Reliable State Identification and State Transition Detection in Fluorescence Intensity-Based Single-Molecule Förster Resonance Energy-Transfer Data

A single CAA interrupt in a DNA three-way junction containing a CAG repeat hairpin results in parity-dependent trapping

An increasing number of human disorders are attributed to genomic expansions of short tandem repeats (STRs). Secondary DNA structures formed by STRs are believed to play an important role in expansion, while the presence of nucleotide interruptions within the pure repeat sequence is known to delay the onset and progression of disease. We have used two single-molecule fluorescence techniques to analyse the structure and dynamics of DNA three-way junctions (3WJs) containing CAG repeat hairpin slipouts, with and without a single CAA interrupt. For a 3WJ with a (CAG)10 slipout, the CAA interrupt is preferentially located in the hairpin loop, and the branch migration dynamics are 4-fold slower than for the 3WJ with a pure (CAG)10, and 3-fold slower than a 3WJ with a pure (CAG)40 repeat. The (CAG)11 3WJ with CAA interrupt adopts a conformation that places the interrupt in or near the hairpin loop, with similar dynamics to the pure (CAG)10 and (CAG)11 3WJs. We have shown that changing a single nucleotide (G to A) in a pure repeat can have a large impact on 3WJ structure and dynamics, which may be important for the protective role of interrupts in repeat expansion diseases.

Transition Time Determination of Single-Molecule FRET Trajectories via Wasserstein Distance Analysis in Steady-State Variations in smFRET (WAVE)

Many biological molecules respond to external stimuli that can cause their conformational states to shift from one steady state to another. Single-molecule FRET (Fluorescence Resonance Energy Transfer) is of particular interest to not only define the steady-state conformational ensemble usually averaged out in the ensemble of molecules but also characterize the dynamics of biomolecules. To study steady-state transitions, i.e., non-equilibrium transitions, a data analysis methodology is necessary to analyze single-molecule FRET photon trajectories, which contain mixtures of contributions from two steady-state statuses and include non-equilibrium transitions. In this study, we introduce a novel methodology called WAVE (Wasserstein distance Analysis in steady-state Variations in smFRET) to detect and locate non-equilibrium transition positions in FRET trajectories. Our method first utilizes a combined STaSI-HMM (Stepwise Transitions with State Inference Hidden Markov Model) algorithm to convert the original FRET trajectories into discretized trajectories. We then apply Maximum Wasserstein Distance analysis to differentiate the FRET state compositions of the fitting trajectories before and after the non-equilibrium transition. Forward and backward algorithms, based on the Minimum Description Length (MDL) principle, are used to find the refined positions of the non-equilibrium transitions. This methodology allows us to observe changes in experimental conditions in chromophore-tagged biomolecules or vice versa.

Real-time detection of human telomerase DNA synthesis by multiplexed single-molecule FRET

Genomic stability in proliferating cells critically depends on telomere maintenance by telomerase reverse transcriptase. Here we report the development and proof-of-concept results of a single-molecule approach to monitor the catalytic activity of human telomerase in real time and with single-nucleotide resolution. Using zero-mode waveguides and multicolor FRET, we recorded the processive addition of multiple telomeric repeats to individual DNA primers. Unlike existing biophysical and biochemical tools, the novel approach enables the quantification of nucleotide-binding kinetics before nucleotide incorporation. Moreover, it provides a means to dissect the unique translocation dynamics that telomerase must undergo after synthesis of each hexameric DNA repeat. We observed an unexpectedly prolonged binding dwell time of dGTP in the enzyme active site at the start of each repeat synthesis cycle, suggesting that telomerase translocation is composed of multiple rate-contributing sub-steps that evade classical biochemical analysis.

