Empirical Bayes methods enable advanced population-level analyses of single-molecule FRET experiments

Increasing the accuracy of single-molecule data analysis using tMAVEN

Time-dependent single-molecule experiments contain rich kinetic information about the functional dynamics of biomolecules. A key step in extracting this information is the application of kinetic models, such as hidden Markov models (HMMs), which characterize the molecular mechanism governing the experimental system. Unfortunately, researchers rarely know the physicochemical details of this molecular mechanism a priori, which raises questions about how to select the most appropriate kinetic model for a given single-molecule data set and what consequences arise if the wrong model is chosen. To address these questions, we have developed and used time-series modeling, analysis, and visualization environment (tMAVEN), a comprehensive, open-source, and extensible software platform. tMAVEN can perform each step of the single-molecule analysis pipeline, from preprocessing to kinetic modeling to plotting, and has been designed to enable the analysis of a single-molecule data set with multiple types of kinetic models. Using tMAVEN, we have systematically investigated mismatches between kinetic models and molecular mechanisms by analyzing simulated examples of prototypical single-molecule data sets exhibiting common experimental complications, such as molecular heterogeneity, with a series of different types of HMMs. Our results show that no single kinetic modeling strategy is mathematically appropriate for all experimental contexts. Indeed, HMMs only correctly capture the underlying molecular mechanism in the simplest of cases. As such, researchers must modify HMMs using physicochemical principles to avoid the risk of missing the significant biological and biophysical insights into molecular heterogeneity that their experiments provide. By enabling the facile, side-by-side application of multiple types of kinetic models to individual single-molecule data sets, tMAVEN allows researchers to carefully tailor their modeling approach to match the complexity of the underlying biomolecular dynamics and increase the accuracy of their single-molecule data analyses.

Sequence-specific dynamic DNA bending explains mitochondrial TFAM's dual role in DNA packaging and transcription initiation

Mitochondrial transcription factor A (TFAM) employs DNA bending to package mitochondrial DNA (mtDNA) into nucleoids and recruit mitochondrial RNA polymerase (POLRMT) at specific promoter sites, light strand promoter (LSP) and heavy strand promoter (HSP). Herein, we characterize the conformational dynamics of TFAM on promoter and non-promoter sequences using single-molecule fluorescence resonance energy transfer (smFRET) and single-molecule protein-induced fluorescence enhancement (smPIFE) methods. The DNA-TFAM complexes dynamically transition between partially and fully bent DNA conformational states. The bending/unbending transition rates and bending stability are DNA sequence-dependent-LSP forms the most stable fully bent complex and the non-specific sequence the least, which correlates with the lifetimes and affinities of TFAM with these DNA sequences. By quantifying the dynamic nature of the DNA-TFAM complexes, our study provides insights into how TFAM acts as a multifunctional protein through the DNA bending states to achieve sequence specificity and fidelity in mitochondrial transcription while performing mtDNA packaging.

RNase E searches for cleavage sites in RNA by linear diffusion: direct evidence from single-molecule FRET

The ability of obstacles in cellular transcripts to protect downstream but not upstream sites en masse from attack by RNase E has prompted the hypothesis that this mRNA-degrading endonuclease may scan 5'-monophosphorylated RNA linearly for cleavage sites, starting at the 5' end. However, despite its proposed regulatory importance, the migration of RNase E on RNA has never been directly observed. We have now used single-molecule FRET to monitor the dynamics of this homotetrameric enzyme on RNA. Our findings reveal that RNase E slides along unpaired regions of RNA without consuming a molecular source of energy such as ATP and that its forward progress can be impeded when it encounters a large structural discontinuity. This movement, which is bidirectional, occurs in discrete steps of variable length and requires an RNA ligand much longer than needed to occupy a single RNase E subunit. These results indicate that RNase E scans for cleavage sites by one-dimensional diffusion and suggest a possible molecular mechanism.

G-quadruplex modulation by E. coli SSB: A comprehensive study on binding affinities and modes using single-molecule FRET

G-quadruplexes (GQs) are essential guanine-rich secondary structures found in DNA and RNA, playing crucial roles in genomic maintenance and stability. Recent studies have unveiled GQs in the intergenic regions of the E. coli genome, suggesting their biological significance and potential as anti-microbial targets. Here, we investigated the interaction between homo-tetrameric E. coli SSB and GQ-forming single-stranded DNA (ssDNA) sequence with varying lengths. Combining Microscale Thermophoresis (MST) and conventional spectroscopic techniques, we explored E. coli SSB binding to ssDNA and the structural changes of these secondary DNA structures upon protein binding. Subsequently, we have utilized smFRET to probe the conformational changes of GQ-ssDNA structures upon SSB binding. Our results provide detailed insights into SSB's access to various GQ-ssDNA sequencies and the wrapping of this homo-tetrameric protein around GQ-ssDNA in multiple distinct binding modalities. This study sheds light on the intricate details of E. coli SSB's interaction with ssDNA and the resulting widespread conformational changes within these oligonucleotide structures after protein binding. It offers a thorough insight into SSB's accesses to various GQ-ssDNA architectures. The finding demonstrates the multifaceted binding methods through which this homo-tetrameric protein envelops GQ-ssDNA and could prove valuable in deciphering biological processes that involve DNA G-quadruplexes.

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.

RNA compaction and iterative scanning for small RNA targets by the Hfq chaperone

RNA-guided enzymes must quickly search a vast sequence space for their targets. This search is aided by chaperones such as Hfq, a protein that mediates regulation by bacterial small RNAs (sRNAs). How RNA binding proteins enhance this search is little known. Using single-molecule Förster resonance energy transfer, we show that E. coli Hfq performs a one-dimensional scan in which compaction of the target RNA delivers sRNAs to sites distant from the location of Hfq recruitment. We also show that Hfq can transfer an sRNA between different target sites in a single mRNA, favoring the most stable duplex. We propose that compaction and segmental transfer, combined with repeated cycles of base pairing, enable the kinetic selection of optimal sRNA targets. Finally, we show that RNA compaction and sRNA transfer require conserved arginine patches. We suggest that arginine patches are a widespread strategy for enabling the movement of RNA across protein surfaces.

Increasing the accuracy of single-molecule data analysis using tMAVEN

Time-dependent single-molecule experiments contain rich kinetic information about the functional dynamics of biomolecules. A key step in extracting this information is the application of kinetic models, such as hidden Markov models (HMMs), which characterize the molecular mechanism governing the experimental system. Unfortunately, researchers rarely know the physico-chemical details of this molecular mechanism a priori, which raises questions about how to select the most appropriate kinetic model for a given single-molecule dataset and what consequences arise if the wrong model is chosen. To address these questions, we have developed and used time-series Modeling, Analysis, and Visualization ENvironment (tMAVEN), a comprehensive, open-source, and extensible software platform. tMAVEN can perform each step of the single-molecule analysis pipeline, from pre-processing to kinetic modeling to plotting, and has been designed to enable the analysis of a single-molecule dataset with multiple types of kinetic models. Using tMAVEN, we have systematically investigated mismatches between kinetic models and molecular mechanisms by analyzing simulated examples of prototypical single-molecule datasets exhibiting common experimental complications, such as molecular heterogeneity, with a series of different types of HMMs. Our results show that no single kinetic modeling strategy is mathematically appropriate for all experimental contexts. Indeed, HMMs only correctly capture the underlying molecular mechanism in the simplest of cases. As such, researchers must modify HMMs using physico-chemical principles to avoid the risk of missing the significant biological and biophysical insights into molecular heterogeneity that their experiments provide. By enabling the facile, side-by-side application of multiple types of kinetic models to individual single-molecule datasets, tMAVEN allows researchers to carefully tailor their modeling approach to match the complexity of the underlying biomolecular dynamics and increase the accuracy of their single-molecule data analyses.

Structural and functional basis of inositol hexaphosphate stimulation of NHEJ through stabilization of Ku-XLF interaction

The classical Non-Homologous End Joining (c-NHEJ) pathway is the predominant process in mammals for repairing endogenous, accidental or programmed DNA Double-Strand Breaks. c-NHEJ is regulated by several accessory factors, post-translational modifications, endogenous chemical agents and metabolites. The metabolite inositol-hexaphosphate (IP6) stimulates c-NHEJ by interacting with the Ku70-Ku80 heterodimer (Ku). We report cryo-EM structures of apo- and DNA-bound Ku in complex with IP6, at 3.5 Å and 2.74 Å resolutions respectively, and an X-ray crystallography structure of a Ku in complex with DNA and IP6 at 3.7 Å. The Ku-IP6 interaction is mediated predominantly via salt bridges at the interface of the Ku70 and Ku80 subunits. This interaction is distant from the DNA, DNA-PKcs, APLF and PAXX binding sites and in close proximity to XLF binding site. Biophysical experiments show that IP6 binding increases the thermal stability of Ku by 2°C in a DNA-dependent manner, stabilizes Ku on DNA and enhances XLF affinity for Ku. In cells, selected mutagenesis of the IP6 binding pocket reduces both Ku accrual at damaged sites and XLF enrolment in the NHEJ complex, which translate into a lower end-joining efficiency. Thus, this study defines the molecular bases of the IP6 metabolite stimulatory effect on the c-NHEJ repair activity.

Extract latent features of single-particle trajectories with historical experience learning

Single-particle tracking has enabled real-time, in situ quantitative studies of complex systems. However, inferring dynamic state changes from noisy and undersampling trajectories encounters challenges. Here, we introduce a data-driven method for extracting features of subtrajectories with historical experience learning (Deep-SEES), where a single-particle tracking analysis pipeline based on a self-supervised architecture automatically searches for the latent space, allowing effective segmentation of the underlying states from noisy trajectories without prior knowledge on the particle dynamics. We validated our method on a variety of noisy simulated and experimental data. Our results showed that the method can faithfully capture both stable states and their dynamic switch. In highly random systems, our method outperformed commonly used unsupervised methods in inferring motion states, which is important for understanding nanoparticles interacting with living cell membranes, active enzymes, and liquid-liquid phase separation. Self-generating latent features of trajectories could potentially improve the understanding, estimation, and prediction of many complex systems.

A versatile and high-throughput flow-cell system combined with fluorescence imaging for simultaneous single-molecule force measurement and visualization

A flow-cell offers many advantages for single-molecule studies. But, its merit as a quantitative single-molecule tool has long been underestimated. In this work, we developed a gas-pumped fully calibrated flow-cell system combined with fluorescence imaging for simultaneous single-molecule force measurement and visualization. Such a flow-cell system has considered the hydrodynamic drags on biomolecules and hence can apply and measure force up to more than 100 pN in sub-pN precision with an ultra-high force stability (force drift <0.01 pN in 10 minutes) and tuning accuracy (∼0.04 pN). Meanwhile, it also allows acquiring force signals and fluorescence images at the same time, parallelly tracking hundreds of protein motors in real time as well as monitoring the conformational changes of biomolecules under a well-controlled force, as demonstrated by a series of single-molecule experiments in this work, including the studies of DNA overstretching dynamics, transcription under force and DNA folding/unfolding dynamics. Interesting findings, such as the very tight association of single-stranded binding (SSB) proteins with ssDNA and the reversed transcription, have also been made. These results together lay down an essential foundation for a flow-cell to be used as a versatile, quantitative and high-throughput tool for single-molecule manipulation and visualization.

Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures

Single-molecule experiments have changed the way we explore the physical world, yet data analysis remains time-consuming and prone to human bias. Here, we introduce Deep-LASI (Deep-Learning Assisted Single-molecule Imaging analysis), a software suite powered by deep neural networks to rapidly analyze single-, two- and three-color single-molecule data, especially from single-molecule Förster Resonance Energy Transfer (smFRET) experiments. Deep-LASI automatically sorts recorded traces, determines FRET correction factors and classifies the state transitions of dynamic traces all in ~20-100 ms per trajectory. We benchmarked Deep-LASI using ground truth simulations as well as experimental data analyzed manually by an expert user and compared the results with a conventional Hidden Markov Model analysis. We illustrate the capabilities of the technique using a highly tunable L-shaped DNA origami structure and use Deep-LASI to perform titrations, analyze protein conformational dynamics and demonstrate its versatility for analyzing both total internal reflection fluorescence microscopy and confocal smFRET data.

Linking folding dynamics and function of SAM/SAH riboswitches at the single molecule level

Riboswitches are regulatory elements found in bacterial mRNAs that control downstream gene expression through ligand-induced conformational changes. Here, we used single-molecule FRET to map the conformational landscape of the translational SAM/SAH riboswitch and probe how co-transcriptional ligand-induced conformational changes affect its translation regulation function. Riboswitch folding is highly heterogeneous, suggesting a rugged conformational landscape that allows for sampling of the ligand-bound conformation even in the absence of ligand. The addition of ligand shifts the landscape, favoring the ligand-bound conformation. Mutation studies identified a key structural element, the pseudoknot helix, that is crucial for determining ligand-free conformations and their ligand responsiveness. We also investigated ribosomal binding site accessibility under two scenarios: pre-folding and co-transcriptional folding. The regulatory function of the SAM/SAH riboswitch involves kinetically favoring ligand binding, but co-transcriptional folding reduces this preference with a less compact initial conformation that exposes the Shine-Dalgarno sequence and takes min to redistribute to more compact conformations of the pre-folded riboswitch. Such slow equilibration decreases the effective ligand affinity. Overall, our study provides a deeper understanding of the complex folding process and how the riboswitch adapts its folding pattern in response to ligand, modulates ribosome accessibility and the role of co-transcriptional folding in these processes.

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.

DNA-directed termination of RNA polymerase II transcription

RNA polymerase II (RNAPII) transcription involves initiation from a promoter, transcriptional elongation through the gene, and termination in the terminator region. In bacteria, terminators often contain specific DNA elements provoking polymerase dissociation, but RNAPII transcription termination is thought to be driven entirely by protein co-factors. We used biochemical reconstitution, single-molecule studies, and genome-wide analysis in yeast to study RNAPII termination. Transcription into natural terminators by pure RNAPII results in spontaneous termination at specific sequences containing T-tracts. Single-molecule analysis indicates that termination involves pausing without backtracking. The "torpedo" Rat1-Rai1 exonuclease (XRN2 in humans) greatly stimulates spontaneous termination but is ineffectual on other paused RNAPIIs. By contrast, elongation factor Spt4-Spt5 (DSIF) suppresses termination. Genome-wide analysis further indicates that termination occurs by transcript cleavage at the poly(A) site exposing a new 5' RNA-end that allows Rat1-Rai1 loading, which then catches up with destabilized RNAPII at specific termination sites to end transcription.

Methods for automating the analysis of live-cell single-molecule FRET data

Single-molecule FRET (smFRET) is a powerful imaging platform capable of revealing dynamic changes in the conformation and proximity of biological molecules. The expansion of smFRET imaging into living cells creates both numerous new research opportunities and new challenges. Automating dataset curation processes is critical to providing consistent, repeatable analysis in an efficient manner, freeing experimentalists to advance the technical boundaries and throughput of what is possible in imaging living cells. Here, we devise an automated solution to the problem of multiple particles entering a region of interest, an otherwise labor-intensive and subjective process that had been performed manually in our previous work. The resolution of these two issues increases the quantity of FRET data and improves the accuracy with which FRET distributions are generated, increasing knowledge about the biological functions of the molecules under study. Our automated approach is straightforward, interpretable, and requires only localization and intensity values for donor and acceptor channel signals, which we compute through our previously published smCellFRET pipeline. The development of our automated approach is informed by the insights of expert experimentalists with extensive experience inspecting smFRET trajectories (displacement and intensity traces) from live cells. We test our automated approach against our recently published research on the metabotropic glutamate receptor 2 (mGluR2) and reveal substantial similarities, as well as potential shortcomings in the manual curation process that are addressable using the algorithms we developed here.

Structural basis of TFIIIC-dependent RNA polymerase III transcription initiation

RNA polymerase III (Pol III) is responsible for transcribing 5S ribosomal RNA (5S rRNA), tRNAs, and other short non-coding RNAs. Its recruitment to the 5S rRNA promoter requires transcription factors TFIIIA, TFIIIC, and TFIIIB. Here, we use cryoelectron microscopy (cryo-EM) to visualize the S. cerevisiae complex of TFIIIA and TFIIIC bound to the promoter. Gene-specific factor TFIIIA interacts with DNA and acts as an adaptor for TFIIIC-promoter interactions. We also visualize DNA binding of TFIIIB subunits, Brf1 and TBP (TATA-box binding protein), which results in the full-length 5S rRNA gene wrapping around the complex. Our smFRET study reveals that the DNA within the complex undergoes both sharp bending and partial dissociation on a slow timescale, consistent with the model predicted from our cryo-EM results. Our findings provide new insights into the transcription initiation complex assembly on the 5S rRNA promoter and allow us to directly compare Pol III and Pol II transcription adaptations.

Comparing FRET Pairs that Report on Intersubunit Rotation in Bacterial Ribosomes

Mediated by elongation factor G (EF-G), ribosome translocation along mRNA is accompanied by rotational movement between ribosomal subunits. Here, we reassess whether the intersubunit rotation requires GTP hydrolysis by EF-G or can occur spontaneously. To that end, we employ two independent FRET assays, which are based on labeling either ribosomal proteins (bS6 and bL9) or rRNAs (h44 of 16S and H101 of 23S rRNA). Both FRET pairs reveal three FRET states, corresponding to the non-rotated, rotated and semi-rotated conformations of the ribosome. Both FRET assays show that in the absence of EF-G, pre-translocation ribosomes containing deacylated P-site tRNA undergo spontaneous intersubunit rotations between non-rotated and rotated conformations. While the two FRET pairs exhibit largely similar behavior, they substantially differ in the fraction of ribosomes showing spontaneous fluctuations. Nevertheless, instead of being an invariable intrinsic property of each FRET pair, the fraction of spontaneously fluctuating molecules changes in both FRET assays depending on experimental conditions. Our results underscore importance of using multiple FRET pairs in studies of ribosome dynamics and highlight the role of thermally-driven large-scale ribosome rearrangements in translation.

Bleaching-resistant, Near-continuous Single-molecule Fluorescence and FRET Based on Fluorogenic and Transient DNA Binding

Photobleaching of fluorescent probes limits the observation span of typical single-molecule fluorescence measurements and hinders observation of dynamics at long timescales. Here, we present a general strategy to circumvent photobleaching by replenishing fluorescent probes via transient binding of fluorogenic DNAs to complementary DNA strands attached to a target molecule. Our strategy allows observation of near-continuous single-molecule fluorescence for more than an hour, a timescale two orders of magnitude longer than the typical photobleaching time of single fluorophores under our conditions. Using two orthogonal sequences, we show that our method is adaptable to Förster Resonance Energy Transfer (FRET) and that can be used to study the conformational dynamics of dynamic structures, such as DNA Holliday junctions, for extended periods. By adjusting the temporal resolution and observation span, our approach enables capturing the conformational dynamics of proteins and nucleic acids over a wide range of timescales.

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.

Allosteric activation of cell wall synthesis during bacterial growth

The peptidoglycan (PG) cell wall protects bacteria against osmotic lysis and determines cell shape, making this structure a key antibiotic target. Peptidoglycan is a polymer of glycan chains connected by peptide crosslinks, and its synthesis requires precise spatiotemporal coordination between glycan polymerization and crosslinking. However, the molecular mechanism by which these reactions are initiated and coupled is unclear. Here we use single-molecule FRET and cryo-EM to show that an essential PG synthase (RodA-PBP2) responsible for bacterial elongation undergoes dynamic exchange between closed and open states. Structural opening couples the activation of polymerization and crosslinking and is essential in vivo. Given the high conservation of this family of synthases, the opening motion that we uncovered likely represents a conserved regulatory mechanism that controls the activation of PG synthesis during other cellular processes, including cell division.

Comparing FRET pairs that report on intersubunit rotation in bacterial ribosomes

Mediated by elongation factor G (EF-G), ribosome translocation along mRNA is accompanied by rotational movement between ribosomal subunits. Here, we reassess whether the intersubunit rotation requires GTP hydrolysis by EF-G or can occur spontaneously. To that end, we employ two independent FRET assays, which are based on labeling either ribosomal proteins (bS6 and bL9) or rRNAs (h44 of 16S and H101 of 23S rRNA). Both FRET pairs reveal three FRET states, corresponding to the non-rotated, rotated and semi-rotated conformations of the ribosome. Both FRET assays show that in the absence of EF-G, pre-translocation ribosomes containing deacylated P-site tRNA undergo spontaneous intersubunit rotations between non-rotated and rotated conformations. While the two FRET pairs exhibit largely similar behavior, they substantially differ in the fraction of ribosomes showing spontaneous fluctuations. Nevertheless, instead of being an invariable intrinsic property of each FRET pair, the fraction of spontaneously fluctuating molecules changes in both FRET assays depending on experimental conditions. Our results underscore importance of using multiple FRET pairs in studies of ribosome dynamics and highlight the role of thermally-driven large-scale ribosome rearrangements in translation.

Ubiquitin modulates 26S proteasome conformational dynamics and promotes substrate degradation

The 26S proteasome recognizes thousands of appropriate protein substrates in eukaryotic cells through attached ubiquitin chains and uses its adenosine triphosphatase (ATPase) motor for mechanical unfolding and translocation into a proteolytic chamber. Here, we used single-molecule Förster resonance energy transfer measurements to monitor the conformational dynamics of the proteasome, observe individual substrates during their progression toward degradation, and elucidate how these processes are regulated by ubiquitin chains. Rapid transitions between engagement- and processing-competent proteasome conformations control substrate access to the ATPase motor. Ubiquitin chain binding functions as an allosteric regulator to slow these transitions, stabilize the engagement-competent state, and aid substrate capture to accelerate degradation initiation. Upon substrate engagement, the proteasome remains in processing-competent states for translocation and unfolding, except for apparent motor slips when encountering stably folded domains. Our studies revealed how ubiquitin chains allosterically regulate degradation initiation, which ensures substrate selectivity in a crowded cellular environment.

