The more the merrier: high-throughput single-molecule techniques

Single-molecule DNA-flow stretching assay as a versatile hybrid tool for investigating DNA-protein interactions

Single-molecule techniques allow researchers to investigate individual molecules and obtain unprecedented details of the heterogeneous nature of biological entities. They play instrumental roles in studying DNA-protein interactions due to the ability to visualize DNA or proteins and to manipulate individual DNA molecules by applying force or torque. Here, we describe single-molecule DNA-flow stretching assays as hybrid tools that combine forces with fluorescence. We also review how widely these assays are utilized in elucidating working mechanisms of DNA-binding proteins. Additionally, we provide a brief explanation of various efforts to prepare DNA substrates with desired internal protein-binding sequences. More complicated needs for DNA-protein interaction research have led to improvements in single-molecule DNA flow-stretching techniques. Several DNA flow-stretching variants such as DNA curtain, DNA motion capture assays, and protein-induced fluorescence enhancement (PIFE) are introduced in this mini review. Singlemolecule DNA flow-stretching assays will keep contributing to our understanding of how DNA-binding proteins function due to their multiplexed, versatile, and robust capabilities. [BMB Reports 2025; 58(1): 41-51].

Massively parallel analysis of single-molecule dynamics on next-generation sequencing chips

Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe multiplexed single-molecule characterization at the library scale (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profiled the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding-rewinding dynamics. The ability to explore a large sequence space for Cas9 allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes.

When Force Met Fluorescence: Single-Molecule Manipulation and Visualization of Protein-DNA Interactions

Myriad DNA-binding proteins undergo dynamic assembly, translocation, and conformational changes while on DNA or alter the physical configuration of the DNA substrate to control its metabolism. It is now possible to directly observe these activities-often central to the protein function-thanks to the advent of single-molecule fluorescence- and force-based techniques. In particular, the integration of fluorescence detection and force manipulation has unlocked multidimensional measurements of protein-DNA interactions and yielded unprecedented mechanistic insights into the biomolecular processes that orchestrate cellular life. In this review, we first introduce the different experimental geometries developed for single-molecule correlative force and fluorescence microscopy, with a focus on optical tweezers as the manipulation technique. We then describe the utility of these integrative platforms for imaging protein dynamics on DNA and chromatin, as well as their unique capabilities in generating complex DNA configurations and uncovering force-dependent protein behaviors. Finally, we give a perspective on the future directions of this emerging research field.

Magnetic tweezers principles and promises

Magnetic tweezers have become popular with the outbreak of single molecule micromanipulation: catching a single molecule of DNA, RNA or a single protein and applying mechanical constrains using micron-size magnetic beads and magnets turn out to be easy. Various factors have made this possible: the fact that manufacturers have been preparing these beads to catch various biological entities-the ease of use provided by magnets which apply a force or a torque at a distance thus inside a flow cell-some chance: since the forces so generated are in the right range to stretch a single molecule. This is a little less true for torque. Finally, one feature which also appears very important is the simplicity of their calibration using Brownian motion. Here we start by describing magnetic tweezers used routinely in our laboratory where we have tried to develop a device as simple as possible so that the experimentalist can really focus on the biological aspect of the biomolecules that he/she is interested in. We discuss the implications of the various components and their important features. Next, we summarize what is easy to achieve and what is less easy. Then we refer to contributions by other groups who have brought valuable insights to improve magnetic tweezers.

Strategies for Overcoming the Single-Molecule Concentration Barrier

Fluorescence-based single-molecule approaches have helped revolutionize our understanding of chemical and biological mechanisms. Unfortunately, these methods are only suitable at low concentrations of fluorescent molecules so that single fluorescent species of interest can be successfully resolved beyond background signal. The application of these techniques has therefore been limited to high-affinity interactions despite most biological and chemical processes occurring at much higher reactant concentrations. Fortunately, recent methodological advances have demonstrated that this concentration barrier can indeed be broken, with techniques reaching concentrations as high as 1 mM. The goal of this Review is to discuss the challenges in performing single-molecule fluorescence techniques at high-concentration, offer applications in both biology and chemistry, and highlight the major milestones that shatter the concentration barrier. We also hope to inspire the widespread use of these techniques so we can begin exploring the new physical phenomena lying beyond this barrier.

