Waltenspühl Yann, Jeliazkov Jeliazko R, Kummer Lutz, Plückthun Andreas
Department of Biochemistry, University of Zürich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
Sci Rep. 2021 Apr 21;11(1):8630. doi: 10.1038/s41598-021-87793-9.
Membrane proteins such as G protein-coupled receptors (GPCRs) carry out many fundamental biological functions, are involved in a large number of physiological responses, and are thus important drug targets. To allow detailed biophysical and structural studies, most of these important receptors have to be engineered to overcome their poor intrinsic stability and low expression levels. However, those GPCRs with especially poor properties cannot be successfully optimised even with the current technologies. Here, we present an engineering strategy, based on the combination of three previously developed directed evolution methods, to improve the properties of particularly challenging GPCRs. Application of this novel combination approach enabled the successful selection for improved and crystallisable variants of the human oxytocin receptor, a GPCR with particularly low intrinsic production levels. To analyse the selection results and, in particular, compare the mutations enriched in different hosts, we developed a Next-Generation Sequencing (NGS) strategy that combines long reads, covering the whole receptor, with exceptionally low error rates. This study thus gave insight into the evolution pressure on the same membrane protein in prokaryotes and eukaryotes. Our long-read NGS strategy provides a general methodology for the highly accurate analysis of libraries of point mutants during directed evolution.
膜蛋白，如G蛋白偶联受体（GPCRs），执行许多基本的生物学功能，参与大量的生理反应，因此是重要的药物靶点。为了进行详细的生物物理和结构研究，这些重要受体中的大多数都必须经过工程改造，以克服其固有的稳定性差和表达水平低的问题。然而，即使采用当前技术，那些特性特别差的GPCRs也无法成功优化。在此，我们提出一种基于三种先前开发的定向进化方法相结合的工程策略，以改善特别具有挑战性的GPCRs的特性。应用这种新颖的组合方法能够成功筛选出人类催产素受体的改良且可结晶的变体，催产素受体是一种固有产生水平特别低的GPCR。为了分析筛选结果，特别是比较在不同宿主中富集的突变，我们开发了一种下一代测序（NGS）策略，该策略结合了覆盖整个受体的长读长和极低的错误率。因此，这项研究深入了解了原核生物和真核生物中同一膜蛋白上的进化压力。我们的长读长NGS策略为定向进化过程中高度准确地分析点突变文库提供了一种通用方法。