Rapid 40S scanning and its regulation by mRNA structure during eukaryotic translation initiation

How the eukaryotic 43S preinitiation complex scans along the 5' untranslated region (5' UTR) of a capped mRNA to locate the correct start codon remains elusive. Here, we directly track yeast 43S-mRNA binding, scanning, and 60S subunit joining by real-time single-molecule fluorescence spectroscopy. 43S engagement with mRNA occurs through a slow, ATP-dependent process driven by multiple initiation factors including the helicase eIF4A. Once engaged, 43S scanning occurs rapidly and directionally at ∼100 nucleotides per second, independent of multiple cycles of ATP hydrolysis by RNA helicases post ribosomal loading. Scanning ribosomes can proceed through RNA secondary structures, but 5' UTR hairpin sequences near start codons drive scanning ribosomes at start codons backward in the 5' direction, requiring rescanning to arrive once more at a start codon. Direct observation of scanning ribosomes provides a mechanistic framework for translational regulation by 5' UTR structures and upstream near-cognate start codons.

H2A.Z deposition by SWR1C involves multiple ATP-dependent steps

Histone variant H2A.Z is a conserved feature of nucleosomes flanking protein-coding genes. Deposition of H2A.Z requires ATP-dependent replacement of nucleosomal H2A by a chromatin remodeler related to the multi-subunit enzyme, yeast SWR1C. How these enzymes use ATP to promote this nucleosome editing reaction remains unclear. Here we use single-molecule and ensemble methodologies to identify three ATP-dependent phases in the H2A.Z deposition reaction. Real-time analysis of single nucleosome remodeling events reveals an initial priming step that occurs after ATP addition that involves a combination of both transient DNA unwrapping from the nucleosome and histone octamer deformations. Priming is followed by rapid loss of histone H2A, which is subsequently released from the H2A.Z nucleosomal product. Surprisingly, rates of both priming and the release of the H2A/H2B dimer are sensitive to ATP concentration. This complex reaction pathway provides multiple opportunities to regulate timely and accurate deposition of H2A.Z at key genomic locations.

Revealing the DNA Unwinding Activity and Mechanism of Fork Reversal by RecG While Exposed to Variants of Stalled Replication-fork at Single-Molecular Resolution

RecG, belonging to the category of Superfamily-2 plays a vital role in rescuing different kinds of stalled fork. The elemental mechanism of the helicase activity of RecG with several non-homologous stalled fork structures resembling intermediates formed during the process of DNA repair has been investigated in the present study to capture the dynamic stages of genetic rearrangement. The functional characterization has been exemplified through quantifying the response of the substrate in terms of their molecular heterogeneity and dynamical response by employing single-molecule fluorescence methods. An elevated processivity of RecG is observed for the stalled fork where progression of lagging daughter strand is ahead as compared to that of the leading strand. Through precise alteration of its function in terms of unwinding, depending upon the substrate DNA, RecG catalyzes the formation of Holliday junction from a stalled fork DNA. RecG is found to adopt an asymmetric mode of locomotion to unwind the lagging daughter strand for facilitating formation of Holliday junction that acts as a suitable intermediate for recombinational repair pathway. Our results emphasize the mechanism adopted by RecG during its 'sliding back' mode along the lagging daughter strand to be 'active translocation and passive unwinding'. This also provide clues as to how this helicase decides and controls the mode of translocation along the DNA to unwind.

Rapid quantification of miRNAs using dynamic FRET-FISH

MicroRNAs (miRNAs) are short regulatory RNAs that control gene expression at the post-transcriptional level. Various miRNAs playing important roles in cancer development are emerging as promising diagnostic biomarkers for early cancer detection. Accurate miRNA detection, however, remains challenging because they are small and highly homologous. Recently developed miRNA detection techniques based on single-molecule imaging enabled highly specific miRNA quantification without amplification, but the time required for these techniques to detect a single miRNA was larger than 10 minutes, making rapid profiling of numerous miRNAs impractical. Here we report a rapid miRNA detection technique, dynamic FRET-FISH, in which single-molecule imaging at high probe concentrations and thus high-speed miRNA detection is possible. Dynamic FRET-FISH can detect miRNAs in 10 s at 1.2 μM probe concentration while maintaining the high-specificity of single-nucleotide discrimination. We expect dynamic FRET-FISH will be utilized for early detection of cancers by profiling hundreds of cancer biomarkers in an hour.

Dynamic Refolding of OxyS sRNA by the Hfq RNA Chaperone

The Sm protein Hfq chaperones small non-coding RNAs (sRNAs) in bacteria, facilitating sRNA regulation of target mRNAs. Hfq acts in part by remodeling the sRNA and mRNA structures, yet the basis for this remodeling activity is not understood. To understand how Hfq remodels RNA, we used single-molecule Förster resonance energy transfer (smFRET) to monitor conformational changes in OxyS sRNA upon Hfq binding. The results show that E. coli Hfq first compacts OxyS, bringing its 5' and 3 ends together. Next, Hfq destabilizes an internal stem-loop in OxyS, allowing the RNA to adopt a more open conformation that is stabilized by a conserved arginine on the rim of Hfq. The frequency of transitions between compact and open conformations depend on interactions with Hfqs flexible C-terminal domain (CTD), being more rapid when the CTD is deleted, and slower when OxyS is bound to Caulobacter crescentus Hfq, which has a shorter and more stable CTD than E. coli Hfq. We propose that the CTDs gate transitions between OxyS conformations that are stabilized by interaction with one or more arginines. These results suggest a general model for how basic residues and intrinsically disordered regions of RNA chaperones act together to refold RNA.