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.

Exploring molecular biology in sequence space: The road to next-generation single-molecule biophysics

Next-generation sequencing techniques have led to a new quantitative dimension in the biological sciences. In particular, integrating sequencing techniques with biophysical tools allows sequence-dependent mechanistic studies. Using the millions of DNA clusters that are generated during sequencing to perform high-throughput binding affinity and kinetics measurements enabled the construction of energy landscapes in sequence space, uncovering relationships between sequence, structure, and function. Here, we review the approaches to perform ensemble fluorescence experiments on next-generation sequencing chips for variations of DNA, RNA, and protein sequences. As the next step, we anticipate that these fluorescence experiments will be pushed to the single-molecule level, which can directly uncover kinetics and molecular heterogeneity in an unprecedented high-throughput fashion. Molecular biophysics in sequence space, both at the ensemble and single-molecule level, leads to new mechanistic insights. The wide spectrum of applications in biology and medicine ranges from the fundamental understanding of evolutionary pathways to the development of new therapeutics.

Single-molecule FRET and conformational analysis of beta-arrestin-1 through genetic code expansion and a Se-click reaction

Single-molecule Förster resonance energy transfer (smFRET) is a powerful tool for investigating the dynamic properties of biomacromolecules. However, the success of protein smFRET relies on the precise and efficient labeling of two or more fluorophores on the protein of interest (POI), which has remained highly challenging, particularly for large membrane protein complexes. Here, we demonstrate the site-selective incorporation of a novel unnatural amino acid (2-amino-3-(4-hydroselenophenyl) propanoic acid, SeF) through genetic expansion followed by a Se-click reaction to conjugate the Bodipy593 fluorophore on calmodulin (CaM) and β-arrestin-1 (βarr1). Using this strategy, we monitored the subtle but functionally important conformational change of βarr1 upon activation by the G-protein coupled receptor (GPCR) through smFRET for the first time. Our new method has broad applications for the site-specific labeling and smFRET measurement of membrane protein complexes, and the elucidation of their dynamic properties such as transducer protein selection.

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.

Biochemistry: one molecule at a time

Biological processes are orchestrated by complex networks of molecules. Conventional approaches for studying the action of biomolecules operate on a population level, averaging out any inhomogeneities within the ensemble. Investigating one biological macromolecule at a time allows researchers to directly probe individual behaviours, and thus characterise the intrinsic molecular heterogeneity of the system. Single-molecule methods have unravelled unexpected modes of action for many seemingly well-characterised biomolecules and often proved instrumental in understanding the intricate mechanistic basis of biological processes. This collection of reviews aims to showcase how single-molecule techniques can be used to address important biological questions and to inspire biochemists to ‘zoom in’ to the population and probe individual molecular behaviours, beyond the ensemble average. Furthermore, this issue of Essays in Biochemistry is the very first written and edited entirely by early career researchers, and so it also highlights the strength, diversity and excellence of the younger generation single-molecule scientists who drive this exciting field of research forward.

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.

High-Fidelity Single Molecule Quantification in a Flow Cytometer Using Multiparametric Optical Analysis

Microfluidic techniques are widely used for high-throughput quantification and discrete analysis of micron-scale objects but are difficult to apply to molecular-scale targets. Instead, single-molecule methods primarily rely on low-throughput microscopic imaging of immobilized molecules. Here we report that commercial-grade flow cytometers can detect single nucleic acid targets following enzymatic extension and dense labeling with multiple distinct fluorophores. We focus on microRNAs, short nucleic acids that can be extended by rolling circle amplification (RCA). We labeled RCA-extended microRNAs with multicolor fluorophores to generate repetitive nucleic acid products with submicron sizes and tunable multispectral profiles. By cross-correlating the multiparametric optical features, signal-to-background ratios were amplified 1600-fold to allow single-molecule detection across 4 orders of magnitude of concentration. The limit of detection was measured to be 47 fM, which is 100-fold better than gold-standard methods based on polymerase chain reaction. Furthermore, multiparametric analysis allowed discrimination of different microRNA sequences in the same solution using distinguishable optical barcodes. Barcodes can apply both ratiometric and colorimetric signatures, which could facilitate high-dimensional multiplexing. Because of the wide availability of flow cytometers, we anticipate that this technology can provide immediate access to high-throughput multiparametric single-molecule measurements and can further be adapted to the diverse range of molecular amplification methods that are continually emerging.

