Combinatorial engineering pinpoints shikimate pathway bottlenecks in para-aminobenzoic acid production in Pseudomonas putida.

ABSTRACT: Combinatorial expression libraries to optimize multigene pathways can improve product titers, but the large number of potential genetic variants makes exhaustive testing impractical. Statistical Design of Experiments (DoE) offers a powerful alternative to enable efficient exploration of gene expression landscapes with a limited number of measurements. Here, we applied this approach to modulate expression levels across all genes in the shikimate and para-aminobenzoic acid (pABA) biosynthesis pathways in Pseudomonas putida. From a theoretical library of 512 strain variants, we trained a regression model using a statistically structured sample comprising 2.7% of the total library, as defined by our DoE approach, and used the model to predict new genotypes with improved pABA titers. This strat

SUBMITTER: Campos-Magana MA 

PROVIDER: S-EPMC12487284 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature