Repurposing an organelle for specialized metabolism provides an avenue for fermentable, unicellular organisms such as Saccharomyces cerevisiae to mimic compartmentalization of metabolic pathways within different plant tissues. Peroxisomes are attractive organelles for repurposing as they are not required for yeast viability when grown on glucose and can efficiently compartmentalize heterologous enzymes to enable physical separation of cytosolic native metabolism and peroxisomal engineered metabolism. However, when not required, peroxisomes are repressed, leading to low functional capacities for heterologous proteins. Here we engineer peroxisomes with enhanced functional capacities, with the goal of compartmentalizing up to eight metabolic enzymes to enhance titers. We implement a machine learning pipeline that allows the identification of factors to overexpress, culminating in a 137% increase in peroxisome functional capacity compared to a wild-type strain. Improved pathway compartmentalization enables an 80% increase in the biosynthesis titers of the monoterpene geraniol, up to 9.5 g L⁻¹.

将细胞器重新用于特殊代谢为可发酵的单细胞生物（如酿酒酵母）提供了一条途径，以模拟不同植物组织内代谢途径的区室化。过氧化物酶体是有吸引力的再利用细胞器，因为它们在葡萄糖上生长时不需要酵母活力，并且可以有效地分隔异源酶，以实现胞质天然代谢和过氧化物酶体工程代谢的物理分离。然而，当不需要时，过氧化物酶体被抑制，导致异源蛋白的功能容量低。在这里，我们设计了具有增强功能能力的过氧化物酶体，目标是将多达 8 种代谢酶区区化以提高滴度。我们实施了一个机器学习管道，可以识别过表达的因子，与野生型菌株相比，最终使过氧化物酶体功能容量增加了 137%。改进的途径区室化使单萜香叶醇的生物合成滴度增加 80%，最高可达 9.5 g ^L-1。