Navigable Genome Engineering: Stepwise Correlation for Precision-Guided Optimization of Microbial Cell Factory Phenotypes

Microbial cell factories, akin to “chips” in biomanufacturing, concentrate the most intricate scientific challenges, technical bottlenecks, and densest intellectual property. However, despite extensive efforts in rational engineering, the inherent complexity of biological systems and the limited knowledge of their underlying mechanisms still incur substantial trial-and-error costs. This Perspective seeks to explore the potential of a prior-knowledge-independent approach for optimizing microbial cell factory phenotypes. We discuss the feasibility of stepwise genotypic navigation in genome engineering and emphasize its ability to generate high-quality genotype–phenotype association data, thereby advancing AI-assisted genome modeling and further enabling precision-guided optimization.