthetic microbial communities;robustness;reverse engineering;design constraints;design-build-test-learn (DBTL) cycle38|6|0更新时间：2026-08-04
- 摘要：Microbial communities are ubiquitous in both natural and engineered environments, where they drive complex biotransformations and biogeochemical cycles and exhibit diverse and efficient functional outputs. Building on these properties, microbiome engineering has emerged as a promising framework for applications in environmental remediation, agriculture, and biomanufacturing. In recent years, extensive efforts have elucidated key regulatory mechanisms in low-complexity synthetic communities, particularly those mediated by metabolic cross-feeding and metabolic division of labor. However, these mechanisms are largely derived from idealized and low-dimensional systems, and their applicability and generalizability remain to be validated, especially when extrapolated to complex engineered microbiomes, where systematic design principles are still lacking. Moreover, engineered microbiomes typically operate under dynamic conditions, in which microbial interactions are continuously reshaped by environmental fluctuations, spatiotemporal heterogeneity, and species immigration and emigration. As a result, mechanisms derived from static and closed systems are difficult to directly apply to the prediction and design of complex microbiome systems. In this context, this review focuses on the critical challenge of translating mechanistic insights into microbiome interactions into the rational design of complex engineered microbiomes. We summarize recent advances in understanding canonical interaction mechanisms in simplified systems and analyze the key gaps that limit their extrapolation to complex communities. We further discuss the major challenges associated with scaling interaction mechanisms across temporal and spatial dimensions, and review how environmental fluctuations and species turnover in open systems regulate microbial interactions and community dynamics. Based on these insights, we highlight the need to extend studies from pairwise to higher-order interactions, to develop quantitative frameworks based on mechanistic classification and standardized parameters, and to construct predictive models across spatiotemporal scales. We also propose that interaction mechanisms should be investigated under dynamic and open conditions, and that robustness-testing frameworks tailored to engineering applications should be established to enhance the predictability and transferability of microbiome design principles.关键词：microbial interactions;Microbiome;microbiome engineering;spatiotemporal scales;context dependency;principles of rational design66|6|0更新时间：2026-07-31
- 摘要：Microbial community-scale metabolic model (MCMM) is a community-level metabolic modelling framework developed on the basis of single-species genome-scale metabolic model (GSMM). By integrating the metabolic networks of multiple community members within a shared environmental context, MCMM provides a mechanistic approach for analysing resource competition, metabolite exchange, cross-feeding, community-level functional outputs, and their potential influences on microbial community assembly and evolution. This review systematically summarizes the construction basis, major modelling approaches, representative computational tools, and future development of MCMM. The general workflow for constructing single-species GSMM includes initial model reconstruction, model refinement, structural quality assessment, functional validation, and further optimization. The reliability of GSMM is affected by genome annotation, reaction completeness, network connectivity, exchange reactions, environmental conditions, and model validation. Because MCMM is generally assembled from multiple individual GSMM, errors or uncertainties in single-species GSMM may accumulate and propagate during community-scale simulation, thereby influencing the prediction of resource allocation, metabolic exchange, and community function. The basic principles of steady-state MCMM are then reviewed. Different steady-state modelling methods are compared in terms of their assumptions, optimization objectives, input requirements, major outputs, and suitable application scenarios. Their characteristics in community-level optimization, stable coexistence prediction, sample-specific metabolic analysis, and identification of metabolic dependency are discussed. Although steady-state MCMM is widely used because of its relatively clear mathematical formulation and manageable computational cost, the steady-state assumption limits its ability to represent temporal variation, population fluctuation, environmental disturbance, and spatial heterogeneity in microbial communities. Dynamic MCMM further extends the modelling framework by incorporating time-dependent substrate consumption, metabolite accumulation, changes in population abundance, environmental feedback, spatial diffusion, and local resource gradients. These processes enable the description of microbial community succession, disturbance response, transient metabolic interaction, and spatially heterogeneous processes. Compared with steady-state MCMM, dynamic MCMM expands community metabolic modelling from the prediction of possible metabolic states to the simulation of ecological and metabolic processes over time and space. The future development of MCMM depends on improvements in model quality, realistic definition of environmental constraints, rational parameter setting, integration of multi-omics data, and machine learning-assisted model reconstruction and prediction. Closer integration between computational modelling and experimental validation is also required to improve the biological reliability, interpretability, and predictive capacity of MCMM. This review provides a reference for mechanistic studies of microbial metabolic interaction and for the prediction of microbial community function.关键词：microbial community-scale metabolic model;genome-scale metabolic model;metabolic interaction;multi-omics;Machine learning74|14|0更新时间：2026-07-31
