Investigating Uncertainties in Single-Molecule Localization Microscopy Using Experimentally Informed Monte Carlo Simulation.

Single-molecule localization microscopy (SMLM) enables the visualization of cellular nanostructures in vitro with sub-20 nm resolution. While substructures can generally be imaged with SMLM, the structural understanding of the images remains elusive. To better understand the link between SMLM images and the underlying structure, we developed a Monte Carlo (MC) simulation based on experimental imaging parameters and geometric information to generate synthetic SMLM images. We chose the nuclear pore complex (NPC), a nanosized channel on the nuclear membrane which gates nucleo-cytoplasmic transport of biomolecules, as a test geometry for testing our MC model. Using the MC model to simulate SMLM images, we first optimized our clustering algorithm to separate >106 molecular localizations of fluorescently labeled NPC proteins into hundreds of individual NPCs in each cell. We then illustrated using our MC model to generate cellular substructures with different angles of labeling to inform our structural understanding through the SMLM images obtained.

Constructing a cost-efficient, high-throughput and high-quality single-molecule localization microscope for super-resolution imaging.

Single-molecule localization microscopy (SMLM) leverages the power of modern optics to unleash ultra-precise structural nanoscopy of complex biological machines in their native environments as well as ultra-sensitive and high-throughput medical diagnostics with the sensitivity of a single molecule. To achieve this remarkable speed and resolution, SMLM setups are either built by research laboratories with strong expertise in optical engineering or commercially sold at a hefty price tag. The inaccessibility of SMLM to life scientists for technical or financial reasons is detrimental to the progress of biological and biomedical discoveries reliant on super-resolution imaging. In this work, we present the NanoPro, an economic, high-throughput, high-quality and easy-to-assemble SMLM for super-resolution imaging. We show that our instrument performs similarly to the most expensive, best-in-class commercial microscopes and rivals existing open-source microscopes at a lower price and construction complexity. To facilitate its wide adoption, we compiled a step-by-step protocol, accompanied by extensive illustrations, to aid inexperienced researchers in constructing the NanoPro as well as assessing its performance by imaging ground-truth samples as small as 20 nm. The detailed visual instructions make it possible for students with little expertise in microscopy engineering to construct, validate and use the NanoPro in <1 week, provided that all components are available.

Precision in iterative modulation enhanced single-molecule localization microscopy.

Modulation enhanced single-molecule localization microscopy (meSMLM) methods improve the localization precision by using patterned illumination to encode additional position information. Iterative meSMLM (imeSMLM) methods iteratively generate prior information on emitter positions, used to locally improve the localization precision during subsequent iterations. The Cramér-Rao lower bound cannot incorporate prior information to bound the best achievable localization precision because it requires estimators to be unbiased. By treating estimands as random variables with a known prior distribution, the Van Trees inequality (VTI) can be used to bound the best possible localization precision of imeSMLM methods. An imeSMLM method is considered, where the positions of in-plane standing-wave illumination patterns are controlled over the course of multiple iterations. Using the VTI, we analytically approximate a lower bound on the maximum localization precision of imeSMLM methods that make use of standing-wave illumination patterns. In addition, we evaluate the maximally achievable localization precision for different illumination pattern placement strategies using Monte Carlo simulations. We show that in the absence of background and under perfect modulation, the information content of signal photons increases exponentially as a function of the iteration count. However, the information increase is no longer exponential as a function of the iteration count under non-zero background, imperfect modulation, or limited mechanical resolution of the illumination positioning system. As a result, imeSMLM with two iterations reaches at most a fivefold improvement over SMLM at 8 expected background photons per pixel and 95% modulation contrast. Moreover, the information increase from imeSMLM is balanced by a reduced signal photon rate. Therefore, SMLM outperforms imeSMLM when considering an equal measurement time and illumination power per iteration. Finally, the VTI is an excellent tool for the assessment of the performance of illumination control and is therefore the method of choice for optimal design and control of imeSMLM methods.

Tweezepy: A Python package for calibrating forces in single-molecule video-tracking experiments.

