Evolutionary regain of lost gene circuit function
Evolutionary regain of lost gene circuit function
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DOI：
10.1073/pnas.1912257116
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发表时间：
2019-12-10
影响因子：
11.1
通讯作者：
Balazsi, Gabor
中科院分区：
文献类型：
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作者：
Gouda, Mirna Kheir;Manhart, Michael;Balazsi, Gabor
进化的可逆性-恢复失去的功能的能力-是进化生物学和合成生物学中的一个重要问题，修复被进化过程破坏的天然或合成系统可能是有价值的。在这里，我们使用一个合成的正反馈（PF）基因电路整合到单倍体酿酒酵母细胞，以测试人口是否可以恢复失去的PF功能。在以前的进化实验中，基因突变消除了PF激活的适应性成本。由于PF活化也提供耐药性，因此将此类受损或破坏的突变体暴露于药物和诱导剂应产生选择压力以重新获得耐药性和可能的PF功能。事实上，在药物存在下进化7种PF突变株揭示了通过基因组PF外部突变的3种适应情况，这些突变可能通过影响转录、翻译、降解和其他基本细胞过程来提高PF基础表达。非功能性突变体获得耐药性，从来没有开发高表达，而准功能和功能失调的PF突变体开发高表达非遗传，然后减少，虽然更缓慢的功能失调突变体的回复突变克隆出现。这些结果突出了细胞内环境（如生长速率）如何影响调控网络动力学和进化动力学，这对理解耐药性的进化和开发未来的合成生物学应用具有重要意义。
Evolutionary reversibility-the ability to regain a lost function-is an important problem both in evolutionary and synthetic biology, where repairing natural or synthetic systems broken by evolutionary processes may be valuable. Here, we use a synthetic positive-feedback (PF) gene circuit integrated into haploid Saccharomyces cerevisiae cells to test if the population can restore lost PF function. In previous evolution experiments, mutations in a gene eliminated the fitness costs of PF activation. Since PF activation also provides drug resistance, exposing such compromised or broken mutants to both drug and inducer should create selection pressure to regain drug resistance and possibly PF function. Indeed, evolving 7 PF mutant strains in the presence of drug revealed 3 adaptation scenarios through genomic, PF-external mutations that elevate PF basal expression, possibly by affecting transcription, translation, degradation, and other fundamental cellular processes. Nonfunctional mutants gained drug resistance without ever developing high expression, while quasifunctional and dysfunctional PF mutants developed high expression nongenetically, which then diminished, although more slowly for dysfunctional mutants where revertant clones arose. These results highlight how intracellular context, such as the growth rate, can affect regulatory network dynamics and evolutionary dynamics, which has important consequences for understanding the evolution of drug resistance and developing future synthetic biology applications.