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通过表位选择性蛋白酶利用活酵母生物传感器检测肽变体

Peptide Variant Detection by a Living Yeast Biosensor via an Epitope-Selective Protease.

作者信息

Crnković Tea, Bokor Benjamin J, Lockwood Mead E, Cornish Virginia W

机构信息

Department of Chemistry, Columbia University, New York, NY 10027, USA.

Department of Biological Sciences, Columbia University, New York, NY 10027, USA.

出版信息

Biodes Res. 2023 Mar 15;5:0003. doi: 10.34133/bdr.0003. eCollection 2023.

Abstract

We previously demonstrated that we could hijack the fungal pheromone signaling pathway to provide a living yeast biosensor where peptide biomarkers were recognized by G-protein-coupled receptors and engineered to transcribe a readout. Here, we demonstrated that the protease could be reintroduced to the biosensor to provide a simple mechanism for distinguishing single-amino-acid changes in peptide ligands that, otherwise, would likely be difficult to detect using binding-based assays. We characterized the dose-response curves for five fungal pheromone G-protein-coupled receptors, peptides, and proteases, , , , and . Alanine scanning was carried out for the most selective of these- and -with and without the protease. Two peptide variants were discovered, which showed diminished cleavage by the protease (CaPep2A and CaPep2A13A). Those peptides were then distinguished by utilizing the biosensor strains with and without the protease, which selectively cleaved and altered the apparent concentration of peptide required for half-maximal activation for 2 peptides-CaPep and CaPep13A, respectively-by more than one order of magnitude. These results support the hypothesis that the living yeast biosensor with a sequence-specific protease can translate single-amino-acid changes into more than one order of magnitude apparent shift in the concentration of peptide required for half-maximal activation. With further engineering by computational modeling and directed evolution, the biosensor could likely distinguish a wide variety of peptide sequences beyond the alanine scanning carried out here. In the future, we envision incorporating proteases into our living yeast biosensor for use as a point of care diagnostic, a scalable communication language, and other applications.

摘要

我们之前证明,我们可以劫持真菌信息素信号通路,构建一种活酵母生物传感器,其中肽生物标志物由G蛋白偶联受体识别,并经过工程改造以转录出读数。在此,我们证明可以将蛋白酶重新引入生物传感器,以提供一种简单机制,用于区分肽配体中的单氨基酸变化,否则,使用基于结合的分析方法可能很难检测到这些变化。我们对五种真菌信息素G蛋白偶联受体、肽和蛋白酶( 、 、 、 和 )的剂量反应曲线进行了表征。对其中选择性最高的 和 在有和没有蛋白酶的情况下进行了丙氨酸扫描。发现了两种肽变体,它们被蛋白酶切割的能力减弱(CaPep2A和CaPep2A13A)。然后,利用有和没有蛋白酶的生物传感器菌株对这些肽进行区分,蛋白酶分别选择性切割并改变了两种肽(CaPep和CaPep13A)达到半数最大激活所需的肽的表观浓度,变化幅度超过一个数量级。这些结果支持了这样一种假设,即带有序列特异性蛋白酶的活酵母生物传感器可以将单氨基酸变化转化为达到半数最大激活所需的肽浓度超过一个数量级的表观变化。通过计算建模和定向进化进行进一步工程改造后,该生物传感器可能能够区分此处进行丙氨酸扫描之外的多种肽序列。未来,我们设想将蛋白酶纳入我们的活酵母生物传感器,用作即时诊断工具、可扩展的通信语言以及其他应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbb6/10084949/5d3372bcf163/bdr.0003.fig.001.jpg

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