Iterative Landmark-Based Umbrella Sampling (ILBUS) Protocol for Sampling of Conformational Space of Biomolecules

Computer simulations of biomolecules such as molecular dynamics often suffer from insufficient sampling. Due to limited computational resources, insufficient sampling prevents obtaining proper equilibrium distributions of observed properties. To deal with this problem, we proposed a simulation protocol for efficient resampling of collected off-equilibrium trajectories. These trajectories are utilized for the initial mapping of the conformational space, which is later properly resampled by the introduced Iterative Landmark-Based Umbrella Sampling (ILBUS) method. Reconstruction of static equilibrium properties is achieved by the multistate Bennett acceptance ratio (MBAR) method, which enables efficient use of simulated data. The ILBUS protocol is geometry-based and does not demand any additional collective variable or a dimensional-reduction technique. The only requirement is a set of suitably spaced reference conformations, which serve as landmarks in the mapped conformational space. Additionally, the ILBUS protocol encompasses an iterative process that optimizes the force constant used in the umbrella sampling simulation. Such tuning is an inherent feature of the protocol and does not need to be performed by the user in advance. Furthermore, even the simulations with suboptimal force constants can be used in estimates by MBAR. We demonstrate the feasibility and the performance of this approach in the study of the conformational landscape of the alanine dipeptide, met-enkephalin, and adenylate kinase.

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.

Translation initiation site of mRNA is selected through dynamic interaction with the ribosome

SignificanceRibosomes translate the genetic codes of messenger RNA (mRNA) to make proteins. Translation must begin at the correct initiation site; otherwise, abnormal proteins will be produced. Here, we show that a short ribosome-specific sequence in the upstream followed by an unstructured downstream sequence is a favorable initiation site. Those mRNAs lacking either of these two characteristics do not associate tightly with the ribosome. Initiator transfer RNA (tRNA) and initiation factors facilitate the binding. However, when the downstream site forms structures, initiation factor 3 triggers the dissociation of the accommodated initiator tRNA and the subsequent disassembly of the ribosome-mRNA complex. Thus, initiation factors help the ribosome distinguish unfavorable structured sequences that may not act as the mRNA translation initiation site.

High-Force Application by a Nanoscale DNA Force Spectrometer

The ability to apply and measure high forces (>10 pN) on the nanometer scale is critical to the development of nanomedicine, molecular robotics, and the understanding of biological processes such as chromatin condensation, membrane deformation, and viral packaging. Established force spectroscopy techniques including optical traps, magnetic tweezers, and atomic force microscopy rely on micron-sized or larger handles to apply forces, limiting their applications within constrained geometries including cellular environments and nanofluidic devices. A promising alternative to these approaches is DNA-based molecular calipers. However, this approach is currently limited to forces on the scale of a few piconewtons. To study the force application capabilities of DNA devices, we implemented DNA origami nanocalipers with tunable mechanical properties in a geometry that allows application of force to rupture a DNA duplex. We integrated static and dynamic single-molecule characterization methods and statistical mechanical modeling to quantify the device properties including force output and dynamic range. We found that the thermally driven dynamics of the device are capable of applying forces of at least 20 piconewtons with a nanometer-scale dynamic range. These characteristics could eventually be used to study other biomolecular processes such as protein unfolding or to control high-affinity interactions in nanomechanical devices or molecular robots.

Structure and conformational dynamics of Clostridioides difficile toxin A

This study presents a complete structural model of TcdA holotoxin and sheds new lights into the conformational dynamics of TcdA and its roles in TcdA intoxication.

Clostridioides difficile toxin A and B (TcdA and TcdB) are two major virulence factors responsible for diseases associated with C. difficile infection (CDI). Here, we report the 3.18-Å resolution crystal structure of a TcdA fragment (residues L843–T2481), which advances our understanding of the complete structure of TcdA holotoxin. Our structural analysis, together with complementary single molecule FRET and limited proteolysis studies, reveal that TcdA adopts a dynamic structure and its CROPs domain can sample a spectrum of open and closed conformations in a pH-dependent manner. Furthermore, a small globular subdomain (SGS) and the CROPs protect the pore-forming region of TcdA in the closed state at neutral pH, which could contribute to modulating the pH-dependent pore formation of TcdA. A rationally designed TcdA mutation that trapped the CROPs in the closed conformation showed drastically reduced cytotoxicity. Taken together, these studies shed new lights into the conformational dynamics of TcdA and its roles in TcdA intoxication.

