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二氢叶酸还原酶催化效率中的高阶上位性在甲氧苄啶选择压力下产生了崎岖的适应度景观。

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection.

机构信息

Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX.

Faculty of Science and Engineering, University of Groningen, Groningen, Netherlands.

出版信息

Mol Biol Evol. 2019 Jul 1;36(7):1533-1550. doi: 10.1093/molbev/msz086.

DOI:10.1093/molbev/msz086
PMID:30982891
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6573477/
Abstract

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

摘要

已经全面绘制了几种抗生素靶蛋白的进化适合度景观,显示出突变之间存在强烈的高阶上位性,但在生化和结构水平上理解这些影响仍然存在。在这里,我们进行了广泛的实验和计算研究,以定量了解甲氧苄啶诱导选择存在下大肠杆菌二氢叶酸还原酶 (DHFR) 酶的进化动态。为此,我们开发了一种新的体外测定法,用于快速表征 DHFR 的稳态动力学。针对 DHFR 底物结合口袋的十个残基靶向的总共十个抗性赋予突变的生化和结构表征,揭示了突变 DHFR 酶的催化效率的明显变化。接下来,我们测量了携带六个抗性赋予 DHFR 突变的所有可能组合的突变体文库的生化参数(Km、Ki 和 kcat),并量化了它们之间的上位性相互作用。我们发现,DHFR 的高阶上位性(kcat 和 Km)在甲氧苄啶选择下产生了复杂的适合度景观。总之,我们的数据提供了一个具体的例证,说明生化参数水平的上位性耦合如何导致复杂的适合度景观,并为开发突变体特异性抑制剂提供了新的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/e74dcd159f0c/msz086f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/485ef873d806/msz086f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/0ec049492f6c/msz086f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/7bbfed1e6696/msz086f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/61aee2cf0f50/msz086f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/546a3499092f/msz086f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/a0990a25f044/msz086f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/e74dcd159f0c/msz086f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/485ef873d806/msz086f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/0ec049492f6c/msz086f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/7bbfed1e6696/msz086f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/61aee2cf0f50/msz086f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/546a3499092f/msz086f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/a0990a25f044/msz086f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed30/6573477/e74dcd159f0c/msz086f7.jpg

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