Single-molecule force spectroscopy (SMFS) instruments (e.g., magnetic and optical tweezers) often use video tracking to measure the three-dimensional position of micron-scale beads under an applied force. The force in these experiments is calibrated by comparing the bead trajectory to a thermal motion-based model with the drag coefficient, γ, and trap spring constant, κ, as parameters. Estimating accurate parameters is complicated by systematic biases from spectral distortions, the camera exposure time, parasitic noise, and least-squares fitting methods. However, while robust calibration methods exist that correct for these biases, they are not always used because they can be complex to implement computationally. To address this barrier, we present Tweezepy: a Python package for calibrating forces in SMFS video-tracking experiments. Tweezepy uses maximum likelihood estimation (MLE) to estimate parameters and their uncertainties from a single bead trajectory via the power spectral density (PSD) and Allan variance (AV). It is well-documented, fast, easy to use, and accounts for most common sources of biases in SMFS video-tracking experiments. Here, we provide a comprehensive overview of Tweezepy's calibration scheme, including a review of the theory underlying thermal motion-based parameter estimates, a discussion of the PSD, AV, and MLE, and an explanation of their implementation.

Quantitative assessment of engineered Cas9 variants for target specificity enhancement by single-molecule reaction pathway analysis.

There have been many engineered Cas9 variants that were developed to minimize unintended cleavage of off-target DNAs, but detailed mechanism for the way they regulate the target specificity through DNA:RNA heteroduplexation remains poorly understood. We used single-molecule FRET assay to follow the dynamics of DNA:RNA heteroduplexation for various engineered Cas9 variants with respect to on-target and off-target DNAs. Just like wild-type Cas9, these engineered Cas9 variants exhibit a strong correlation between their conformational structure and nuclease activity. Compared with wild-type Cas9, the fraction of the cleavage-competent state dropped more rapidly with increasing base-pair mismatch, which gives rise to their enhanced target specificity. We proposed a reaction model to quantitatively analyze the degree of off-target discrimination during the successive process of R-loop expansion. We found that the critical specificity enhancement step is activated during DNA:RNA heteroduplexation for evoCas9 and HypaCas9, while it occurs in the post-heteroduplexation stage for Cas9-HF1, eCas9, and Sniper-Cas9. This study sheds new light on the conformational dynamics behind the target specificity of Cas9, which will help strengthen its rational designing principles in the future.

A cross-nearest neighbor/Monte Carlo algorithm for single-molecule localization microscopy defines interactions between p53, Mdm2, and MEG3.

The functions of long noncoding (lnc)RNAs, such as MEG3, are defined by their interactions with other RNAs and proteins. These interactions, in turn, are shaped by their subcellular localization and temporal context. Therefore, it is important to be able to analyze the relationships of lncRNAs while preserving cellular architecture. The ability of MEG3 to suppress cell proliferation led to its recognition as a tumor suppressor. MEG3 has been proposed to activate p53 by disrupting the interaction of p53 with mouse double minute 2 homolog (Mdm2). To test this mechanism in the native cellular context, we employed two-color direct stochastic optical reconstruction microscopy, a single-molecule localization microscopy technique, to detect and quantify the localizations of p53, Mdm2, and MEG3 in U2OS cells. We developed a new cross-nearest neighbor/Monte Carlo algorithm to quantify the association of these molecules. Proof of concept for our method was obtained by examining the association between FKBP1A and mTOR, MEG3 and p53, and Mdm2 and p53. In contrast to previous models, our data support a model in which MEG3 modulates p53 independently of the interaction with Mdm2.

Assessment of ROS Production in the Mitochondria of Live Cells.

Production of reactive oxygen species (ROS) in the mitochondria plays multiple roles in physiology, and excessive production of ROS leads to the development of various pathologies. ROS in the mitochondria are generated by various enzymes, mainly in the electron transporvt chain, and it is important to identify not only the trigger but also the source of free radical production. It is important to measure mitochondrial ROS in live, intact cells, because activation of ROS production could be initiated by changes in extramitochondrial processes which could be overseen when using isolated mitochondria. Here we describe the approaches, which allow to measure production of ROS in the matrix of mitochondria in live cells. We also demonstrate how to measure kinetic changes in lipid peroxidation in mitochondria of live cells. These methods could be used for understanding the mechanisms of pathology in a variety of disease models and also for testing neuro- or cardioprotective chemicals.

