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Dynamic membrane contacts between lipid droplets (LDs) and mitochondria play key roles in lipid metabolism and energy homeostasis. Understanding the dynamics of LDs under energy stimulation is thereby crucial to disclosing the metabolic mechanism. Here, the reversible interactions between LDs and mitochondria are tracked in real‐time using a robust LDs‐specific fluorescent probe (LDs‐Tags). Through tracking the dynamics of LDs at the single‐particle level, spatiotemporal heterogeneity is revealed. LDs in starved cells communicate and integrate their activities (i.e., lipid exchange) through a membrane contact site‐mediated mechanism. Thus the diffusion is intermittently alternated between active and confined states. Statistical analysis shows that the translocation of LDs in response to starvation stress is non‐Gaussian, and obeys nonergodic‐like behavior. These results provide deep understanding of the anomalous diffusion of LDs in living cells, and also afford guidance for rationally designing efficient transporter.

Single‐particle tracking and optical tweezers are powerful techniques for studying diverse processes at the microscopic scale. The stochastic behavior of a microscopic particle contains information about its interaction with surrounding molecules, and an optical tweezer can further facilitate this observation with its ability to constrain the particle to an area of interest. Although these techniques found their initial applications in biology, they can also shed new light on microscopic interface phenomena by unveiling nanoscale morphologies and molecular‐level interactions in real time, which are obscured in traditional ensemble analysis. Here, the application of single‐particle tracking and optical tweezers are demonstrated for studying molecular interactions at solid–liquid interfaces. Specifically, the surfactant behaviors at the water–glass interface are investigated by tracing gold nanoparticles that are optically trapped on these molecules. The underlying mechanisms governing the particle motion, which can be explained by hydrophobic interactions, disruptions, and rearrangements among surfactant monomers at the interfaces, are discovered. These interpretations are further supported by statistical analysis of an individual trajectory and comparison with theoretical predictions. The findings provide new insights into the surfactant dynamics and also illustrate the promise of single‐particle tracking and optical manipulation for studying nanoscale physics and chemistry of surfaces and interfaces. Observing the Brownian motion of microscopic particles provides information about their interactions with their surroundings. Optical tweezers can facilitate these observations by providing the tracer particle precise access to the region of interest and confining the particle within this region. The movement of a single nanoparticle inside an optical trap can reveal molecular‐level interactions at the nanoscale in real time.

Volumetric subcellular imaging has long been essential for studying structures and dynamics in cells and tissues. However, due to limited imaging speed and depth of field, it has been challenging to perform live-cell imaging and single-particle tracking. Here we report a 2.5D fluorescence microscopy combined with highly inclined illumination beams, which significantly reduce not only the image acquisition time but also the out-of-focus background by ∼2-fold compared to epi-illumination. Instead of sequential -scanning, our method projects a certain depth of volumetric information onto a 2D plane in a single shot using multi-layered glass for incoherent wavefront splitting, enabling high photon detection efficiency. We apply our method to multi-color immunofluorescence imaging and volumetric super-resolution imaging, covering ∼3–4 µm thickness of samples without -scanning. Additionally, we demonstrate that our approach can substantially extend the observation time of single-particle tracking in living cells.

Swarming bacteria can organize themselves into different local communities, ranging from active cell rafts to reticular biofilms. How millions of motile and immotile cells are dynamically linked together and still function as a whole is a critical interdisciplinary issue. Besides biochemical and molecular characterizations, concerns on the microscopic communication mechanisms underlying the complicated microsystem have been largely simplified to biophysics or physical interactions between individual isolated bacteria. Herein, by single‐cell tracking of fluorescent bacteria in the motile cell layer and single‐particle tracking of gold nanoparticles (AuNPs) in the upper fluid layer in different regions across a swarming colony of Bacillus subtilis, we studied collective multibacteria interactions, using the upper fluid as the medium, in detail. While the dynamic properties differ spatially, both cell migrations and AuNP transports in the swarming edge, the intermediate and the biofilm‐like center regions of the colony can be described with the Lévy‐walk‐like superdiffusion model. Moreover, the speed and motion range of the AuNPs are always much smaller than the bacteria, indicating that the intercellular fluid flow alone cannot explain long‐range cell‐to‐cell signaling. Referring to previous literature, we propose the presence of a decentralized two‐tier “active‐mixing” network in the bacterial community for efficient information exchange. Bacterial community is a typical model system to study the behavior of multicellular organization, how millions of cells are organized, and how they communicate efficiently microscopically on large spatiotemporal scales have attracted a lot of attention. By single‐cell tracking of fluorescent bacteria in the motile cell layer and single‐particle tracking of gold nanoparticles (AuNPs) in the upper fluid layer in different regions across a swarming colony of Bacillus subtilis, we studied collective multibacteria interactions, using the upper fluid as the medium, in detail. And we propose a novel “active‐mixing” signal‐transport mechanism, which may provide an efficient and robust active transport network for long‐range cell‐cell communication.

