Single Particle Tracking: From Theory to Biophysical Applications

Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking

In single-particle tracking, individual particles are localized and tracked over time to probe their diffusion and molecular interactions. Temporal crossing of trajectories, blinking particles, and false-positive localizations present computational challenges that have remained difficult to overcome. Here we introduce a robust, parameter-free alternative to single-particle tracking: temporal analysis of relative distances (TARDIS). In TARDIS, an all-to-all distance analysis between localizations is performed with increasing temporal shifts. These pairwise distances represent either intraparticle distances originating from the same particle, or interparticle distances originating from unrelated particles, and are fitted analytically to obtain quantitative measures on particle dynamics. We showcase that TARDIS outperforms tracking algorithms, benchmarked on simulated and experimental data of varying complexity. We further show that TARDIS performs accurately in complex conditions characterized by high particle density, strong emitter blinking or false-positive localizations, and is in fact limited by the capabilities of localization algorithms. TARDIS' robustness enables fivefold shorter measurements without loss of information.

Diffusion and Oligomerization States of the Muscarinic M1 Receptor in Live Cells─The Impact of Ligands and Membrane Disruptors

G protein-coupled receptors (GPCRs) are a major gateway to cellular signaling, which respond to ligands binding at extracellular sites through allosteric conformational changes that modulate their interactions with G proteins and arrestins at intracellular sites. High-resolution structures in different ligand states, together with spectroscopic studies and molecular dynamics simulations, have revealed a rich conformational landscape of GPCRs. However, their supramolecular structure and spatiotemporal distribution is also thought to play a significant role in receptor activation and signaling bias within the native cell membrane environment. Here, we applied single-molecule fluorescence techniques, including single-particle tracking, single-molecule photobleaching, and fluorescence correlation spectroscopy, to characterize the diffusion and oligomerization behavior of the muscarinic M1 receptor (M1R) in live cells. Control samples included the monomeric protein CD86 and fixed cells, and experiments performed in the presence of different orthosteric M1R ligands and of several compounds known to change the fluidity and organization of the lipid bilayer. M1 receptors exhibit Brownian diffusion characterized by three diffusion constants: confined/immobile (∼0.01 μm2/s), slow (∼0.04 μm2/s), and fast (∼0.14 μm2/s), whose populations were found to be modulated by both orthosteric ligands and membrane disruptors. The lipid raft disruptor C6 ceramide led to significant changes for CD86, while the diffusion of M1R remained unchanged, indicating that M1 receptors do not partition in lipid rafts. The extent of receptor oligomerization was found to be promoted by increasing the level of expression and the binding of orthosteric ligands; in particular, the agonist carbachol elicited a large increase in the fraction of M1R oligomers. This study provides new insights into the balance between conformational and environmental factors that define the movement and oligomerization states of GPCRs in live cells under close-to-native conditions.

Impact of temporal resolution in single particle tracking analysis

Temporal resolution is a key parameter in the observation of dynamic processes, as in the case of single molecules motions visualized in real time in two-dimensions by wide field (fluorescence) microscopy, but a systematic investigation of its effects in all the single particle tracking analysis steps is still lacking. Here we present tools to quantify its impact on the estimation of diffusivity and of its distribution using one of the most popular tracking software for biological applications on simulated data and movies. We found important shifts and different widths for diffusivity distributions, depending on the interplay of temporal sampling conditions with various parameters, such as simulated diffusivity, density of spots, signal-to-noise ratio, lengths of trajectories, and kind of boundaries in the simulation. We examined conditions starting from the ones of experiments on the fluorescently labelled receptor p75NTR, a relatively fast-diffusing membrane receptor (diffusivity around 0.5-1 µm2/s), visualized by TIRF microscopy on the basal membrane of living cells. From the analysis of the simulations, we identified the best conditions in cases similar to these ones; considering also the experiments, we could confirm a range of values of temporal resolution suitable for obtaining reliable diffusivity results. The procedure we present can be exploited in different single particle/molecule tracking applications to find an optimal temporal resolution.

Electrochemiluminescence-Based Single-Particle Tracking of the Biomolecules Moving along Intercellular Membrane Nanotubes between Live Cells

Electrochemiluminescence (ECL) imaging, a rapidly evolving technology, has attracted significant attention in the field of cellular imaging. However, its primary limitation lies in its inability to analyze the motion behaviors of individual particles in live cellular environments. In this study, we leveraged the exceptional ECL properties of quantum dots (QDs) and the excellent electrochemical properties of carbon dots (CDs) to develop a high-brightness ECL nanoprobe (CDs-QDs) for real-time ECL imaging between living cells. This nanoprobe has excellent signal-to-noise ratio imaging capabilities for the single-particle tracking (SPT) of biomolecules. Our finding elucidated the enhanced ECL mechanism of CDs-QDs in the presence of reactive oxygen species through photoluminescence, electrochemistry, and ECL techniques. We further tracked the movement of single particles on membrane nanotubes between live cells and confirmed that the ECL-based SPT technique using CD-QD nanoparticles is an effective approach for monitoring the transport behaviors of biomolecules on membrane nanotubes between live cells. This opens a promising avenue for the advancement of ECL-based single-particle detection and the dynamic quantitative imaging of biomolecules.

Expanding the Palette of SWIR Emitting Nanoparticles Based on Au Nanoclusters for Single-Particle Tracking Microscopy

Single-molecule localization microscopy has proved promising to unravel the dynamics and molecular architecture of thin biological samples down to nanoscales. For applications in complex, thick biological tissues shifting single-particle emission wavelengths to the shortwave infrared (SWIR also called NIR II) region between 900 to 2100 nm, where biological tissues are more transparent is key. To date, mainly single-walled carbon nanotubes (SWCNTs) enable such applications, but they are inherently 1D objects. Here, 0D ultra-small luminescent gold nanoclusters (AuNCs, <3 nm) and ≈25 nm AuNC-loaded-polymeric particles that can be detected at the single-particle level in the SWIR are presented. Thanks to high brightness and excellent photostability, it is shown that the dynamics of the spherical polymeric particles can be followed at the single-particle level in solution at video rates for minutes. We compared single particle tracking of AuNC-loaded-polymeric particles with that of SWCNT diffusing in agarose gels demonstrating the specificity and complementarity of diffusion properties of these SWIR-emitting nano-objects when exploring a complex environment. This extends the library of photostable SWIR emitting nanomaterials to 0D nano-objects of variable size for single-molecule localization microscopy in the second biological window, opening unprecedented possibilities for mapping the structure and dynamics of complex biological systems.