Sample preparation method to improve the efficiency of high-throughput single-molecule force spectroscopy

Inefficient sample preparation methods hinder the performance of high-throughput single-molecule force spectroscopy (H-SMFS) for viscous damping among reactants and unstable linkage. Here, we demonstrated a sample preparation method for H-SMFS systems to achieve a higher ratio of effective target molecules per sample cell by gas-phase silanization and reactant hydrophobization. Digital holographic centrifugal force microscopy (DH-CFM) was used to verify its performance. The experimental result indicated that the DNA stretching success ratio was improved from 0.89% to 13.5%. This enhanced efficiency preparation method has potential application for force-based DNA stretching experiments and other modifying procedures.

Force Spectroscopy and Beyond: Innovations and Opportunities

Life operates at the intersection of chemistry and mechanics. Over the years, we have made remarkable progress in understanding life from a biochemical perspective and the mechanics of life at the single-molecule scale. Yet the full integration of physical and mechanical models into mainstream biology has been impeded by technical and conceptual barriers, including limitations in our ability to 1) easily measure and apply mechanical forces to biological systems, 2) scale these measurements from single-molecule characterization to more complex biomolecular systems, and 3) model and interpret biophysical data in a coherent way across length scales that span single molecules to cells to multicellular organisms. In this manuscript, through a look at historical and recent developments in force spectroscopy techniques and a discussion of a few exemplary open problems in cellular biomechanics, we aim to identify research opportunities that will help us reach our goal of a more complete and integrated understanding of the role of force and mechanics in biological systems.

Detection of kinetic change points in piece-wise linear single molecule motion

Single-molecule approaches present a powerful way to obtain detailed kinetic information at the molecular level. However, the identification of small rate changes is often hindered by the considerable noise present in such single-molecule kinetic data. We present a general method to detect such kinetic change points in trajectories of motion of processive single molecules having Gaussian noise, with a minimum number of parameters and without the need of an assumed kinetic model beyond piece-wise linearity of motion. Kinetic change points are detected using a likelihood ratio test in which the probability of no change is compared to the probability of a change occurring, given the experimental noise. A predetermined confidence interval minimizes the occurrence of false detections. Applying the method recursively to all sub-regions of a single molecule trajectory ensures that all kinetic change points are located. The algorithm presented allows rigorous and quantitative determination of kinetic change points in noisy single molecule observations without the need for filtering or binning, which reduce temporal resolution and obscure dynamics. The statistical framework for the approach and implementation details are discussed. The detection power of the algorithm is assessed using simulations with both single kinetic changes and multiple kinetic changes that typically arise in observations of single-molecule DNA-replication reactions. Implementations of the algorithm are provided in ImageJ plugin format written in Java and in the Julia language for numeric computing, with accompanying Jupyter Notebooks to allow reproduction of the analysis presented here.

Design of DNA rolling-circle templates with controlled fork topology to study mechanisms of DNA replication

Rolling-circle DNA amplification is a powerful tool employed in biotechnology to produce large from small amounts of DNA. This mode of DNA replication proceeds via a DNA topology that resembles a replication fork, thus also providing experimental access to the molecular mechanisms of DNA replication. However, conventional templates do not allow controlled access to multiple fork topologies, which is an important factor in mechanistic studies. Here we present the design and production of a rolling-circle substrate with a tunable length of both the gap and the overhang, and we show its application to the bacterial DNA-replication reaction.