- 摘要：Polar microbial resources represent an important frontier for sustainable biomanufacturing because they originate from ecosystems shaped by long-term geographic isolation and multiple environmental stresses, including low temperature, freeze-thaw cycles, oligotrophy, high salinity, strong ultraviolet radiation, and low oxygen availability. These evolutionary and ecological processes have generated a wide range of unique functional genes, metabolic pathways, and adaptive traits, making polar microorganisms valuable sources of cold-active enzymes, antifreeze and ice-binding proteins, extracellular polysaccharides, pigments, biosynthetic gene clusters (BGCs), stress-tolerance modules, and potential non-model chassis. However, their practical utilization remains constrained by fragmented resource collections, low culturability, insufficient functional validation, incomplete integration of digital sequence information (DSI), limited genetic toolkits, and underdeveloped biosafety and governance frameworks. Following the theme of "from polar exploration to biomanufacturing", this review summarizes the development of China's polar microbial resource system across Antarctica, the Arctic, and the Third Pole. We first describe the resource acquisition network established through Chinese polar research stations, icebreaker expeditions, Arctic observation programs, and long-term investigations of the Qinghai-Tibet Plateau cryosphere, and discuss the complementary roles of the three polar regions in resource discovery, ecological research, functional validation, and engineering translation. We then review the accumulation of cultivable microbial resources, including bacteria, actinomycetes, yeasts, filamentous fungi, and microalgae, together with advances in functional genes, BGCs, stress-resistance modules, and emerging chassis candidates. Particular attention is given to the transition from physical samples and strain collections to genome catalogs, metagenome-assembled genomes, multi-omics datasets, and DSI platforms, which are enabling data-driven discovery and synthetic biology-guided reconstruction of polar functional resources. The potential applications of these resources in low-temperature industrial processes, environmental remediation and resource recycling, cold-region agriculture, high-value bioproduct development, biomining and one-carbon (C1) biomanufacturing are further discussed in relation to China's environmental and low-carbon development needs. Finally, future priorities are proposed, including coordinated sampling and preservation, phenotype annotation, artificial intelligence (AI)-assisted resource mining, non-model chassis engineering, automated design–build–test–learn workflows, process scale-up, techno-economic assessment, lifecycle analysis, biosafety evaluation, and international governance coordination. Overall, polar microbial resources provide an expanding foundation for the discovery, validation, and engineering of functional biological components and may contribute to future environmental sustainability, low-carbon transition, and advanced biomanufacturing.关键词：polar microorganisms;Third Pole;biomanufacturing;cold-active enzymes;environmental synthetic biology;digital sequence information53|6|0更新时间：2026-07-27
- 摘要：Carbohydrates constitute the most structurally diverse class of biological macromolecules in nature, with their glycan chains playing irreplaceable roles in cell recognition, signal transduction, and immune regulation. Unlike the template-driven biosynthesis of nucleic acids and proteins, glycan biosynthesis operates without a direct molecular template. Glycosidic linkage positions (1→2, 1→3, 1→4, 1→6), anomeric configurations (α or β), branching patterns, and modification groups are collectively determined by glycosyltransferases (GTs) localized across distinct subcellular compartments. This multi-dimensional structural freedom endows carbohydrates with the high information density among biomolecules, yet it has historically constrained scalable production of complex glycans: chemical synthesis of glycans demands laborious protecting-group manipulations and stringent stereochemical control, while natural sources yield structurally heterogeneous mixtures that preclude systematic structure–activity relationship studies. Synthetic biology fundamentally reframes this challenge by redefining glycosylation systems as engineerable, reconfigurable networks amenable to rational design. Through genome mining and protein engineering of GTs, precision tuning of sugar nucleotide metabolic networks, and systematic optimization of microbial cell factories, the field is advancing toward the programmable biomanufacturing of structurally defined glycans, from simple monosaccharides to complex glycoconjugates, with unprecedented efficiency and precision. The defining contribution of glycosynthetic biology is methodological. It transforms glycoscience from a discipline that catalogs what nature provides into one that engineers what we need. For decades, glycans were the dark matter of molecular biology. They were structurally intractable, biosynthetically opaque, and functionally elusive, yet they sat at the center of development, immunity, infection, and tumorigenesis. Synthetic biology breaks this deadlock. By making homogeneous glycans accessible on demand, it enables the systematic elucidation of structure–function relationships that had been the missing foundation of the field. Three bottlenecks remain. The first is functional annotation of GTs. Over 500,000 sequences are catalogued in the CAZy database; fewer than 5% have been experimentally validated for substrate specificity and kinetics. Glycosylation pathway design therefore remains a screening exercise, not a rational assembly of standardized parts. The second is sugar nucleotide supply control. These metabolic networks are deeply embedded in central carbon metabolism. A perturbation in one pathway, be it GDP-fucose or CMP-Neu5Ac, ripples unpredictably through the entire system. Independent, dynamic, and precise control of multiple sugar nucleotide pools remains unsolved. The third is glycan structure–activity relationships. These defy the frameworks built for small molecules and proteins. The same epitope elicits different responses depending on backbone context, whether N-glycan, O-glycan, or glycolipid. Multivalency produces non-linear effects that cannot be extrapolated from monovalent affinities. This is not a data problem fixable by more measurements; it is an epistemological one requiring new conceptual tools. This review examines twenty years of progress through four enabling technologies. GT element engineering spans genomic mining against CAZy, structure-guided rational design, directed evolution, and ancestral sequence reconstruction. It has produced variants with orders-of-magnitude gains in catalytic efficiency, altered substrate specificity, and improved process stability. Metabolic pathway rewiring and cell factory design have delivered landmark achievements: the first transplantation of prokaryotic N-glycosylation into E. coli, the humanization of yeast for complex sialylated N-glycans, the CRISPR-enabled glycoform customization of CHO cells, and the de novo microbial biosynthesis of glycosaminoglycans including heparin and hyaluronic acid. Cell-free synthetic systems bypass the constraints of living chassis entirely. There are no membrane barriers, no metabolic cross-talk, no product toxicity. They uniquely enable the incorporation of non-natural sugar nucleotides for bioorthogonal applications. AI and machine learning are accelerating glycan structure prediction, GT function annotation, and pathway optimization. Yet their defining handicap is structural: glycan databases are orders of magnitude smaller than those for proteins or nucleic acids. This places a hard ceiling on what data-hungry models can currently deliver. Four product categories illustrate the translational arc from concept to commerce. Human milk oligosaccharides, led by 2′-fucosyllactose, represent the most mature success. Fermentation titers have surpassed 100 g/L; the