AutoStepfinder: A fast and automated step detection method for single-molecule analysis

Sequential requirements for distinct Polθ domains during theta-mediated end joining

DNA polymerase θ (Polθ) plays a central role in a DNA double-strand break repair pathway termed theta-mediated end joining (TMEJ). TMEJ functions by pairing short-sequence "microhomologies" (MHs) in single-stranded DNA at each end of a break and subsequently initiating DNA synthesis. It is not known how the Polθ helicase domain (HD) and polymerase domain (PD) operate to bring together MHs and facilitate repair. To resolve these transient processes in real time, we utilized in vitro single-molecule FRET approaches and biochemical analyses. We find that the Polθ-HD mediates the initial capture of two ssDNA strands, bringing them in close proximity. The Polθ-PD binds and stabilizes pre-annealed MHs to form a synaptic complex (SC) and initiate repair synthesis. Individual synthesis reactions show that Polθ is inherently non-processive, accounting for complex mutational patterns during TMEJ. Binding of Polθ-PD to stem-loop-forming sequences can substantially limit synapsis, depending on the available dNTPs and sequence context.

Sister chromatid cohesion establishment during DNA replication termination

Newly copied sister chromatids are tethered together by the cohesin complex, but how sister chromatid cohesion coordinates with DNA replication is poorly understood. Prevailing models suggest that cohesin complexes, bound to DNA before replication, remain behind the advancing replication fork to keep sister chromatids together. By visualizing single replication forks colliding with preloaded cohesin complexes, we find that the replisome instead pushes cohesin to where a converging replisome is met. Whereas the converging replisomes are removed during DNA replication termination, cohesin remains on nascent DNA and provides cohesion. Additionally, we show that CMG (CDC45-MCM2-7-GINS) helicase disassembly during replication termination is vital for proper cohesion in budding yeast. Together, our results support a model wherein sister chromatid cohesion is established during DNA replication termination.

Identification of Conformational Variants for Bradykinin Biomarker Peptides from a Biofluid Using a Nanopore and Machine Learning

There is a current need to develop methods for the sensitive detection of peptide biomarkers in complex mixtures of molecules, such as biofluids, to enable early disease detection. Moreover, to our knowledge, there is currently no detection method capable of identifying the different conformations of a peptide biomarker differing by a single amino acid. Single-molecule nanopore sensing promises to provide this level of resolution. In order to be able to identify these differences in a biofluid such as serum, it is necessary to carefully characterize electrical parameters to obtain specific signatures of each biomarker population observed. We are interested here in a family of peptide biomarkers, kinins such as bradykinin and des-Arg9 bradykinin, that are involved in many disabling pathologies (allergy, asthma, angioedema, sepsis, or cancer). We show the proof of concept for direct identification of these biomarkers in serum at the single-molecule level using a protein nanopore. Each peptide exhibits two unique electrical signatures attributed to specific conformations in bulk. The same signatures are found in serum, allowing their discrimination and identification in a complex mixture such as biofluid. To extend the utility of our experimental results, we developed a principal component analysis approach to define the most relevant electrical parameters for their identification. Finally, we used semisupervised classification to assign each event type to a specific biomarker at physiological serum concentration. In the future, single-molecule scale analysis of peptide biomarkers using a powerful nanopore coupled with machine learning will facilitate the identification and quantification of other clinically relevant biomarkers from biofluids.

Assembly mechanism of the inflammasome sensor AIM2 revealed by single molecule analysis

Pathogenic dsDNA prompts AIM2 assembly leading to the formation of the inflammasome, a multimeric complex that triggers the inflammatory response. The recognition of foreign dsDNA involves AIM2 self-assembly concomitant with dsDNA binding. However, we lack mechanistic and kinetic information on the formation and propagation of the assembly, which can shed light on innate immunity's time response and specificity. Combining optical traps and confocal fluorescence microscopy, we determine here the association and dissociation rates of the AIM2-DNA complex at the single molecule level. We identify distinct mechanisms for oligomer growth via the binding of incoming AIM2 molecules to adjacent dsDNA or direct interaction with bound AIM2 assemblies, resembling primary and secondary nucleation. Through these mechanisms, the size of AIM2 oligomers can increase fourfold in seconds. Finally, our data indicate that single AIM2 molecules do not diffuse/scan along the DNA, suggesting that oligomerization depends on stochastic encounters with DNA and/or DNA-bound AIM2.

