Methane is one of the most prominent greenhouse gases contributing to global warming. It is also a valuable source of energy and a raw material for the production of chemicals. Gas-to-liquid technologies for its conversion into methanol are particularly interesting, methanol being considered as a platform molecule for the chemical industry and a prospective fuel for low-emission transport. Methane oxidation into methanol is up to day carried out industrially under energy-consuming conditions, associated to significant CO2 emissions. Methanotrophic catalysis has arisen as a promising greener alternative since methanotrophs are naturally-occurring microorganisms (bacteria and archaea) able to uptake methane under mild conditions. Methanotrophic bacteria express the Methane MonoOxygenase (MMO) enzyme, able to selectively hydroxylate methane. However, their large-scale implementation is currently hindered by both biological and process constraints. This review summarizes recent developments in bioprocesses for methanol production from methane, including methanotroph-based ones. Whole-cell methanotrophs, cell-free (enzymatic) processes and MMO heterologous expression have been covered.
{"title":"Methane conversion into methanol by biotechnological processes: Challenges and perspectives","authors":"Héloïse Baldo , Stéphane Sauvagère , Christian Siatka , Laurence Soussan","doi":"10.1016/j.biotechadv.2026.108795","DOIUrl":"10.1016/j.biotechadv.2026.108795","url":null,"abstract":"<div><div>Methane is one of the most prominent greenhouse gases contributing to global warming. It is also a valuable source of energy and a raw material for the production of chemicals. Gas-to-liquid technologies for its conversion into methanol are particularly interesting, methanol being considered as a platform molecule for the chemical industry and a prospective fuel for low-emission transport. Methane oxidation into methanol is up to day carried out industrially under energy-consuming conditions, associated to significant CO<sub>2</sub> emissions. Methanotrophic catalysis has arisen as a promising greener alternative since methanotrophs are naturally-occurring microorganisms (bacteria and archaea) able to uptake methane under mild conditions. Methanotrophic bacteria express the Methane MonoOxygenase (MMO) enzyme, able to selectively hydroxylate methane. However, their large-scale implementation is currently hindered by both biological and process constraints. This review summarizes recent developments in bioprocesses for methanol production from methane, including methanotroph-based ones. Whole-cell methanotrophs, cell-free (enzymatic) processes and MMO heterologous expression have been covered.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108795"},"PeriodicalIF":12.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894427","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}
Pub Date : 2025-12-29DOI: 10.1016/j.biotechadv.2025.108792
Peng-Cheng Hu , La-Mei Ding , Qiao-Qin Zhao , Mao-Cheng Tang , Pei-Fang Xiao , Chong Wang , Xiang-Yang Lu , Yun Tian , Hu-Hu Liu
Squalene, as a natural triterpenoid exhibiting various physiological activities, is primarily extracted from shark liver oil. However, due to the declining shark populations and conservation concerns, the alternative methods for squalene production are needed. Synthetic biology offers the strategies for engineered yeasts capable of producing squalene. Although the extensive studies have been performed on squalene production by the engineered yeasts, a comprehensive systematic review summarizing these efforts is lack ing. Herein, firstly, this review describes the characteristics of the squalene biosynthesis pathway in yeast cells. Secondly, metabolic strategies for enhancing squalene production in yeasts are summarized. Thirdly, the advanced genetic engineering tools to boost squalene and other terpenoids production are investigated. Fourthly, the potential of emerging other yeasts for squalene synthesis is explored. Finally, the potential technologies applied in yeasts for improving squalene production are discussed. This review will provide comprehensive information on yeasts as chassis for squalene production, laying the foundation for squalene production in yeasts.