Single-Molecule-Resolution Approaches in Synaptic Biology

Synapses between neurons are the primary loci for information transfer and storage in the brain. An individual neuron, alone, can make over 10000 synaptic contacts. It is, however, not easy to investigate what goes on locally within a synapse because many synaptic compartments are only a few hundred nanometers wide in size─close to the diffraction limit of light. To observe the biomolecular machinery and processes within synapses, in situ single-molecule techniques are emerging as powerful tools. Guided by important biological questions, this Perspective will highlight recent advances in using these techniques to obtain in situ measurements of synaptic molecules in three aspects: the cell-biological machinery within synapses, the synaptic architecture, and the synaptic neurotransmitter receptors. These advances showcase the increasing importance of single-molecule-resolution techniques for accessing subcellular biophysical and biomolecular information related to the brain.

Real-time single-molecule imaging of transcriptional regulatory networks in living cells

Gene regulatory networks drive the specific transcriptional programmes responsible for the diversification of cell types during the development of multicellular organisms. Although our knowledge of the genes involved in these dynamic networks has expanded rapidly, our understanding of how transcription is spatiotemporally regulated at the molecular level over a wide range of timescales in the small volume of the nucleus remains limited. Over the past few decades, advances in the field of single-molecule fluorescence imaging have enabled real-time behaviours of individual transcriptional components to be measured in living cells and organisms. These efforts are now shedding light on the dynamic mechanisms of transcription, revealing not only the temporal rules but also the spatial coordination of underlying molecular interactions during various biological events.

Deep Learning-Assisted Automated Multidimensional Single Particle Tracking in Living Cells

The translational and rotational dynamics of anisotropic optical nanoprobes revealed in single particle tracking (SPT) experiments offer molecular-level information about cellular activities. Here, we report an automated high-speed multidimensional SPT system integrated with a deep learning algorithm for tracking the 3D orientation of anisotropic gold nanoparticle probes in living cells with high localization precision (<10 nm) and temporal resolution (0.9 ms), overcoming the limitations of rotational tracking under low signal-to-noise ratio (S/N) conditions. This method can resolve the azimuth (0°-360°) and polar angles (0°-90°) with errors of less than 2° on the experimental and simulated data under S/N of ∼4. Even when the S/N approaches the limit of 1, this method still maintains better robustness and noise resistance than the conventional pattern matching methods. The usefulness of this multidimensional SPT system has been demonstrated with a study of the motions of cargos transported along the microtubules within living cells.

Targeted Single Particle Tracking with Upconverting Nanoparticles

Single particle tracking (SPT) is a powerful technique for real-time microscopic visualization of the movement of individual biomolecules within or on the surface of living cells. However, SPT often suffers from the suboptimal performance of the photon-emitting labels used to tag the biomolecules of interest. For example, fluorescent dyes have poor photostability, while quantum dots suffer from blinking that hampers track acquisition and interpretation. Upconverting nanoparticles (UCNPs) have recently emerged as a promising anti-Stokes luminescent label for SPT. In this work, we demonstrated targeted SPT using UCNPs. For this, we synthesized 30 nm diameter doped UCNPs and coated them with amphiphilic polymers decorated with polyethylene glycol chains to make them water-dispersible and minimize their nonspecific interactions with cells. Coated UCNPs highly homogeneous in brightness (as confirmed by a single particle investigation) were functionalized by immunoglobulin E (IgE) using a biotin-streptavidin strategy. Using these IgE-UCNP SPT labels, we tracked high-affinity IgE receptors (FcεRI) on the membrane of living RBL-2H3 mast cells at 37 °C in the presence and absence of antigen and obtained good agreement with the literature. Moreover, we used the FcεRI-IgE receptor-antibody system to directly compare the performance of UCNP-based SPT labels to organic dyes (AlexaFluor647) and quantum dots (QD655). Due to their photostability as well as their backgroundless and continuous luminescence, SPT trajectories obtained with UCNP labels are no longer limited by the photophysics of the label but only by the dynamics of the system and, in particular, the movement of the label out of the field of view and/or focal plane.

Packaging Quantum Dots in Viral Particles via a Strep-tag II/Streptavidin System for Single-Virus Tracking

Single-virus tracking provides a powerful tool for studying virus infection with high spatiotemporal resolution. Quantum dots (QDs) are used to label and track viral particles due to their brightness and photostability. However, labeling viral particles with QDs is not easy. We developed a new method for labeling viral particles with QDs by using the Strep-tag II/streptavidin system. In this method, QDs were site-specifically ligated to viral proteins in live cells and then packaged into viral-like particles (VLPs) of tick-borne encephalitis virus (TBEV) and Ebola virus during viral assembly. With TBEV VLP-QDs, we tracked the clathrin-mediated endocytic entry of TBEV and studied its intracellular dynamics at the single-particle level. Our Strep-tag II/streptavidin labeling procedure eliminates the need for BirA protein expression or biotin addition, providing a simple and general method for site-specifically labeling viral particles with QDs for single-virus tracking.

Real-Time Dissection of the Exosome Pathway for Influenza Virus Infection

Exosomes play an important role in the spread of viral infections and immune escape. However, the exact ability and mechanisms by which exosomes produced during viral infections (vExos) infect host cells are still not fully understood. In this study, we developed a dual-color exosome labeling strategy that simultaneously labels the external and internal structures of exosomes with quantum dots to enable in situ monitoring of the transport process of vExos in live cells using the single-particle tracking technique. Our finding revealed that vExos contains the complete influenza A virus (IAV) genome and viral ribonucleoprotein complexes (vRNPs) proteins but lacks viral envelope proteins. Notably, these vExos have the ability to infect cells and produce progeny viruses. We also found that vExos are transported in three stages, slow-fast-slow, and move to the perinuclear region via microfilaments and microtubules. About 30% of internalized vExos shed the external membrane and release the internal vRNPs into the cytoplasm by fusion with endolysosomes. This study suggested that vExos plays a supporting role in IAV infection by assisting with IAV propagation in a virus-independent manner. It emphasizes the need to consider the infectious potential of vExos and draws attention to the potential risk of exosomes produced by viral infections.

