Current opinion in biotechnology最新文献

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Resource allocation models: theory and applications in microbial biotechnology 资源配置模型：微生物生物技术的理论与应用

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-24 DOI: 10.1016/j.copbio.2025.103391

Bas Teusink , Pranas Grigaitis , Maaike Remeijer , Frank Bruggeman , Ralf Steuer

Wild-type cells allocate their limited resources to express proteins that support growth and survival in their natural environments. In contrast, biotechnology aims to maximize key performance indicators such as yield, productivity, or titer. Maximizing performance indicators, however, inevitably encounters physical, biochemical, genetic, and evolutionary constraints that create trade-offs between competing objectives. A central challenge in microbial biotechnology is therefore to align cellular behavior with production goals, which can be achieved by manipulating cultivation conditions and intracellular resource allocation strategies through targeted metabolic engineering or adaptive laboratory evolution. Resource allocation models provide a theoretical framework to understand and guide such optimization efforts. Here, we review the current state of resource allocation modeling, including tools, methods, and theoretical foundations, and discuss their current applications in microbial biotechnology.

野生型细胞将其有限的资源分配给表达在自然环境中支持生长和生存的蛋白质。相反，生物技术的目标是最大限度地提高关键性能指标，如产量、生产力或滴度。然而，最大化性能指标不可避免地会遇到物理的、生化的、遗传的和进化的限制，这些限制会在相互竞争的目标之间产生权衡。因此，微生物生物技术的核心挑战是使细胞行为与生产目标保持一致，这可以通过有针对性的代谢工程或适应性实验室进化来操纵培养条件和细胞内资源分配策略来实现。资源分配模型为理解和指导这种优化工作提供了理论框架。本文综述了资源配置建模的现状，包括工具、方法和理论基础，并讨论了它们在微生物生物技术中的应用现状。

引用次数: 0

Microfluidics meets cell-free systems: from molecular engineering to synthetic cells 微流体满足无细胞系统：从分子工程到合成细胞

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-21 DOI: 10.1016/j.copbio.2025.103384

Amogh K Baranwal, Sebastian J Maerkl

Cell-free systems have emerged as a powerful platform for protein production, characterization, and bottom-up construction of artificial cells, offering direct control over biochemical environments. However, achieving high-throughput and iterative design–build–test cycles requires advanced strategies beyond conventional methods. Microfluidic technologies address these challenges by enabling miniaturization, automation, and exceptional control over reaction conditions. The integration of cell-free systems with microfluidics has unlocked new capabilities by enabling high-throughput assays, long-lived reactions in continuous-flow systems, and the generation of liposome-based artificial cells. This review highlights recent advances at this interface, focusing on microfluidic strategies for protein characterization, gene regulatory studies, and the bottom-up construction of artificial cells exhibiting life-like functions.

无细胞系统已经成为蛋白质生产、表征和自下而上构建人工细胞的强大平台，提供对生化环境的直接控制。然而，实现高吞吐量和迭代的设计-构建-测试周期需要超越传统方法的高级策略。微流控技术通过实现小型化、自动化和对反应条件的特殊控制来解决这些挑战。无细胞系统与微流体的集成通过实现高通量分析、连续流动系统中的长寿命反应以及基于脂质体的人工细胞的生成，释放了新的功能。本文综述了该界面的最新进展，重点介绍了用于蛋白质表征、基因调控研究的微流体策略，以及具有类似生命功能的人工细胞的自下而上构建。

引用次数: 0

Resolving misconceptions and constraints in growth-coupled bioproduction 解决生长耦合生物生产中的误解和限制

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-21 DOI: 10.1016/j.copbio.2025.103388

Lena M Hümmler , Stefan Hristov , Lucas Hille , Elad Noor , Steffen N Lindner

Growth-coupled bioproduction (GCBP) is a metabolic engineering approach that introduces an obligatory dependency between metabolic activity and production, ensuring a high minimal yield and genetic stability. Here, product yield is primarily limited by pathway constraints, which can be overcome by further metabolic engineering. However, misconceptions persist in understanding GCBP among metabolic and process engineers. Contrary to misperceptions, yield is not stoichiometrically constrained by the growth-restoring enzymatic step, cell division is nonessential for production, and GCBP is compatible with multistage fermentation processes. Finally, GCBP addresses reduced production arising from genetic drift caused by population heterogeneity. Still, challenges remain: the lack of metabolic engineering tools for nonmodel organisms, limited in silico design capabilities, and the existence of uncharacterized metabolism. Nevertheless, by setting a high minimal stoichiometric yield, GCBP facilitates continuous bioproduction. Overall, integrating GCBP with metabolic engineering and improved computational design has the potential to reshape industrial biotechnology toward robust and efficient bioproduction.