{"title":"A review on squalene production by engineered yeasts: Current advances and perspectives","authors":"Peng-Cheng Hu , La-Mei Ding , Qiao-Qin Zhao , Mao-Cheng Tang , Pei-Fang Xiao , Chong Wang , Xiang-Yang Lu , Yun Tian , Hu-Hu Liu","doi":"10.1016/j.biotechadv.2025.108792","DOIUrl":"10.1016/j.biotechadv.2025.108792","url":null,"abstract":"<div><div>Squalene, as a natural triterpenoid exhibiting various physiological activities, is primarily extracted from shark liver oil. However, due to the declining shark populations and conservation concerns, the alternative methods for squalene production are needed. Synthetic biology offers the strategies for engineered yeasts capable of producing squalene. Although the extensive studies have been performed on squalene production by the engineered yeasts, a comprehensive systematic review summarizing these efforts is lack ing. Herein, firstly, this review describes the characteristics of the squalene biosynthesis pathway in yeast cells. Secondly, metabolic strategies for enhancing squalene production in yeasts are summarized. Thirdly, the advanced genetic engineering tools to boost squalene and other terpenoids production are investigated. Fourthly, the potential of emerging other yeasts for squalene synthesis is explored. Finally, the potential technologies applied in yeasts for improving squalene production are discussed. This review will provide comprehensive information on yeasts as chassis for squalene production, laying the foundation for squalene production in yeasts.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108792"},"PeriodicalIF":12.5,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877552","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}
Pub Date : 2025-12-29DOI: 10.1016/j.biotechadv.2025.108794
Shaoru Hu , Shenglong Wang , Ziyi Zhao , Yichen Wu , Ziyao Zheng , Xiang Ma , Jun Li , Mingfeng Cao , Hao Liu , Weixia Gao
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-N-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.
人乳寡糖（HMOs）是对婴儿营养至关重要的复合碳水化合物，其中乳-n -新四糖（LNnT）是一种关键的乙酰化成分，约占总HMOs的10. %。LNnT的合成涉及一个连续的酶促过程，该过程由β-1,3- n -乙酰氨基葡萄糖转移酶（β3GNT）和β-1,4-半乳糖转移酶（β4GalT）促进，以UDP-GlcNAc和UDP-Gal为底物。本文综述了微生物LNnT生产的重大进展，重点关注两个主要领域：(1)酶工程的创新，通过计算重新设计和定向进化提高糖基转移酶的活性和特异性；(2)利用模块化途径和转运体控制优化代谢通量以平衡前体的策略。目前的挑战包括提高糖基转移酶的特异性，以减少不必要的反应和管理复杂的前体流动调节网络。利用酶设计来提高催化效率和自适应途径控制以响应代谢变化的新方法对于大规模食品添加剂生产似乎很有希望。通过将这些进步与gras认证的微生物平台相结合，未来的生物工艺可以在遵守严格的食品安全法规的同时应对经济挑战。本综述强调需要将LNnT生产从实验阶段推进到可靠的、具有成本效益的生物处理系统，以满足全球食品工业的需求。
{"title":"Metabolic engineering strategies for enhanced microbial synthesis of lacto-N-neotetraose: a key acetylated human milk oligosaccharide","authors":"Shaoru Hu , Shenglong Wang , Ziyi Zhao , Yichen Wu , Ziyao Zheng , Xiang Ma , Jun Li , Mingfeng Cao , Hao Liu , 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":"2025-12-29","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}
Pub Date : 2025-12-29DOI: 10.1016/j.biotechadv.2025.108786
Juntao Ke, Li Wan, Maiqi Chen, Yizheng Lv, Yingying Zhu, Wenli Zhang, Wanmeng Mu
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.
