Diffraction-unlimited imaging: from pretty pictures to hard numbers

Triggered cagedSTORM microscopy

In standard SMLM methods, the photoswitching of single fluorescent molecules and the data acquisition processes are independent, which leads to the detection of single molecule blinking events on several consecutive frames. This mismatch results in several data points with reduced localization precision, and it also increases the possibilities of overlapping. Here we discuss how the synchronization of the fluorophores' ON state to the camera exposure time increases the average intensity of the captured point spread functions and hence improves the localization precision. Simulations and theoretical results show that such synchronization leads to fewer localizations with 15% higher sum signal on average, while reducing the probability of overlaps by 10%.

Smart genetically-encoded biosensors for the chemical monitoring of living systems

Genetically-encoded biosensors provide the all-optical and non-invasive visualization of dynamic biochemical events within living systems, which has allowed the discovery of profound new insights. Twenty-five years of biosensor development has steadily improved their performance and has provided us with an ever increasing biosensor repertoire. In this feature article, we present recent advances made in biosensor development and provide a perspective on the future direction of the field.

Smoothness correction for better SOFI imaging

Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals. We find that our method works well to correct photodestruction, especially when it occurs quickly. The resulting images show a much higher contrast, strongly suppressed background and a more detailed visualization of cellular structures. Our method is parameter-free and computationally efficient, and can be readily applied on both two-dimensional and three-dimensional data.

Confocal Fluorescence-Lifetime Single-Molecule Localization Microscopy

Fluorescence lifetime imaging microscopy is an important technique that adds another dimension to intensity and color acquired by conventional microscopy. In particular, it allows for multiplexing fluorescent labels that have otherwise similar spectral properties. Currently, the only super-resolution technique that is capable of recording super-resolved images with lifetime information is stimulated emission depletion microscopy. In contrast, all single-molecule localization microscopy (SMLM) techniques that employ wide-field cameras completely lack the lifetime dimension. Here, we combine fluorescence-lifetime confocal laser-scanning microscopy with SMLM for realizing single-molecule localization-based fluorescence-lifetime super-resolution imaging. Besides yielding images with a spatial resolution much beyond the diffraction limit, it determines the fluorescence lifetime of all localized molecules. We validate our technique by applying it to direct stochastic optical reconstruction microscopy and points accumulation for imaging in nanoscale topography imaging of fixed cells, and we demonstrate its multiplexing capability on samples with two different labels that differ only by fluorescence lifetime but not by their spectral properties.

Analysis of sparse molecular distributions in fibrous arrangements based on the distance to the first neighbor in single molecule localization microscopy

Single Molecule Localization Microscopy (SMLM) currently attains a lateral resolution of around 10 nm approaching molecular size. Together with increasingly specific fluorescent labeling, it opens the possibility to quantitatively analyze molecular organization. When the labeling density is high enough, SMLM provides clear images of the molecular organization. However, either due to limited labeling efficiency or due to intrinsically low molecular abundance, SMLM delivers a small set of sparse and highly precise localizations. In this work, we introduce a correlation analysis of molecular locations based on the functional dependence of the complementary cumulative distribution function (CCDF) of the distance to the first neighbor (r₁). We demonstrate that the log(-log(CCDF(r₁))) vs. log(r₁) is characterized by a scaling exponent n that takes extreme values of 2 for a random 2D distribution and 1 for a strictly linear arrangement, and find that n is a robust and sensitive metric to distinguish characteristics of the underlying structure responsible for the molecular distribution, even at a very low labeling density. The method enables the detection of fibrillary organization and the estimation of the diameter of host fibers under conditions where a visual inspection provides no clue.

Super-resolution Microscopy for Nanomedicine Research

Super-resolution microscopy, or nanoscopy, revolutionized the field of cell biology, enabling researchers to visualize cellular structures with nanometric resolution, single-molecule sensitivity, and in multiple colors. However, the impact of these techniques goes beyond biology as the fields of nanotechnology and nanomedicine can greatly benefit from them, as well. Nanoscopy can visualize nanostructures in vitro and in cells and can contribute to the characterization of their structures and nano-bio interactions. In this Perspective, we discuss the potential of super-resolution imaging for nanomedicine research, its technical challenges, and the future developments we envision for this technology.

An extended quantitative model for super-resolution optical fluctuation imaging (SOFI)

Super-resolution optical fluctuation imaging (SOFI) provides super-resolution (SR) fluorescence imaging by analyzing fluctuations in the fluorophore emission. The technique has been used both to acquire quantitative SR images and to provide SR biosensing by monitoring changes in fluorophore blinking dynamics. Proper analysis of such data relies on a fully quantitative model of the imaging. However, previous SOFI imaging models made several assumptions that can not be realized in practice. In this work we address these limitations by developing and verifying a fully quantitative model that better approximates real-world imaging conditions. Our model shows that (i) SOFI images are free of bias, or can be made so, if the signal is stationary and fluorophores blink independently, (ii) allows a fully quantitative description of the link between SOFI imaging and probe dynamics, and (iii) paves the way for more advanced SOFI image reconstruction by offering a computationally fast way to calculate SOFI images for arbitrary probe, sample and instrumental properties.

