Wytock Thomas P, Zhang Manjing, Jinich Adrian, Fiebig Aretha, Crosson Sean, Motter Adilson E
Department of Physics and Astronomy, Northwestern University, Evanston, Illinois.
The Committee on Microbiology, University of Chicago, Chicago, Illinois.
Biophys J. 2020 Nov 17;119(10):2074-2086. doi: 10.1016/j.bpj.2020.09.038. Epub 2020 Oct 15.
Antagonistic interactions in biological systems, which occur when one perturbation blunts the effect of another, are typically interpreted as evidence that the two perturbations impact the same cellular pathway or function. Yet, this interpretation ignores extreme antagonistic interactions wherein an otherwise deleterious perturbation compensates for the function lost because of a prior perturbation. Here, we report on gene-environment interactions involving genetic mutations that are deleterious in a permissive environment but beneficial in a specific environment that restricts growth. These extreme antagonistic interactions constitute gene-environment analogs of synthetic rescues previously observed for gene-gene interactions. Our approach uses two independent adaptive evolution steps to address the lack of experimental methods to systematically identify such extreme interactions. We apply the approach to Escherichia coli by successively adapting it to defined glucose media without and with the antibiotic rifampicin. The approach identified multiple mutations that are beneficial in the presence of rifampicin and deleterious in its absence. The analysis of transcription shows that the antagonistic adaptive mutations repress a stringent response-like transcriptional program, whereas nonantagonistic mutations have an opposite transcriptional profile. Our approach represents a step toward the systematic characterization of extreme antagonistic gene-drug interactions, which can be used to identify targets to select against antibiotic resistance.
生物系统中的拮抗相互作用,即一种干扰减弱另一种干扰的作用,通常被解释为这两种干扰影响相同细胞途径或功能的证据。然而,这种解释忽略了极端拮抗相互作用,即在其他情况下有害的干扰会补偿先前干扰导致的功能丧失。在此,我们报告了基因 - 环境相互作用,涉及在宽松环境中有害但在限制生长的特定环境中有益的基因突变。这些极端拮抗相互作用构成了先前在基因 - 基因相互作用中观察到的合成拯救的基因 - 环境类似物。我们的方法使用两个独立的适应性进化步骤来解决缺乏系统识别此类极端相互作用的实验方法的问题。我们将该方法应用于大肠杆菌,通过先后使其适应不含和含有抗生素利福平的限定葡萄糖培养基。该方法鉴定出多个在有 rifampicin 时有益而在其不存在时有害的突变。转录分析表明,拮抗适应性突变抑制了一种类似严谨反应的转录程序,而非拮抗突变具有相反的转录谱。我们的方法朝着系统表征极端拮抗基因 - 药物相互作用迈出了一步,这可用于识别针对抗生素抗性进行选择的靶点。