Molecular Rotors: Fluorescent Sensors for Microviscosity and Conformation of Biomolecules

The viscosity and crowding of biological environment are considered vital for the correct cellular function, and alterations in these parameters are known to underly a number of pathologies including diabetes, malaria, cancer and neurodegenerative diseases, to name a few. Over the last decades, fluorescent molecular probes termed molecular rotors proved extremely useful for exploring viscosity, crowding, and underlying molecular interactions in biologically relevant settings. In this review, we will discuss the basic principles underpinning the functionality of these probes and will review advances in their use as sensors for lipid order, protein crowding and conformation, temperature and non-canonical nucleic acid structures in live cells and other relevant biological settings.

Everything, everywhere, almost at once

A new platform that can follow the movement of individual proteins inside millions of cells in a single day will help contribute to existing knowledge of cell biology and identify new therapeutics.

M13-Phage-Based Star-Shaped Particles with Internal Flexibility

We report on the construction and the dynamics of monodisperse star-shaped particles, mimicking, at the mesoscale, star polymers. Such multiarm star-like particles result from the self-assembly of gold nanoparticles, forming the core, with tip-linked filamentous viruses (M13 bacteriophages) acting as spines in a sea urchin-like structure. By combining fluorescence and dark-field microscopy with dynamic light scattering, we investigate the diffusion of these hybrid spiny particles. We reveal the internal dynamics of the star particles by probing their central metallic core, which exhibits a hindered motion that can be described as a Brownian particle trapped in a harmonic potential. We therefore show that the filamentous viruses and specifically their tip proteins behave as entropic springs, extending the relevance of the study of such hybrid mesoscopic analogues of star polymers to phage biotechnology.

Measuring Solvent Exchange in Silica Nanoparticles with Rotor-Based Fluorophore

Measuring the diffusivity of molecules is the first step toward understanding their dependence and controlling diffusion, but the challenge increases with the decrease of molecular size, particularly for non-fluorescent and non-reactive molecules such as solvents. Here, the capability to monitor the solvent exchange process within the micropores of silica with millisecond time resolution is demonstrated, by simply embedding a rotor-based fluorophore (thioflavin T) in colloidal silica nanoparticles. Basically, the silica provides an extreme case of viscous microenvironment, which is affected by the polarity of the solvents. The fluorescence intensity traces can be well fitted to the Fickian diffusion model, allowing analytical solution of the diffusion process, and revealing the diffusion coefficients. The validation experiments, involving the water-to-ethanol and ethanol-to-water solvent exchange, the comparison of different drying conditions, and the variation in the degree of cross-linking in silica, confirmed the effectiveness and sensitivity of this method for characterizing diffusion in silica micropores. This work focuses on the method development of measuring diffusivity and the high temporal resolution in tracking solvent exchange dynamics over a short distance (within 165 nm) opens enormous possibilities for further studies.

Single-molecule analysis of intracellular insulin granule behavior and its application to analyzing cytoskeletal dependence and pathophysiological implications

Introduction: Mobilization of intracellular insulin granules to the plasma membrane plays a crucial role in regulating insulin secretion. However, the regulatory mechanisms of this mobilization process have been poorly understood due to technical limitations. In this study, we propose a convenient approach for assessing intracellular insulin granule behavior based on single-molecule analysis of insulin granule membrane proteins labeled with Quantum dot fluorescent nanocrystals. Methods: This approach allows us to analyze intracellular insulin granule movement with subpixel accuracy at 33 fps. We tracked two insulin granule membrane proteins, phogrin and zinc transporter 8, fused to HaloTag in rat insulinoma INS-1 cells and, by evaluating the tracks with mean-square displacement, demonstrated the characteristic behavior of insulin granules. Results and discussion: Pharmacological perturbations of microtubules and F-actin affected insulin granule behavior on distinct modalities. Specifically, microtubule dynamics and F-actin positively and negatively regulate insulin granule behavior, respectively, presumably by modulating each different behavioral mode. Furthermore, we observed impaired insulin granule behavior and cytoskeletal architecture under chronic treatment of high concentrations of glucose and palmitate. Our approach provides detailed information regarding intracellular insulin granule mobilization and its pathophysiological implications. This study sheds new light on the regulatory mechanisms of intracellular insulin granule mobilization and has important implications for understanding the pathogenesis of diabetes.

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.

Single-molecule tracking of myelin basic protein during oligodendrocyte differentiation

This study aimed to expand our understanding of myelin basic protein (MBP), a key component of central nervous system myelin, by developing a protocol to track and quantifying individual MBP particles during oligodendrocyte (OL) differentiation. MBP particle directionality, confinement, and diffusion were tracked by rapid TIRF and HILO imaging of Dendra2 tagged MBP in three stages of mouse oligodendroglia: OL precursors, early myelinating OLs, and mature myelinating OLs. The directionality and confinement of MBP particles increased at each stage consistent with progressive transport toward, and recruitment into, emerging myelin structures. Unexpectedly, diffusion data presented a more complex pattern with subpopulations of the most diffusive particles disappearing at the transition between the precursor and early myelinating stage, before reemerging in the membrane sheets of mature OLs. This diversity of particle behaviors, which would be undetectable by conventional ensemble-averaged methods, are consistent with a multifunctional view of MBP involving roles in myelin expansion and compaction.

Biophysical screening and characterisation in medicinal chemistry

In the last two decades the use of biophysical assays and methods in medicinal chemistry has increased significantly, to meet the demands of the novel targets and modalities that drug discoverers are looking to tackle. The desire to obtain accurate affinities, kinetics, thermodynamics and structural data as early as possible in the drug discovery process has fuelled this innovation. This review introduces the principles underlying the techniques in common use and provides a perspective on the weaknesses and strengths of different methods. Case studies are used to further illustrate some of the applications in medicinal chemistry and a discussion of the emerging biophysical methods on the horizon is presented.

Heterodyne dynamic light scattering for the characterization of particle dispersions

Particle self-diffusivities in unimodal and bimodal aqueous dispersions are characterized by dynamic light scattering (DLS) applying a heterodyne detection scheme. For unimodal dispersions close to infinite dilution, it could be evidenced that pure homodyne conditions cannot be realized, leading to an increasing underestimation of diffusivity with a decreasing concentration. Even for bimodal dispersions and neglecting any local oscillator field, the coherent superposition of scattered light from different particle species hinders a clear assignment of the measured signals and their evaluation for diffusivity. In this case, the impact of a cross term on the determined diffusivities cannot be neglected. The results emphasize that the use of a heterodyne detection scheme in DLS experiments is a key aspect for an accurate determination of particle diffusivities in low-concentrated unimodal and bimodal dispersions.