global market exceeds one billion USD. Multiple species, including 3-FL, LNT, LNnT, 3′-SL, and 6′-SL, have reached industrial production. Glycoengineered antibodies demonstrate glycan-level pharmacology. Removal of core fucose from IgG1 Fc enhances FcγRIIIa binding by approximately 50-fold, boosting ADCC from therapeutically marginal to clinically decisive. The FDA approval of afucosylated obinutuzumab for chronic lymphocytic leukemia validated this principle. Terminal galactosylation tunes complement activation; α2,6-sialylation extends serum half-life. These parameters are independently controllable, making the Fc glycan a multi-dimensional tuning interface. Glycoconjugate vaccines are being reshaped by recombinant bioconjugation. Engineered E. coli enzymatically transfers target oligosaccharides to carrier proteins, eliminating the chemical coupling and multi-step purification that dominate traditional conjugate vaccine manufacturing. Functional polysaccharides have fulfilled the promise of metabolic engineering at scale. Hyaluronic acid, produced at hundred-ton scale in engineered Bacillus subtilis, now serves ophthalmic surgery, joint injection, and aesthetic medicine. Its success validated the general design principle of push–pull UDP-sugar flux control. Underlying all four cases is a common trajectory: from empirical iteration toward predictive, computation-guided design, powered by the modular assembly of standardized biological parts.Three grand challenges define the next decade. The first is deciphering the glyco-code, the rules that translate glycan structure into biological function. Unlike the genetic code, this mapping is non-linear, multivalent, and context-dependent. Progress demands the convergence of glycan microarray technology, high-resolution mass spectrometry, and AI-driven pattern recognition. It also demands training data that currently does not exist in sufficient quantity. The second is transitioning from trial-and-error to intelligent design. This requires comprehensive, standardized GT kinetics databases. It requires embedding AI prediction models within automated biofoundry workflows. It requires low-resource machine learning methods that can learn from sparse, heterogeneous datasets, a fundamentally different challenge from the data-rich ecosystems of proteomics and genomics. The third is bridging the lab-to-plant gap. Cell factory robustness must withstand industrial fermentation conditions, including temperature swings, pH drift, and osmotic stress. Phage contamination remains an existential threat in bacterial chassis. Downstream purification still consumes 50 to 70 percent of total production costs.Beyond these challenges, emerging frontiers are reshaping the boundaries of the field. C1 feedstock-driven glycan biosynthesis, using CO₂, methanol, or formate as sole carbon sources, promises to decouple carbohydrate production from arable land and plant photosynthesis. Non-natural glycan therapeutics, including fluorinated antivirals, thio-sugar glycosidase inhibitors, and amino-glycoside antibiotic potentiators, extend the accessible chemical space beyond nature's monosaccharide repertoire. Personalized glycan vaccines designed against patient-specific tumor glycoforms and CRISPR-like programmable glycan editing tools point toward a future where glycan structures can be edited as precisely as genes. Glycosynthetic biology is completing a fundamental transformation. It is moving from discovering what nature provides to designing and manufacturing what we desire. Carbohydrates are emerging from the neglected periphery of molecular biology to a frontier at the intersection of discovery and industry. The destination is clear: a standardized glycan operating system for the programmable, on-demand biomanufacturing of structurally defined glycans.关键词：Glycosynthetic Biology;glycosyltransferase;metabolic engineering;cell factory;Sugar Nucleotide;human milk oligosaccharides;Cell-Free Synthetic System73|7|0更新时间：2026-07-27
- 摘要：Rapid development in synthetic biology and metabolic engineering has driven significant progress in the microbial biosynthesis of functional saccharides, such as human milk oligosaccharides (HMOs), D-allulose, N-acetylglucosamine (GlcNAc), and N-acetylneuraminic acid (NeuAc). Nevertheless, conventional static metabolic engineering strategies frequently suffer from metabolic imbalances and resource allocation conflicts within chassis cells, and the bottleneck in high-throughput screening for key enzymes severely hinders further enhancements in biosynthetic efficiency. Furthermore, the bottleneck in high-throughput screening for key enzymes severely hinders further enhancements in biosynthetic efficiency. To address these challenges, biosensors have emerged as powerful tools, playing a prominent role in the dynamic regulation of microbial cell factories and the high-throughput screening of key enzymes and high-yield strains. This review provides a systematic overview of the core modules of genetically encoded biosensors and elucidates the fundamental working principles of various types, including transcription factor-based, RNA-based, two-component system-based, and fluorescent protein-based biosensors. Additionally, essential performance metrics of genetically encoded biosensors—such as specificity, dynamic range, sensitivity, basal leakage, response time, and orthogonality—are systematically discussed, and major strategies for optimizing these key parameters are comprehensively summarized. Furthermore, major strategies for optimizing key parameters such as specificity, sensitivity, and dynamic range are comprehensively summarized. Subsequently, we systematically review the latest studies of these biosensors in the biosynthesis of functional saccharides, including HMOs, D-allulose, GlcNAc, and NeuAc. Various biosensors (e.g., lactose-, temperature-, quorum-sensing-, and metabolite-responsive) are employed to achieve precise dynamic regulation of metabolic pathways, successfully balancing precursor supply and pushing fermentation titers to more than hundred-gram scales. Through coupling biosensors with droplet microfluidics, fluorescence-activated cell sorting (FACS), and toxin-antitoxin systems, the directed evolution of key enzymes and high-throughput screening of overproducing strains are rapidly driven. Future biosensor engineering in functional saccharide biosynthesis centers on AI-assisted de novo design, diversified non-transcription-factor mechanisms, and host expansion into eukaryotic chassis. Crucially, integrating multi-signal logic gates will facilitate autonomous phase switching and metabolic balance. Concurrently, automation-platform-driven integration with biofoundries, droplet microfluidics, and machine learning will accelerate high-throughput iterative optimization. Together, these technological advancements will seamlessly propel functional saccharide production from empirical static optimization toward a new paradigm of highly intelligent, autonomous metabolic regulation. These advances will propel biosynthesis of functional saccharides from static optimization towards intelligent, autonomous regulation.关键词：biosensors;functional saccharides;dynamic regulation;high-throughput screening101|33|0更新时间：2026-07-24
