Biotechnology advances最新文献_第5页

Morphological regulation of filamentous fungi improves industrial production 丝状真菌的形态调控促进了工业生产

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-12-27 DOI: 10.1016/j.biotechadv.2025.108793

Qinghua Li , Chen Zhang , Jingwen Zhou , Zhaofeng Li , Guocheng Du , Jian Chen , Guoqiang Zhang

{"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":"2026-03-01","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}

引用次数: 0

The key role that cellulose accessibility plays in restricting enzyme-mediated hydrolysis of cellulose 纤维素可及性在限制酶介导的纤维素水解中起关键作用

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-12-14 DOI: 10.1016/j.biotechadv.2025.108780

Jie Wu , Tianjie Ao , Yufeng Yuan , Zhangmin Wan , Richard Chandra , Jack Saddler

{"title":"The key role that cellulose accessibility plays in restricting enzyme-mediated hydrolysis of cellulose","authors":"Jie Wu , Tianjie Ao , Yufeng Yuan , Zhangmin Wan , Richard Chandra , Jack Saddler","doi":"10.1016/j.biotechadv.2025.108780","DOIUrl":"10.1016/j.biotechadv.2025.108780","url":null,"abstract":"<div><div>Although cellulose can be found in nature in an unassociated form (e.g., cotton, microbially derived cellulose, etc.), it is typically associated with other polymers such as lignin and hemicellulose. However, even “pure” cellulose has proven difficult to hydrolyze, primarily due to the lack of enzyme accessibility to the glycan chains. Thus, typically, much higher protein/enzyme concentrations and longer incubation times are needed as compared to hydrolyzing starch, a related glucose polymer. The “crystalline” structure of most of the cellulose and its close association with other lignocellulosic components (e.g., lignin, etc.) restrict the enzyme accessibility of the cellulase enzyme “cocktail”. Consequently, some form of pretreatment plus the addition of accessory enzymes are typically needed to enhance cellulose hydrolysis. Although biomass-derived sugars can be readily detected and quantified, assessing cellulose accessibility by methods such as pore-volume, Simon's stain, cellulose binding domain (CBM) adsorption, etc., has proven problematic. Effective pretreatment, which maximizes the recovery of biomass components and increases cellulose accessibility, is typically required to achieve high glucose yields from biomass feedstocks. In addition, an optimized “cellulase cocktail,” which further improves accessibility and is more resistant to factors such as end-product inhibition, is usually necessary to reach efficient hydrolysis. The influence of these and other issues are discussed below.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108780"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753507","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}

引用次数: 0

Computational methods for spatial multi-omics integration 空间多组学集成的计算方法

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2026-01-19 DOI: 10.1016/j.biotechadv.2026.108807

Aoyun Geng , Chunyan Cui , Zhenjie Luo , Junlin Xu , Yajie Meng , Feifei Cui , Leyi Wei , Quan Zou , Zilong Zhang

{"title":"Computational methods for spatial multi-omics integration","authors":"Aoyun Geng , Chunyan Cui , Zhenjie Luo , Junlin Xu , Yajie Meng , Feifei Cui , Leyi Wei , Quan Zou , Zilong Zhang","doi":"10.1016/j.biotechadv.2026.108807","DOIUrl":"10.1016/j.biotechadv.2026.108807","url":null,"abstract":"<div><div>The rapid development of spatial multi-omics technologies has enabled the simultaneous acquisition of transcriptomic, proteomic, and epigenomic information from the same tissue section. However, substantial differences in distributional properties, data dimensionality, and noise levels across modalities, together with the inherent sparsity and incompleteness of spatial information, pose major challenges for data integration and modeling. In recent years, deep learning–based spatial multi-omics integration algorithms have emerged rapidly, offering new approaches for constructing unified latent representations and achieving cross-modal fusion. In this review, we systematically summarize existing spatial multi-omics integration methods for the first time, categorizing and comparing them from two perspectives. We not only systematically surveyed the datasets employed by these methods, but also highlighted the key downstream analytical tasks they support, and further summarized the major challenges currently faced in spatial multi-omics integration research. Furthermore, we compare the strengths and limitations of different approaches to assist researchers in selecting appropriate methods more efficiently, thereby advancing the application of spatial multi-omics in uncovering multilayer regulatory mechanisms of tissue microenvironments and disease processes.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108807"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146000872","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}

引用次数: 0

Methane conversion into methanol by biotechnological processes: Challenges and perspectives 甲烷转化为甲醇的生物技术过程：挑战和前景

