Solid-state nanopore has the ability to detect proteins at a single-molecule level with its high sensitivity, high-throughput, and low cost. Improvements in fabrication, functionalization, and characterization of solid-state nanopores keep evolving. Various analytical methods targeted towards diagnostic applications using nanopore-based devices are appearing. This review article provides an overview of recent progress in the field of solid-state and biological nanopores for protein detection in a complex analyte. The advantages and challenges involved in nanopore sensing have been discussed. Further, the review surpasses the steady-state resistive pulse techniques of sensing and incorporate transient variations in the nanopore conductance. Application of the power spectral density of these fluctuations toward sensing has been highlighted with importance on reducing the detection limit in a complex environment. Lastly, the current problems and future perspectives have been discussed with a perspective to increase nanopores performance towards diagnostic applications in complex medium.

In two decades, the solid state and polymer nanopores became attractive method for the protein sensing with high specificity and sensitivity. They also allow the characterization of conformational changes, unfolding, assembly and aggregation as well the following of enzymatic reaction. This review aims to provide an overview of the protein sensing regarding the technique of detection: the resistive pulse and ionic diodes. For each strategy, we report the most significant achievement regarding the detection of peptides and protein as well as the conformational change, protein-protein assembly and aggregation process. We discuss the limitations and the recent strategies to improve the nanopore resolution and accuracy. A focus is done about concomitant problematic such as protein adsorption and nanopore lifetime.

ClpXP in Escherichia coli is a proteasome degrading protein substrates. It consists of one hexamer of ATPase (ClpX) and two heptamers of peptidase (ClpP). The ClpX binds ATP and translocates the substrate protein into the ClpP chamber by binding and hydrolysis of ATP. At single molecular level, ClpX harnesses cycles of power stroke (dwell and burst) to unfold the substrates, then releases the ADP and Pi. Based on the construction and function of ClpXP, especially the recent progress on how ClpX unfold protein substrates, in this mini-review, a currently proposed single ClpX molecular model system detected by optical tweezers, and its prospective for the elucidation of the mechanism of force generation of ClpX in its power stroke and the subunit interaction with each other, were discussed in detail.

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

Enzymes are dynamic in nature and understanding their activity depends on exploring their overall structural fluctuation as well as transformation at the active site in free state as well as turnover conditions. In this chapter, the application of several different spectroscopy techniques viz. single molecule spectroscopy, ultrafast spectroscopy and Raman spectroscopy in the context of enzyme dynamics and catalysis are discussed. The importance of such studies are significant in the understanding of new discoveries of drugs, cure for some lethal diseases, gene modification as well as in industrial applications.

Object tracking is an instrumental tool supporting studies of cellular trafficking. There are three challenges in object tracking: the identification of targets; the precise determination of their position and boundaries; and the assembly of correct trajectories. This last challenge is particularly relevant when dealing with densely populated images with low signal-to-noise ratios-conditions that are often encountered in applications such as organelle tracking, virus particle tracking or single-molecule imaging. We have developed a set of methods that can handle a wide variety of signal complexities. They are compiled into a free software package called Diatrack. Here we review its main features and utility in a range of applications, providing a survey of the dynamic imaging field together with recommendations for effective use. The performance of our framework is shown to compare favorably to a wide selection of custom-developed algorithms, whether in terms of localization precision, processing speed or correctness of tracks.

N-ethylmaleimide sensitive factor (NSF) is a key protein of intracellular membrane traffic. NSF is a highly conserved protein belonging to the ATPases associated with other activities (AAA+ proteins). AAA+ share common domains and all transduce ATP hydrolysis into major conformational movements that are used to carry out conformational work on client proteins. Together with its cofactor SNAP, NSF is specialized on disassembling highly stable SNARE complexes that form after each membrane fusion event. Although essential for all eukaryotic cells, however, the details of this reaction have long been enigmatic. Recently, major progress has been made in both elucidating the structure of NSF/SNARE complexes and in understanding the reaction mechanism. Advances in both cryo EM and single molecule measurements suggest that NSF, together with its cofactor SNAP, imposes a tight grip on the SNARE complex. After ATP hydrolysis and phosphate release, it then builds up mechanical tension that is ultimately used to rip apart the SNAREs in a single burst. Because the AAA domains are extremely well-conserved, the molecular mechanism elucidated for NSF is presumably shared by many other AAA+ ATPases. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 518-531, 2016.

Nanopores have emerged over the past two decades to become an important technique in single molecule experimental physics and biomolecule sensing. Recently DNA nanotechnology, in particular DNA origami, has been used for the formation of nanopores in insulating materials. DNA origami is a very attractive technique for the formation of nanopores since it enables the construction of 3D shapes with precise control over geometry and surface functionality. DNA origami has been applied to nanopore research by forming hybrid architectures with solid state nanopores and by direct insertion into lipid bilayers. This review discusses recent experimental work in this area and provides an outlook for future avenues and challenges.