Bosshart Patrick D, Casagrande Fabio, Frederix Patrick L T M, Ratera Merce, Bippes Christian A, Müller Daniel J, Palacin Manuel, Engel Andreas, Fotiadis Dimitrios
M E Müller Institute for Structural Biology, Biozentrum of the University of Basel, CH-4056 Basel, Switzerland.
Nanotechnology. 2008 Sep 24;19(38):384014. doi: 10.1088/0957-4484/19/38/384014. Epub 2008 Aug 12.
Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerful tool for studying the mechanical properties, intermolecular and intramolecular interactions, unfolding pathways, and energy landscapes of membrane proteins. One limiting factor for the large-scale applicability of SMFS on membrane proteins is its low efficiency in data acquisition. We have developed a semi-automated high-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, we present a coarse filter to efficiently extract protein unfolding events from large data sets. The HT-SMFS procedure and the coarse filter were validated using the proton pump bacteriorhodopsin (BR) from Halobacterium salinarum and the L-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen for molecular interactions between AdiC and its substrates, we recorded data sets in the absence and in the presence of L-arginine, D-arginine, and agmatine. Altogether ∼400 000 force-distance curves were recorded. Application of coarse filtering to this wealth of data yielded six data sets with ∼200 (AdiC) and ∼400 (BR) force-distance spectra in each. Importantly, the raw data for most of these data sets were acquired in one to two days, opening new perspectives for HT-SMFS applications.
基于原子力显微镜的单分子力谱(SMFS)是研究膜蛋白的力学性质、分子间和分子内相互作用、解折叠途径以及能量景观的有力工具。SMFS在膜蛋白大规模应用中的一个限制因素是其数据采集效率低。我们开发了一种半自动高通量SMFS(HT-SMFS)程序以实现高效的数据采集。此外,我们提出了一种粗滤器,用于从大数据集中有效提取蛋白质解折叠事件。使用来自盐生盐杆菌的质子泵细菌视紫红质(BR)和来自大肠杆菌的L-精氨酸/胍丁胺反向转运蛋白AdiC对HT-SMFS程序和粗滤器进行了验证。为了筛选AdiC与其底物之间的分子相互作用,我们在不存在和存在L-精氨酸、D-精氨酸和胍丁胺的情况下记录了数据集。总共记录了约400000条力-距离曲线。对这些丰富的数据应用粗滤得到了六个数据集,每个数据集中有大约200条(AdiC)和400条(BR)力-距离谱。重要的是,这些数据集中大多数的原始数据在一到两天内就采集完成,为HT-SMFS的应用开辟了新的前景。