BIOTECHNOLOGY ADVANCES生物技术进展
BIOTECHNOLOGY ADVANCES(英文缩写 BIOTECHNOL ADV),ISSN 0734-9750,eISSN 1873-1899,中文译名:生物技术进展 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-27 至 2026-09-27，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 17.681 | Q1 |
| 2022 | 16.000 | Q1 |
| 2023 | 12.100 | Q1 |
| 2024 | 12.500 | Q1 |
| 2025 | 14.100 | Q1 |
BIOTECHNOLOGY ADVANCES 最新收录文献
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1. Site-specific recombinases and their essential role in synthetic biology.
PMID:日期:2026-11-01Site-specific recombinases, enzymes that bind to specific DNA attachment sites and catalyze DNA rearrangement reactions resulting in permanent and heritable genetic modifications, have emerged as powerful tools in synthetic biology. Their broad applications in genome engineering, genetic circuit design, DNA assembly, and computational design have significantly advanced the field over the past decades. To provide a systematic overview of both fundamental concepts and recent progress, this review comprehensively summarizes site-specific recombinases across enzyme categories, structural mechanisms, key characteristics of individual recombinases, recombination models, engineering strategies, and diverse functional applications. We anticipate that continued discovery, characterization, and engineering of site-specific recombinases will further accelerate the development of synthetic biology and support the establishment of more robust, versatile, and practical genetic toolboxes for future applications.
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2. Harnessing machine learning to decode and optimize bioelectrochemical systems: Principles, progress and future directions.
PMID:日期:2026-11-01Bioelectrochemical systems (BES) represent an interdisciplinary convergence of biology, electrochemistry, materials science, environmental engineering and mechanical engineering, offering transformative potential for renewable energy generation, wastewater treatment and resource valorization. However, the inherent structural intricacy and mechanistic complexity of BES pose significant challenges to system understanding and optimization. With robust capabilities in pattern recognition and nonlinear system modeling, machine learning (ML) appears to be a good approach to decipher the complex mechanisms of BES. A systematic literature review reveals that ML applications in BES date back to 2006, with a marked surge around 2021, reflecting the growing research interest in this interdisciplinary field. The application domains primarily fall into four categories: (1) analysis and prediction of microbial communities, (2) intelligent design of system components, (3) performance prediction and system optimization, and (4) real-time monitoring and assisted intelligent control. Among these, performance prediction and system optimization constitute the dominant application area, and model interpretability and generalization are cross-cutting requirements for reliable and transferable ML deployment in BES. Among the BES subtypes that have employed ML, microbial fuel cells (MFC) account for the largest share (42.4%), followed by electrochemical biosensor (EB, 37.6%) and microbial electrolysis cells (MEC, 10.9%), with other types occupying smaller proportions. Regarding algorithmic choices, artificial neural networks are the most frequently used method (30.9%), followed by support vector machines or support vector regression (17.3%), principal component analysis (14.5%), and regression trees (13.1%). ML has exhibited significant potential in elevating BES design, manufacture, operation and application. However, constrained by data scarcity and heterogeneity, present models are with limited transferability across scales. Further efforts are warranted to promote the application of ML in BES by expanding data accumulation, diversifying datasets, and developing targeted models. This will ultimately enable a deeper understanding, enhanced optimization and broader deployment of BES.
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3. Assessing transporter systems of methanogens to boost archaea biotechnology.
PMID:日期:2026-11-01Methanogenic archaea (methanogens) are key drivers of global carbon cycling and biomethane production, thriving in diverse anaerobic environments through specialized metabolic and transport systems. While methanogenesis is well understood, transport mechanisms underlying nutrient uptake, ion homeostasis, and macromolecule translocation remain poorly understood. This review compiles current knowledge on transporter proteins and substrate uptake in methanogens. It also highlights fundamental knowledge gaps and outlines experimental procedures for identifying new transporters experimentally and bioinformatic strategies to identify transporter-encoding genes. These approaches enable the investigation of cultured and uncultured methanogens, providing a broader view of transporter diversity and global distribution. Advancing transporter research will enhance insights into archaeal physiology and supports further developing biotechnological applications of methanogens for biofuels and chemical production, and sustainable energy systems.