DeepFRET, a software for rapid and automated single-molecule FRET data classification using deep learning.

Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the development of rapid, standardized, and automated methodologies to objectively analyze the wealth of produced data. Here we present DeepFRET, an automated, open-source standalone solution based on deep learning, where the only crucial human intervention in transiting from raw microscope images to histograms of biomolecule behavior, is a user-adjustable quality threshold. Integrating standard features of smFRET analysis, DeepFRET consequently outputs the common kinetic information metrics. Its classification accuracy on ground truth data reached >95% outperforming human operators and commonly used threshold, only requiring ~1% of the time. Its precise and rapid operation on real data demonstrates DeepFRET's capacity to objectively quantify biomolecular dynamics and the potential to contribute to benchmarking smFRET for dynamic structural biology.

Proteins are folded into particular shapes in order to carry out their roles in the cell. However, their structures are not rigid: proteins bend and rotate in response to their environment. Identifying these movements is an important part of understanding how proteins work and interact with each other. Unfortunately, when researchers study the structures of proteins, they often look at the 'average' shape a protein takes, missing out on other conformations the protein might only be in temporarily. An important technique for studying protein flexibility is known as single molecule Förster resonance energy transfer (FRET). In this technique, two light-sensitive tags are attached to the same protein molecule and give off a signal when they come into close contact. This nano-scale sensor allows structural biologists to get information from individual protein movements that can be lost when looking at the average conformations of proteins. Advances in the instruments used to perform FRET have made observing the motion of individual proteins more widely accessible to non-specialists, but the analysis of the data that these instruments produce still requires a high level of expertise. To lower the barrier for non-specialists to use the technology, and to ensure that experiments can be reproduced on different instruments and by different researchers, Thomsen et al. have developed a new way to automate the data analysis. They used machine learning technology to recognize, filter and characterize data so as to produce reliable results, with the user only needing to perform a couple of steps. This new analysis approach could help expand the use of single-molecule FRET to different fields , allowing researchers to investigate the importance of protein flexibility for certain diseases, or to better understand the roles that proteins have in a cell.

Quantitative Assessment of Tip Effects in Single-Molecule High-Speed Atomic Force Microscopy Using DNA Origami Substrates.

High-speed atomic force microscopy (HS-AFM) is widely employed in the investigation of dynamic biomolecular processes at a single-molecule level. However, it remains an open and somewhat controversial question, how these processes are affected by the rapidly scanned AFM tip. While tip effects are commonly believed to be of minor importance in strongly binding systems, weaker interactions may significantly be disturbed. Herein, we quantitatively assess the role of tip effects in a strongly binding system using a DNA origami-based single-molecule assay. Despite its femtomolar dissociation constant, we find that HS-AFM imaging can disrupt monodentate binding of streptavidin (SAv) to biotin (Bt) even under gentle scanning conditions. To a lesser extent, this is also observed for the much stronger bidentate SAv-Bt complex. The presented DNA origami-based assay can be universally employed to quantify tip effects in strongly and weakly binding systems and to optimize the experimental settings for their reliable HS-AFM imaging.

Comparative Colocalization Single-Molecule Spectroscopy (CoSMoS) with Multiple RNA Species.

Colocalization single-molecule spectroscopy (CoSMoS) allows studying RNA-protein complexes in the full complexity of their cellular environment at single-molecule resolution. Conventionally, the interaction between a single RNA species and multiple proteins is monitored in real time. However, comparing interactions of the same proteins with different RNA species in the same cell extract promises unique insights into RNA biology. Here, we describe an approach to monitor multiple RNA species simultaneously to enable direct comparison. This approach represents a technological development to avoid conventional inter-experiment comparisons.

RNA Folding and Unfolding Under Force: Single-Molecule Experiments and Their Analysis.