生长偶联生物生产（GCBP）是一种代谢工程方法，它引入了代谢活动和生产之间的强制性依赖关系，确保了高最低产量和遗传稳定性。在这里，产物产量主要受到途径约束的限制，这可以通过进一步的代谢工程来克服。然而，代谢和工艺工程师对GCBP的理解仍然存在误解。与误解相反，产量不受生长恢复酶步骤的化学计量限制，细胞分裂对生产不是必需的，GCBP与多阶段发酵过程兼容。最后，GCBP解决了由种群异质性引起的遗传漂变导致的产量下降问题。然而，挑战仍然存在：缺乏非模式生物的代谢工程工具，有限的硅设计能力，以及存在未表征的代谢。然而，通过设定一个高的最小化学计量产量，GCBP促进了连续的生物生产。总的来说，将GCBP与代谢工程和改进的计算设计相结合，有可能重塑工业生物技术，使其朝着稳健和高效的生物生产方向发展。

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引用次数: 0

Whole-cell and cell-free biosensor-driven metabolic engineering 全细胞和无细胞生物传感器驱动的代谢工程。

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-18 DOI: 10.1016/j.copbio.2025.103385

Jiho Seok, Mark P Styczynski

Metabolic engineering employs microbial cell factories to produce high-value products from low-cost feedstocks. Designing, optimizing, and evaluating biosynthetic pathways in microbial cell factories is essential, yet these processes remain time- and labor-intensive. Biosensors help metabolic engineers address this challenge by converting target metabolite concentrations into observable outputs, enabling efficient assessment of microbial production. Whole-cell biosensors, which operate within living microorganisms, and cell-free biosensors, which function independently of cell growth using transcription–translation machinery, have contributed to microbial biosynthesis optimization through distinct approaches. This review summarizes recent advances in biosensor-driven metabolic engineering facilitated by whole-cell and cell-free biosensors.

代谢工程利用微生物细胞工厂以低成本的原料生产高价值的产品。设计、优化和评估微生物细胞工厂的生物合成途径是必不可少的，但这些过程仍然是时间和劳动密集型的。生物传感器通过将目标代谢物浓度转化为可观察的输出，帮助代谢工程师解决这一挑战，从而有效评估微生物的产生。在活的微生物中工作的全细胞生物传感器和利用转录翻译机制独立于细胞生长的无细胞生物传感器，通过不同的方法为微生物生物合成优化做出了贡献。本文综述了全细胞和无细胞生物传感器在生物传感器驱动代谢工程方面的最新进展。

引用次数: 0

Engineering metabolism of Saccharomyces cerevisiae for production of chemicals 用于化工生产的酿酒酵母菌工程代谢。

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-18 DOI: 10.1016/j.copbio.2025.103387

Yi Yu , Xiaoying Fu , Jinmiao Hu , Jens Nielsen , Shuobo Shi

The sustainable production of chemicals from renewable, nonedible biomass has become crucial to address environmental challenges like climate change and resource depletion caused by fossil resource dependence. Saccharomyces cerevisiae has emerged as a versatile microbial chassis for industrial bioproduction of chemicals, with engineered breakthroughs in central carbon metabolism, lipid metabolism, and terpenoid metabolism. This review examines three transformative paradigms: (1) optimizing metabolic flux and redirecting yeast pathways for chemical biosynthesis (e.g. farnesene), (2) enhancing yeast robustness to improve biomass and biochemical production under fermentation stresses (e.g. succinic acid), and (3) expanding feedstock flexibility through engineered substrate assimilation (e.g. ethanol). These examples pave the way for producing sustainable chemicals. We also discuss future challenges and propose AI (Artificial Intelligence)-driven design tools, CRISPR-based genome editing, and integrated biological-chemical hybrid processes as next-generation solutions to advance a yeast-mediated circular bioeconomy.