Recent Advances in Single-Molecule Tracking and Imaging Techniques

Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

Real-time single-molecule observation of chaperone-assisted protein folding

The ability of heat shock protein 70 (Hsp70) molecular chaperones to remodel the conformation of their clients is central to their biological function; however, questions remain regarding the precise molecular mechanisms by which Hsp70 machinery interacts with the client and how this contributes toward efficient protein folding. Here, we used total internal reflection fluorescence (TIRF) microscopy and single-molecule fluorescence resonance energy transfer (smFRET) to temporally observe the conformational changes that occur to individual firefly luciferase proteins as they are folded by the bacterial Hsp70 system. We observed multiple cycles of chaperone binding and release to an individual client during refolding and determined that high rates of chaperone cycling improves refolding yield. Furthermore, we demonstrate that DnaJ remodels misfolded proteins via a conformational selection mechanism, whereas DnaK resolves misfolded states via mechanical unfolding. This study illustrates that the temporal observation of chaperone-assisted folding enables the elucidation of key mechanistic details inaccessible using other approaches.

A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Heterogeneous migration routes of DNA triplet repeat slip-outs

It is unclear how the length of a repetitive DNA tract determines the onset and progression of repeat expansion diseases, but the dynamics of secondary DNA structures formed by repeat sequences are believed to play an important role. It was recently shown that three-way DNA junctions containing slip-out hairpins of CAG or CTG repeats and contiguous triplet repeats in the adjacent duplex displayed single-molecule FRET (smFRET) dynamics that were ascribed to both local conformational motions and longer-range branch migration. Here we explore these so-called "mobile" slip-out structures through a detailed kinetic analysis of smFRET trajectories and coarse-grained modeling. Despite the apparent structural simplicity, with six FRET states resolvable, most smFRET states displayed biexponential dwell-time distributions, attributed to structural heterogeneity and overlapping FRET states. Coarse-grained modeling for a (GAC)₁₀ repeat slip-out included trajectories that corresponded to a complete round of branch migration; the structured free energy landscape between slippage events supports the dynamical complexity observed by smFRET. A hairpin slip-out with 40 CAG repeats, which is above the repeat length required for disease in several triplet repeat disorders, displayed smFRET dwell times that were on average double those of 3WJs with 10 repeats. The rate of secondary-structure rearrangement via branch migration, relative to particular DNA processing pathways, may be an important factor in the expansion of triplet repeat expansion diseases.

Single-Molecule Kinetic Studies of Nucleic Acids by Förster Resonance Energy Transfer

Single-molecule microscopy is often used to observe and characterize the conformational dynamics of nucleic acids (NA). Due to the large variety of NA structures and the challenges specific to single-molecule observation techniques, the data recorded in such experiments must be processed via multiple statistical treatments to finally yield a reliable mechanistic view of the NA dynamics. In this chapter, we propose a comprehensive protocol to analyze single-molecule trajectories in the scope of single-molecule Förster resonance energy transfer (FRET) microscopy. The suggested protocol yields the conformational states common to all molecules in the investigated sample, together with the associated conformational transition kinetics. The given model resolves states that are indistinguishable by their observed FRET signals and is estimated with 95% confidence using error calculations on FRET states and transition rate constants. In the end, a step-by-step user guide is given to reproduce the protocol with the Multifunctional Analysis Software to Handle single-molecule FRET data (MASH-FRET).

FRETboard: Semisupervised classification of FRET traces

Förster resonance energy transfer (FRET) is a useful phenomenon in biomolecular investigations, as it can be leveraged for nanoscale measurements. The optical signals produced by such experiments can be analyzed by fitting a statistical model. Several software tools exist to fit such models in an unsupervised manner but lack the flexibility to adapt to different experimental setups and require local installations. Here, we propose to fit models to optical signals more intuitively by adopting a semisupervised approach, in which the user interactively guides the model to fit a given data set, and introduce FRETboard, a web tool that allows users to provide such guidance. We show that our approach is able to closely reproduce ground truth FRET statistics in a wide range of simulated single-molecule scenarios and correctly estimate parameters for up to 11 states. On in vitro data, we retrieve parameters identical to those obtained by laborious manual classification in a fraction of the required time. Moreover, we designed FRETboard to be easily extendable to other models, allowing it to adapt to future developments in FRET measurement and analysis.

