Genome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits

The reliable engineering of biological systems requires quantitative mapping of predictable and context-independent expression over a broad range of protein expression levels. However, current techniques for modifying expression levels are cumbersome and are not amenable to high-throughput approaches. Here we present major improvements to current techniques through the design and construction of E. coli genome-wide libraries using synthetic DNA cassettes that can tune expression over a ∼104 range. The cassettes also contain molecular barcodes that are optimized for next-generation sequencing, enabling rapid and quantitative tracking of alleles that have the highest fitness advantage. We show these libraries can be used to determine which genes and expression levels confer greater fitness to E. coli under different growth conditions.可靠的生物系统工程化构建，需要在宽泛的蛋白质表达水平区间内，构建可预测且不受环境影响的蛋白质表达定量图谱。然而，当前用于调控基因表达水平的技术操作繁琐，且难以适配高通量研究方案。本研究通过设计与构建基于合成DNA盒的大肠杆菌（E. coli）全基因组文库，对现有技术实现了重大改进：该合成DNA盒可将基因表达水平调控在约10^4的范围内，同时搭载了针对下一代测序（next-generation sequencing）优化的分子条形码，能够实现对具有最高适应优势的等位基因的快速定量追踪。本研究证实，该文库可用于明确在不同生长条件下，哪些基因及其表达水平可赋予大肠杆菌更强的适应能力。