Biotechnology advances最新文献

{"title":"Advances in transcription factor-based biosensors for natural product biosynthesis: Optimization, emerging technologies, and future prospects","authors":"Xiaohan Zhang ,&nbsp;Xinping Wu ,&nbsp;Hui Chen ,&nbsp;Qingsong Shao ,&nbsp;Zheng Ma ,&nbsp;Yefei Wu ,&nbsp;Shengliang Wu ,&nbsp;Lianghong Yin ,&nbsp;Nana Ding","doi":"10.1016/j.biotechadv.2025.108765","DOIUrl":"10.1016/j.biotechadv.2025.108765","url":null,"abstract":"<div><div>Natural products (NPs) are increasingly applied in food, medicine, and biotechnology. However, their biosynthesis remains constrained by low titers and yields. Transcription factor-based biosensors (TFBs) can convert biological signals into measurable outputs, enabling real-time monitoring and dynamic regulation of biosynthetic pathways, thereby facilitating the overcoming of these limitations. This review highlights recent advances in applying TFBs to NP production, with a focus on high-throughput screening, adaptive evolution, and dynamic control. We further discuss innovative engineering approaches aimed at optimizing TFB performance, including <em>in silico</em> TF identification, protein engineering, and fine-tuning of regulatory elements. Finally, we examine the challenges associated with using TFBs for microbial NP production and explore their potential in emerging platforms such as cell-free systems and non-model microorganisms. These insights offer valuable perspectives on overcoming the current limitations of biosensing technologies and advancing the scalable production of NPs.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108765"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145559758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enzyme symphony in bio-inspired multi-enzyme cascades for enhanced biosynthesis","authors":"Huan Liu ,&nbsp;Lunjie Wu ,&nbsp;Songyin Zhao ,&nbsp;Yan Xu ,&nbsp;Yao Nie","doi":"10.1016/j.biotechadv.2025.108789","DOIUrl":"10.1016/j.biotechadv.2025.108789","url":null,"abstract":"<div><div>Artificial multi-enzyme cascades utilize enzymatic catalysis to achieve continuous complex biosynthesis, thus, standing out as a promising approach. The remarkable efficiency of cascade reactions arises from the precise coordination among multiple enzymes, which facilitates efficient intermediate transfer and maximizing pathway flux. This coordination closely parallels the precise and synchronized collaboration of performers in a symphony orchestra. This review summarizes the value-added biosynthetic capabilities of multi-enzyme cascades, focusing on their ability to convert inexpensive substrates into high-value complex products. Various working forms of multi-enzyme systems are presented and primarily classified into four approaches: free enzymes, assembled complexes, fusion enzymes, and bio-based immobilized enzymes, with emphasis on the unique value of confined microenvironments as crucial platforms for achieving highly efficient cascade reactions. Furthermore, we emphasize the spatial architecture and dynamic regulation of multi-enzyme complexes, while exploring strategies for the rational design of artificial multi-enzyme assemblies tailored to cascade reaction requirements. Finally, emerging trends in AI-assisted design of cascade reactions and multi-enzyme complexes are highlighted to guide future developments.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108789"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic engineering strategies for enhanced microbial synthesis of lacto-N-neotetraose: a key acetylated human milk oligosaccharide","authors":"Shaoru Hu ,&nbsp;Shenglong Wang ,&nbsp;Ziyi Zhao ,&nbsp;Yichen Wu ,&nbsp;Ziyao Zheng ,&nbsp;Xiang Ma ,&nbsp;Jun Li ,&nbsp;Mingfeng Cao ,&nbsp;Hao Liu ,&nbsp;Weixia Gao","doi":"10.1016/j.biotechadv.2025.108794","DOIUrl":"10.1016/j.biotechadv.2025.108794","url":null,"abstract":"<div><div>Human milk oligosaccharides (HMOs) are complex carbohydrates crucial for infant nutrition, with lacto-N-neotetraose (LNnT) being a key acetylated component that makes up about 10 % of total HMOs. The synthesis of LNnT involves a sequential enzymatic process that modifies lactose, facilitated by β-1,3-<em>N</em>-acetylglucosaminyltransferase (β3GNT) and β-1,4-galactosyltransferase (β4GalT) using UDP-GlcNAc and UDP-Gal as substrates. This review highlights significant advancements in microbial LNnT production, focusing on two main areas: (1) innovations in enzyme engineering that improve glycosyltransferase activity and specificity through computational redesign and directed evolution; (2) strategies for optimizing metabolic flux to balance precursors using modular pathways and transporter controls. Ongoing challenges include enhancing glycosyltransferase specificity to reduce unwanted reactions and managing the complex regulatory networks of precursor flow. New approaches that utilize enzyme design for better catalytic efficiency and adaptive pathway control in response to metabolic changes appear promising for large-scale food additive production. By combining these advancements with GRAS-certified microbial platforms, future bioprocesses can tackle economic challenges while adhering to strict food safety regulations. This overview highlights the need to advance LNnT production from experimental stages to reliable, cost-effective bioprocessing systems that meet the needs of the global food industry.