- 摘要：With the advancement of global carbon neutrality strategies and the increasing demand for food security and sustainable supply, traditional methods of carbohydrate production based on natural photosynthesis face several fundamental limitations. These include limited land resources, strong climate dependence, and low energy efficiency. Carbon dioxide (CO2), a major greenhouse gas, is an abundant, non-toxic, and readily available C1 resource. Converting CO2 into key C1 intermediates, such as carbon monoxide (CO), methanol, formaldehyde, and formic acid, and subsequently extending the carbon chain to synthesize carbohydrates (Cn), provides a promising strategy to overcome the temporal and spatial constraints of agricultural production. This approach also creates new opportunities for the high-value utilization of C1 resources and the establishment of an artificial carbon cycle. This review systematically summarizes the development of multiple catalytic pathway, including chemocatalytic system, in vitro multi-enzyme cascade systems, and microbial cell factory–based approaches. In the chemocatalytic system, substantial progress has been achieved through increasingly sophisticated catalyst design and systematic optimization of reaction conditions, which have significantly improved CO2 conversion efficiencies and product selectivities. Neverthless, several critical challenges remain unresolved, including limited lifetimes of catalyst, difficulties in generating and stabilizing high concentrations of formaldehyde, and insufficient selectivity toward specific carbohydrates. By contrast, in vitro multi-enzyme cascade systems and microbial cell factories have demonstrated outstanding selectivity and structural precision in the synthesis of monosaccharides, oligosaccharides, and even starch-like polymers. These biologically inspired routes benefit from the inherent specificity of enzymes and metabolic pathways, allowing fine control over carbon–carbon bond formation and stereochemistry. However, their large-scale application is still constrained by several factors, such as insufficient metabolic flux, toxicity of reactive intermediates, high costs associated with enzyme production and purification, and the complexity of cofactor regeneration and energy supply. This article provides a comprehensive review of research progress over the past decade in the artificial synthesis of carbohydrates from CO₂. Particular emphasis is placed on catalyst design principles in chemical systems, strategies for enzyme engineering and performance enhancement, and the construction and optimization of synthetic metabolic pathways. A systematic comparison between chemical and biological routes is presented, highlighting their respective technological potentials, intrinsic limitations, and suitability for different application scenarios. Finally, the key bottlenecks currently hindering the practical implementation of CO₂-to-carbohydrate technologies are critically discussed. Future research directions are outlined, including hybrid chemo–bio systems, integration with renewable energy inputs, and scalable process design. These perspectives aim to provide both theoretical insights and practical guidance for the sustainable production of carbohydrates under the overarching framework of carbon neutrality and global food security.关键词：carbon dioxide;Artificial Synthesized Carbohydrates;Sugar;Starch;Chemocatalytic System;In vitro Multi-Enzyme Cascade System;Microbial Cell Factory System118|19|0更新时间：2026-07-24
- 摘要：Escherichia coli is a commonly used host for recombinant protein expression. However, endotoxins released from its outer membrane may induce endotoxin-related adverse reactions, such as inflammatory responses, fever, and even endotoxin shock, thereby limiting its application in the production of biopharmaceutical recombinant proteins, including vaccine antigens. This study aimed to construct a low-endotoxin E. coli expression system and evaluate its application potential in the recombinant expression of candidate antigens against porcine pleuropneumonia. Using E. coli BL21(DE3) as the parental strain, CRISPR/Cas9-mediated genome editing was employed to modify pathways related to core oligosaccharide biosynthesis, O-antigen assembly, lipid A modification, and surface polysaccharide synthesis, resulting in a series of low-endotoxin candidate strains. These pathway modifications caused defects in lipopolysaccharide structural assembly, a significant decrease in heptose content in extracellular polysaccharides, disappearance of lipopolysaccharide bands, and increased cell surface roughness. Among the candidate strains, the endotoxin levels in the lysate supernatants of ETF13 and ETF15 decreased by 35% and 73%, respectively. Considering both endotoxin levels and strain growth status, ETF13 showed a favorable balance between low-endotoxin characteristics and chassis applicability and was therefore selected as the host for subsequent recombinant protein expression. Using four subunit vaccine candidate antigens against of Actinobacillus pleuropneumoniae, namely ApxI, ApxII, ApxIII, and OMP, as model proteins, ETF13 exhibited recombinant protein expression levels comparable to those of the parental strain. In addition, the residual endotoxin levels in the four purified proteins were reduced by more than 50%. Taken together, these results demonstrate that this engineered low-endotoxin E. coli expression system provides a promising alternative chassis for the large-scale production of medical recombinant proteins.关键词：Low-endotoxin Escherichia coli;Lipopolysaccharide;gene editing;Subunit vaccine;Porcine contagious pleuropneumonia79|11|0更新时间：2026-07-23
- 摘要：Exosomes are 30-150 nm extracellular vesicles secreted by nearly all living cells, serving as essential carriers for intercellular communication. The glycocalyx on exosome surfaces, mainly composed of glycans from glycoproteins and glycolipids, acts as a critical "glycocode" that governs target recognition, cellular internalization, immune modulation, and signal transduction. However, the inherent high heterogeneity of native exosome glycans severely restricts their clinical translation, especially as drug delivery vehicles, due to insufficient targeting, low intracellular delivery efficiency, and rapid clearance by the immune system in vivo. Exosome glycan editing, an emerging interdisciplinary technology integrating glycobiology, synthetic biology, chemical biology, and nanotechnology, enables precise manipulation, modification, or de novo reconstruction of exosome glycan structures, offering a revolutionary strategy to optimize exosome performance and expand their therapeutic applications.This review systematically summarizes the compositional characteristics, advanced analytical techniques, and core biological functions of exosome glycans. It elaborates on three major glycan editing strategies: host cell engineering (in vivo editing), in vitro direct modification, and