Scanning single molecule localization microscopy (scanSMLM) for super-resolution volume imaging

Over the last decade, single-molecule localization microscopy (SMLM) has developed into a set of powerful techniques that have improved spatial resolution over diffraction-limited microscopy and demonstrated the ability to resolve biological features down to a few tens of nanometers. We introduce a single molecule-based scanning SMLM (scanSMLM) system that enables rapid volume imaging. Along with epi-illumination, the system employs a scanning-based 4f detection for volume imaging. The 4f system comprises a combination of an electrically-tunable lens and high NA detection objective lens. By rapidly changing the aperture (or equivalently the focus) of an electrically-tunable lens (ETL) in a 4f detection system, the selectivity of the axial object plane is achieved, for which the image forms in the image/detector plane. So, in principle, one can scan the object volume by just altering the aperture of ETL. Two schemes were adopted to carry out volume imaging: cyclic scan and conventional scan. The cyclic scheme scans the volume in each scan cycle, whereas plane-wise scanning is performed in the conventional scheme. Hence, the cyclic scan ensures uniform dwell time on each frame during data collection, thereby evenly distributing photobleaching throughout the cell volume. With a minimal change in the system hardware (requiring the addition of an ETL lens and related electronics for step-voltage generation) in the existing SMLM system, volume scanning (along the z-axis) can be achieved. To calibrate and derive critical system parameters, we imaged fluorescent beads embedded in a gel-matrix 3D block as a test sample. Subsequently, scanSMLM is employed to visualize the architecture of actin-filaments and the distribution of Meos-Tom20 molecules on the mitochondrial membrane. The technique is further exploited to understand the clustering of Hemagglutinin (HA) protein single molecules in a transfected cell for studying Influenza-A disease progression. The system, for the first time, enabled 3D visualization of HA distribution that revealed HA cluster formation spanning the entire cell volume, post 24 hrs of transfection. Critical biophysical parameters related to HA clusters (density, the number of HA molecules per cluster, axial span, fraction of clustered molecules, and others) are also determined, giving an unprecedented insight into Influenza-A disease progression at the single-molecule level.

Live-cell imaging uncovers the relationship between histone acetylation, transcription initiation, and nucleosome mobility

Histone acetylation and RNA polymerase II phosphorylation are associated with transcriptionally active chromatin, but their spatiotemporal relationship in live cells remains poorly understood. To address this problem, we combine Fab-based labeling of endogenous protein modifications with single-molecule tracking to quantify the dynamics of chromatin enriched with histone H3 lysine-27 acetylation (H3K27ac) and RNA polymerase II serine-5 phosphorylation (RNAP2-Ser5ph). Our analysis reveals that chromatin enriched with these two modifications is generally separate. In these separated sites, we show that the two modifications are inversely correlated with one another on the minutes time scale and that single nucleosomes within each region display distinct and opposing dynamics on the subsecond time scale. While nucleosomes diffuse ~15% faster in chromatin enriched with H3K27ac, they diffuse ~15% slower in chromatin enriched with RNAP2-Ser5ph. These results argue that high levels of H3K27ac and RNAP2-Ser5ph are not often present together at the same place and time, but rather each marks distinct transcriptionally poised or active sites, respectively.

Nanoparticle Dynamics in Composite Hydrogels Exposed to Low-Frequency Focused Ultrasound

Pulsed focused ultrasound (FUS) in combination with microbubbles has been shown to improve delivery and penetration of nanoparticles in tumors. To understand the mechanisms behind this treatment, it is important to evaluate the contribution of FUS without microbubbles on increased nanoparticle penetration and transport in the tumor extracellular matrix (ECM). A composite agarose hydrogel was made to model the porous structure, the acoustic attenuation and the hydraulic conductivity of the tumor ECM. Single-particle tracking was used as a novel method to monitor nanoparticle dynamics in the hydrogel during FUS exposure. FUS exposure at 1 MHz and 1 MPa was performed to detect any increase in nanoparticle diffusion or particle streaming at acoustic parameters relevant for FUS in combination with microbubbles. Results were compared to a model of acoustic streaming. The nanoparticles displayed anomalous diffusion in the hydrogel, and FUS with a duty cycle of 20% increased the nanoparticle diffusion coefficient by 23%. No increase in diffusion was found for lower duty cycles. FUS displaced the hydrogel itself at duty cycles above 10%; however, acoustic streaming was found to be negligible. In conclusion, pulsed FUS alone cannot explain the enhanced penetration of nanoparticles seen when using FUS and microbubbles for nanoparticle delivery, but it could be used as a tool to enhance diffusion of particles in the tumor ECM.

Single molecule analysis of CENP-A chromatin by high-speed atomic force microscopy

Chromatin accessibility is modulated in a variety of ways to create open and closed chromatin states, both of which are critical for eukaryotic gene regulation. At the single molecule level, how accessibility is regulated of the chromatin fiber composed of canonical or variant nucleosomes is a fundamental question in the field. Here, we developed a single-molecule tracking method where we could analyze thousands of canonical H3 and centromeric variant nucleosomes imaged by high-speed atomic force microscopy. This approach allowed us to investigate how changes in nucleosome dynamics in vitro inform us about transcriptional potential in vivo. By high-speed atomic force microscopy, we tracked chromatin dynamics in real time and determined the mean square displacement and diffusion constant for the variant centromeric CENP-A nucleosome. Furthermore, we found that an essential kinetochore protein CENP-C reduces the diffusion constant and mobility of centromeric nucleosomes along the chromatin fiber. We subsequently interrogated how CENP-C modulates CENP-A chromatin dynamics in vivo. Overexpressing CENP-C resulted in reduced centromeric transcription and impaired loading of new CENP-A molecules. From these data, we speculate that factors altering nucleosome mobility in vitro, also correspondingly alter transcription in vivo. Subsequently, we propose a model in which variant nucleosomes encode their own diffusion kinetics and mobility, and where binding partners can suppress or enhance nucleosome mobility.