MicroRNAs (miRNAs) associate with components of the RNA‐induced silencing complex (RISC) to assemble on mRNA targets and regulate protein expression in higher eukaryotes. Here we describe a method for the intracellular single‐molecule, high‐resolution localization and counting (iSHiRLoC) of miRNAs. Microinjected, singly fluorophore‐labelled, functional miRNAs were tracked within diffusing particles, a majority of which contained single such miRNA molecules. Mobility and mRNA‐dependent assembly changes suggest the existence of two kinetically distinct pathways for miRNA assembly, revealing the dynamic nature of this important gene regulatory pathway. iSHiRLOC achieves an unprecedented resolution in the visualization of functional miRNAs, paving the way to understanding RNA silencing through single‐molecule systems biology. This study reports a new method—iSHiRLOC—that allows an unprecedented resolution in the visualization of functional small RNAs. Its use has revealed the existence of both a time‐dependent and an mRNA‐dependent pathway for miRNA assembly.

A single particle observation of quantum dots (QDs) was performed on lipid bilayers formed on graphene oxide (GO). The long-range fluorescence quenching of GO has been applied to biosensing for various biomolecules. We demonstrated the single particle observation of a QD on supported lipid bilayers in this study, aiming to detect the quenching efficiency of lipid and protein molecules in a lipid bilayer by fluorescence single particle tacking (SPT). A single lipid bilayer or double lipid bilayers were formed on GO flakes deposited on a thermally oxidized silicon substrate by the vesicle fusion method. The QDs were conjugated on the lipid bilayers, and single particle images of the QDs were obtained under the quenching effect of GO. The quenching efficiency of a single QD was evaluated from the fluorescence intensities on the regions with and without GO. The quenching efficiency reflecting the layer numbers of the lipid bilayers was obtained.

Cell-penetrating peptides (CPPs) can translocate across cell membranes, and thus have great potential for the cellular delivery of macromolecular cargoes. However, the mechanism of this cellular uptake process is not yet fully understood. In this study, a time-lapse single-particle light-sheet microscopy technique was implemented to obtain a parallel visualization of the translocating process of individual human immunodeficiency virus 1 (HIV-1) transactivator of transcription (Tat) peptide conjugated quantum dots (TatP-QDs) in complex cellular terrains. Here, TatP-QDs served as nanoscale dynamic pens, which depict remarkable trajectory aggregates of TatP-QDs on the cell surface. Spectral-embedding analysis of the trajectory aggregates revealed a manifold formed by isotropic diffusion and a fraction of directed movement, possibly caused by interaction between the Tat peptides and heparan sulfate groups on the plasma membrane. Further analysis indicated that the membrane deformation induced by Tat-peptide attachment increased with the disruption of the actin framework in cytochalasin D (cyto D)-treated cells, yielding higher interactions on the TatP-QDs. In native cells, the Tat peptides can remodel the actin framework to reduce their interaction with the local membrane environment. Characteristic hot spots for interaction were detected on the membrane, suggesting that a funnel passage may have formed for the Tat-coated particles. This finding offers valuable insight into the cellular delivery of nanoscale cargo, suggesting an avenue for direct therapeutic delivery.

Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug nanocarrier delivery. The inherently complex diffusion in such biological systems can vary drastically both in time and across systems, consequently imposing considerable analytical challenges, and currently requires an a priori knowledge of the system. Here we introduce a method for SPT data analysis, processing, and classification, which we term “diffusional fingerprinting.” This method allows for dissecting the features that underlie diffusional behavior and establishing molecular identity, regardless of the underlying diffusion type. The method operates by isolating 17 descriptive features for each observed motion trajectory and generating a diffusional map of all features for each type of particle. Precise classification of the diffusing particle identity is then obtained by training a simple logistic regression model. A linear discriminant analysis generates a feature ranking that outputs the main differences among diffusional features, providing key mechanistic insights. Fingerprinting operates by both training on and predicting experimental data, without the need for pretraining on simulated data. We found this approach to work across a wide range of simulated and experimentally diverse systems, such as tracked lipases on fat substrates, transcription factors diffusing in cells, and nanoparticles diffusing in mucus. This flexibility ultimately supports diffusional fingerprinting’s utility as a universal paradigm for SPT diffusional analysis and prediction.

SignificanceThe plant plasma membrane acts as the front line for cellular perception of the environment. As such, signaling and transport proteins which perceive or transport environmental signals, developmental cues, and nutrients are located within it. A number of studies have revealed that proteins located within the plasma membrane do not simply freely diffuse within its plane. Rather, proteins are localized in nanodomains. In addition to the plasma membrane, plant cells also have an extracellular matrix, the cell wall. Here we have shown that the cell wall has a role in regulating the dynamics and size of plasma-membrane nanodomains for proteins involved in morphogenesis (PIN3) and pathogen perception (FLS2). Plant plasma-membrane (PM) proteins are involved in several vital processes, such as detection of pathogens, solute transport, and cellular signaling. For these proteins to function effectively there needs to be structure within the PM allowing, for example, proteins in the same signaling cascade to be spatially organized. Here we demonstrate that several proteins with divergent functions are located in clusters of differing size in the membrane using subdiffraction-limited Airyscan confocal microscopy. Single particle tracking reveals that these proteins move at different rates within the membrane. Actin and microtubule cytoskeletons appear to significantly regulate the mobility of one of these proteins (the pathogen receptor FLS2) and we further demonstrate that the cell wall is critical for the regulation of cluster size by quantifying single particle dynamics of proteins with key roles in morphogenesis (PIN3) and pathogen perception (FLS2). We propose a model in which the cell wall and cytoskeleton are pivotal for regulation of protein cluster size and dynamics, thereby contributing to the formation and functionality of membrane nanodomains.

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. Proteins, the molecules that make up the cells’ internal machinery, are responsible for almost every process that keeps cells alive. Watching how proteins move and interact within a living cell can help scientists to better understand these biological mechanisms. Single-particle tracking is a recent technique that makes these observations possible by taking ‘live’ recordings of individual proteins in a cell. Typically, the goal of a single-particle tracking experiment is to assign proteins into groups, or subpopulations, based on the way they move in the cell. For example, one subpopulation may be bound to other cellular structures, a second moving freely at a high speed, and a third diffusing slowly. This informs on the biological roles of the proteins. The method involves an experimental stage and an analysis stage. During the experiment, proteins of interest are labeled with a small dye molecule that produces light when excited by a laser. The laser then illuminates the cell, stimulating all the labels in a thin layer. The position of each molecule is then determined with a microscope and a ‘snapshot’ taken. By repeating this process over multiple images, the movement of each molecule over time can be tracked. However, experimental problems can make the interpretation difficult. Motion blurring takes place when the proteins move so fast they appear as blurs in the images; tracking errors happen when so many proteins are present in the same space their trajectories overlap. Here, Hansen, Woringer et al. combine two pre-existing methods to improve the experimental set-up. Using lasers that flash like a strobe light reduces motion blurring by essentially taking snapshots of the proteins at short time intervals. Tracking errors are addressed by a technique whereby only one protein at a time produces light. Once the images are obtained and analyzed to yield trajectories, the trajectories themselves need to be analyzed to determine the number and properties of the protein subpopulations. Several factors can skew this analysis stage. For example, there is often a bias against fast-moving particles because the laser only lights up a thin layer of the cell. The proteins travelling slowly stay in focus long enough to be detected across many images; the fast ones quickly move out of the layer and are therefore counted less often. Hansen, Woringer et al. designed a free and user-friendly algorithm package called Spot-On to correct for this issue. Spot-On was thoroughly benchmarked against other solutions, demonstrating both its accuracy and robustness. Single-particle tracking can lead to misleading results if used incorrectly. It is essential to publically share solutions that help make this technique more rigorous, especially since a growing number of scientists have already started to use the method.