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Micro/nanoswimmers convert diverse energy sources into directional movement, demonstrating significant promise for biomedical and environmental applications, many of which involve complex, tortuous, or crowded environments. Here, we investigated the transport behavior of self-propelled catalytic Janus particles in a complex interconnected porous void space, where the rate-determining step involves the escape from a cavity and translocation through holes to adjacent cavities. Surprisingly, self-propelled nanoswimmers escaped from cavities more than 20× faster than passive (Brownian) particles, despite the fact that the mobility of nanoswimmers was less than 2× greater than that of passive particles in unconfined bulk liquid. Combining experimental measurements, Monte Carlo simulations, and theoretical calculations, we found that the escape of nanoswimmers was enhanced by nuanced secondary effects of self-propulsion which were amplified in confined environments. In particular, active escape was facilitated by anomalously rapid confined short-time mobility, highly efficient surface-mediated searching for holes, and the effective abolition of entropic and/or electrostatic barriers at the exit hole regions by propulsion forces. The latter mechanism converted the escape process from barrier-limited to search-limited. These findings provide general and important insights into micro/nanoswimmer mobility in complex environments.
Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.
Soft matter at solid–liquid interfaces plays an important role in multiple scientific disciplines as well as in various technological fields. For microgels, representing highly interesting soft matter systems, we demonstrate that the preparation method, i.e. the way how the microgel is applied to the specific surface, plays a key role. Focusing on the three most common sample preparation methods (spin-coating, drop-casting and adsorption from solution), we performed a comparative study of the deformation behavior of microgels at the solid–liquid interface on three different surfaces with varying hydrophilicities. For in situ visualization of the deformation of pNIPMAM microgels, we conducted highly sensitive 3D super resolution fluorescence microscopy methods. We furthermore performed complementary molecular dynamics simulations to determine the driving force responsible for the deformation depending on the surface and the deposition method. The combination of experiments and simulations revealed that the simulated equilibrium structure obtained after simulation of the completely dry microgel after deposition is retained after rehydration and subsequent fluorescent imaging.
Optical diffraction limits resolution in visible spectrum to 200 nm in the lateral dimension (x-y) and 500 nm in axial dimension (z). Recent advances in engineering properties of fluorescent proteins and dyes have enabled nanometer scale visualization by localizing sparse ensembles of photoswitchable/photoactivatable molecules through many frames. A final image is formed by combining locations of all the molecules to form a “super-resolution image”. The family of techniques is known as single-molecule localization microscopy (SMLM). Although SMLM enables high precision imaging of 10-20 nm in the lateral dimension, it lacks axial (z) resolution, especially near focus. The Double-Helix Point Spread function (DH-PSF) offers a solution to this problem by enabling high-depth and high-precision 3D imaging.
An outstanding challenge in single-molecule localization microscopy is the accurate and precise localization of individual point emitters in three dimensions in densely labeled samples. One established approach for three-dimensional single-molecule localization is point-spread-function (PSF) engineering, in which the PSF is engineered to vary distinctively with emitter depth using additional optical elements. However, images of dense emitters, which are desirable for improving temporal resolution, pose a challenge for algorithmic localization of engineered PSFs, due to lateral overlap of the emitter PSFs. Here we train a neural network to localize multiple emitters with densely overlapping Tetrapod PSFs over a large axial range. We then use the network to design the optimal PSF for the multi-emitter case. We demonstrate our approach experimentally with super-resolution reconstructions of mitochondria and volumetric imaging of fluorescently labeled telomeres in cells. Our approach, DeepSTORM3D, enables the study of biological processes in whole cells at timescales that are rarely explored in localization microscopy.