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108794"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geminivirus vectors: From gene silencing to synthetic biology","authors":"Yi Zhang ,&nbsp;Shulin Deng","doi":"10.1016/j.biotechadv.2025.108771","DOIUrl":"10.1016/j.biotechadv.2025.108771","url":null,"abstract":"<div><div>Geminiviruses, the largest plant DNA virus family, cause devastating diseases in crops worldwide. These viruses possess distinctive features, such as the stem-loop structure and replication protein (Rep), which enable the creation of functional geminiviral replicons (GVRs) in plants. Over three decades, geminiviruses have been developed into vectors for virus-induced gene silencing (VIGS), high-level protein expression, and genome editing. This review introduces the genomic structure, Rep protein domains and functions, as well as the historical applications of geminiviruses, then highlights their prominent roles in VIGS and synthetic biology. As VIGS vectors, bipartite geminiviruses utilize <em>AV1</em> gene replacement, while monopartite species rely on satellite DNAs to insert target sequences, enabling gene silencing in diverse plants. In synthetic biology, GVRs facilitate high-level protein expression through autonomous replication and enhance CRISPR/Cas genome editing efficiency in crops. Additionally, gene regulatory elements, including tissue-specific promoters and gene expression enhancement sequences from geminiviral genomes or satellite DNA expand their utility in genetic engineering. Finally, this review provides an outlook on the future development of geminivirus vectors. GVRs can work as plasmid-like DNAs for supporting diverse and creative designs in plant synthetic biology. The stem-loop structure and Rep are not unique to geminiviruses, a fact that suggests potential cross-kingdom applications of GVRs beyond plants. Vast viral resources enable further acceleration of GVR applications through resource mining and optimization. Moreover, attenuated or engineered geminiviral strains hold promise as “plant vaccines” via cross-protection. Collectively, geminivirus vectors bridge fundamental viral research with practical innovations in crop improvement, biomanufacturing, and synthetic biology.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108771"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145619677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optogenetic tools for optimizing key signalling nodes in synthetic biology","authors":"Yuehui Tian ,&nbsp;Shanshan Xu ,&nbsp;Zidong Ye,&nbsp;Huiru Liu,&nbsp;Dongqing Wei,&nbsp;Hossain M. Zabed,&nbsp;Junhua Yun,&nbsp;Guoyan Zhang,&nbsp;Yufei Zhang,&nbsp;Cheng Zhang,&nbsp;Ruiqi Liu,&nbsp;Jia Li,&nbsp;Xianghui Qi","doi":"10.1016/j.biotechadv.2025.108770","DOIUrl":"10.1016/j.biotechadv.2025.108770","url":null,"abstract":"<div><div>The modification of key enzymes for chemical production plays a crucial role in enhancing the yield of targeted products. However, manipulating key nodes in specific signalling pathways remains constrained by traditional gene overexpression or knockout strategies. Discovering and designing optogenetic tools enable us to regulate enzymatic activity or gene expression at key nodes in a spatiotemporal manner, rather than relying solely on chemical induction throughout production processes. In this review, we discuss the recent applications of optogenetic tools in the regulation of microbial metabolites, plant sciences and disease therapies. We categorize optogenetic tools into five classes based on their distinct applications. First, light-induced gene expression schedules can balance the trade-off between chemical production and cell growth phases. Second, light-triggered liquid-liquid phase separation (LLPS) modules provide opportunities to co-localize and condense key enzymes for enhancing catalytic efficiency. Third, light-induced subcellular localized photoreceptors enable the relocation of protein of interest across various subcellular compartments, allowing for the investigation of their dynamic regulatory processes. Fourth, light-regulated enzymes can dynamically regulate production of cyclic nucleotides or investigate endogenous components similar with conditional depletion or recovery function of protein of interest. Fifth, light-gated ion channels and pumps can be utilized to investigate dynamic ion signalling cascades in both animals and plants, or to boost ATP accumulation for enhancing biomass or bioproduct yields in microorganisms. Overall, this review aims to provide a comprehensive overview of optogenetic strategies that have the potential to advance both basic research and bioindustry within the field of synthetic biology.