Real-Time Single-Molecule Studies of RNA Polymerase-Promoter Open Complex Formation Reveal Substantial Heterogeneity Along the Promoter-Opening Pathway

The expression of most bacterial genes commences with the binding of RNA polymerase (RNAP)-σ70 holoenzyme to the promoter DNA. This initial RNAP-promoter closed complex undergoes a series of conformational changes, including the formation of a transcription bubble on the promoter and the loading of template DNA strand into the RNAP active site; these changes lead to the catalytically active open complex (RPO) state. Recent cryo-electron microscopy studies have provided detailed structural insight on the RPO and putative intermediates on its formation pathway. Here, we employ single-molecule fluorescence microscopy to interrogate the conformational dynamics and reaction kinetics during real-time RPO formation on a consensus lac promoter. We find that the promoter opening may proceed rapidly from the closed to open conformation in a single apparent step, or may instead involve a significant intermediate between these states. The formed RPO complexes are also different with respect to their transcription bubble stability. The RNAP cleft loops, and especially the β' rudder, stabilise the transcription bubble. The RNAP interactions with the promoter upstream sequence (beyond -35) stimulate transcription bubble nucleation and tune the reaction path towards stable forms of the RPO.

Joint Detection of Change Points in Multichannel Single-Molecule Measurements

Recent developments in single-molecule measurement technology have expanded the capability to measure multiple parameters. These emergent modalities provide more holistic observations of complex biomolecular processes and call for new analysis methods to detect state changes in multichannel data. Here we develop an algorithm called MULLR (MUlti-channel Log-Likelihood Ratio test) to jointly identify change points in multichannel single-molecule measurements. MULLR is an extension of the popular single-channel implementation for change point detection based on a binary segmentation and log-likelihood ratio test framework. We validate the algorithm on simulated data and characterize the power of detection and false positive rate. We show that MULLR can identify change points in experimental multichannel data and naturally works with different noise statistics and time resolutions across channels. Further, we quantify the benefit of MULLR compared to single-channel analysis. We envision that the MULLR algorithm will be useful to a range of multiparameter single-molecule measurements.

Cohesin mediates DNA loop extrusion by a "swing and clamp" mechanism

Structural maintenance of chromosomes (SMC) complexes organize genome topology in all kingdoms of life and have been proposed to perform this function by DNA loop extrusion. How this process works is unknown. Here, we have analyzed how loop extrusion is mediated by human cohesin-NIPBL complexes, which enable chromatin folding in interphase cells. We have identified DNA binding sites and large-scale conformational changes that are required for loop extrusion and have determined how these are coordinated. Our results suggest that DNA is translocated by a spontaneous 50 nm-swing of cohesin's hinge, which hands DNA over to the ATPase head of SMC3, where upon binding of ATP, DNA is clamped by NIPBL. During this process, NIPBL "jumps ship" from the hinge toward the SMC3 head and might thereby couple the spontaneous hinge swing to ATP-dependent DNA clamping. These results reveal mechanistic principles of how cohesin-NIPBL and possibly other SMC complexes mediate loop extrusion.

Transcription initiation at a consensus bacterial promoter proceeds via a 'bind-unwind-load-and-lock' mechanism

Transcription initiation starts with unwinding of promoter DNA by RNA polymerase (RNAP) to form a catalytically competent RNAP-promoter complex (RPo). Despite extensive study, the mechanism of promoter unwinding has remained unclear, in part due to the transient nature of intermediates on path to RPo. Here, using single-molecule unwinding-induced fluorescence enhancement to monitor promoter unwinding, and single-molecule fluorescence resonance energy transfer to monitor RNAP clamp conformation, we analyse RPo formation at a consensus bacterial core promoter. We find that the RNAP clamp is closed during promoter binding, remains closed during promoter unwinding, and then closes further, locking the unwound DNA in the RNAP active-centre cleft. Our work defines a new, ‘bind-unwind-load-and-lock’, model for the series of conformational changes occurring during promoter unwinding at a consensus bacterial promoter and provides the tools needed to examine the process in other organisms and at other promoters.

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.

Mechanistic studies of non-canonical amino acid mutagenesis

Over the past decade, harnessing the cellular protein synthesis machinery to incorporate non-canonical amino acids (ncAAs) into tailor-made peptides has significantly advanced many aspects of molecular science. More recently, groundbreaking progress in our ability to engineer this machinery for improved ncAA incorporation has led to significant enhancements of this powerful tool for biology and chemistry. By revealing the molecular basis for the poor or improved incorporation of ncAAs, mechanistic studies of ncAA incorporation by the protein synthesis machinery have tremendous potential for informing and directing such engineering efforts. In this chapter, we describe a set of complementary biochemical and single-molecule fluorescence assays that we have adapted for mechanistic studies of ncAA incorporation. Collectively, these assays provide data that can guide engineering of the protein synthesis machinery to expand the range of ncAAs that can be incorporated into peptides and increase the efficiency with which they can be incorporated, thereby enabling the full potential of ncAA mutagenesis technology to be realized.

Single-molecule binding characterization of primosomal protein PriA involved in replication restart

DNA damage leads to stalled or collapsed replication forks. Replication restart primosomes re-initiate DNA synthesis at these stalled or collapsed DNA replication forks, which is important for bacterial survival. Primosomal protein PriA specifically recognizes the DNA fork structure and recruits other primosomal proteins to load the replicative helicase, in order to re-establish the replication fork. PriA binding on DNA is the first step to restart replication forks for proper DNA repair. Using a single-molecule fluorescence colocalization experiment, we measured the thermodynamic and real-time kinetic properties of fluorescence-labeled Gram-positive bacteria Geobacillus stearothermophilus PriA binding on DNA forks. We showed that PriA preferentially binds to a DNA fork structure with a fully duplexed leading strand at sub-nanomolar affinity (Kd = 268 ± 99 pM). PriA binds dynamically, and its association and dissociation rate constants can be determined using the appearance and disappearance of the fluorescence signal. In addition, we showed that PriA binds to DNA forks as a monomer using photobleaching step counting. This information offers a molecular basis essential for understanding the mechanism of replication restart.