{"title":"Spatial engineering for biocatalytic cascade control through biomolecular compartmentalization","authors":"Juntao Ke, Li Wan, Maiqi Chen, Yizheng Lv, Yingying Zhu, Wenli Zhang, 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":"2025-12-29","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}
Pub Date : 2025-12-27DOI: 10.1016/j.biotechadv.2025.108793
Qinghua Li , Chen Zhang , Jingwen Zhou , Zhaofeng Li , Guocheng Du , Jian Chen , Guoqiang Zhang
Filamentous fungi have emerged as ideal chassis cells for high-value products such as industrial enzymes, therapeutic proteins, and antibiotics, due to their broad substrate adaptability, efficient protein secretion capacity, and well-developed post-translational modification systems. However, the morphological characteristics of filamentous fungi during submerged fermentation present a significant challenge that cannot be overlooked in the biotechnology industry. This review systematically elaborates the fundamental role of polar growth and branching in hyphal morphogenesis and discusses the crucial impact of morphological regulation on fermentation performance. Through in-depth analysis of multi-level strategies, including process-based engineering control, genetic and cell wall modification approaches, and signaling pathway-mediated precise regulation, it clarifies the synergistic mechanisms underlying different regulatory methodologies. The rapid development of technologies such as high-throughput screening, genome editing, multi-omics sequencing, and artificial intelligence has enabled their integration into a collaborative engineering framework through functional complementarity and closed-loop data integration. This system, operating through a workflow of data-driven design, precise editing verification, and intelligent optimization iteration, will significantly enhance the efficiency and precision of morphological regulation. Such technological integration not only provides a systematic theoretical framework and technical guidance for understanding regulatory mechanisms and developing novel strategies, but also promotes the evolution of industrial fermentation toward intelligent and refined processes, thereby offering new technical pathways for green biomanufacturing.
{"title":"Morphological regulation of filamentous fungi improves industrial production","authors":"Qinghua Li , Chen Zhang , Jingwen Zhou , Zhaofeng Li , Guocheng Du , Jian Chen , Guoqiang Zhang","doi":"10.1016/j.biotechadv.2025.108793","DOIUrl":"10.1016/j.biotechadv.2025.108793","url":null,"abstract":"<div><div>Filamentous fungi have emerged as ideal chassis cells for high-value products such as industrial enzymes, therapeutic proteins, and antibiotics, due to their broad substrate adaptability, efficient protein secretion capacity, and well-developed post-translational modification systems. However, the morphological characteristics of filamentous fungi during submerged fermentation present a significant challenge that cannot be overlooked in the biotechnology industry. This review systematically elaborates the fundamental role of polar growth and branching in hyphal morphogenesis and discusses the crucial impact of morphological regulation on fermentation performance. Through in-depth analysis of multi-level strategies, including process-based engineering control, genetic and cell wall modification approaches, and signaling pathway-mediated precise regulation, it clarifies the synergistic mechanisms underlying different regulatory methodologies. The rapid development of technologies such as high-throughput screening, genome editing, multi-omics sequencing, and artificial intelligence has enabled their integration into a collaborative engineering framework through functional complementarity and closed-loop data integration. This system, operating through a workflow of data-driven design, precise editing verification, and intelligent optimization iteration, will significantly enhance the efficiency and precision of morphological regulation. Such technological integration not only provides a systematic theoretical framework and technical guidance for understanding regulatory mechanisms and developing novel strategies, but also promotes the evolution of industrial fermentation toward intelligent and refined processes, thereby offering new technical pathways for green biomanufacturing.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108793"},"PeriodicalIF":12.5,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845088","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}
Pub Date : 2025-12-27DOI: 10.1016/j.biotechadv.2025.108785
Hang Chen , Ying Shi , Meiling Yuan , Huihui Li , Xiaowei Liu
Target identification is pivotal for developing novel therapeutics in cancer and other diseases. Traditional experiment screening methods are constrained by low throughput and the complexity of biological systems. Multi-omics technologies offer a transformative solution by providing comprehensive, multi-dimensional insights into molecular mechanisms. However, the exponential growth of multi-omics data necessitates efficient computational algorithms for dimensionality reduction and unravel the intricate biological processes. Artificial intelligence (AI) has emerged as a powerful tool capable of analyzing complementary multi-modal data streams. The integration of multi-omics technologies and AI algorithms has revolutionized target identification and drug discovery. This review highlights prevalent omics techniques and their role in target identification and drug discovery, outlines key machine learning (ML) classifications, and describes the integration of multi-omics with AI. We explore the applications of AI-driven multi-omics in various stages of drug discovery, including target identification, target validation, lead optimization, as well as clinical evaluation, underscoring the transformative potential of this approach. Additionally, we discuss the challenges associated with this integrative strategy and future trends in the field. As the integration of multi-omics and AI continues to expand, we anticipate a paradigm shift in target identification and drug discovery, paving the way for more precise and effective therapies.