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108770"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145611805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From traditional to AI-driven: The evolution of intelligent enzyme engineering for biocatalysis","authors":"Feifei Lv ,&nbsp;Jiaxing Zhang ,&nbsp;Shengping You ,&nbsp;Wei Qi","doi":"10.1016/j.biotechadv.2025.108788","DOIUrl":"10.1016/j.biotechadv.2025.108788","url":null,"abstract":"<div><div>Enzyme engineering involves enhancing enzyme function and application through multidimensional technological systems. Its development encompasses elucidating sequence-structure-function relationships, exploring fitness landscapes, and multiscale regulation. Conventional enzyme engineering strategies include directed evolution (DE), rational/semi-rational design, residue co-evolution, and de novo design. DE mimics natural selection but is limited by high-throughput screening efficiency. Rational/semi-rational design integrates computational simulation with experimental validation to regulate enzyme performance. Residue co-evolution combines sequence co-evolution analysis and kinetic simulations, and de novo design is dedicated to achieving precise protein folding through physical modeling. In recent years, the breakthrough progress in machine learning (ML), especially deep learning (DL), has significantly enhanced the efficiency of all the above-mentioned methods; by accurately predicting mutational effects and efficiently exploring discontinuous sequence space, it provides powerful tools to improve or supplement the above strategies, thereby aiding in escaping local fitness optima traps. This review summarizes common strategies in enzyme engineering, including directed evolution, rational/semi-rational design, residue co-evolution, and de novo design, and further introduces the latest applications of ML and DL models in each of these fields. Although challenges persist, such as force field accuracy limitations, mutation sampling constraints, experimental throughput limitations, and epistatic effects, more comprehensive multimodal foundation models in the future are expected to integrate cross-scale parameters for intelligent design, and the establishment of standardized enzymology databases will enhance prediction reliability. Overall, AI-empowered enzyme engineering will drive a profound transformation toward a predictable and highly efficient pathway for enzyme design, providing more precise and powerful solutions for biocatalysis.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108788"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Membranes: The only chance for the mRNA tortoise to win, economically","authors":"Thomas G. Neuman ,&nbsp;Surya Karla ,&nbsp;James (Chip) Kilduff ,&nbsp;Joel Plawsky ,&nbsp;Georges Belfort","doi":"10.1016/j.biotechadv.2025.108774","DOIUrl":"10.1016/j.biotechadv.2025.108774","url":null,"abstract":"<div><div>The RNA revolution, advancing beyond traditional vaccines to new therapeutic modalities and constructs such as self-amplifying RNA (saRNA) and circular RNA (circRNA), continues to place increasing pressure on downstream purification. Diffusion-limited resins, the time-tested workhorse of protein purification, are fundamentally incompatible because mRNA is an enormous (&gt;40 nm) molecule with low diffusivity (10⁻¹¹–10⁻¹² m²/s). Our perspective, rooted in core chemical engineering principles, applies transport analysis and re-examines published performance data to demonstrate why even optimized perfusion chromatographic resin systems, exhibiting 0.1 % of total flow through the resin particles, cannot overcome the inherent diffusional barriers preventing efficient RNA purification. Alternatively, convection-based devices, notably membranes and monoliths, are well situated as their transport characteristics are not limited by the molecular transport properties of RNA. Ultimately, pressure-driven flow enables the potential for increased device capacity at orders of magnitude (10³x) lower process time and smaller device footprint contributing to markedly improved productivity. Taken together, these findings suggest that a paradigm shift is required toward convective membrane systems to create a platform capable of delivering scalable, economic, and ultimately industrially attractive mRNA purification.