KERA: analysis tool for multi-process, multi-state single-molecule data

Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA's utility by analyzing conformational dynamics of two DNA binding proteins: replication protein A and xeroderma pigmentosum complementation group D helicase.

MASH-FRET: A Simplified Approach for Single-Molecule Multiplexing Using FRET

Multiplexed detection has been a big motivation in biomarker analysis as it not only saves cost and labor but also improves the reliability of diagnosis. Among the many approaches for multiplexed detection, fluorescence resonance energy transfer (FRET)-based multiplexing is gaining popularity particularly due to its low background and quantitative nature. Although several FRET-based approaches have been developed for multiplexing, they require either multiple FRET pairs in combination with multiple excitation sources or complicated algorithms to accurately assign signals for individual FRET pairs. Therefore, the need for multiple FRET pairs and multiple excitation sources not only complicates the experimental design but also increases the cost and labor. In this regard, multiplexed sensing by tuning the interdye distance of a single FRET pair could be an ideal solution if identification of multiple FRET efficiencies in a single imaging is possible. Here, implementing a program called MASH-FRET, we evaluated the rigor and capability of this program in identifying seemingly overlapped FRET populations obtained from a multiplexed detection experiment using a single FRET pair. Through MASH-FRET-enabled bootstrap-based analysis of FRET data (also called BOBA-FRET), we demonstrated that the resolution and statistical confidence of the poorly resolved or even unresolved FRET populations can be readily determined. Using simulated FRET data, we further demonstrated that the program can easily identify FRET populations separated by ∼0.1 in mean FRET values, indicating an upper limit of ∼9-fold multiplexing without the need for complicated labeling schemes and multiexcitation sources. Therefore, this paper presents a data analysis approach on an existing platform that has a great potential to simplify the technological needs for multiplexing and to broaden the scope of FRET-based single-molecule analyses.

Pushing Camera-Based Single-Molecule Kinetic Measurements to the Frame Acquisition Limit with Stroboscopic smFRET

Single-molecule fluorescence resonance energy transfer (smFRET) experiments permit detailed examination of microscopic dynamics. However, kinetic rate constants determined by smFRET are susceptible to systematic underestimation when the rate constants are comparable to the data acquisition rate. We demonstrate how such systematic errors in camera-based total internal reflection fluorescence microscopy experiments can be greatly reduced by using stroboscopic illumination/detection, allowing accurate rate constant determination up to the data sampling rate and yielding an order of magnitude increase in the dynamic range. Implementation of these stroboscopic smFRET ideas is straightforward, and the stroboscopically obtained data are compatible with multiple trajectory analysis methods, including dwell-time analysis and hidden Markov modeling. Such stroboscopic methods therefore offer a remarkably simple yet valuable addition to the smFRET toolkit, requiring only relatively modest modification to the normal data collection and analysis procedures.

Recent developments in the characterization of nucleic acid hybridization kinetics

Hybridization of nucleic acids (NAs) is a fundamental molecular mechanism that drives many cellular processes and enables new biotechnologies as well as therapeutics. However, existing methods that measure hybridization kinetics of nucleic acids are either performed at the ensemble level or constrained to non-native physiological conditions. Recent advances in 3D single-molecule tracking techniques break these limitations by allowing multiple annealing and melting events to be observed on a single oligonucleotide freely diffusing inside a live mammalian cell. This review provides an overview of diverse approaches to measuring NA hybridization kinetics at the single-molecule level and in live cells, and concludes with a synopsis of unresolved challenges and opportunities in the live-cell hybridization kinetics measurements. Important discoveries made by NA kinetics measurements and biotechnologies that can be improved with a deeper understanding of hybridization kinetics are also described.

