Essential genes are the hubs of cellular networks, but lack of high-throughput methods for titrating gene expression has limited our understanding of the fitness landscapes against which their expression levels are optimized. We developed a modified CRISPRi system leveraging the predictable reduction in efficacy of imperfectly matched sgRNAs to generate defined levels of CRISPRi activity and demonstrated its broad applicability. Using libraries of mismatched sgRNAs predicted to span the full range of knockdown levels, we characterized the expression-fitness relationships of most essential genes in Escherichia coli and Bacillus subtilis. We find that these relationships vary widely from linear to bimodal but are similar within pathways. Notably, despite ∼2 billion years of evolutionary separation between E. coli and B. subtilis, most essential homologs have similar expression-fitness relationships with rare but informative differences. Thus, the expression levels of essential genes may reflect homeostatic or evolutionary constraints shared between the two organisms.

基本基因是细胞网络的枢纽，但缺乏用于滴定基因表达的高通量方法限制了我们对其表达水平进行优化的适应度景观的理解。我们开发了一种改进的 CRISPRi 系统，利用不完全匹配的 sgRNA 的功效的可预测降低来生成定义的 CRISPRi 活性水平，并证明了其广泛的适用性。使用预测跨越整个敲低水平的错配 sgRNA 文库，我们表征了大肠杆菌和枯草芽孢杆菌中大多数必需基因的表达-适应度关系. 我们发现这些关系从线性到双峰变化很大，但在路径内是相似的。值得注意的是，尽管大肠杆菌和枯草芽孢杆菌之间存在约 20 亿年的进化分离，但大多数基本同源物具有相似的表达-适合度关系，但存在罕见但信息量大的差异。因此，必需基因的表达水平可能反映了两种生物之间共享的稳态或进化限制。