Highly multiplexed mammalian metabolic engineering with a shotgun approach.

Abstract

Mammalian metabolic engineering advances basic biology, bioproduction and cell therapy. However, as pathway complexity increases, so does the size of the combinatorial design space and required DNA constructs, rendering unbiased screens intractable. Here, we developed shotgun genetic engineering (SGE), which exploits the ease of delivering many barcoded small constructs-rather than a single large one-into mammalian cells. Each cell serves as an independent experiment, carrying a synthetic pathway that explores gene content, stoichiometry and organellar localization. Functional pathways are identified by sequencing barcodes from cells exhibiting the desired phenotype. Using SGE, we screened millions of pathway combinations to engineer essential amino acid biosynthesis, achieving near-wild-type growth without valine and enabling isoleucine-free growth in Chinese hamster ovary cells, as well as valine-free growth in Jurkat cells. Functional pathways favored mitochondrial localization and required the integration of tens of kilobases of synthetic DNA, beyond the scale of conventional screening. The resulting datasets support machine-learning-guided decoding and engineering of complex biosynthetic traits in mammalian systems.