A Python Toolbox for Unbiased Statistical Analysis of Fluorescence Intermittency of Multilevel Emitters

We report on a Python toolbox for unbiased statistical analysis of fluorescence intermittency properties of single emitters. Intermittency, that is, step-wise temporal variations in the instantaneous emission intensity and fluorescence decay rate properties, is common to organic fluorophores, II-VI quantum dots, and perovskite quantum dots alike. Unbiased statistical analysis of intermittency switching time distributions, involved levels, and lifetimes are important to avoid interpretation artifacts. This work provides an implementation of Bayesian changepoint analysis and level clustering applicable to time-tagged single-photon detection data of single emitters that can be applied to real experimental data and as a tool to verify the ramifications of hypothesized mechanistic intermittency models. We provide a detailed Monte Carlo analysis to illustrate these statistics tools and to benchmark the extent to which conclusions can be drawn on the photophysics of highly complex systems, such as perovskite quantum dots that switch between a plethora of states instead of just two.

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

Single-molecule techniques allow the visualization of the molecular dynamics of nucleic acids and proteins with high spatiotemporal resolution. Valuable kinetic information of biomolecules can be obtained when the discrete states within single-molecule time trajectories are determined. Here, we present a fast, automated, and bias-free step detection method, AutoStepfinder, that determines steps in large datasets without requiring prior knowledge on the noise contributions and location of steps. The analysis is based on a series of partition events that minimize the difference between the data and the fit. A dual-pass strategy determines the optimal fit and allows AutoStepfinder to detect steps of a wide variety of sizes. We demonstrate step detection for a broad variety of experimental traces. The user-friendly interface and the automated detection of AutoStepfinder provides a robust analysis procedure that enables anyone without programming knowledge to generate step fits and informative plots in less than an hour.

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Fast, automated, and bias-free detection of steps within single-molecule trajectories

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Robust step detection without any prior knowledge on the data

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A dual-pass strategy for the detection of steps over a wide variety of scales

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A user-friendly interface for a simplified step fitting procedure

Single-molecule techniques have made it possible to track individual protein complexes in real time with a nanometer spatial resolution and a millisecond timescale. Accurate determination of the dynamic states within single-molecule time traces provides valuable kinetic information that underlie the function of biological macromolecules. Here, we present a new automated step detection method called AutoStepfinder, a versatile, robust, and easy-to-use algorithm that allows researchers to determine the kinetic states within single-molecule time trajectories without any bias.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

Dissection of Interaction Kinetics through Single-Molecule Interaction Simulation

The ability to extract kinetic interaction parameters from single-molecule fluorescence resonance energy transfer trajectories without the need for solving complex single-molecule differential equations has the potential to address some of the critical biophysical questions. Here, we provide a noise-free single-molecule interaction simulation (SMIS) tool to give the expected dwell-time distributions and relative populations of each FRET level based on the assigned kinetic model and to dissect kinetic interaction parameters from single-molecule FRET trajectories. The method provides the expected dwell-time distributions, average transition rates, and relative populations of each FRET level based on the assigned kinetic model. By comparing with ground truth data and experimental data, we demonstrated that SMIS is useful to quantify the interaction kinetic rate constants without using the traditional single-molecule analytical solution approach.

Top-down machine learning approach for high-throughput single-molecule analysis

Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large datasets, existing analysis tools are not suitable to process the large volume of data obtained in high-throughput paradigms. Here, we present a new analysis platform (DISC) that accelerates unsupervised analysis of single-molecule trajectories. By merging model-free statistical learning with the Viterbi algorithm, DISC idealizes single-molecule trajectories up to three orders of magnitude faster with improved accuracy compared to other commonly used algorithms. Further, we demonstrate the utility of DISC algorithm to probe cooperativity between multiple binding events in the cyclic nucleotide binding domains of HCN pacemaker channel. Given the flexible and efficient nature of DISC, we anticipate it will be a powerful tool for unsupervised processing of high-throughput data across a range of single-molecule experiments.