synthetic biology reconstitution, highlighting their technical principles, advantages, and recent breakthroughs. The review further dissects the regulatory mechanisms of edited glycans on exosome biological behaviors, including targeting specificity, endocytic pathways, immunogenicity, and cargo loading (e.g., miRNAs). It also comprehensively presents the application prospects of glycan-engineered exosomes in the treatment of tumors, inflammatory diseases, neurodegenerative disorders, and metabolic diseases.Nevertheless, the field still faces critical challenges, such as uncontrollable exosome heterogeneity, limited precision of glycan editing, high costs of large-scale preparation, and the lack of standardized quality control and regulatory systems for clinical translation. Future directions will focus on the integration of CRISPR gene editing, cell-free synthesis, microfluidics, and AI-assisted glycan design to develop microenvironment-responsive intelligent glycan editing, elucidate the molecular mechanisms of glycan-cargo crosstalk, establish unified industrial standards, and accelerate clinical translation. This review emphasizes that interdisciplinary convergence is indispensable for achieving precise programming of exosome glycan functions, which will greatly boost the development of exosome-based precision medicine and biotherapeutics.关键词：exosomes;glycosylation;glycan Editing;synthetic biology;intercellular communication;drug delivery;metabolic labeling21|9|0更新时间：2026-07-23
- 摘要：Pollutant removal in soils, sediments, and wastewater is often constrained by interfacial mass transfer, strong sorption, limited contaminant bioavailability, and instability of introduced microbial functions under open environmental conditions. Lipopeptide biosurfactants offer a distinctive route to address these constraints because they combine strong interfacial activity, biodegradability, relatively low environmental burden, and nonribosomal peptide synthetase (NRPS)-encoded structural programmability. Given the interfacial mass-transfer limitations in pollutant remediation and the design requirements of environmental synthetic biology, this review reframes lipopeptides not merely as exogenous surfactant additives, but as programmable interfacial functional modules that connect contaminant partitioning, microbial adhesion, community organization, and field deployment. We summarize the structural features and NRPS assembly logic of representative lipopeptide families, discuss chassis engineering, metabolic regulation, mixed-culture production, low-grade biomass valorization, and evaluate application evidence in the pollution remediation of petroleum hydrocarbons, heavy metals, antibiotics, and pesticides. Current progress indicates that the central advances in this field have moved beyond the simple enhancement of contaminant solubility. First, fatty-acid chain length, peptide-ring composition, and homologue distribution can be engineered to tune critical micelle concentration, emulsification, adsorption, membrane interaction, and metal-complexation behavior. Second, in situ lipopeptide generation and synthetic microbial consortia can couple interfacial mass transfer with colonization, division of labor, and community persistence. Third, integration with low-grade biomass feedstocks, foam-based in situ recovery, process scale-up, and biosafety control provides a more realistic route toward deployable remediation systems. This perspective also clarifies why lipopeptide performance must be interpreted through the joint effects of molecular structure, phase behavior, microbial physiology, and site heterogeneity rather than by surface tension alone. We further analyze dose-window effects, micellar sequestration, membrane stress, chassis compatibility, foam management, downstream recovery, regulatory constraints, and genetic biocontainment as key boundaries for translation. Future research should establish programmable lipopeptide libraries, standardized interfacial phenotyping, data-driven Design-Build-Test-Learn cycles, scenario-specific dose windows, and biosafety-by-design strategies. Such developments would enable lipopeptides to evolve from empirical remediation enhancers into designable, predictable, and controllable modules within environmental synthetic biology.关键词：biosurfactants;synthetic biology;lipopeptides;Pollutant Degradation;Bioremediation55|10|0更新时间：2026-07-23
- 摘要：Under the growing global demand for sugar reduction, sweet proteins have emerged as promising natural sweeteners owing to their ultrahigh sweetness, favorable sensory attributes, and negligible impact on blood glucose metabolism. Despite their considerable commercial potential, large-scale application remains constrained by challenges including high production costs, limited protein stability, and sensory characteristics that differ from those of sucrose. This review systematically summarizes the current research progress on eight representative sweet proteins, including thaumatin, brazzein, monellin, mabinlin, neoculin, curculin, miraculin, and pentadin. Their sources, structural features, sweetness characteristics, and physicochemical properties are comprehensively discussed. Particular emphasis is placed on the molecular mechanisms underlying sweet taste perception, including the interaction of sweet proteins with the human sweet taste receptor and recent advances in elucidating receptor activation pathways through structural biology and computational modeling. These findings provide an important theoretical foundation for the rational design and optimization of sweet proteins. Furthermore, recent advances in synthetic biology-enabled biomanufacturing of sweet proteins are reviewed, covering chassis cell engineering, promoter and codon optimization, secretion pathway regulation, fermentation process development, and downstream purification strategies. The applications of protein engineering approaches, including rational design, directed evolution, computational redesign, and structure-guided mutagenesis, are also discussed with respect to improving protein expression, sweetness potency, thermostability, pH tolerance, and overall industrial applicability. Particular attention is devoted to the emerging role of artificial intelligence (AI) in sweet protein research and development. Recent breakthroughs in protein structure prediction, generative protein design, machine learning-assisted sequence optimization, and AI-driven codon engineering have significantly accelerated the discovery and engineering of sweet proteins. AI-based frameworks integrated with structural biology, molecular simulation, and Design-Build-Test-Learn (DBTL) cycles are enabling the development of novel sweet proteins with enhanced functionality and manufacturability. Moreover, advances in de novo protein design offer unprecedented opportunities for creating artificial sweet proteins beyond the limitations of naturally occurring protein scaffolds. Finally, this review discusses the techno-economic feasibility, regulatory considerations, and commercialization prospects of sweet protein production. Future developments are expected to arise from the convergence of synthetic biology, protein engineering, structural biology, and artificial intelligence, driving the transition from natural sweet protein optimization toward the rational creation of next-generation sweet proteins. These advances will facilitate the establishment of sustainable, intelligent, and economically viable production platforms, supporting the broader adoption of sweet proteins as key ingredients in the future healthy food industry.关键词：sweet proteins;Protein engineering;Komagataella phaffii;green biomanufacturing;artificial intelligence194|20|0更新时间：2026-07-23