We have previously described (Geffroy et al. Methods Mol Biol 1665:25-40, 2018) how to unfold (or fold) a single RNA molecule under force using a dual-beam optical trap setup. In this chapter, we complementarily describe how to analyze the corresponding data and how to interpret it in terms of RNA three-dimensional structure. As with all single-molecule methods, single RNA molecule force data often exhibit several discrete states where state-to-state transitions are blurred in a noisy signal. In order to cope with this limitation, we have implemented a novel strategy to analyze the data, which uses a hidden Markov modeling procedure. A representative example of such an analysis is presented.

Quality Assessment of Virus-Like Particles at Single Particle Level: A Comparative Study.

Virus-like particles (VLPs) have emerged as a powerful scaffold for antigen presentation and delivery strategies. Compared to single protein-based therapeutics, quality assessment requires a higher degree of refinement due to the structure of VLPs and their similar properties to extracellular vesicles (EVs). Advances in the field of nanotechnology with single particle and high-resolution analysis techniques provide appealing approaches to VLP characterization. In this study, six different biophysical methods have been assessed for the characterization of HIV-1-based VLPs produced in mammalian and insect cell platforms. Sample preparation and equipment set-up were optimized for the six strategies evaluated. Electron Microscopy (EM) disclosed the presence of several types of EVs within VLP preparations and cryogenic transmission electron microscopy (cryo-TEM) resulted in the best technique to resolve the VLP ultrastructure. The use of super-resolution fluorescence microscopy (SRFM), nanoparticle tracking analysis (NTA) and flow virometry enabled the high throughput quantification of VLPs. Interestingly, differences in the determination of nanoparticle concentration were observed between techniques. Moreover, NTA and flow virometry allowed the quantification of both EVs and VLPs within the same experiment while analyzing particle size distribution (PSD), simultaneously. These results provide new insights into the use of different analytical tools to monitor the production of nanoparticle-based biologicals and their associated contaminants.

Analysis of the Diffusivity Change from Single-Molecule Trajectories on Living Cells.

With the wide application of live-cell single-molecule imaging and tracking of biomolecules at work, deriving diffusion state changes of individual molecules is of particular interest as these changes reflect molecular oligomerization or interaction with other cellular components and thus correlate with functional changes. We have developed a Rayleigh mixture distribution-based hidden Markov model method to analyze time-lapse diffusivity change of single molecules, especially membrane proteins, with unknown dynamic states in living cells. With this method, the diffusion parameters, including diffusion state number, state transition probability, diffusion coefficient, and state mixture ratio, can be extracted from the single-molecule diffusion trajectories accurately via easy computation. The validity of our method has been demonstrated with not only experiments on synthetic trajectories but also single-molecule fluorescence imaging data of two typical membrane receptors. Our method offers a new analytical tool for the investigation of molecular interaction kinetics at the single-molecule level.

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.

Visualisation of dCas9 target search in vivo using an open-microscopy framework.

CRISPR-Cas9 is widely used in genomic editing, but the kinetics of target search and its relation to the cellular concentration of Cas9 have remained elusive. Effective target search requires constant screening of the protospacer adjacent motif (PAM) and a 30 ms upper limit for screening was recently found. To further quantify the rapid switching between DNA-bound and freely-diffusing states of dCas9, we developed an open-microscopy framework, the miCube, and introduce Monte-Carlo diffusion distribution analysis (MC-DDA). Our analysis reveals that dCas9 is screening PAMs 40% of the time in Gram-positive Lactoccous lactis, averaging 17 ± 4 ms per binding event. Using heterogeneous dCas9 expression, we determine the number of cellular target-containing plasmids and derive the copy number dependent Cas9 cleavage. Furthermore, we show that dCas9 is not irreversibly bound to target sites but can still interfere with plasmid replication. Taken together, our quantitative data facilitates further optimization of the CRISPR-Cas toolbox.

Statistical physics and mesoscopic modeling to interpret tethered particle motion experiments.