When Weak Is Strong: A Plea for Low-Affinity Binders for Optical Microscopy

The exploitation of low-affinity molecular interactions in protein labeling is an emerging topic in optical microscopy. Such non-covalent and low-affinity interactions can be realized with various concepts from chemistry and for different molecule classes, and lead to a constant renewal of fluorescence signals at target sites. Further benefits are a versatile use across microscopy methods, in 3D, live and many-target applications. In recent years, several classes of low-affinity labels were developed and a variety of powerful applications demonstrated. Still, this research field is underdeveloped, while the potential is huge.

Single-Particle Tracking in Poly(Ethylene Glycol) Diacrylate: Probe Size Effect on the Diffusion Behaviors of Nanoparticles in Unentangled Polymer Solutions

A thorough understanding of the relevant factors governing the transport of nanoparticles in poly(ethylene glycol) diacrylate (PEGDA) is crucial for many applications utilizing this polymer. Here, single-particle tracking (SPT) was used to systematically investigate the role of the probe size (3-200 nm) on the diffusion behaviors of individual fluorescent nanoparticles in semidilute and unentangled PEGDA solutions. The quantitative assessment of the SPT data via the recorded single-particle trajectories and diffusion coefficients (D) not only showed that the observed probe dynamics in PEGDA were temporally and spatially heterogeneous, but more importantly that the measured D were observed to be significantly reduced (vs in solvent) and strongly size-dependent. We explained these results based on a modified multiscale model for particle diffusion, built upon well-established hydrodynamics and obstruction theories. We furthermore showed that the presence of steric interactions and probe confinement effects in highly crowded, unentangled PEGDA microstructures can lead to deviations in the single-particle displacements from the expected Gaussian behavior, as revealed by the van Hove displacement distributions and the associated non-Gaussian parameters. This study has demonstrated the power of SPT methods in offering an advanced characterization of the transport characteristics in complex polymer structures, overcoming challenges posed by traditional characterization techniques.

Transition between Different Diffusion Modes of Individual Lipids during the Membrane-Specific Action of As-CATH4 Peptides

The cell membrane permeabilization ability of immune defense antimicrobial peptides (AMPs) is widely applied in biomedicine. Although the mechanisms of peptide-membrane interactions have been widely investigated, analyses at the molecular level are still lacking. Herein, the membrane-specific action of a native AMP, As-CATH4, is investigated using a single-lipid tracking method in combination with live cell and model membrane assays conducted at different scales. The peptide-membrane interaction process is characterized by analyzing single-lipid diffusion behaviors. As-CATH4 exhibits potent antimicrobial activity through bacterial membrane permeabilization, with moderate cytotoxicity against mammalian cells. In-plane diffusion analyses of individual lipids show that the lipid molecules exhibit non-Gaussian and heterogeneous diffusion behaviors in both pristine and peptide-treated membranes, which can be decomposed into two Gaussian subgroups corresponding to normal- and slow-diffusive lipids. Assessment of the temporal evolution of these two diffusion modes of lipids reveal that the peptide action states of As-CATH4 include surface binding, transmembrane defect formation, and dynamic equilibrium. The action mechanisms of As-CATH4 at varying concentrations and against different membranes are distinguished. This work resolves the simultaneous mixed diffusion mechanisms of single lipids in biomimetic cell membranes, especially during dynamic membrane permeabilization by AMPs.

Information optimization of laser scanning microscopes for real-time feedback-driven single particle tracking

Real-time feedback-driven single particle tracking (RT-FD-SPT) is a class of microscopy techniques that uses measurements of finite excitation/detection volume in a feedback control loop to actuate that volume and track with high spatio-temporal resolution a single particle moving in three dimensions. A variety of methods have been developed, each defined by a set of user-defined choices. Selection of those values is typically done through ad hoc, off-line tuning for the best perceived performance. Here we present a mathematical framework, based on optimization of the Fisher information, to select those parameters such that the best information is acquired for estimating parameters of interest, such as the location of the particle, specifics of the excitation beam such as its dimensions or peak intensity, or the background noise. For concreteness, we focus on tracking of a fluorescently-labeled particle and apply this framework to determine the optimal parameters for three existing fluorescence-based RT-FD-SPT techniques with respect to particle localization.

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.

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

Spatially Resolving Size Effects on Diffusivity in Nanoporous Extracellular Matrix-like Materials with Fluorescence Correlation Spectroscopy Super-Resolution Optical Fluctuation Imaging

It is well documented that the nanoscale structures within porous microenvironments greatly impact the diffusion dynamics of molecules. However, how the interaction between the environment and molecules influences the diffusion dynamics has not been thoroughly explored. Here, we show that fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) can be used to accurately measure the diffusion dynamics of molecules within varying matrices such as nanopatterned surfaces and porous agarose hydrogels. Our data demonstrate the robustness of fcsSOFI, where it is possible not only to quantify the diffusion speeds of molecules in heterogeneous media but also to recover the matrix structure with resolution on the order of 100 nm. Using dextran molecules of varying sizes, we show that the diffusion coefficient is sensitive to the change in the molecular hydrodynamic radius. fcsSOFI images further reveal that smaller dextran molecules can freely move through the small pores of the hydrogel and report the detailed porous structure and local diffusion heterogeneities not captured by the average diffusion coefficient. Conversely, bigger dextran molecules are confined and unable to freely move through the hydrogel, highlighting only the larger pore structures. These findings establish fcsSOFI as a powerful tool to characterize spatial and diffusion information of diverse macromolecules within biorelevant matrices.

Simple, Economic, and Robust Rail-Based Setup for Super-Resolution Localization Microscopy

Research during the past 2 decades has showcased the power of single-molecule localization microscopy (SMLM) as a tool for exploring the nanoworld. However, SMLM systems are typically available in specialized laboratories and imaging facilities, owing to their expensiveness as well as complex assembly and alignment procedure. Here, we lay out the blueprint of a sturdy, rail-based, cost-efficient, multicolor SMLM setup that is easy to construct and align in service of simplifying the accessibility of SMLM. We characterize the optical properties of the design and assess its capabilities, robustness, and stability. The performance of the system is assayed using super-resolution imaging of biological samples. We believe that this design will make SMLM more affordable and broaden its availability.