从可再生、不可食用的生物质中可持续生产化学品，对于应对气候变化和化石资源依赖造成的资源枯竭等环境挑战至关重要。酿酒酵母菌已成为化学工业生物生产的多功能微生物基础，在中心碳代谢、脂质代谢和萜类代谢方面取得了工程突破。本文综述了三种变革范式：(1)优化代谢通量和重定向酵母化学生物合成途径（如法尼烯），(2)增强酵母稳健性以提高发酵应激下的生物量和生化产量（如琥珀酸），以及(3)通过工程底物吸收扩大原料灵活性（如乙醇）。这些例子为生产可持续化学品铺平了道路。我们还讨论了未来的挑战，并提出了AI（人工智能）驱动的设计工具，基于crispr的基因组编辑和集成的生物化学混合过程作为推进酵母介导的循环生物经济的下一代解决方案。

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Biochemical surface patterning in microfluidic devices 微流体装置中的生化表面图像化

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-15 DOI: 10.1016/j.copbio.2025.103390

Kate Collins , Claire E Stanley , Thomas E Ouldridge

The capacity to pattern biomolecules within microfluidic devices expands the scope of microfluidic technologies. In such patterned systems, surface-bound components remain localized, while the microfluidic network supplies reagents and removes waste products. This approach has enabled continuous protein expression from patterned DNA, chemical synthesis from immobilized enzymes, and cell capture assays. Here, we review methods to pattern surfaces within microfluidic devices. Patterns may be printed before or after the device is assembled; pre-bonding methods are compatible with well-established open-surface patterning protocols but present challenges for device bonding and alignment. Conversely, post-bonding methods are compatible with standard bonding procedures but rely on less established, sequential patterning protocols. Future progress will require consistent reporting of pattern signal and noise relative to controls.

在微流控装置中对生物分子进行模式化的能力扩大了微流控技术的范围。在这种模式系统中，表面结合的组分保持局部定位，而微流控网络提供试剂并去除废物。这种方法已经实现了连续的蛋白质表达，从固定酶的化学合成，和细胞捕获测定。在这里，我们回顾了在微流体装置中对表面进行图案设计的方法。图案可以在设备组装之前或之后打印；预键合方法与成熟的开放表面图形协议兼容，但对器件键合和对准提出了挑战。相反，后键合方法与标准键合程序兼容，但依赖于较少建立的顺序模式协议。未来的进展将需要一致地报告模式信号和相对于控制的噪声。

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Controlled protein synthesis and spatial organisation in microfluidic environments 微流体环境中受控的蛋白质合成和空间组织

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-14 DOI: 10.1016/j.copbio.2025.103389

Aukse Gaizauskaite , Emma E. Crean , Imre Banlaki , Jan L. Kalkowski , Henrike Niederholtmeyer

Performing cell-free expression (CFE) in tailored microfluidic environments is a powerful tool to investigate the organisation of biosystems from molecular to multicellular scales. While cell-free transcription–translation systems simplify and open up cellular biochemistry for manipulation, microfluidics enables miniaturisation and precise control over geometries and reaction conditions. In this review, we highlight the benefits of combining microfluidics with CFE reactions for the study and engineering of molecular functions and the construction of life-like systems from nonliving components. By defining spatial organisation at different scales and sustaining nonequilibrium conditions, microfluidic environments play a key role in the quest to ‘boot up’ the biochemistry of life.

在定制的微流体环境中进行无细胞表达（CFE）是研究从分子到多细胞尺度生物系统组织的有力工具。而无细胞转录翻译系统简化和打开细胞生物化学操作，微流体使小型化和精确控制几何形状和反应条件。在这篇综述中，我们强调了将微流体与CFE反应相结合在分子功能研究和工程以及由非生物成分构建类生命系统方面的好处。通过定义不同尺度的空间组织和维持非平衡条件，微流体环境在寻求“启动”生命的生物化学过程中发挥了关键作用。

引用次数: 0

Building trust in automated experimentation: uncertainty quantification in the era of high-throughput biolabs 在自动化实验中建立信任：高通量生物实验室时代的不确定度量化。

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-13 DOI: 10.1016/j.copbio.2025.103382

Wolfgang Wiechert , Laura M Helleckes , Katharina Nöh

Uncertainty quantification (UQ) is central to data analytics, particularly in the life sciences, where experiments are often affected by significant measurement noise. In emerging automated high-throughput biolabs, such as biofoundries, parallel cultivation systems, and smart analytics platforms, UQ should be a built-in feature rather than an optional add-on. These environments pose a unique challenge: robotic liquid handling must be combined with miniaturized biochemical analytics (including omics), process monitoring, online data analytics, and digital control. Although traditional UQ methods from classical and computational statistics remain valid and applicable, integrating them into highly parallelized experimental and digital workflows presents new challenges. These include data preprocessing, model-based data integration, decision-making, and experimental control. In this review, we examine the emerging demands on UQ in automated experimentation and survey recent frameworks, strategies, and computational tools designed to address them.