- 摘要：Eukaryotic microalgae have attracted increasing attention as promising chassis organisms for green biomanufacturing and ecological remediation because of their capacity for efficient photosynthetic carbon fixation and biosynthesis of diverse high-value compounds, including lipids, carotenoids, polyunsaturated fatty acids, extracellular polysaccharides, and bioactive metabolites. However, their industrial application remains constrained by unstable product accumulation, limited precision in metabolic regulation, and the strong dependence on environmental fluctuations. Light intensity and quality, nutrient availability, salinity, temperature, and other environmental factors can substantially reshape microalgal growth, stress responses, and carbon allocation, thereby affecting both biomass productivity and target product yield. Therefore, understanding how microalgae perceive and transduce environmental signals is essential for developing controllable and scalable microalgal biomanufacturing systems. This review systematically summarizes the mechanisms by which microalgae sense major environmental signals, including light, nutrient limitation, and osmotic or salt stress. Particular attention is given to the roles of reactive oxygen species, calcium signaling, and mitogen-activated protein kinase cascades in mediating stress perception and intracellular signal transduction. We further discuss how these signaling networks drive metabolic reprogramming associated with lipid accumulation, carotenoid biosynthesis, and extracellular polysaccharide production. Building on this foundation, recent advances in genetic engineering tools for microalgae are reviewed, with emphasis on CRISPR/Cas-mediated genome editing and CRISPR activation or interference systems for transcriptional regulation. These tools provide important technical support for targeted pathway modification, regulatory element characterization, and dynamic control of metabolic flux. In addition, this review highlights the potential applications of environmentally responsive microalgal systems in wastewater treatment, resource recovery, and sustainable biomanufacturing. Current studies indicate that integrating environmental response elements into synthetic biology-based metabolic engineering strategies may enable the construction of dynamic and tunable regulatory networks. With the assistance of artificial intelligence-driven modeling, such systems could improve the prediction of environmental responses, optimize genetic circuit design, and coordinate carbon flux and energy distribution under changing cultivation conditions. Nevertheless, major challenges remain, including the nonlinear coupling of environmental signaling pathways, insufficient standardization and transferability of regulatory elements across microalgal species, and the lack of closed-loop control systems linking environmental inputs with genetic regulation. Future development should focus on temporal metabolic programming, environment-responsive synthetic regulatory circuits, and AI-assisted design-build-test-learn platforms to improve the robustness, controllability, and scalability of microalgal biomanufacturing.关键词：microalgal synthetic biology;gene editing;environmental response regulation;metabolic reprogramming;high-value product biosynthesis56|37|0更新时间：2026-07-08
- 摘要：By integrating the superior photoelectric properties of nanomaterials with the efficient biotransformation capabilities of microorganisms, nanomaterial-microorganism hybrids exhibit tremendous potential in environmental remediation and resource recovery. Recent advancements in materials and microbial engineering have significantly expanded the applications of these biohybrids in complex, highly dynamic environmental scenarios. Focusing on photoelectron generation, interfacial electron transfer, and intracellular electron utilization, this review systematically elucidates the mechanistic principles underlying these hybrids in environmental fields. Specifically, we detail how photogenerated electrons are harvested, transferred across the nano–bio interface, and ultimately incorporated into cellular metabolic networks to drive targeted redox reactions and resource conversion processes. Furthermore, we summarize their current applications across various environmental domains and categorize recent breakthroughs by target pollutant types and resource recovery outputs. For inorganic pollutants, biohybrids enable sustainable nitrate reduction and heavy metal detoxification via biomineralization or valence state transformation, effectively immobilizing hazardous contaminants such as hexavalent chromium and lead. For organic pollutants, they facilitate the degradation of recalcitrant compounds, such as azo dyes and emerging pharmaceutical antibiotics, often utilizing advanced heterojunction designs to enhance charge separation and minimize energy recombination losses. The review also highlights their crucial role in the high-value conversion of carbon dioxide (CO2) into fuels and biochemicals, including methane, acetate, and bioplastics. To overcome existing performance bottlenecks in real-world environments, we explore advanced optimization strategies, such as the enhancement of energy input through multi-physical field coupling, the development of environmentally compatible nano-photosensitive materials and the engineering of environmental microbial chassis. Additionally, a critical assessment is provided regarding current limitations, particularly techno‑economic barriers that hinder large-scale deployment, reactive oxygen species (ROS) toxicity, and ecological safety concerns about genetic escape in open ecosystems. Finally, this review proposes forward-looking research directions. We emphasize integrating artificial intelligence, machine learning, and digital twin technologies to map, model, and intelligently optimize these complex biohybrid systems for practical applications.关键词：Nanomaterial-Microorganism Biohybrids;Interfacial Electron Transfer;Pollutant Degradation;CO2 valorization231|44|0更新时间：2026-07-01