★Track: Inferred counting and tracking of replicating DNA loci

Fluorescent microscopy is the primary method to study DNA organization within cells. However, the variability and low signal/noise commonly associated with live-cell time-lapse imaging challenges quantitative measurements. In particular, obtaining quantitative or mechanistic insight often depends on the accurate tracking of fluorescent particles. Here, we present ★Track, an inference method that determines the most likely temporal tracking of replicating intracellular particles such DNA loci while accounting for missing, merged, and spurious detections. It allows the accurate prediction of particle copy numbers as well as the timing of replication events. We demonstrate ★Track's abilities and gain new insight into plasmid copy number control and the volume dependence of bacterial chromosome replication initiation. By enabling the accurate tracking of DNA loci, ★Track can help to uncover the mechanistic principles of chromosome organization and dynamics across a range of systems.

Digital and Absolute Assays for Low Abundance Molecular Biomarkers

There has been a recent surge of advances in biomolecular assays based on the measurement of discrete molecular targets as opposed to signals averaged across molecular ensembles. Many of these "digital" assay designs derive from now-mature technologies involving single-molecule imaging and microfluidics and provide an assortment of new modalities to quantify nucleic acids and proteins in biospecimens such as blood and tissue homogenates. A primary new benefit is the robust detection of trace analytes at attomolar to femtomolar concentrations for which many ensemble assays cannot distinguish signals above noise levels. In addition, multiple biomolecules can be differentiated within a mixture using optical barcodes, with much faster and simpler readouts compared with sequencing methods. In ideal digital assays, signals should, in theory, further represent absolute molecular counts, rather than relative levels, eliminating the need for calibration standards that are the mainstay of typical assays. Several digital assay platforms have now been commercialized but challenges hinder the adoption and diversification of these new formats, as there are broad needs to balance sensitivity and dynamic range of detection, increase analyte multiplexing, improve sample throughput, and reduce cost. Our lab and others have developed technologies to address these challenges by redesigning molecular probes and labels, improving molecular transport within detection focal volumes, and applying solution-based readout methods in flow.This Account describes the principles, formats, and design constraints of digital biomolecular assays that apply optical labels toward the goal of simple and routine target counting that may ultimately approach absolute readout standards. The primary challenges can be understood from fundamental concepts in thermodynamics and kinetics of association reactions, mass transport, and discrete statistics. Major advances include (1) new inorganic nanocrystal probes for more robust counting compared with dyes, (2) diverse molecular amplification tools that endow attachment of numerous labels to single targets, (3) specialized surfaces with patterned features for electromagnetic coupling to labels for signal amplification, (4) surface capture enhancement methods to concentrate targets through disruption of diffusion depletion zones, and (5) flow counting in which analytes are rapidly counted in solution without pull-down to a surface. Further progress and integration of these tools for biomolecular counting could improve the precision of laboratory measurements in life sciences research and benefit clinical diagnostic assays for low abundance biomarkers in limiting biospecimen volumes that are out of reach of traditional ensemble-level bioassays.

Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

Single-Molecule Tracking of Reagent Diffusion during Chemical Reactions

Recent experiments have shown that the diffusion of reagent molecules is inconsistent with what the Stokes-Einstein equation predicts during a chemical reaction. Here, we used single-molecule tracking to observe the diffusion of reactive reagent molecules during click and Diels-Alder (DA) reactions. We found that the diffusion coefficient of the reagents remained unchanged within the experimental uncertainty upon the DA reaction. Yet, diffusion of reagent molecules is faster than predicted during the click reaction when the reagent concentration and catalyst concentration exceed a threshold. A stepwise analysis suggested that the fast diffusion scenario is due to the reaction but not the involvement of the tracer with the reaction itself. The present results provide experimental evidence on the faster-than-expected reagent diffusion during a CuAAC reaction in specific conditions and propose new insights into understanding this unexpected behavior.

Single-Molecule Displacement Mapping Indicates Unhindered Intracellular Diffusion of Small (≲1 kDa) Solutes

While fundamentally important, the intracellular diffusion of small (≲1 kDa) solutes has been difficult to elucidate due to challenges in both labeling and measurement. Here we quantify and spatially map the translational diffusion patterns of small solutes in mammalian cells by integrating several recent advances. In particular, by executing tandem stroboscopic illumination pulses down to 400 μs separation, we extend single-molecule displacement/diffusivity mapping (SMdM), a super-resolution diffusion quantification tool, to small solutes with high diffusion coefficients D of >300 μm2/s. We thus show that for multiple water-soluble dyes and dye-tagged nucleotides, intracellular diffusion is dominated by vast regions of high diffusivity ∼60-70% of that in vitro, up to ∼250 μm2/s in the fastest cases. Meanwhile, we also visualize sub-micrometer foci of substantial slowdowns in diffusion, thus underscoring the importance of spatially resolving the local diffusion behavior. Together, these results suggest that the intracellular diffusion of small solutes is only modestly scaled down by the slightly higher viscosity of the cytosol over water but otherwise not further hindered by macromolecular crowding. We thus lift a paradoxically low speed limit for intracellular diffusion suggested by previous experiments.

Palmitate-mediated disruption of the endoplasmic reticulum decreases intracellular vesicle motility

Essential cellular processes such as metabolism, protein synthesis, and autophagy require the intracellular transport of membrane-bound vesicles. The importance of the cytoskeleton and associated molecular motors for transport is well documented. Recent research has suggested that the endoplasmic reticulum (ER) may also play a role in vesicle transport through a tethering of vesicles to the ER. We use single-particle tracking fluorescence microscopy and a Bayesian change-point algorithm to characterize vesicle motility in response to the disruption of the ER, actin, and microtubules. This high-throughput change-point algorithm allows us to efficiently analyze thousands of trajectory segments. We find that palmitate-mediated disruption of the ER leads to a significant decrease in vesicle motility. A comparison with the disruption of actin and microtubules shows that disruption of the ER has a significant impact on vesicle motility, greater than the disruption of actin. Vesicle motility was dependent on cellular region, with greater motility in the cell periphery than the perinuclear region, possibly due to regional differences in actin and the ER. Overall, these results suggest that the ER is an important factor in vesicle transport.