不确定度量化（UQ）是数据分析的核心，特别是在生命科学中，实验经常受到显著测量噪声的影响。在新兴的自动化高通量生物实验室中，如生物铸造厂、并行培养系统和智能分析平台，UQ应该是一个内置功能，而不是一个可选的附加功能。这些环境带来了独特的挑战：机器人液体处理必须与小型化生化分析（包括组学）、过程监控、在线数据分析和数字控制相结合。尽管传统的经典统计和计算统计方法仍然有效和适用，但将它们集成到高度并行的实验和数字工作流程中提出了新的挑战。这包括数据预处理、基于模型的数据集成、决策和实验控制。在这篇综述中，我们研究了自动化实验中对UQ的新需求，并调查了为解决这些需求而设计的最新框架、策略和计算工具。

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Recent advances in AI-enabled automation of DNA assembly in biofoundries 生物铸造厂中基于人工智能的DNA组装自动化的最新进展

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-07 DOI: 10.1016/j.copbio.2025.103386

Ji Hun Kim , Jae Heon Kim , Seong Do Kim , Haseong Kim , Byung-Kwan Cho

Biofoundries are transforming synthetic biology, with the DNA assembly workflow being critical for successful biofoundry operation. This review examines recent advances in automated DNA assembly strategies for biofoundry, focusing on three key perspectives. First, we discuss emerging platforms ranging from high-throughput and highly efficient systems to affordable and accessible solutions. Second, we explore how standardized design tools enable seamless interoperability across diverse biofoundries, facilitating protocol sharing and reproducibility. Third, we analyze the integration of machine learning into assembly workflows, in which AI-driven systems dynamically optimize protocols, diagnose failures, and close the DBTL loop through real-time learning. These convergent advances are establishing a new paradigm in which experiments continuously improve through iteration, promising to accelerate both fundamental research and industrial applications.

生物铸造厂正在改变合成生物学，DNA组装工作流程是成功的生物铸造厂操作的关键。本文综述了生物铸造厂自动化DNA组装策略的最新进展，重点介绍了三个关键观点。首先，我们讨论了新兴平台，从高吞吐量和高效率的系统到经济实惠的解决方案。其次，我们探讨了标准化设计工具如何实现跨不同生物铸造厂的无缝互操作性，促进协议共享和可重复性。第三，我们分析了机器学习与装配工作流程的集成，其中人工智能驱动的系统通过实时学习动态优化协议、诊断故障并关闭DBTL循环。这些融合的进步正在建立一种新的范式，在这种范式中，实验通过迭代不断改进，有望加速基础研究和工业应用。

引用次数: 0

Molecular methods for high-throughput, multiplexed, and automated genome editing in prokaryotes and eukaryotes 原核生物和真核生物高通量、多路复用和自动化基因组编辑的分子方法

IF 7 2区工程技术 Q1 BIOCHEMICAL RESEARCH METHODS

Current opinion in biotechnology

Pub Date : 2025-11-07 DOI: 10.1016/j.copbio.2025.103381

Dominic Kösters , Jan Marienhagen

Novel approaches to genome engineering are crucial to rapidly advance the capabilities of strain engineering and synthetic biology. With ongoing developments in DNA editing techniques, researchers have begun to engineer organisms at higher throughput and can now perform multiple genome modifications simultaneously. As laboratory automation becomes more accessible, workflows are being transferred to robot-assisted platforms, enabling large-scale and highly parallelized genome editing campaigns. These platforms play a key role in fully utilizing the potential of modern molecular biology tools. Here, we review recent developments in technologies for high-throughput, multiplexed, and automated strain engineering in prokaryotic and eukaryotic organisms.

基因组工程的新方法对于快速提高菌株工程和合成生物学的能力至关重要。随着DNA编辑技术的不断发展，研究人员已经开始以更高的通量设计生物体，现在可以同时进行多个基因组修改。随着实验室自动化变得越来越容易，工作流程正在转移到机器人辅助平台，从而实现大规模和高度并行的基因组编辑活动。这些平台在充分利用现代分子生物学工具的潜力方面发挥着关键作用。在这里，我们回顾了在原核和真核生物中高通量、多路复用和自动化菌株工程技术的最新进展。

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Current opinion in biotechnology

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