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4. ε-Poly-l-lysine biomanufacturing advances: From biosynthesis to specification-grade products and applications.
PMID:日期:2026-11-01ε-Poly-l-lysine (ε-PL) is transitioning from a food preservative to a bio-based cationic functional scaffold with opportunities spanning food, agriculture, and biomaterials. However, progress in the field is hampered by a persistent disconnect between titer-driven manufacturing optimization and performance-driven application development. To bridge this gap, we propose a specification-driven (spec-driven) framework that uses critical quality attributes (CQAs) to link molecular structure, industrial production, and application translation. First, we define a minimal, actionable set of ε-PL CQAs and map their molecular determinants to functional relevance. Next, we delineate the biological feasibility windows and constraints that govern these CQAs under high-throughput biosynthesis. We then synthesize integrated strain, process, and recovery engineering strategies to illustrate how CQAs can be translated into reproducible industrial specifications. Finally, application requirements are reverse-mapped to the CQA combinations most frequently required across use scenarios. We conclude that while titer remains important, further gains in titer alone are insufficient to unlock broad translation. Among the proposed CQAs, chain-length distribution, impurity profile, and manufacturing consistency are particularly critical because they determine functional performance, safety boundaries, and lot-to-lot reproducibility. Accordingly, chain-length control, impurity reduction, and integrated strain-process-downstream control represent key rate-limiting steps for developing specification-grade ε-PL product families.
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5. Machine learning for precision prediction of antimicrobial peptide activity and spectrum.
PMID:日期:2026-11-01The accelerating global crisis of antibiotic resistance demands new therapeutic paradigms, and antimicrobial peptides (AMPs) have emerged as promising candidates owing to their broad activity and reduced propensity for resistance development. However, despite rapid progress in AMP discovery and generation, the accurate prediction of antimicrobial potency and activity spectrum remains a major bottleneck for clinical translation. In this Review, we examine how recent advances in machine learning are reshaping AMP research, driving a shift from large-scale discovery toward precision-guided prediction and design. We first summarize the molecular mechanisms underlying AMP function and critically assess existing AMP databases from the perspective of machine learning readiness, highlighting limitations in quantitative and spectrum-resolved annotations. We then review recent developments in peptide representation learning, describing how modern models encode sequence, structure, and dynamic features to capture antimicrobial activity. Building on this foundation, we discuss progress in de novo AMP design and emerging frameworks for quantitative minimum inhibitory concentration prediction and strain-specific spectrum profiling. Finally, we outline future directions for the field, emphasizing integrated generative-predictive pipelines, interpretable models, and closed-loop experimental validation as key enablers for the development of potent, selective, and clinically viable antimicrobial therapeutics.
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6. CRISPR-based live-cell DNA imaging: Technologies, biological insights and future perspectives.
PMID:日期:2026-11-01Live-cell DNA imaging provides a direct view of genome behavior in real-time and has advanced rapidly with the development of the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) system. Here, we review progress in live-cell DNA imaging from two major directions: non-repetitive loci visualization and multicolor imaging. We also highlight biological insights enabled by these technologies, covering DNA replication, damage and repair, chromatin organization and interactions, epigenetic regulation, extrachromosomal DNA, and viral genome dynamics. We then discuss future trends in live-cell DNA imaging and its potential impact on both biotechnology and biomedical research.
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7. Microbial single-cell sequencing technologies: Principles, applications, and spatial integration.
PMID:日期:2026-11-01The advent of microbial single-cell sequencing technology provides unprecedented resolution to study microbial ecosystems, revealing cellular heterogeneity, interactions, and genetic evolution of microorganisms. This review systematically compiles current microbial single-cell sequencing technologies, providing a detailed synthesis of their underlying technical principles, illuminating the strengths and limitations of various approaches. In-depth summaries of the technical challenges they encounter in different microbial domains and their practical applications are provided. Finally, we summarized the emerging field of microbial spatial omics, with a particular focus on advanced imaging techniques utilizing sequencing and fluorescence in situ hybridization.