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108774"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial engineering for biocatalytic cascade control through biomolecular compartmentalization","authors":"Juntao Ke,&nbsp;Li Wan,&nbsp;Maiqi Chen,&nbsp;Yizheng Lv,&nbsp;Yingying Zhu,&nbsp;Wenli Zhang,&nbsp;Wanmeng Mu","doi":"10.1016/j.biotechadv.2025.108786","DOIUrl":"10.1016/j.biotechadv.2025.108786","url":null,"abstract":"<div><div>Spatial engineering has emerged as a transformative paradigm for orchestrating metabolic flux through biomolecular compartmentalization. In cellular systems, the cytosolic dispersion of heterologous enzymes and evolutionary-driven metabolic priorities of native pathways necessitate spatial solutions that transcend conventional enzyme engineering. Concurrently, in vitro metabolons provide critical mechanistic insights into enzymatic cascade reactions through controlled assembly. This review systematically evaluates several spatial engineering platforms for biocatalytic process control—including scaffolded compartments (liposomes, DNA origami, polymersomes, and bacterial microcompartments) and scaffoldless assemblies (membraneless organelles and coacervates)—designed to reconfigure metabolic landscapes in cellular or cell-free contexts. Through critical analysis of recent advances in model construction and functionalized applications, we establish a framework for understanding different spatial control principles governing pathway efficiency and flux redistribution. Finally, we conclude with a comprehensive assessment of current limitations in mechanistic elucidation, dynamic regulation and cross-system compatibility, while projecting future developments towards multifunctional spatial organization tools and biomimetic platforms for synthetic biology and cellular engineering.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108786"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial transcriptomics: integrating platforms and computational approaches for clinical insights","authors":"Wei Song ,&nbsp;Duo Wang ,&nbsp;Jinming Li ,&nbsp;Rui Zhang","doi":"10.1016/j.biotechadv.2025.108791","DOIUrl":"10.1016/j.biotechadv.2025.108791","url":null,"abstract":"<div><div>Spatial transcriptomics (ST) is a significant advancement in life science research, enabling transcriptome analysis to transition from traditional bulk and single-cell levels to spatial location levels, thereby expanding the boundaries of biological research and pathological diagnosis. This technological breakthrough has provided unprecedented insights into complex biological processes, disease mechanisms, and clinical diagnosis. Despite the impressive advances in the field in recent years, it still faces several challenges, including technical complexity, difficulties in data analysis, and the lack of standardization. This review provides a comprehensive comparison of the technical principles and data analysis processes of ST, while also summarizing its latest applications and the current state of standardization. It aims to provide researchers with a clear framework for understanding the progresses, challenges, and future directions, thereby promoting the further development and clinical transition of ST technologies.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108791"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peroxisome engineering in yeast: Advances, challenges, and prospects","authors":"Cuifang Ye ,&nbsp;Xiaoqian Li ,&nbsp;Tao Liu ,&nbsp;Shiyu Li ,&nbsp;Mengyu Zhang ,&nbsp;Yao Zhao ,&nbsp;Jintao Cheng ,&nbsp;Guiling Yang ,&nbsp;Peiwu Li","doi":"10.1016/j.biotechadv.2025.108747","DOIUrl":"10.1016/j.biotechadv.2025.108747","url":null,"abstract":"<div><div>Peroxisome engineering in yeast has emerged as a promising strategy for biomanufacturing, as it enables the compartmentalization of biosynthetic pathways and thus alleviates key bottlenecks in natural product biosynthesis. By sequestering specific metabolic pathways within peroxisomes, this strategy effectively reduces product cytotoxicity, enhances intracellular product storage, and allows precise redirection of metabolic fluxes. Nevertheless, its broader application remains limited by several unresolved challenges, including the insufficient understanding of peroxisomal membrane permeability, inadequate cofactor supply, and glucose-mediated repression of peroxisomal capacity. To overcome these obstacles, a range of conventional and emerging approaches—such as engineering peroxisomal targeting signal type 1 (PTS1), regulation of peroxisome proliferation, development of orthogonal artificial peroxisomal protein transport systems, and applying machine learning to predict gene overexpression for optimizing peroxisomal functional capacity—have expanded the toolkit for peroxisome engineering in yeast. This review summarizes recent advances in peroxisomal surface display engineering, peroxisomal matrix engineering, and multi-organelle spatial combination coordination, highlighting the importance of peroxisome engineering in optimizing yeast-based cell factories for natural product biosynthesis. Moreover, it critically evaluates current limitations, along with a comprehensive discussion of both conventional and emerging approaches aimed at further optimizing peroxisome engineering. In the future, integrating peroxisome engineering with advanced machine learning will be crucial for addressing remaining challenges and fully realizing the potential of sustainable and scalable yeast-based biomanufacturing.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"86 ","pages":"Article 108747"},"PeriodicalIF":12.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145423995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}