Primary cilia in many cell types contain a periaxonemal subcompartment called the inversin compartment. Four proteins have been found to assemble within the inversin compartment: INVS, ANKS6, NEK8, and NPHP3. The function of the inversin compartment is unknown, but it appears to be critical for normal development, including left–right asymmetry and renal tissue homeostasis. Here we combine superresolution imaging of human RPE1 cells, a classic model for studying primary cilia in vitro, with a genetic dissection of the protein–protein binding relationships that organize compartment assembly to develop a new structural model. We observe that INVS is the core structural determinant of a compartment composed of novel fibril-like substructures, which we identify here by three-dimensional single-molecule superresolution imaging. We find that NEK8 and ANKS6 depend on INVS for localization to these fibrillar assemblies and that ANKS6-NEK8 density within the compartment is regulated by NEK8. Together, NEK8 and ANKS6 are required downstream of INVS to localize and concentrate NPHP3 within the compartment. In the absence of these upstream components, NPHP3 is redistributed within cilia. These results provide a more detailed structure for the inversin compartment and introduce a new example of a membraneless compartment organized by protein–protein interactions.
Translocation from one cavity to another through a narrow constriction (i.e., a “hole”) represents the fundamental elementary process underlying hindered mass transport of nanoparticles and macromolecules within many natural and synthetic porous materials, including intracellular environments. This process is complex and may be influenced by long-range (e.g., electrostatic) particle–wall interactions, transient adsorption/desorption, surface diffusion, and hydrodynamic effects. Here, we used a three-dimensional (3D) tracking method to explicitly visualize the process of nanoparticle diffusion within periodic porous nanostructures, where electrostatic interactions were mediated via ionic strength. The effects of electrostatic interactions on nanoparticle transport were surprisingly large. For example, an increase in the Debye length of only a few nanometers (in a material with a hole diameter of ∼100 nm) increased the mean cavity escape time 3-fold. A combination of computational and experimental analyses indicated that this hindered cavity escape was due to an electrostatic energy barrier in the region of the hole, which was quantitatively explained using DLVO theory. These findings explicitly demonstrate that the cavity escape process was barrier-limited and dominated by electrostatic effects.
Selective recruitment and concentration of signalling proteins within membraneless compartments is a ubiquitous mechanism for subcellular organization. The dynamic flow of molecules into and out of these compartments occurs on faster timescales than for membrane-enclosed organelles, presenting a possible mechanism to control spatial patterning within cells. Here, we combine single-molecule tracking and super-resolution microscopy, light-induced subcellular localization, reaction-diffusion modelling and a spatially resolved promoter activation assay to study signal exchange in and out of the 200 nm cytoplasmic pole-organizing protein popZ (PopZ) microdomain at the cell pole of the asymmetrically dividing bacterium Caulobacter crescentus. Two phospho-signalling proteins, the transmembrane histidine kinase CckA and the cytoplasmic phosphotransferase ChpT, provide the only phosphate source for the cell fate-determining transcription factor CtrA. We find that all three proteins exhibit restricted rates of entry into and escape from the microdomain as well as enhanced phospho-signalling within, leading to a submicron gradient of activated CtrA-P that is stable and sublinear. Entry into the microdomain is selective for cytosolic proteins and requires a binding pathway to PopZ. Our work demonstrates how nanoscale protein assemblies can modulate signal propagation with fine spatial resolution, and that in Caulobacter, this modulation serves to reinforce asymmetry and differential cell fate of the two daughter cells. and differential cell fate of the two daughter cells.
We demonstrate that a deep neural network can be trained to virtually refocus a two-dimensional fluorescence image onto user-defined three-dimensional (3D) surfaces within the sample. Using this method, termed Deep-Z, we imaged the neuronal activity of a Caenorhabditis elegans worm in 3D using a time sequence of fluorescence images acquired at a single focal plane, digitally increasing the depth-of-field by 20-fold without any axial scanning, additional hardware or a trade-off of imaging resolution and speed. Furthermore, we demonstrate that this approach can correct for sample drift, tilt and other aberrations, all digitally performed after the acquisition of a single fluorescence image. This framework also cross-connects different imaging modalities to each other, enabling 3D refocusing of a single wide-field fluorescence image to match confocal microscopy images acquired at different sample planes. Deep-Z has the potential to improve volumetric imaging speed while reducing challenges relating to sample drift, aberration and defocusing that are associated with standard 3D fluorescence microscopy.
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