Tethered particle motion experiments are versatile single-molecule techniques enabling one to address in vitro the molecular properties of DNA and its interactions with various partners involved in genetic regulations. These techniques provide raw data such as the tracked particle amplitude of movement, from which relevant information about DNA conformations or states must be recovered. Solving this inverse problem appeals to specific theoretical tools that have been designed in the two last decades, together with the data pre-processing procedures that ought to be implemented to avoid biases inherent to these experimental techniques. These statistical tools and models are reviewed in this paper.

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software.

With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3D SMLM software packages. We generated realistic simulated datasets for popular imaging modalities-2D, astigmatic 3D, biplane 3D and double-helix 3D-and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D SMLM software and provides a holistic view of how the latest 2D and 3D SMLM packages perform in realistic conditions. This resource allows researchers to identify optimal analytical software for their experiments, allows 3D SMLM software developers to benchmark new software against the current state of the art, and provides insight into the current limits of the field.

Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking.

The trajectory of a single protein in the cytosol of a living cell contains information about its molecular interactions in its native environment. However, it has remained challenging to accurately resolve and characterize the diffusive states that can manifest in the cytosol using analytical approaches based on simplifying assumptions. Here, we show that multiple intracellular diffusive states can be successfully resolved if sufficient single-molecule trajectory information is available to generate well-sampled distributions of experimental measurements and if experimental biases are taken into account during data analysis. To address the inherent experimental biases in camera-based and MINFLUX-based single-molecule tracking, we use an empirical data analysis framework based on Monte Carlo simulations of confined Brownian motion. This framework is general and adaptable to arbitrary cell geometries and data acquisition parameters employed in two-dimensional or three-dimensional single-molecule tracking. We show that, in addition to determining the diffusion coefficients and populations of prevalent diffusive states, the timescales of diffusive state switching can be determined by stepwise increasing the time window of averaging over subsequent single-molecule displacements. Time-averaged diffusion analysis of single-molecule tracking data may thus provide quantitative insights into binding and unbinding reactions among rapidly diffusing molecules that are integral for cellular functions.

Probing RNA structure and interaction dynamics at the single molecule level.

RNA structures and their dynamic fluctuations lie at the heart of understanding key biological process such as transcription, splicing, translation and RNA decay. While conventional bulk assays have proven to identify and characterize key pathway intermediates, the generally dynamic nature of RNA structures renders the information obtained from time and ensemble averaging techniques necessarily lacking in critical details. Here we detail Single-Molecule Kinetic Analysis of RNA Transient Structure (SiM-KARTS), a method that readily monitors structural fluctuations of single RNA molecules through the repetitive interaction of fluorescent probes with an unlabeled, surface-immobilized RNA target of virtually any length and in any biological context. In addition, we demonstrate the broad applicability of SiM-KARTS by kinetically fingerprinting the binding of cognate tRNA ligand to single immobilized T-box riboswitch molecules. SiM-KARTS represents a valuable tool for probing biologically relevant structure and interaction features of potentially many diverse RNA metabolic pathways.

Single-molecule trapping and spectroscopy reveals photophysical heterogeneity of phycobilisomes quenched by Orange Carotenoid Protein.

The Orange Carotenoid Protein (OCP) is a cytosolic photosensor that is responsible for non-photochemical quenching (NPQ) of the light-harvesting process in most cyanobacteria. Upon photoactivation by blue-green light, OCP binds to the phycobilisome antenna complex, providing an excitonic trap to thermally dissipate excess energy. At present, both the binding site and NPQ mechanism of OCP are unknown. Using an Anti-Brownian ELectrokinetic (ABEL) trap, we isolate single phycobilisomes in free solution, both in the presence and absence of activated OCP, to directly determine the photophysics and heterogeneity of OCP-quenched phycobilisomes. Surprisingly, we observe two distinct OCP-quenched states, with lifetimes 0.09 ns (6% of unquenched brightness) and 0.21 ns (11% brightness). Photon-by-photon Monte Carlo simulations of exciton transfer through the phycobilisome suggest that the observed quenched states are kinetically consistent with either two or one bound OCPs, respectively, underscoring an additional mechanism for excitation control in this key photosynthetic unit.