Size-Dependent Suppression of Molecular Diffusivity in Expandable Hydrogels: A Single-Molecule Study

By repurposing the recently popularized expansion microscopy to control the meshwork size of hydrogels, we examine the size-dependent suppression of molecular diffusivity in the resultant tuned hydrogel nanomatrices over a wide range of polymer fractions of ∼0.14-7 wt %. With our recently developed single-molecule displacement/diffusivity mapping (SMdM) microscopy methods, we thus show that with a fixed meshwork size, larger molecules exhibit more impeded diffusion and that, for the same molecule, diffusion is progressively more suppressed as the meshwork size is reduced; this effect is more prominent for the larger molecules. Moreover, we show that the meshwork-induced obstruction of diffusion is uncoupled from the suppression of diffusion due to increased solution viscosities. Thus, the two mechanisms, respectively, being diffuser-size-dependent and independent, may separately scale down molecular diffusivity to produce the final diffusion slowdown in complex systems like the cell.

Machine-learning-powered extraction of molecular diffusivity from single-molecule images for super-resolution mapping

While critical to biological processes, molecular diffusion is difficult to quantify, and spatial mapping of local diffusivity is even more challenging. Here we report a machine-learning-enabled approach, pixels-to-diffusivity (Pix2D), to directly extract the diffusion coefficient D from single-molecule images, and consequently enable super-resolved D spatial mapping. Working with single-molecule images recorded at a fixed framerate under typical single-molecule localization microscopy (SMLM) conditions, Pix2D exploits the often undesired yet evident motion blur, i.e., the convolution of single-molecule motion trajectory during the frame recording time with the diffraction-limited point spread function (PSF) of the microscope. Whereas the stochastic nature of diffusion imprints diverse diffusion trajectories to different molecules diffusing at the same given D, we construct a convolutional neural network (CNN) model that takes a stack of single-molecule images as the input and evaluates a D-value as the output. We thus validate robust D evaluation and spatial mapping with simulated data, and with experimental data successfully characterize D differences for supported lipid bilayers of different compositions and resolve gel and fluidic phases at the nanoscale.

Trap-and-Track for Characterizing Surfactants at Interfaces

Understanding the behavior of surfactants at interfaces is crucial for many applications in materials science and chemistry. Optical tweezers combined with trajectory analysis can become a powerful tool for investigating surfactant characteristics. In this study, we perform trap-and-track analysis to compare the behavior of cetyltrimethylammonium bromide (CTAB) and cetyltrimethylammonium chloride (CTAC) at water-glass interfaces. We use optical tweezers to trap a gold nanoparticle and statistically analyze the particle's movement in response to various surfactant concentrations, evidencing the rearrangement of surfactants adsorbed on glass surfaces. Our results show that counterions have a significant effect on surfactant behavior at the interface. The greater binding affinity of bromide ions to CTA+ micelle surfaces reduces the repulsion among surfactant head groups and enhances the mobility of micelles adsorbed on the interface. Our study provides valuable insights into the behavior of surfactants at interfaces and highlights the potential of optical tweezers for surfactant research. The development of this trap-and-track approach can have important implications for various applications, including drug delivery and nanomaterials.

Real-Time Dissection of the Transportation and miRNA-Release Dynamics of Small Extracellular Vesicles

Extracellular vesicles (EVs) are cell-derived membrane-enclosed structures that deliver biomolecules for intercellular communication. Developing visualization methods to elucidate the spatiotemporal dynamics of EVs' behaviors will facilitate their understanding and translation. With a quantum dot (QD) labeling strategy, a single particle tracking (SPT) platform is proposed here for dissecting the dynamic behaviors of EVs. The interplays between tumor cell-derived small EVs (T-sEVs) and endothelial cells (ECs) are specifically investigated based on this platform. It is revealed that, following a clathrin-mediated endocytosis by ECs, T-sEVs are transported to the perinuclear region in a typical three-stage pattern. Importantly, T-sEVs frequently interact with and finally enter lysosomes, followed by quick release of their carried miRNAs. This study, for the first time, reports the entire process and detailed dynamics of T-sEV transportation and cargo-release in ECs, leading to better understanding of their proangiogenic functions. Additionally, the QD-based SPT technique will help uncover more secrets of sEV-mediated cell-cell communication.

Non-Gaussian Diffusion Near Surfaces

We study the diffusion of particles confined close to a single wall and in double-wall planar channel geometries where the local diffusivities depend on the distance to the boundaries. Displacement parallel to the walls is Brownian as characterized by its variance, but it is non-Gaussian having a nonzero fourth cumulant. Establishing a link with Taylor dispersion, we calculate the fourth cumulant and the tails of the displacement distribution for general diffusivity tensors along with potentials generated by either the walls or externally, for instance, gravity. Experimental and numerical studies of the motion of a colloid in the direction parallel to the wall give measured fourth cumulants which are correctly predicted by our theory. Interestingly, contrary to models of Brownian-yet-non-Gaussian diffusion, the tails of the displacement distribution are shown to be Gaussian rather than exponential. All together, our results provide additional tests and constraints for the inference of force maps and local transport properties near surfaces.

Anomalous fluctuations of extremes in many-particle diffusion

In many-particle diffusions, particles that move the furthest and fastest can play an outsized role in physical phenomena. A theoretical understanding of the behavior of such extreme particles is nascent. A classical model, in the spirit of Einstein's treatment of single-particle diffusion, has each particle taking independent homogeneous random walks. This, however, neglects the fact that all particles diffuse in a common and often inhomogeneous environment that can affect their motion. A more sophisticated model treats this common environment as a space-time random biasing field which influences each particle's independent motion. While the bulk (or typical particle) behavior of these two models has been found to match to high degree, recent theoretical work of G. Barraquand and I. Corwin, Probab. Theory Relat. Fields 167, 1057 (2017)0178-805110.1007/s00440-016-0699-z and G. Barraquand and P. Le Doussal, J. Phys. A: Math. Theor. 53, 215002 (2020)1751-811310.1088/1751-8121/ab8b39 on a one-dimensional exactly solvable version of this random environment model suggests that the extreme behavior is quite different between the two models. We transform these asymptotic (in system size and time) results into physically applicable predictions. Using high-precision numerical simulations we reconcile different asymptotic phases in a manner that matches numerics down to realistic system sizes, amenable to experimental confirmation. We characterize the behavior of extreme diffusion in the random environment model by the presence of a new phase with anomalous fluctuations related to the Kardar-Parisi-Zhang universality class and equation.