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2026-01-02 DOI: 10.1016/j.biotechadv.2026.108795

Héloïse Baldo , Stéphane Sauvagère , Christian Siatka , Laurence Soussan

{"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":"2026-03-01","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}

引用次数: 0

Decoding polyphenol–protein interactions with deep learning: From molecular mechanisms to food applications 用深度学习解码多酚-蛋白质相互作用：从分子机制到食品应用。

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2026-01-14 DOI: 10.1016/j.biotechadv.2026.108803

Qiang Liu , Tiantian Wang , Binbin Nian , Feiyang Ma , Siqi Zhao , Andrés F. Vásquez , Liping Guo , Chao Ding , Mehdi D. Davari

{"title":"Decoding polyphenol–protein interactions with deep learning: From molecular mechanisms to food applications","authors":"Qiang Liu , Tiantian Wang , Binbin Nian , Feiyang Ma , Siqi Zhao , Andrés F. Vásquez , Liping Guo , Chao Ding , Mehdi D. Davari","doi":"10.1016/j.biotechadv.2026.108803","DOIUrl":"10.1016/j.biotechadv.2026.108803","url":null,"abstract":"<div><div>Polyphenols and proteins are essential biomolecules that influence food functionality and, by extension, human health. Their interactions—hereafter referred to as <em>PhPIs</em> (Polyphenol–Protein Interactions)— affect key processes such as nutrient bioavailability, antioxidant activity, and therapeutic efficacy. However, these interactions remain challenging due to the structural diversity of polyphenols and the dynamic nature of protein binding. Traditional experimental techniques like nuclear magnetic resonance (NMR) and mass spectrometry (MS), along with computational tools such as molecular docking and molecular dynamics (MD) have offered important insights but face constraints in scalability, throughput, and reproducibility. This review explores how deep learning (DL) is reshaping the study of PhPIs by enabling efficient prediction of binding sites, interaction affinities, and MD using high-dimensional bio- and cheminformatics data. While DL enhances prediction accuracy and reduces experimental redundancy, its effectiveness remains limited by data availability, quality, and representativeness—particularly in the context of natural products. We critically assess current DL frameworks for PhPIs analysis and outline future directions, including multimodal data integration, improved model generalizability, and development of domain-specific benchmark datasets. This synthesis offers guidance for researchers aiming to apply DL in unraveling structure–function relationships of polyphenols, accelerating discovery in nutritional science and therapeutic development.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108803"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145987994","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}

引用次数: 0

Geometric deep learning assists protein engineering. Opportunities and Challenges 几何深度学习有助于蛋白质工程。机遇与挑战

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-12-26 DOI: 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

{"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":"2026-03-01","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}

引用次数: 0

Microbial computing: Review and Perspectives 微生物计算：回顾与展望

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-11-27 DOI: 10.1016/j.biotechadv.2025.108766

Paul Ahavi , Audrey Le Gouellec , Jean-Loup Faulon

{"title":"Microbial computing: Review and Perspectives","authors":"Paul Ahavi , Audrey Le Gouellec , Jean-Loup Faulon","doi":"10.1016/j.biotechadv.2025.108766","DOIUrl":"10.1016/j.biotechadv.2025.108766","url":null,"abstract":"<div><div>Engineering microbial computers has been a longstanding endeavor in synthetic biology. Like other unconventional computing disciplines, the goal is to bring computation into real-world scenarios. Several potential applications in bioproduction, bioremediation, and biomedicine highlight the promise of this discipline. The first biocomputers were <em>bottom-up</em> predictable circuits that relied on a monoculture-based digital logic and were able to emulate simple logic gates. Drawing from computer theory and extending the analogy with conventional hardware has enabled the engineering of more complex circuits. However, this abstraction soon reached its limits and introduced a semantic gap, which, alongside the constraints imposed by the monoculture paradigm, led to significant scalability limitations such as metabolic burden, orthogonality issues and noisy expression. This review outlines the strategies developed to overcome these issues and engineer more complex biodevices: (i) mitigation strategies that focus on the optimization of the circuits, (ii) multicellular computing that distributes the metabolic load across a consortium and (iii) the implementation of more energy-efficient computing frameworks, such as analog and neuromorphic architectures. While these <em>bottom-up</em> strategies have yielded significant progress, they remain insufficient to emulate the computational complexity of the cellular signal-processing system. In this review, we additionally introduce a new perspective on biocomputing with a <em>top-down</em> approach named reservoir computing. This framework leverages the inherent dynamical computational capabilities and functionalities of biosystems to solve more complex and diverse tasks, thus offering a promising new path for engineering the next generation of microbial computers.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108766"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609474","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}

