Efficient unfolding pattern recognition in single molecule force spectroscopy data

POTATO: Automated pipeline for batch analysis of optical tweezers data

Optical tweezers are a single-molecule technique that allows probing of intra- and intermolecular interactions that govern complex biological processes involving molecular motors, protein-nucleic acid interactions, and protein/RNA folding. Recent developments in instrumentation eased and accelerated optical tweezers data acquisition, but analysis of the data remains challenging. Here, to enable high-throughput data analysis, we developed an automated python-based analysis pipeline called POTATO (practical optical tweezers analysis tool). POTATO automatically processes the high-frequency raw data generated by force-ramp experiments and identifies (un)folding events using predefined parameters. After segmentation of the force-distance trajectories at the identified (un)folding events, sections of the curve can be fitted independently to a worm-like chain and freely jointed chain models, and the work applied on the molecule can be calculated by numerical integration. Furthermore, the tool allows plotting of constant force data and fitting of the Gaussian distance distribution over time. All these features are wrapped in a user-friendly graphical interface, which allows researchers without programming knowledge to perform sophisticated data analysis.

Insertion and activation of functional Bacteriorhodopsin in a floating bilayer

The proton pump transmembrane protein bacteriorhodopsin was successfully incorporated into planar floating lipid bilayers in gel and fluid phases, by applying a detergent-mediated incorporation method. The method was optimized on single supported bilayers by using quartz crystal microbalance, atomic force and fluorescence microscopy techniques. Neutron and X-ray reflectometry were used on both single and floating bilayers with the aim of determining the structure and composition of this membrane-protein system before and after protein reconstitution at sub-nanometer resolution. Lipid bilayer integrity and protein activity were preserved upon the reconstitution process. Reversible structural modifications of the membrane, induced by the bacteriorhodopsin functional activity triggered by visible light, were observed and characterized at the nanoscale.

Conformational rearrangements in the transmembrane domain of CNGA1 channels revealed by single-molecule force spectroscopy

Cyclic nucleotide-gated (CNG) channels are activated by binding of cyclic nucleotides. Although structural studies have identified the channel pore and selectivity filter, conformation changes associated with gating remain poorly understood. Here we combine single-molecule force spectroscopy (SMFS) with mutagenesis, bioinformatics and electrophysiology to study conformational changes associated with gating. By expressing functional channels with SMFS fingerprints in Xenopus laevis oocytes, we were able to investigate gating of CNGA1 in a physiological-like membrane. Force spectra determined that the S4 transmembrane domain is mechanically coupled to S5 in the open state, but S3 in the closed state. We also show there are multiple pathways for the unfolding of the transmembrane domains, probably caused by a different degree of α-helix folding. This approach demonstrates that CNG transmembrane domains have dynamic structure and establishes SMFS as a tool for probing conformational change in ion channels.

Cyclic nucleotide gated channels are activated after binding cyclic nucleotides. Here, using single molecule force spectroscopy, the authors reveal that cyclic nucleotide binding causes conformational changes and tighter coupling of the S4 helix to the pore forming domain.

Improving single molecule force spectroscopy through automated real-time data collection and quantification of experimental conditions

The benefits of single molecule force spectroscopy (SMFS) clearly outweigh the challenges which include small sample sizes, tedious data collection and introduction of human bias during the subjective data selection. These difficulties can be partially eliminated through automation of the experimental data collection process for atomic force microscopy (AFM). Automation can be accomplished using an algorithm that triages usable force-extension recordings quickly with positive and negative selection. We implemented an algorithm based on the windowed fast Fourier transform of force-extension traces that identifies peaks using force-extension regimes to correctly identify usable recordings from proteins composed of repeated domains. This algorithm excels as a real-time diagnostic because it involves <30 ms computational time, has high sensitivity and specificity, and efficiently detects weak unfolding events. We used the statistics provided by the automated procedure to clearly demonstrate the properties of molecular adhesion and how these properties change with differences in the cantilever tip and protein functional groups and protein age.

Reference-free alignment and sorting of single-molecule force spectroscopy data

Single-molecule force spectroscopy has become a versatile tool for investigating the (un)folding of proteins and other polymeric molecules. Like other single-molecule techniques, single-molecule force spectroscopy requires recording and analysis of large data sets to extract statistically meaningful conclusions. Here, we present a data analysis tool that provides efficient filtering of heterogeneous data sets, brings spectra into register based on a reference-free alignment algorithm, and determines automatically the location of unfolding barriers. Furthermore, it groups spectra according to the number of unfolding events, subclassifies the spectra using cross correlation-based sorting, and extracts unfolding pathways by principal component analysis and clustering methods to extracted peak positions. Our approach has been tested on a data set obtained through mechanical unfolding of bacteriorhodopsin (bR), which contained a significant number of spectra that did not show the well-known bR fingerprint. In addition, we have tested the performance of the data analysis tool on unfolding data of the soluble multidomain (Ig27)(8) protein.