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8. Converging quality by design, artificial intelligence, and biofoundry automation: A new paradigm for scalable circular biomanufacturing.
PMID:日期:2026-11-01Synthetic biology applies engineering principles to the rational design of biological systems with the aim of producing predictable and tunable behaviour. Although the field's conceptual foundations and core technologies are well established, the recent simultaneous maturation of Quality by Design (QbD), artificial intelligence (AI)-assisted biological design, and automated biofoundry workflows is beginning to outline a more replicable pathway from laboratory innovation to industrial-scale circular biomanufacturing. This review argues that the convergence of these three elements, rather than any one alone, characterises the current phase of the field. We examine how the Design-Build-Test-Learn (DBTL) cycle is being transformed from a research heuristic into a systematic industrial development framework; show how shared toolsets now transfer across microbial, plant, and animal systems to enable a holistic bioeconomy; benchmark synthetic biology-derived products against conventional alternatives where techno-economic and life-cycle data permit; and examine scale-up, regulatory, and societal bottlenecks through recent market-scale case studies in which these bottlenecks have been navigated in practice. We also contrast EU and US regulatory frameworks to show how policy divergence shapes technology adoption. We conclude by identifying what the coming decade of convergent synthetic biology must deliver to support a circular bioeconomy at the scale the 2030 Agenda demands.
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9. Aptamer screening within sample matrices: Toward reliable applications.
PMID:日期:2026-11-01Nucleic acid aptamers are short oligonucleotide sequences selected in vitro by Systematic Evolution of Ligands by EXponential enrichment (SELEX). Often described as "chemical antibodies", they can recognize diverse targets with high affinity and specificity through structure-dependent interactions and offer multiple attractive features. Although riboswitches contain natural aptamer domains, SELEX has remained the dominant strategy for aptamer generation for over 35 years, with ongoing methodological development. These advances have expanded the application potential of aptamers in food safety, disease diagnosis, and drug delivery. Nevertheless, their reliable translation into practical applications remains challenging, largely due to complex matrix effects in real samples, which may interfere with aptamer folding, stability, and target recognition. In response to this challenge, increasing efforts have focused on matrix-integrated SELEX strategies that incorporate representative sample environments into the selection process. This review systematically summarizes recent progress in this developing field and discusses its potential as an upstream strategy for improving aptamer robustness and applicability. We first outline the biological basis of aptamers and the evolution of SELEX, followed by a brief overview of post-SELEX optimization approaches. We then provide an integrated analysis of matrix-integrated SELEX strategies, with emphasis on matrix-spiked selection, matrix-based negative selection, and holistic matrix selection, together with their underlying mechanisms, performance outcomes, and representative applications in environmental adaptation, interference suppression, and biomarker discovery. Finally, we discuss the remaining technical and conceptual challenges and highlight future directions for developing more robust, efficient, and application-oriented aptamer screening platforms.
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10. Microbe-specific and product-specific strategies for scalable biomanufacturing.
10. 针对微生物和产品的可扩展生物制造策略PMID:日期:2026-11-01The translation of microbial biotechnology from laboratory research to commercial application remains a persistent challenge, despite decades of effort. A key yet often neglected issue is the misalignment between microbial host selection, product properties, and process constraints at the early stages, which often limits scalability. Here, we propose Microbe-Specific and Product-Specific Strategies (MPSS) as a conceptual framework to rationalize host-product pairing based on intrinsic microbial traits and product specifications. By incorporating Applied Microbial Population Biology (AMPB), the framework extends this rationale to the strain level, emphasizing application-oriented strain selection and engineering from the outset of a project. Together, MPSS and AMPB offer a structured approach to align early-stage laboratory research with the practical requirements of industrial biomanufacturing, enabling the development of biotechnological solutions with significant societal and economic impact.