Single Elementary Charge Fluctuations on Nanoparticles in Aqueous Solution

100 years ago, in 1923, the Nobel prize in physics was awarded for measurement of the unit charge. In addition to a profound impact on contemporary physics, this discovery has reshaped our understanding of charge-based interactions in chemistry and biology, ranging from oxidation and ionization to protein folding and metabolism. In a liquid, the discrete nature of the electric charge becomes prominent at the nanoscale when a charge carrier is exchanged between a molecule or a nanoparticle and the surrounding medium. However, our ability to observe the dynamics of such interactions at the level of a single elementary charge is limited due to the abundance of ions in water. Here, we report on the observation of single binding-unbinding events with elementary charge resolution at the surface of a nanoparticle suspended in water. Discrete steps in the electrical charge are revealed by analyzing the motion of optically trapped nanoparticles under the influence of an applied sinusoidal electric field. The measurements are sufficiently fast and long to observe individual (dis)charging events that occur on average every 3 s. Our results offer prospective routes for studying the dynamics of diverse chemical and biological phenomena on the nanoscale with elementary charge resolution.

Detecting secondary structure formation with FRET-PAINT

We present single molecule studies demonstrating the capabilities of the FRET-PAINT method to detect secondary structures that would be challenging to detect with alternative methods, particularly single molecule FRET (smFRET). Instead of relying on the change in end-to-end separation as in smFRET, we use the change in accessibility to a small probe as the criterion for secondary structure formation and relative stability. As a model system, we study G-triplex formation by human telomeric repeat sequences in different structural contexts.

Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation

Our current understanding of biomolecular condensate formation is largely based on observing the final near-equilibrium condensate state. Despite expectations from classical nucleation theory, pre-critical protein clusters were recently shown to form under subsaturation conditions in vitro; if similar long-lived clusters comprising more than a few molecules are also present in cells, our understanding of the physical basis of biological phase separation may fundamentally change. Here, we combine fluorescence microscopy with photobleaching analysis to quantify the formation of clusters of NELF proteins in living, stressed cells. We categorise small and large clusters based on their dynamics and their response to p38 kinase inhibition. We find a broad distribution of pre-condensate cluster sizes and show that NELF protein cluster formation can be explained as non-classical nucleation with a surprisingly flat free-energy landscape for a wide range of sizes and an inhibition of condensation in unstressed cells.

CTCF is a DNA-tension-dependent barrier to cohesin-mediated loop extrusion

In eukaryotes, genomic DNA is extruded into loops by cohesin1. By restraining this process, the DNA-binding protein CCCTC-binding factor (CTCF) generates topologically associating domains (TADs)2,3 that have important roles in gene regulation and recombination during development and disease1,4-7. How CTCF establishes TAD boundaries and to what extent these are permeable to cohesin is unclear8. Here, to address these questions, we visualize interactions of single CTCF and cohesin molecules on DNA in vitro. We show that CTCF is sufficient to block diffusing cohesin, possibly reflecting how cohesive cohesin accumulates at TAD boundaries, and is also sufficient to block loop-extruding cohesin, reflecting how CTCF establishes TAD boundaries. CTCF functions asymmetrically, as predicted; however, CTCF is dependent on DNA tension. Moreover, CTCF regulates cohesin's loop-extrusion activity by changing its direction and by inducing loop shrinkage. Our data indicate that CTCF is not, as previously assumed, simply a barrier to cohesin-mediated loop extrusion but is an active regulator of this process, whereby the permeability of TAD boundaries can be modulated by DNA tension. These results reveal mechanistic principles of how CTCF controls loop extrusion and genome architecture.