- 摘要：Global organic waste generation continues to rise, while conventional treatment processes struggle to achieve efficient recovery and conversion of the carbon resources contained therein. The reverse β-oxidation (RBO) pathway, a cyclic carbon chain elongation platform, offers distinct advantages including high carbon atom economy, a single energy input form, and a streamlined enzymatic composition. Engineering this pathway thus represents a highly promising synthetic biology route for the 'carbon upgrading' of organic waste. Existing reviews have largely focused on metabolic engineering strategies for the RBO pathway, yet a strategic perspective that explicitly connects these engineering efforts with organic waste processing remains lacking. This review systematically summarizes progress in engineering the RBO pathway, covering metabolic engineering strategies such as pathway transplantation and modular reconstruction, carbon flux redirection, redox balance regulation, and product spectrum expansion, as well as approaches to counter product toxicity. Building upon this, we delineate a progressive research roadmap for the RBO pathway—"model substrates → characteristic waste components → real complex wastes"—and propose synthetic co-culture systems as a bridging link that connects rational design to practical application. We then systematically analyze the potential and challenges of such systems in closing the gap between pure-culture rational design and mixed-culture fermentation. Finally, focusing on key bottlenecks including precise pathway flux regulation, mining of novel enzymes, construction of industrial strains, and enhancement of robustness in open environments, we offer perspectives on future research directions to advance the engineered RBO pathway from the laboratory toward industrial applications for high-value conversion of organic waste. This review aims to integrate the design capabilities of synthetic biology with the contextual understanding of environmental engineering, thereby providing theoretical support for moving engineered RBO pathways from model studies to efficient application in real waste scenarios.关键词：reverse β-oxidation pathway;chain elongation;metabolic engineering;medium-chain fatty acid;organic waste;synthetic consortia;Co-culture123|62|0更新时间：2026-07-01
- 摘要：The compositional diversity and complex interaction networks of natural microbial communities, together with their dynamic regulation by environmental and host conditions, make it difficult to achieve predictable, targeted control and engineered utilization of naturally formed microbiomes. Synthetic microbial communities, also known as SynComs, are assembled according to defined design principles and possess clearly characterized microbial compositions and functional traits. They can be applied to integrated environmental pollution remediation and agricultural productivity enhancement, and can also serve as controllable experimental systems for elucidating ecological rules and emergent functions. With the continuous increase in culturable microbial strain resources, the expansion of strain resource banks, and the deepening understanding of strain functions and traits, a central task and key challenge for the standardization and engineering application of synthetic microbial communities is how to effectively utilize these valuable microbial strain resources. Specifically, it is necessary to quantitatively identify key interactions within candidate strain sets and achieve rational assembly, so that community-level functional outputs and ecological stability can be predictably balanced. Here, we propose a strain-resource-bank-driven framework for identifying interactions and assembling communities. This framework is based on systematic strain resource banks and standardized metadata, takes quantitative characterization of microbial interactions as the core basis for assembly rules, and incorporates an iterative design-build-test-learn, or DBTL, workflow to optimize the trade-off between community function and stability. In this way, it supports rapid adaptation to personalized application scenarios. Meanwhile, the establishment of shared infrastructure platforms integrating strains, data, and methods will promote resource interoperability and the accumulation of quantitative evidence, enhance the comparability of results across laboratories, and provide foundational support for biosafety assessment and large-scale translation. Oriented toward application needs such as pollution remediation and soil health improvement, this framework aims to advance synthetic microbial communities from empirical trial-and-error approaches toward predictable, rational design based on quantitative evidence.关键词：synthetic microbial communities;strain resource biobank;interaction characterization;community assembly;design-build-test-learn;colonization662|81|0更新时间：2026-06-26
- 摘要：Environmental pollution is becoming increasingly complex, driven by the coexistence of conventional pollutants and emerging contaminants, posing significant risks to ecosystems and human health. Accurate, real-time, and in situ detection of these pollutants is essential for effective environmental governance and early risk warning. Traditional analytical techniques, represented by high-performance liquid chromatography and mass spectrometry, deliver high sensitivity and accuracy but are inherently limited by exorbitant instrumentation costs, labor-intensive and time-consuming sample pretreatment protocols, dependence on highly skilled personnel, and inability to perform continuous in-field monitoring, making them unsuitable for large-scale environmental surveillance. Conventional biosensors are portable but often suffer from limited specificity, poor resistance to matrix interference, narrow detection ranges, and low sensitivity, which restrict their performance in complex environmental settings. Synthetic biology provides a transformative framework for biosensor design, enabling engineered, modular, and programmable systems that go beyond naturally occurring sensing mechanisms. Specifically, rationally engineered recognition elements (e.g., transcription factors, aptamers, riboswitches, and receptor proteins) exhibit ultra-high target specificity and minimal cross-reactivity, significantly mitigating non-specific binding and matrix interference effects. Diverse tunable signal amplification strategies, including transcriptional cascades, protease cascades, and CRISPR-Cas-based isothermal amplification, have enhanced detection sensitivity by 3–6 orders of magnitude, achieving pM to fM level detection limits for trace contaminants and extending dynamic detection ranges to cover environmentally relevant concentration gradients. Standardized modular component design enables rapid assembly and reconfiguration of biosensors for diverse targets, while genetic logic circuits (AND, OR, NOT gates) enable simultaneous quantitative detection and logical discrimination of multiple pollutants, breaking through the single-analyte limitation of conventional systems. The integration of synthetic biosensors with artificial intelligence (AI) and Internet of Things (IoT) technologies enables intelligent sensing platforms for automated signal acquisition, real-time data analysis, and remote early warning, supporting continuous environmental monitoring. This review summarizes the three-module architecture of synthetic biosensors, including target sensing, signal transduction, and signal output, along with their key functional components. Three major system formats are also discussed: whole-cell, cell-free, and synthetic gene circuit–based biosensors. Recent advances and representative applications in the detection of heavy metals, organic pollutants, antibiotics, endocrine-disrupting chemicals, and microplastics are comprehensively summarized. Emerging trends, including multi-analyte detection enabled by genetic logic circuits and the integration of biosensors with artificial intelligence and the Internet of Things for intelligent sensing, are highlighted. Key challenges—such as matrix interference in complex samples, insufficient standardization of biological components, biosafety concerns, and limitations in stability and cost—are critically discussed. Finally, future perspectives are proposed, focusing on component engineering, system integration, intelligent detection, application-oriented design, and enhanced safety control, aiming to facilitate the practical deployment of synthetic biosensors in environmental monitoring and early warning systems.