The nuclear pore complex regulates nucleocytoplasmic transport by means of a tightly synchronized suite of biochemical reactions. The physicochemical properties of the translocating cargos are emerging as master regulators of their shuttling dynamics. As well as being affected by molecular weight and surface-exposed amino acids, the kinetics of the nuclear translocation of protein cargos also depend on their nanomechanical properties, yet the mechanisms underpinning the mechanoselectivity of the nuclear pore complex are unclear. Here we show that proteins with locally soft regions in the vicinity of the nuclear-localization sequence exhibit higher nuclear-import rates, and that such mechanoselectivity is specifically impaired upon knocking down nucleoporin 153, a key protein in the nuclear pore complex. This allows us to design a short, easy-to-express and chemically inert unstructured peptide tag that accelerates the nuclear-import rate of stiff protein cargos. We also show that U2OS osteosarcoma cells expressing the peptide-tagged myocardin-related transcription factor import this mechanosensitive protein to the nucleus at higher rates and display faster motility. Locally unstructured regions lower the free-energy barrier of protein translocation and might offer a control mechanism for nuclear mechanotransduction.

Viral ribonucleoproteins (vRNPs) are the cornerstones of viral proliferation, as they form the macromolecular complexes that are responsible for the transcription and replication of most single-stranded RNA viruses. The influenza A virus (IAV) polymerase catalyzes RNA synthesis within the context of vRNPs where genomic viral RNA (vRNA) is packaged by the viral nucleoprotein (NP). We used high-speed atomic force microscopy and electron microscopy to study the conformational dynamics of individual IAV recombinant RNPs (rRNPs) during RNA synthesis. The rRNPs present an annular organization that allows for the real-time tracking of conformational changes in the NP-vRNA template caused by the advancing polymerase. We demonstrate that the rRNPs undergo a well-defined conformational cycle during RNA synthesis, which can be interpreted in light of previous transcription models. We also present initial estimations of the average RNA synthesis rate in the rRNP and its dependence on the nucleotide concentration and stability of the nascent RNA secondary structures. Furthermore, we provide evidence that rRNPs can perform consecutive cycles of RNA synthesis, accounting for their ability to recycle and generate multiple copies of RNA.

Proteins drive genome compartmentalization across different length scales. While the identities of these proteins have been well-studied, the physical mechanisms that drive genome organization have remained largely elusive. Studying these mechanisms is challenging owing to a lack of methodologies to parametrize physical models in cellular contexts. Furthermore, because of the complex, entangled, and dense nature of chromatin, conventional live imaging approaches often lack the spatial resolution to dissect these principles. In this chapter, we will describe how to image the interactions of λ-DNA with proteins under purified and cytoplasmic conditions. First, we will outline how to prepare biotinylated DNA, functionalize coverslips with biotin-conjugated poly-ethylene glycol (PEG), and assemble DNA microchannels compatible for the imaging of protein-DNA interactions using total internal fluorescence microscopy. Then we will describe experimental methods to image protein-DNA interactions in vitro and DNA loop extrusion using Xenopus laevis egg extracts.

Genomes are self-organized and self-maintained as long, complex macromolecules of chromatin. The inherent heterogeneity, stochasticity, phase separation, and chromatin dynamics of genome operation make it challenging to study genomes using ensemble methods. Various single-molecule force-, fluorescent-, and sequencing-based techniques rooted in different disciplines have been developed to fill critical gaps in the capabilities of bulk measurements, each providing unique, otherwise inaccessible, insights into the structure and maintenance of the genome. Capable of capturing molecular-level details about the organization, conformational changes, and packaging of genetic material, as well as processive and stochastic movements of maintenance factors, a single-molecule toolbox provides an excellent opportunity for collaborative research to understand how genetic material functions in health and malfunctions in disease. In this review, we discuss novel insights brought to genomic sciences by single-molecule techniques and their potential to continue to revolutionize the field-one molecule at a time.

Processive movement is the key reaction for crystalline polymer degradation by enzyme. Product release is an important phenomenon in resetting the moving cycle, but how it affects chitinase kinetics was unknown. Therefore, we investigated the effect of diacetyl chitobiose (C2) on the biochemical activity and movement of chitinase A from Serratia marcescens (SmChiA). The apparent inhibition constant of C2 on crystalline chitin degradation of SmChiA was 159 μM. The binding position of C2 obtained by X-ray crystallography was at subsite +1, +2 and Trp275 interact with C2 at subsite +1. This binding state is consistent with the competitive inhibition obtained by biochemical analysis. The apparent inhibition constant of C2 on the moving velocity of high-speed (HS) AFM observations was 330 μM, which is close to the biochemical results, indicating that the main factor in crystalline chitin degradation is also the decrease in degradation activity due to inhibition of processive movement. The Trp275 is a key residue for making a sliding intermediate complex. SmChiA W275A showed weaker activity and affinity than WT against crystalline chitin because it is less processive than WT. In addition, biochemical apparent inhibition constant for C2 of SmChiA W275A was 45.6 μM. W275A mutant showed stronger C2 inhibition than WT even though the C2 binding affinity is weaker than WT. This result indicated that Trp275 is important for the interaction at subsite +1, but also important for making sliding intermediate complex and physically block the rebinding of C2 on the catalytic site for crystalline chitin degradation.