Nanopore Discrimination of Coagulation Biomarker Derivatives and Characterization of a Post-Translational Modification

One of the most important health challenges is the early and ongoing detection of disease for prevention, as well as personalized treatment management. Development of new sensitive analytical point-of-care tests are, therefore, necessary for direct biomarker detection from biofluids as critical tools to address the healthcare needs of an aging global population. Coagulation disorders associated with stroke, heart attack, or cancer are defined by an increased level of the fibrinopeptide A (FPA) biomarker, among others. This biomarker exists in more than one form: it can be post-translationally modified with a phosphate and also cleaved to form shorter peptides. Current assays are long and have difficulties in discriminating between these derivatives; hence, this is an underutilized biomarker for routine clinical practice. We use nanopore sensing to identify FPA, the phosphorylated FPA, and two derivatives. Each of these peptides is characterized by unique electrical signals for both dwell time and blockade level. We also show that the phosphorylated form of FPA can adopt two different conformations, each of which have different values for each electrical parameter. We were able to use these parameters to discriminate these peptides from a mix, thereby opening the way for the potential development of new point-of-care tests.

Shelterin reduces the accessibility of telomeric overhangs

Telomeres terminate with a 50-300 bases long single-stranded G-rich overhang, which can be misrecognized as a DNA damage repair site. Shelterin plays critical roles in maintaining and protecting telomere ends by regulating access of various physiological agents to telomeric DNA, but the underlying mechanism is not well understood. Here, we measure how shelterin affects the accessibility of long telomeric overhangs by monitoring transient binding events of a short complementary peptide nucleic acid (PNA) probe using FRET-PAINT in vitro. We observed that the POT1 subunit of shelterin reduces the accessibility of the PNA probe by ∼2.5-fold, indicating that POT1 effectively binds to and protects otherwise exposed telomeric sequences. In comparison, a four-component shelterin stabilizes POT1 binding to the overhang by tethering POT1 to the double-stranded telomeric DNA and reduces the accessibility of telomeric overhangs by ∼5-fold. This enhanced protection suggests shelterin restructures the junction between single and double-stranded telomere, which is otherwise the most accessible part of the telomeric overhang.

Spatiotemporally controlled generation of NTPs for single-molecule studies

Many essential processes in the cell depend on proteins that use nucleoside triphosphates (NTPs). Methods that directly monitor the often-complex dynamics of these proteins at the single-molecule level have helped to uncover their mechanisms of action. However, the measurement throughput is typically limited for NTP-utilizing reactions, and the quantitative dissection of complex dynamics over multiple sequential turnovers remains challenging. Here we present a method for controlling NTP-driven reactions in single-molecule experiments via the local generation of NTPs (LAGOON) that markedly increases the measurement throughput and enables single-turnover observations. We demonstrate the effectiveness of LAGOON in single-molecule fluorescence and force spectroscopy assays by monitoring DNA unwinding, nucleosome sliding and RNA polymerase elongation. LAGOON can be readily integrated with many single-molecule techniques, and we anticipate that it will facilitate studies of a wide range of crucial NTP-driven processes.

A new method for controlling NTP-driven reactions in single-molecule experiments via the local generation of NTPs (LAGOON) markedly increases the measurement throughput and enables single-turnover observations.

Ultraviolet optical horn antennas for label-free detection of single proteins

Single-molecule fluorescence techniques have revolutionized our ability to study proteins. However, the presence of a fluorescent label can alter the protein structure and/or modify its reaction with other species. To avoid the need for a fluorescent label, the intrinsic autofluorescence of proteins in the ultraviolet offers the benefits of fluorescence techniques without introducing the labelling drawbacks. Unfortunately, the low autofluorescence brightness of proteins has greatly challenged single molecule detection so far. Here we introduce optical horn antennas, a dedicated nanophotonic platform enabling the label-free detection of single proteins in the UV. This design combines fluorescence plasmonic enhancement, efficient collection up to 85° angle and background screening. We detect the UV autofluorescence from immobilized and diffusing single proteins, and monitor protein unfolding and dissociation upon denaturation. Optical horn antennas open up a unique and promising form of fluorescence spectroscopy to investigate single proteins in their native states in real time.