{"title":"Integrating multi-omics and artificial intelligence fuels advanced target identification and drug discovery","authors":"Hang Chen , Ying Shi , Meiling Yuan , Huihui Li , Xiaowei Liu","doi":"10.1016/j.biotechadv.2025.108785","DOIUrl":"10.1016/j.biotechadv.2025.108785","url":null,"abstract":"<div><div>Target identification is pivotal for developing novel therapeutics in cancer and other diseases. Traditional experiment screening methods are constrained by low throughput and the complexity of biological systems. Multi-omics technologies offer a transformative solution by providing comprehensive, multi-dimensional insights into molecular mechanisms. However, the exponential growth of multi-omics data necessitates efficient computational algorithms for dimensionality reduction and unravel the intricate biological processes. Artificial intelligence (AI) has emerged as a powerful tool capable of analyzing complementary multi-modal data streams. The integration of multi-omics technologies and AI algorithms has revolutionized target identification and drug discovery. This review highlights prevalent omics techniques and their role in target identification and drug discovery, outlines key machine learning (ML) classifications, and describes the integration of multi-omics with AI. We explore the applications of AI-driven multi-omics in various stages of drug discovery, including target identification, target validation, lead optimization, as well as clinical evaluation, underscoring the transformative potential of this approach. Additionally, we discuss the challenges associated with this integrative strategy and future trends in the field. As the integration of multi-omics and AI continues to expand, we anticipate a paradigm shift in target identification and drug discovery, paving the way for more precise and effective therapies.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108785"},"PeriodicalIF":12.5,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845089","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}
Pub Date : 2025-12-26DOI: 10.1016/j.biotechadv.2025.108790
Julián García-Vinuesa , Jorge Rojas , Nicole Soto-García , Nicolás Martínez , Diego Alvarez-Saravia , Roberto Uribe-Paredes , Mehdi D. Davari , Carlos Conca , Juan A. Asenjo , David Medina-Ortiz
Protein engineering is experiencing a paradigmatic transformation through the integration of geometric deep learning (GDL) into computational design workflows. While traditional approaches such as rational design and directed evolution have achieved significant progress, they remain constrained by the vastness of sequence space and the cost of experimental validation. GDL overcomes these limitations by operating on non-Euclidean domains and by capturing the spatial, topological, and physicochemical features that govern protein function.
This perspective provides a comprehensive and critical overview of GDL applications in stability prediction, functional annotation, molecular interaction modeling, and de novo protein design. It consolidates methodological principles, architectural diversity, and performance trends across representative studies, emphasizing how GDL enhances interpretability and generalization in protein science. Aimed at both computational method developers and experimental protein engineers, the review bridges algorithmic concepts with practical design considerations, offering guidance on data representation, model selection, and evaluation strategies.
By integrating explainable artificial intelligence and structure-based validation within a unified conceptual framework, this work highlights how GDL can serve as a foundation for transparent, interpretable, and autonomous protein design. As GDL converges with generative modeling, molecular simulation, and high-throughput experimentation, it is poised to become a cornerstone technology for next-generation protein engineering and synthetic biology.