Ubiquitination is a process that dictates the lifespan of major histocompatibility complex class II (MHC II)/peptide complexes on antigen-presenting cells. This process is tightly controlled by the levels of ubiquitin ligases, and disruptions in the turnover of MHC II can lead to the improper development of CD4+ T cells within the thymus and hinder the formation of regulatory T cells in the peripheral tissue. To investigate the underlying mechanisms, we utilized dendritic cells lacking the Membrane-associated RING-CH (MARCH) I ubiquitin ligase. We discovered that the overexpression of MARCH I decreases the interaction with LAG-3. Moreover, the MHC II molecules tethered with ubiquitin also showed diminished binding to LAG-3. We employed Diffracted X-ray Blinking (DXB), a technique used for single-molecule X-ray imaging, to observe the protein movements on live cells in real time. Our observations indicated that the normal MHC II molecules moved more rapidly across the cell surface compared to those on the MARCH I-deficient dendritic cells or MHC II KR mutants, which is likely a result of ubiquitination. These findings suggest that the signaling from ubiquitinated MHC II to the T cell receptor differs from the non-ubiquitinated forms. It appears that ubiquitinated MHC II might not be quickly internalized, but rather presents antigens to the T cells, leading to a range of significant immunological responses.

We report the application of machine learning techniques to expedite classification and analysis of protein unfolding trajectories from force spectroscopy data. Using kernel methods, logistic regression, and triplet loss, we developed a workflow called Forced Unfolding and Supervised Iterative Online (FUSION) learning where a user classifies a small number of repeatable unfolding patterns encoded as images, and a machine is tasked with identifying similar images to classify the remaining data. We tested the workflow using two case studies on a multidomain XMod-Dockerin/Cohesin complex, validating the approach first using synthetic data generated with a Monte Carlo algorithm and then deploying the method on experimental atomic force spectroscopy data. FUSION efficiently separated traces that passed quality filters from unusable ones, classified curves with high accuracy, and identified unfolding pathways that were undetected by the user. This study demonstrates the potential of machine learning to accelerate data analysis and generate new insights in protein biophysics.

Magnetic tweezers are a single-molecule force and torque spectroscopy technique that enable the mechanical interrogation in vitro of biomolecules, such as nucleic acids and proteins. They use a magnetic field originating from either permanent magnets or electromagnets to attract a magnetic particle, thus stretching the tethering biomolecule. They nicely complement other force spectroscopy techniques such as optical tweezers and atomic force microscopy (AFM) as they operate as a very stable force clamp, enabling long-duration experiments over a very broad range of forces spanning from 10 fN to 1 nN, with 1-10 milliseconds time and sub-nanometer spatial resolution. Their simplicity, robustness, and versatility have made magnetic tweezers a key technique within the field of single-molecule biophysics, being broadly applied to study the mechanical properties of, e.g., nucleic acids, genome processing molecular motors, protein folding, and nucleoprotein filaments. Furthermore, magnetic tweezers allow for high-throughput single-molecule measurements by tracking hundreds of biomolecules simultaneously both in real-time and at high spatiotemporal resolution. Magnetic tweezers naturally combine with surface-based fluorescence spectroscopy techniques, such as total internal reflection fluorescence microscopy, enabling correlative fluorescence and force/torque spectroscopy on biomolecules. This chapter presents an introduction to magnetic tweezers including a description of the hardware, the theory behind force calibration, its spatiotemporal resolution, combining it with other techniques, and a (non-exhaustive) overview of biological applications.

Folding of the Repeats-in-toxin (RTX) domain of the bacterial adenylate cyclase toxin-hemolysin (CyaA) is critical to its toxin activities and the virulence of the whooping cough agent Bordetella pertussis. The RTX domain (RD) contains five RTX blocks (RTX-i to RTX-v) and their folding is driven by the binding of calcium. However, the detailed molecular mechanism via which the folding signal transmits within the five RTX blocks remains unknown. By combining single molecule optical tweezers, protein engineering, and toxin activity assays, here we demonstrate that the folding of the RD follows a strict hierarchy, with the folding starting from its C-terminal block RTX-v and proceeding towards the N-terminal RTX-i block sequentially. Our results reveal a strict series, templated folding mechanism, where the folding signal is transmitted along the RD in a series fashion from its C terminus continuously to the N terminus. Due to the series nature of this folding signal transmission pathway, the folding of RD can be disrupted at any given RTX block, rendering the RTX blocks located N-terminally to the disruption site and the acylation region of CyaA unfolded and abolishing CyaA\'s toxin activities. Our results reveal key mechanistic insights into the secretion and folding process of CyaA and may open up new potential avenues towards designing new therapeutics to abolish toxin activity of CyaA and combat B. pertussis.

Nanopores are versatile single-molecule sensors that are being used to sense increasingly complex mixtures of structured molecules with applications in molecular data storage and disease biomarker detection. However, increased molecular complexity presents additional challenges to the analysis of nanopore data, including more translocation events being rejected for not matching an expected signal structure and a greater risk of selection bias entering this event curation process. To highlight these challenges, here, we present the analysis of a model molecular system consisting of a nanostructured DNA molecule attached to a linear DNA carrier. We make use of recent advances in the event segmentation capabilities of Nanolyzer, a graphical analysis tool provided for nanopore event fitting, and describe approaches to the event substructure analysis. In the process, we identify and discuss important sources of selection bias that emerge in the analysis of this molecular system and consider the complicating effects of molecular conformation and variable experimental conditions (e.g., pore diameter). We then present additional refinements to existing analysis techniques, allowing for improved separation of multiplexed samples, fewer translocation events rejected as false negatives, and a wider range of experimental conditions for which accurate molecular information can be extracted. Increasing the coverage of analyzed events within nanopore data is not only important for characterizing complex molecular samples with high fidelity but is also becoming essential to the generation of accurate, unbiased training data as machine-learning approaches to data analysis and event identification continue to increase in prevalence.