Intelligent design of nucleic acid elements in biomanufacturing.
- Author:
Jinsheng WANG
1
;
Zhe SUN
1
;
Xueli ZHANG
1
Author Information
- Publication Type:English Abstract
- Keywords: intelligent design; machine learning; metabolic engineering; nucleic acid elements; synthetic biology
- MeSH: Artificial Intelligence; Synthetic Biology; Nucleic Acids/genetics*; Algorithms; Gene Editing; Promoter Regions, Genetic; Biotechnology/methods*
- From: Chinese Journal of Biotechnology 2025;41(3):968-992
- CountryChina
- Language:Chinese
- Abstract: Nucleic acid elements are essential functional sequences that play critical roles in regulating gene expression, optimizing pathways, and enabling gene editing to enhance the production of target products in biomanufacturing. Therefore, the design and optimization of these elements are crucial in constructing efficient cell factories. Artificial intelligence (AI) provides robust support for biomanufacturing by accurately predicting functional nucleic acid elements, designing and optimizing sequences with quantified functions, and elucidating the operating mechanisms of these elements. In recent years, AI has significantly accelerated the progress in biomanufacturing by reducing experimental workloads through the design and optimization of promoters, ribosome-binding sites, terminators, and their combinations. Despite these advancements, the application of AI in biomanufacturing remains limited due to the complexity of biological systems and the lack of highly quantified training data. This review summarizes the various nucleic acid elements utilized in biomanufacturing, the tools developed for predicting and designing these elements based on AI algorithms, and the case studies showcasing the applications of AI in biomanufacturing. By integrating AI with synthetic biology and high-throughput techniques, we anticipate the development of more efficient tools for designing nucleic acid elements and accelerating the application of AI in biomanufacturing.