Condensin extrudes DNA loops in steps up to hundreds of base pairs that are generated by ATP binding events

The condensin SMC protein complex organizes chromosomal structure by extruding loops of DNA. Its ATP-dependent motor mechanism remains unclear but likely involves steps associated with large conformational changes within the ∼50 nm protein complex. Here, using high-resolution magnetic tweezers, we resolve single steps in the loop extrusion process by individual yeast condensins. The measured median step sizes range between 20–40 nm at forces of 1.0–0.2 pN, respectively, comparable with the holocomplex size. These large steps show that, strikingly, condensin typically reels in DNA in very sizeable amounts with ∼200 bp on average per single extrusion step at low force, and occasionally even much larger, exceeding 500 bp per step. Using Molecular Dynamics simulations, we demonstrate that this is due to the structural flexibility of the DNA polymer at these low forces. Using ATP-binding-impaired and ATP-hydrolysis-deficient mutants, we find that ATP binding is the primary step-generating stage underlying DNA loop extrusion. We discuss our findings in terms of a scrunching model where a stepwise DNA loop extrusion is generated by an ATP-binding-induced engagement of the hinge and the globular domain of the SMC complex.

A Guide to Signal Processing Algorithms for Nanopore Sensors

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

Unsupervised selection of optimal single-molecule time series idealization criterion

Single-molecule (SM) approaches have provided valuable mechanistic information on many biophysical systems. As technological advances lead to ever-larger data sets, tools for rapid analysis and identification of molecules exhibiting the behavior of interest are increasingly important. In many cases the underlying mechanism is unknown, making unsupervised techniques desirable. The divisive segmentation and clustering (DISC) algorithm is one such unsupervised method that idealizes noisy SM time series much faster than computationally intensive approaches without sacrificing accuracy. However, DISC relies on a user-selected objective criterion (OC) to guide its estimation of the ideal time series. Here, we explore how different OCs affect DISC’s performance for data typical of SM fluorescence imaging experiments. We find that OCs differing in their penalty for model complexity each optimize DISC’s performance for time series with different properties such as signal/noise and number of sample points. Using a machine learning approach, we generate a decision boundary that allows unsupervised selection of OCs based on the input time series to maximize performance for different types of data. This is particularly relevant for SM fluorescence data sets, which often have signal/noise near the derived decision boundary and include time series of nonuniform length because of stochastic bleaching. Our approach, AutoDISC, allows unsupervised per-molecule optimization of DISC, which will substantially assist in the rapid analysis of high-throughput SM data sets with noisy samples and nonuniform time windows.

Protein Unfolding: Denaturant vs. Force

While protein refolding has been studied for over 50 years since the pioneering work of Christian Anfinsen, there have been a limited number of studies correlating results between chemical, thermal, and mechanical unfolding. The limited knowledge of the relationship between these processes makes it challenging to compare results between studies if different refolding methods were applied. Our current work compares the energetic barriers and folding rates derived from chemical, thermal, and mechanical experiments using an immunoglobulin-like domain from the muscle protein titin as a model system. This domain, I83, has high solubility and low stability relative to other Ig domains in titin, though its stability can be modulated by calcium. Our experiments demonstrated that the free energy of refolding was equivalent with all three techniques, but the refolding rates exhibited differences, with mechanical refolding having slightly faster rates. This suggests that results from equilibrium-based measurements can be compared directly but care should be given comparing refolding kinetics derived from refolding experiments that used different unfolding methods.

Autophosphorylation of the KaiC-like protein ArlH inhibits oligomerization and interaction with ArlI, the motor ATPase of the archaellum

Motile archaea are propelled by the archaellum, whose motor complex consists of the membrane protein ArlJ, the ATPase ArlI, and the ATP-binding protein ArlH. Despite its essential function and the existence of structural and biochemical data on ArlH, the role of ArlH in archaellum assembly and function remains elusive. ArlH is a structural homolog of KaiC, the central component of the cyanobacterial circadian clock. Since autophosphorylation and dephosphorylation of KaiC are central properties for the function of KaiC, we asked whether autophosphorylation is also a property of ArlH proteins. We observed that both ArlH from the euryarchaeon Pyrococcus furiosus (PfArlH) and from the crenarchaeon Sulfolobus acidocaldarius (SaArlH) have autophosphorylation activity. Using a combination of single-molecule fluorescence measurements and biochemical assays, we show that autophosphorylation of ArlH is closely linked to its oligomeric state when bound to hexameric ArlI. These experiments also strongly suggest that ArlH is a hexamer in its ArlI-bound state. Mutagenesis of the putative catalytic residue (Glu-57 in SaArlH) in ArlH results in a reduced autophosphorylation activity and abolished archaellation and motility in S. acidocaldarius, indicating that optimum phosphorylation activity of ArlH is essential for archaellation and motility.