Metal ions and sugar puckering balance single-molecule kinetic heterogeneity in RNA and DNA tertiary contacts

The fidelity of group II intron self-splicing and retrohoming relies on long-range tertiary interactions between the intron and its flanking exons. By single-molecule FRET, we explore the binding kinetics of the most important, structurally conserved contact, the exon and intron binding site 1 (EBS1/IBS1). A comparison of RNA-RNA and RNA-DNA hybrid contacts identifies transient metal ion binding as a major source of kinetic heterogeneity which typically appears in the form of degenerate FRET states. Molecular dynamics simulations suggest a structural link between heterogeneity and the sugar conformation at the exon-intron binding interface. While Mg2+ ions lock the exon in place and give rise to long dwell times in the exon bound FRET state, sugar puckering alleviates this structural rigidity and likely promotes exon release. The interplay of sugar puckering and metal ion coordination may be an important mechanism to balance binding affinities of RNA and DNA interactions in general.

Encapsulation of Fluorescently Labeled RNAs into Surface-Tethered Vesicles for Single-Molecule FRET Studies in TIRF Microscopy

Imaging fluorescently labeled biomolecules on a single-molecule level is a well-established technique to follow intra- and intermolecular processes in time, usually hidden in the ensemble average. The classical approach comprises surface immobilization of the molecule of interest, which increases the risk of restricting the natural behavior due to surface interactions. Encapsulation of such biomolecules into surface-tethered phospholipid vesicles enables to follow one molecule at a time, freely diffusing and without disturbing surface interactions. Further, the encapsulation allows to keep reaction partners (reactants and products) in close proximity and enables higher temperatures otherwise leading to desorption of the direct immobilized biomolecules.Here, we describe a detailed protocol for the encapsulation of a catalytically active RNA starting from surface passivation over RNA encapsulation to data evaluation of single-molecule FRET experiments in TIRF microscopy. We present an optimized procedure that preserves RNA functionality and applies to investigations of, e.g., large ribozymes and RNAs, where direct immobilization is structurally not possible.

Measuring DNA Hybridization Kinetics in Live Cells Using a Time-Resolved 3D Single-Molecule Tracking Method

Single-molecule detection enables direct characterization of annealing/melting kinetics of nucleic acids without the need for synchronization of molecular states, but the current experiments are not carried out in a native cellular context. Here we describe an integrated 3D single-molecule tracking and lifetime measurement method that can follow individual DNA molecules diffusing inside a mammalian cell and observe multiple annealing and melting events on the same molecules. By comparing the hybridization kinetics of the same DNA strand in vitro, we found the association constants can be 13- to 163-fold higher in the molecular crowding cellular environment.

The structural arrangement at intersubunit interfaces in homomeric kainate receptors

Kainate receptors are glutamate-gated cation-selective channels involved in excitatory synaptic signaling and are known to be modulated by ions. Prior functional and structural studies suggest that the dimer interface at the agonist-binding domain plays a key role in activation, desensitization, and ion modulation in kainate receptors. Here we have used fluorescence-based methods to investigate the changes and conformational heterogeneity at these interfaces associated with the resting, antagonist-bound, active, desensitized, and ion-modulated states of the receptor. These studies show that in the presence of Na+ ions the interfaces exist primarily in the coupled state in the apo, antagonist-bound and activated (open channel) states. Under desensitizing conditions, the largely decoupled dimer interface at the agonist-binding domain as seen in the cryo-EM structure is one of the states observed. However, in addition to this state there are several additional states with lower levels of decoupling. Replacing Na+ with Cs+ does not alter the FRET efficiencies of the states significantly, but shifts the population to the more decoupled states in both resting and desensitized states, which can be correlated with the lower activation seen in the presence of Cs+.