关键词：synthetic biology;biosensors;Pollutants;Environmental detection;Whole-cell biosensor;Cell-free biosensor90|34|0更新时间：2026-06-23
- 摘要：Global environmental pollution is currently a multifaceted challenge, exacerbated by the persistence of legacy pollutants and the growing threat of emerging contaminants. These substances originate primarily from anthropogenic activities and can accumulate in ecosystems through atmospheric deposition, aquatic transport, and biomagnification, ultimately leading to widespread systemic toxicity. Rapid, in situ, and precise pollution detection is essential for assessing ecological risks and formulating effective remediation strategies. However, traditional analytical methods, such as chromatography and mass spectrometry, remain challenging to apply to on-site testing and large-scale screening due to expensive equipment, labor-intensive sample preparation, and delayed readouts. Synthetic biology-enabled biosensors offer a reliable approach to environmental monitoring. These biosensors integrate genetic circuit design, protein engineering, and functional module assembly to specifically detect pollutants and convert concentration information into quantifiable physicochemical signals, providing improved detection efficiency, operational simplicity, and cost-effectiveness. By decoupling recognition, transduction, and output modules, these platforms can be tailored to different targets, sample matrices, and deployment scenarios while retaining a clear design logic. Crucially, these platforms are compatible with portable devices, supporting rapid field deployment, continuous in situ monitoring, and high-throughput analysis of environmental samples. In this review, we categorize the main types of synthetic biosensors and elucidate their core signal recognition and transduction mechanisms. We highlight recent advances in the use of these biosensors for detecting heavy metals, inorganic non-metal pollutants, organic compounds, and pathogenic microorganisms. Furthermore, we explore the application value of these platforms in tracking dynamic environmental pollution processes, including biodegradation kinetics, spatial distribution, cross-media migration, toxicological effects, and intelligent targeted bioremediation. We then discuss the advantages, challenges, and future directions of synthetic biosensors in environmental analysis, focusing on recognition element customization, process-level monitoring, field system integration, biosafety, and intelligent data interpretation. These advances may help synthetic biosensors move beyond single-target detection and support integrated environmental risk sensing, early warning, and remediation assessment.关键词：synthetic biology;biosensor;sensing mechanisms;environmental pollutants;environment monitoring73|37|0更新时间：2026-06-23
- 摘要：Toxic metal cadmium (Cd) pollution poses a serious threat to ecological environments and human health, and efficient, green bioremediation technologies are therefore urgently needed. The construction of efficient cadmium biomineralization systems via synthetic biology is regarded as an important direction for future Cd remediation. Tetrahymena thermophila can be easily cultured, its genetic manipulation is well-established, and it is naturally endowed with the capacities for Cd sensing, accumulation, and conversion. Cd2+ can be efficiently removed from water, accumulated intracellularly, and converted into less toxic CdS. Consequently, T. thermophila can be used as a synthetic biology chassis for the construction of "Cd-conversion" cell strains. To construct a high‑efficiency cadmium biomineralization system based on this chassis, the functions and efficiencies of its key genes involved in cadmium mineralization must first be evaluated, after which rational design can be conducted accordingly. In this study, the functions of three key genes involved in Cd2+ conversion during Cd2+ removal and transformation by T. thermophila were examined, namely MTT1 encoding the cadmium-binding protein metallothionein, TtCSA1 encoding cysteine synthase (a key enzyme in the de novo cysteine biosynthesis pathway), and TtCBS1 encoding cystathionine-β-synthase (a key enzyme in the reverse transsulfuration pathway). The results showed that although the Cd2+ tolerance (EC50) of the cells was reduced by 74.8% by MTT1 knockdown, the Cd2+ removal rate and conversion rate were significantly enhanced (reaching as high as 98.7% and 88.1%, respectively, at 5 mg/L Cd2+). The reason may be that after the binding of MTT1 protein to Cd2+ is relieved, the bound Cd2+ is released and then enters the CdS conversion process as a reaction substrate. Cd2+ removal was not affected by knockdown or knockout of TtCBS1 and TtCSA1, but CdS conversion efficiency was significantly decreased, with a greater reduction being observed for TtCBS1 (13.8%) than for TtCSA1 (5.4%) relative to the wild type. Based on these findings, the MTT1 coding region was replaced with TtCBS1 or TtCSA1 via homologous recombination, so that endogenous MTT1 was knocked down while overexpression of TtCBS1 or TtCSA1 was concurrently achieved, and "Cd-conversion" cell strains based on the T. thermophila synthetic biology chassis were constructed. Among them, the EC50 of the MTT1 knockdown combined with TtCBS1 overexpression strain was increased by 252.6% compared with the MTT1 knockdown strain, and a conversion rate of up to 91.6% could be reached at 5 mg/L Cd2+. Through a single genetic modification, Cd2+ sensing response, substrate release, and conversion enhancement were simultaneously achieved by this design, and a cell strain with high efficiency in removing and converting Cd2+ from water was ultimately obtained. The feasibility of T. thermophila as a programmable chassis for toxic metal remediation is validated in this study, and a new strategy for synthetic biology-driven environmental bioremediation is provided.关键词：Tetrahymena thermophila;cadmium;biomineralization;synthetic biology;chassis cell58|12|0更新时间：2026-06-22
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