人工智能在微生物菌株开发和应用中的研究进展

Research progress of artificial intelligence in the development and application of microbial strains

摘要:

微生物作为地球上最古老且种类最丰富的生命形式，因其具有差异化代谢潜能与生物合成能力，为新型药物、天然活性产物的开发提供了核心资源，具有重要的开发价值。目前，人工智能(artificial intelligence, AI)与微生物菌株开发的深度融合，正推动生命科学领域从“经验筛选”向“理性设计”的范式变革。这一变革既源于传统研究方法在解决微生物资源复杂性方面存在局限性，也得益于AI在多组学数据分析、模型预测及实验流程优化方面具有的独特优势。本文系统综述了AI在微生物菌株开发与应用中的作用，涵盖菌种选育、代谢产物开发、疾病诊断与治疗以及外源物质合成4个方面。此外，本文还讨论了AI在菌株开发过程中的核心优势及存在的局限性。概言之，AI通过自动化建模与科学化预测，不仅加速了微生物菌株开发进程，还提供了多维度优化策略，成为推动技术革新的核心驱动力。AI技术融合有望突破传统产业瓶颈，推动微生物产业可持续发展。

Abstract:

Microorganisms, as the oldest and most diverse life forms on Earth, possess significant development value due to their differentiated metabolic potential and biosynthetic capabilities, serving as core resources for the development of novel drugs and natural active products. Currently, the deep integration of artificial intelligence (AI) with microbial strain development is driving a paradigm shift in life sciences from “empirical screening” to “rational design”. This shift is driven both by the limitations of conventional research methods in addressing the complexity of microbial resources and by the unique advantages of AI in multi-omics data analysis, model prediction, and experimental process optimization. This article systematically reviews the roles of AI in the development and application of microbial strains, covering four aspects: strain breeding, metabolite development, disease diagnosis and treatment, and xenobiotic synthesis. Additionally, it discusses the core advantages and existing limitations of AI in the strain development process. In summary, through automated modeling and scientific prediction, AI not only accelerates the efficiency of microbial strain development but also provides multi-dimensional optimization strategies, serving as a core driver for technological innovation. The integration of AI is expected to break through traditional industrial bottlenecks and promote the sustainable development of the microbial industry.