{"title":"Geometric deep learning assists protein engineering. Opportunities and Challenges","authors":"Julián García-Vinuesa , Jorge Rojas , Nicole Soto-García , Nicolás Martínez , Diego Alvarez-Saravia , Roberto Uribe-Paredes , Mehdi D. Davari , Carlos Conca , Juan A. Asenjo , David Medina-Ortiz","doi":"10.1016/j.biotechadv.2025.108790","DOIUrl":"10.1016/j.biotechadv.2025.108790","url":null,"abstract":"<div><div>Protein engineering is experiencing a paradigmatic transformation through the integration of geometric deep learning (GDL) into computational design workflows. While traditional approaches such as rational design and directed evolution have achieved significant progress, they remain constrained by the vastness of sequence space and the cost of experimental validation. GDL overcomes these limitations by operating on non-Euclidean domains and by capturing the spatial, topological, and physicochemical features that govern protein function.</div><div>This perspective provides a comprehensive and critical overview of GDL applications in stability prediction, functional annotation, molecular interaction modeling, and <em>de novo</em> protein design. It consolidates methodological principles, architectural diversity, and performance trends across representative studies, emphasizing how GDL enhances interpretability and generalization in protein science. Aimed at both computational method developers and experimental protein engineers, the review bridges algorithmic concepts with practical design considerations, offering guidance on data representation, model selection, and evaluation strategies.</div><div>By integrating explainable artificial intelligence and structure-based validation within a unified conceptual framework, this work highlights how GDL can serve as a foundation for transparent, interpretable, and autonomous protein design. As GDL converges with generative modeling, molecular simulation, and high-throughput experimentation, it is poised to become a cornerstone technology for next-generation protein engineering and synthetic biology.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108790"},"PeriodicalIF":12.5,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845092","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}
Pub Date : 2025-12-26DOI: 10.1016/j.biotechadv.2025.108789
Huan Liu , Lunjie Wu , Songyin Zhao , Yan Xu , Yao Nie
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.
{"title":"Enzyme symphony in bio-inspired multi-enzyme cascades for enhanced biosynthesis","authors":"Huan Liu , Lunjie Wu , Songyin Zhao , Yan Xu , 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":"2025-12-26","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}
Pub Date : 2025-12-26DOI: 10.1016/j.biotechadv.2025.108791
Wei Song , Duo Wang , Jinming Li , Rui Zhang
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.
{"title":"Spatial transcriptomics: integrating platforms and computational approaches for clinical insights","authors":"Wei Song , Duo Wang , Jinming Li , 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":"2025-12-26","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}
Pub Date : 2025-12-23DOI: 10.1016/j.biotechadv.2025.108784
Dhruvkumar Hariharbhai Soni , V. Reghellin , G. Sbarufatti , P. Minghetti , A. Altomare
Viral safety remains a fundamental requirement in the manufacturing of monoclonal antibodies (mAbs), particularly due to the widespread use of mammalian cell lines susceptible to both endogenous and adventitious viral contamination. This review provides a comprehensive overview of current viral clearance strategies integrated into downstream processing (DSP), highlighting the mechanisms, performance, and practical implementation of key unit operations. Chromatographic methods, including Protein A affinity, ion exchange (CEX and AEX), hydrophobic interaction (HIC), and mixed-mode chromatography (MMC), contribute to virus removal to varying extents, depending on virus type, resin chemistry, and process conditions. Anion exchange membranes have demonstrated high log reduction values (LRVs), especially for small non-enveloped viruses, while mixed-mode resins enhance removal through dual-mode interactions. Dedicated viral inactivation steps, such as low-pH incubation and detergent treatment, remain effective against enveloped viruses, with the use of stabilizing agents like arginine and extremolytes increasingly adopted to preserve product quality. Virus filtration continues to represent the most robust barrier to small viruses, though its performance depends on parameters such as filter material, fouling tendency, and viral load. Emerging solutions, such as activated carbon filtration and membrane chromatography, offer scalable, orthogonal alternatives compatible with disposable and continuous processing formats. Notably, viral clearance strategies have been successfully incorporated into continuous downstream workflows, including multicolumn capture, inline inactivation, and extended-duration filtration. Collectively, these advances support the transition toward more flexible, efficient, and sustainable viral safety frameworks, paving the way for next-generation biomanufacturing platforms.
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