AI-driven high-throughput droplet screening of cell-free gene expression

• Published in: Nature communications Vol. 16; no. 1; pp. 2720 - 13
• Main Authors: Zhu, Jiawei, Meng, Yaru, Gao, Wenli, Yang, Shuo, Zhu, Wenjie, Ji, Xiangyang, Zhai, Xuanpei, Liu, Wan-Qiu, Luo, Yuan, Ling, Shengjie, Li, Jian, Liu, Yifan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.03.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 38/35; 49/56; 49/62; 631/553/552; 631/92/507; 639/638/11/877; Bacillus subtilis - genetics; Bacillus subtilis - metabolism; Cell-Free System; Color coding; Combinatorial analysis; Composition; Constraints; Cost effectiveness; Droplets; E coli; Efficiency; Escherichia coli; Escherichia coli - genetics; Escherichia coli - metabolism; Fluorescence; Gene Expression; Green fluorescent protein; Green Fluorescent Proteins - genetics; Green Fluorescent Proteins - metabolism; High-Throughput Screening Assays - methods; Humanities and Social Sciences; Machine Learning; Microfluidics; Microfluidics - methods; multidisciplinary; Optimization; Proteins; Science; Science (multidisciplinary); Screening; Synthetic Biology - methods; Transfer learning

Cell-free gene expression (CFE) systems enable transcription and translation using crude cellular extracts, offering a versatile platform for synthetic biology by eliminating the need to maintain living cells. However, Such systems are constrained by cumbersome composition, high costs, and limited y...