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.

Single-Molecule Dynamics of SARS-CoV-2 5' Cap Recognition by Human eIF4F

Coronaviruses initiate translation through recognition of the viral RNA 5' m ⁷ GpppA _m cap by translation factor eIF4F. eIF4F is a heterotrimeric protein complex with cap-binding, RNA-binding, and RNA helicase activities. Modulating eIF4F function through cellular regulation or small-molecule inhibition impacts coronavirus replication, including for SARS-CoV-2. Translation initiation involves highly coordinated dynamics of translation factors with messenger or viral RNA. However, how the eIF4F subunits coordinate on the initiation timescale to define cap-binding efficiency remains incompletely understood. Here we report that translation supported by the SARS-CoV-2 5'-UTR is highly sensitive to eIF4A inhibition by rocaglamide. Through a single-molecule fluorescence approach that reports on eIF4E-cap interaction, we dissect how eIF4F subunits contribute to cap-recognition efficiency on the SARS-CoV-2 5' UTR. We find that free eIF4A enhances cap accessibility for eIF4E binding, but eIF4G alone does not change the kinetics of eIF4E-RNA interaction. Conversely, formation of the full eIF4F complex significantly alters eIF4E-cap interaction, suggesting that coordinated eIF4E and eIF4A activities establish the net eIF4F-cap recognition efficiency. Moreover, the eIF4F complex formed with phosphomimetic eIF4E(S209D) binds the viral UTR more efficiently than with wild-type eIF4E. These results highlight a dynamic interplay of eIF4F subunits and mRNA that determines cap-recognition efficiency.

Single-molecule imaging reveals replication fork coupled formation of G-quadruplex structures hinders local replication stress signaling

Guanine-rich DNA sequences occur throughout the human genome and can transiently form G-quadruplex (G4) structures that may obstruct DNA replication, leading to genomic instability. Here, we apply multi-color single-molecule localization microscopy (SMLM) coupled with robust data-mining algorithms to quantitatively visualize replication fork (RF)-coupled formation and spatial-association of endogenous G4s. Using this data, we investigate the effects of G4s on replisome dynamics and organization. We show that a small fraction of active replication forks spontaneously form G4s at newly unwound DNA immediately behind the MCM helicase and before nascent DNA synthesis. These G4s locally perturb replisome dynamics and organization by reducing DNA synthesis and limiting the binding of the single-strand DNA-binding protein RPA. We find that the resolution of RF-coupled G4s is mediated by an interplay between RPA and the FANCJ helicase. FANCJ deficiency leads to G4 accumulation, DNA damage at G4-associated replication forks, and silencing of the RPA-mediated replication stress response. Our study provides first-hand evidence of the intrinsic, RF-coupled formation of G4 structures, offering unique mechanistic insights into the interference and regulation of stable G4s at replication forks and their effect on RPA-associated fork signaling and genomic instability.

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.

RNA polymerase clamp conformational dynamics: long-lived states and modulation by crowding, cations, and nonspecific DNA binding

The RNA polymerase (RNAP) clamp, a mobile structural element conserved in RNAP from all domains of life, has been proposed to play critical roles at different stages of transcription. In previous work, we demonstrated using single-molecule Förster resonance energy transfer (smFRET) that RNAP clamp interconvert between three short-lived conformational states (lifetimes ∼ 0.3–0.6 s), that the clamp can be locked into any one of these states by small molecules, and that the clamp stays closed during initial transcription and elongation. Here, we extend these studies to obtain a comprehensive understanding of clamp dynamics under conditions RNAP may encounter in living cells. We find that the RNAP clamp can populate long-lived conformational states (lifetimes > 1.0 s) and can switch between these long-lived states and the previously observed short-lived states. In addition, we find that clamp motions are increased in the presence of molecular crowding, are unchanged in the presence of elevated monovalent-cation concentrations, and are reduced in the presence of elevated divalent-cation concentrations. Finally, we find that RNAP bound to non-specific DNA predominantly exhibits a closed clamp conformation. Our results raise the possibility of additional regulatory checkpoints that could affect clamp dynamics and consequently could affect transcription and transcriptional regulation.

Single-Molecule FRET Imaging of Virus Spike-Host Interactions

As a major surface glycoprotein of enveloped viruses, the virus spike protein is a primary target for vaccines and anti-viral treatments. Current vaccines aiming at controlling the COVID-19 pandemic are mostly directed against the SARS-CoV-2 spike protein. To promote virus entry and facilitate immune evasion, spikes must be dynamic. Interactions with host receptors and coreceptors trigger a cascade of conformational changes/structural rearrangements in spikes, which bring virus and host membranes in proximity for membrane fusion required for virus entry. Spike-mediated viral membrane fusion is a dynamic, multi-step process, and understanding the structure–function-dynamics paradigm of virus spikes is essential to elucidate viral membrane fusion, with the ultimate goal of interventions. However, our understanding of this process primarily relies on individual structural snapshots of endpoints. How these endpoints are connected in a time-resolved manner, and the order and frequency of conformational events underlying virus entry, remain largely elusive. Single-molecule Förster resonance energy transfer (smFRET) has provided a powerful platform to connect structure–function in motion, revealing dynamic aspects of spikes for several viruses: SARS-CoV-2, HIV-1, influenza, and Ebola. This review focuses on how smFRET imaging has advanced our understanding of virus spikes’ dynamic nature, receptor-binding events, and mechanism of antibody neutralization, thereby informing therapeutic interventions.