引用次数: 0

Machine learning methods for small data and upstream bioprocessing applications: A comprehensive review 小数据和上游生物处理应用的机器学习方法：综合综述

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-11-17 DOI: 10.1016/j.biotechadv.2025.108749

Johnny Peng, Thanh Tung Khuat, Katarzyna Musial, Bogdan Gabrys

{"title":"Machine learning methods for small data and upstream bioprocessing applications: A comprehensive review","authors":"Johnny Peng, Thanh Tung Khuat, Katarzyna Musial, Bogdan Gabrys","doi":"10.1016/j.biotechadv.2025.108749","DOIUrl":"10.1016/j.biotechadv.2025.108749","url":null,"abstract":"<div><div>Data are crucial for machine learning (ML) applications, yet acquiring large datasets can be costly and timeconsuming, especially in complex, resource-intensive fields like biopharmaceuticals. A key process in this industry is upstream bioprocessing, where living cells are cultivated and optimised to produce therapeutic proteins and biologics. The intricate nature of these processes, combined with high resource demands, often limits data collection, resulting in smaller datasets. This comprehensive review explores ML methods designed to address the challenges posed by small data and classifies them into a taxonomy to guide practical applications. Furthermore, each method in the taxonomy was thoroughly analysed, with a detailed discussion of its core concepts and an evaluation of its effectiveness in tackling small data challenges, as demonstrated by application results in the upstream bioprocessing and other related domains. By analyzing how these methods tackle small data challenges from different perspectives, this review provides actionable insights, identifies current research gaps, and offers guidance for leveraging ML in data-constrained environments.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108749"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553993","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}

引用次数: 0

Harnessing spatial transcriptomics to understand host-parasite interactions in plants and animals 利用空间转录组学来了解植物和动物中宿主-寄生虫的相互作用

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-11-17 DOI: 10.1016/j.biotechadv.2025.108760

Anna Pijnacker , Christine W. Bruggeman , Hendrik C. Korswagen , Geert Smant , José L. Lozano-Torres

{"title":"Harnessing spatial transcriptomics to understand host-parasite interactions in plants and animals","authors":"Anna Pijnacker , Christine W. Bruggeman , Hendrik C. Korswagen , Geert Smant , José L. Lozano-Torres","doi":"10.1016/j.biotechadv.2025.108760","DOIUrl":"10.1016/j.biotechadv.2025.108760","url":null,"abstract":"<div><div>Obligate parasites pose a significant threat to animal, human, and plant health by affecting host gene expression through mechanisms that are poorly understood. Spatial transcriptomic technologies are revolutionizing our understanding of animal-parasite interactions, revealing tissue reorganization, cellular responses, and infection dynamics at a microscopic scale. These technologies also accelerate the identification of potential targets for treating animal parasite infections. Despite their potential, the application of spatial transcriptomic technologies to plant-parasite interactions is limited. This review highlights key challenges in applying spatial transcriptomics to plants. By drawing parallels with advances in animal systems, we discuss how spatial transcriptomics could contribute to localize and identify effectors, uncover the molecular mechanisms of plant-parasite infections, and find novel disease control targets. This cross-disciplinary perspective provides a roadmap for future research in plant and animal parasitology.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108760"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145554002","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}

引用次数: 0

Viral clearance in biopharmaceutical manufacturing: Current strategies, challenges, and future directions 生物制药生产中的病毒清除：当前策略、挑战和未来方向

IF 12.5 1区工程技术

Biotechnology advances Pub Date : 2026-03-01 Epub Date: 2025-12-23 DOI: 10.1016/j.biotechadv.2025.108784

Dhruvkumar Hariharbhai Soni , V. Reghellin , G. Sbarufatti , P. Minghetti , A. Altomare

{"title":"Viral clearance in biopharmaceutical manufacturing: Current strategies, challenges, and future directions","authors":"Dhruvkumar Hariharbhai Soni , V. Reghellin , G. Sbarufatti , P. Minghetti , A. Altomare","doi":"10.1016/j.biotechadv.2025.108784","DOIUrl":"10.1016/j.biotechadv.2025.108784","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":8946,"journal":{"name":"Biotechnology advances","volume":"87 ","pages":"Article 108784"},"PeriodicalIF":12.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822889","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}

引用次数: 0