Single-molecule displacement mapping indicates unhindered intracellular diffusion of small (<~1 kDa) solutes

While fundamentally important, the intracellular diffusion of small (<~1 kDa) solutes has been difficult to elucidate due to challenges in both labeling and measurement. Here we quantify and spatially map the translational diffusion patterns of small solutes in mammalian cells by integrating several recent advances. In particular, by executing tandem stroboscopic illumination pulses down to 400-μs separation, we extend single-molecule displacement/diffusivity mapping (SM d M), a super-resolution diffusion quantification tool, to small solutes with high diffusion coefficients D of >300 μm ² /s. We thus show that for multiple water-soluble dyes and dye-tagged nucleotides, intracellular diffusion is dominated by vast regions of high diffusivity ~60-70% of that in vitro , up to ~250 μm ² /s in the fastest cases. Meanwhile, we also visualize sub-micrometer foci of substantial slowdowns in diffusion, thus underscoring the importance of spatially resolving the local diffusion behavior. Together, these results suggest that the intracellular diffusion of small solutes is only modestly scaled down by the slightly higher viscosity of the cytosol over water, but otherwise not further hindered by macromolecular crowding. We thus lift a paradoxically low speed limit for intracellular diffusion suggested by previous experiments.

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Extracting, quantifying, and comparing dynamical and biomechanical properties of living matter through single particle tracking

A panoply of new tools for tracking single particles and molecules has led to an explosion of experimental data, leading to novel insights into physical properties of living matter governing cellular development and function, health and disease. In this Perspective, we present tools to investigate the dynamics and mechanics of living systems from the molecular to cellular scale via single-particle techniques. In particular, we focus on methods to measure, interpret, and analyse complex data sets that are associated with forces, materials properties, transport, and emergent organisation phenomena within biological and soft-matter systems. Current approaches, challenges, and existing solutions in the associated fields are outlined in order to support the growing community of researchers at the interface of physics and the life sciences. Each section focuses not only on the general physical principles and the potential for understanding living matter, but also on details of practical data extraction and analysis, discussing limitations, interpretation, and comparison across different experimental realisations and theoretical frameworks. Particularly relevant results are introduced as examples. While this Perspective describes living matter from a physical perspective, highlighting experimental and theoretical physics techniques relevant for such systems, it is also meant to serve as a solid starting point for researchers in the life sciences interested in the implementation of biophysical methods.

Single molecule imaging simulations with advanced fluorophore photophysics

Advanced fluorescence imaging techniques such as single-molecule localization microscopy (SMLM) fundamentally rely on the photophysical behavior of the employed fluorophores. This behavior is generally complex and impacts data quality in a subtle manner. A simulation software named Single-Molecule Imaging Simulator (SMIS) is introduced that simulates a widefield microscope and incorporates fluorophores with their spectral and photophysical properties. With SMIS, data collection schemes combining 3D, multicolor, single-particle-tracking or quantitative SMLM can be implemented. The influence of advanced fluorophore characteristics, imaging conditions, and environmental parameters can be evaluated, facilitating the design of real experiments and their proper interpretation.

Geometric deep learning reveals the spatiotemporal features of microscopic motion

The characterization of dynamical processes in living systems provides important clues for their mechanistic interpretation and link to biological functions. Owing to recent advances in microscopy techniques, it is now possible to routinely record the motion of cells, organelles and individual molecules at multiple spatiotemporal scales in physiological conditions. However, the automated analysis of dynamics occurring in crowded and complex environments still lags behind the acquisition of microscopic image sequences. Here we present a framework based on geometric deep learning that achieves the accurate estimation of dynamical properties in various biologically relevant scenarios. This deep-learning approach relies on a graph neural network enhanced by attention-based components. By processing object features with geometric priors, the network is capable of performing multiple tasks, from linking coordinates into trajectories to inferring local and global dynamic properties. We demonstrate the flexibility and reliability of this approach by applying it to real and simulated data corresponding to a broad range of biological experiments.

Benchmarking Thiolate-Driven Photoswitching of Cyanine Dyes

Carbocyanines are among the best performing dyes in single-molecule localization microscopy (SMLM), but their performance critically relies on optimized photoswitching buffers. Here, we study the versatile role of thiols in cyanine photoswitching at varying intensities generated in a single acquisition by a microelectromechanical systems (MEMS) mirror placed in the excitation path. The key metrics we have analyzed as a function of the thiolate concentration are photon budget, on-state and off-state lifetimes and the corresponding impact on image resolution. We show that thiolate acts as a concentration bandpass filter for the maximum achievable resolution and determine a minimum of ∼1 mM is necessary to facilitate SMLM measurements. We also identify a concentration bandwidth of 1-16 mM in which the photoswitching performance can be balanced between high molecular brightness and high off-time to on-time ratios. Furthermore, we monitor the performance of the popular oxygen scavenger system based on glucose and glucose oxidase over time and show simple measures to avoid acidification during prolonged measurements. Finally, the impact of buffer settings is quantitatively tested on the distribution of the glucose transporter protein 4 within the plasma membrane of adipocytes. Our work provides a general strategy for achieving optimal resolution in SMLM with relevance for the development of novel buffers and dyes.

Spatial Stochastic Model of the Pre-B Cell Receptor

Survival and proliferation of immature B lymphocytes requires expression and tonic signaling of the pre-B cell receptor (pre-BCR). This low level, ligand-independent signaling is likely achieved through frequent, but short-lived, homo interactions. Tonic signaling is also central in the pathology of precursor B acute lymphoblastic leukemia (B-ALL). In order to understand how repeated, transient events can lead to sustained signaling and to assess the impact of receptor accumulation induced by the membrane landscape, we developed a spatial stochastic model of receptor aggregation and downstream signaling events. Our rule- and agent-based model builds on previous mature BCR signaling models and incorporates novel parameters derived from single particle tracking of pre-BCR on surfaces of two different B-ALL cell lines, 697 and Nalm6. Live cell tracking of receptors on the two cell lines revealed characteristic differences in their dimer dissociation rates and diffusion coefficients. We report here that these differences affect pre-BCR aggregation and consequent signal initiation events. Receptors on Nalm6 cells, which have a lower off-rate and lower diffusion coefficient, more frequently form higher order oligomers than pre-BCR on 697 cells, resulting in higher levels of downstream phosphorylation in the Nalm6 cell line.