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用于构建蛋白质生物传感器的mRNA展示技术流程

mRNA Display Pipeline for Protein Biosensor Construction.

作者信息

Cui Zhenling, Ayva Cagla Ergun, Liew Yi Jin, Guo Zhong, Mutschler Roxane, Dreier Birgit, Fiorito Maria M, Walden Patricia, Howard Christopher B, Ely Fernanda, Plückthun Andreas, Pretorius Carel, Ungerer Jacobus Pj, Buckle Ashley M, Alexandrov Kirill

机构信息

ARC Centre of Excellence in Synthetic Biology, Brisbane, Queensland 4001, Australia.

Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland 4001, Australia.

出版信息

ACS Sens. 2024 Jun 28;9(6):2846-2857. doi: 10.1021/acssensors.3c02471. Epub 2024 May 29.

DOI:10.1021/acssensors.3c02471
PMID:38807313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11218749/
Abstract

Despite the significant potential of protein biosensors, their construction remains a trial-and-error process. The most obvious approach for addressing this is to utilize modular biosensor architectures where specificity-conferring modalities can be readily generated to recognize new targets. Toward this goal, we established a workflow that uses mRNA display-based selection of hyper-stable monobody domains for the target of choice or ribosome display to select equally stable DARPins. These binders were integrated into a two-component allosteric biosensor architecture based on a calmodulin-reporter chimera. This workflow was tested by developing biosensors for liver toxicity markers such as cytosolic aspartate aminotransferase, mitochondrial aspartate aminotransferase, and alanine aminotransferase 1. We demonstrate that our pipeline consistently produced >10 unique binders for each target within a week. Our analysis revealed that the affinity of the binders for their targets was not a direct predictor of the binder's performance in a biosensor context. The interactions between the binding domains and the reporter module affect the biosensor activity and the dynamic range. We conclude that following binding domain selection, the multiplexed biosensor assembly and prototyping appear to be the most promising approach for identifying biosensors with the desired properties.

摘要

尽管蛋白质生物传感器具有巨大潜力,但其构建仍处于反复试验的过程。解决这一问题最明显的方法是利用模块化生物传感器架构,在该架构中可以轻松生成赋予特异性的模式以识别新目标。为了实现这一目标,我们建立了一个工作流程,该流程使用基于mRNA展示的方法为选定目标筛选超稳定单域抗体,或使用核糖体展示来筛选同样稳定的亲环素蛋白。这些结合物被整合到基于钙调蛋白-报告基因嵌合体的双组分变构生物传感器架构中。通过开发针对肝毒性标志物(如胞质天冬氨酸转氨酶、线粒体天冬氨酸转氨酶和丙氨酸转氨酶1)的生物传感器对该工作流程进行了测试。我们证明,我们的流程在一周内针对每个目标持续产生超过10种独特的结合物。我们的分析表明,结合物对其目标的亲和力并非其在生物传感器环境中性能的直接预测指标。结合域与报告模块之间的相互作用会影响生物传感器的活性和动态范围。我们得出结论,在结合域选择之后,多重生物传感器组装和原型制作似乎是识别具有所需特性的生物传感器最有前景的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/a0293e60a60b/se3c02471_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/ecc85420537a/se3c02471_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/ab5319f2b141/se3c02471_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/a54ae2712778/se3c02471_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/e7c4c17585a6/se3c02471_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/a0293e60a60b/se3c02471_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/ecc85420537a/se3c02471_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/ab5319f2b141/se3c02471_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/a54ae2712778/se3c02471_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/e7c4c17585a6/se3c02471_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bef/11218749/a0293e60a60b/se3c02471_0005.jpg

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