Mitochondrial Morphofunction in Mammalian Cells

Significance: In addition to their classical role in cellular ATP production, mitochondria are of key relevance in various (patho)physiological mechanisms including second messenger signaling, neuro-transduction, immune responses and death induction. Recent Advances: Within cells, mitochondria are motile and display temporal changes in internal and external structure ("mitochondrial dynamics"). During the last decade, substantial empirical and in silico evidence was presented demonstrating that mitochondrial dynamics impacts on mitochondrial function and vice versa. Critical Issues: However, a comprehensive and quantitative understanding of the bidirectional links between mitochondrial external shape, internal structure and function ("morphofunction") is still lacking. The latter particularly hampers our understanding of the functional properties and behavior of individual mitochondrial within single living cells. Future Directions: In this review we discuss the concept of mitochondrial morphofunction in mammalian cells, primarily using experimental evidence obtained within the last decade. The topic is introduced by briefly presenting the central role of mitochondria in cell physiology and the importance of the mitochondrial electron transport chain (ETC) therein. Next, we summarize in detail how mitochondrial (ultra)structure is controlled and discuss empirical evidence regarding the equivalence of mitochondrial (ultra)structure and function. Finally, we provide a brief summary of how mitochondrial morphofunction can be quantified at the level of single cells and mitochondria, how mitochondrial ultrastructure/volume impacts on mitochondrial bioreactions and intramitochondrial protein diffusion, and how mitochondrial morphofunction can be targeted by small molecules.

A stochastic view on surface inhomogeneity of nanoparticles

The interactions between and with nanostructures can only be fully understood when the functional group distribution on their surfaces can be quantified accurately. Here we apply a combination of direct stochastic optical reconstruction microscopy (dSTORM) imaging and probabilistic modelling to analyse molecular distributions on spherical nanoparticles. The properties of individual fluorophores are assessed and incorporated into a model for the dSTORM imaging process. Using this tailored model, overcounting artefacts are greatly reduced and the locations of dye labels can be accurately estimated, revealing their spatial distribution. We show that standard chemical protocols for dye attachment lead to inhomogeneous functionalization in the case of ubiquitous polystyrene nanoparticles. Moreover, we demonstrate that stochastic fluctuations result in large variability of the local group density between particles. These results cast doubt on the uniform surface coverage commonly assumed in the creation of amorphous functional nanoparticles and expose a striking difference between the average population and individual nanoparticle coverage.

High-Contrast Imaging of Nanodiamonds in Cells by Energy Filtered and Correlative Light-Electron Microscopy: Toward a Quantitative Nanoparticle-Cell Analysis

Fluorescent nanodiamonds (fNDs) represent an emerging class of nanomaterials offering great opportunities for ultrahigh resolution imaging, sensing and drug delivery applications. Their biocompatibility, exceptional chemical and consistent photostability renders them particularly attractive for correlative light-electron microscopy studies providing unique insights into nanoparticle-cell interactions. Herein, we demonstrate a stringent procedure to image and quantify fNDs with a high contrast down to the single particle level in cells. Individual fNDs were directly visualized by energy-filtered transmission electron microscopy, that is, inside newly forming, early endosomal vesicles during their cellular uptake processes as well as inside cellular organelles such as a mitochondrion. Furthermore, we demonstrate the unequivocal identification, localization, and quantification of individual fNDs in larger fND clusters inside intracellular vesicles. Our studies are of great relevance to obtain quantitative information on nanoparticle trafficking and their various interactions with cells, membranes, and organelles, which will be crucial to design-improved sensors, imaging probes, and nanotherapeutics based on quantitative data.

Systematic Excited State Studies of Reversibly Switchable Fluorescent Proteins

The reversibly switchable fluorescent proteins Dronpa, rsFastLime, rsKame, Padron, and bsDronpa feature the same chromophore but display a 40 nm variation in absorption maxima and an only 18 nm variation in emission maxima. In the present contribution, we employ QM/MM models to investigate the mechanism of such remarkably different spectral variations, which are caused by just a few amino acid replacements. We show that the models, which are based on CASPT2//CASSCF level of QM theory, reproduce the observed trends in absorption maxima, with only a 3.5 kcal/mol blue-shift, and in emission maxima, with an even smaller 1.5 kcal/mol blue-shift with respect to the observed quantities. In order to explain the variations across the series, we look at the chromophore's electronic structure change during absorption and emission. Such analysis indicates that a change in charge-transfer character, which is more pronounced during absorption, triggers a cascade of hydrogen-bond-network rearrangements, suggesting preparation to an isomerization event. We also show how the contribution of Arg 89 and Arg 64 residues to the chromophore conformational changes correlate with the spectral variations in absorption and emission. Furthermore, we describe how the conical intersection stability is related to the protein's photophysical properties. While for the Dronpa, rsFastLime, and rsKame triad, the stability correlates with the photoswitching speed, this does not happen for bsDronpa and Padron, suggesting a less obvious photoisomerization mechanism.

A fluorescence nanoscopy marker for corticotropin-releasing hormone type 1 receptor: computer design, synthesis, signaling effects, super-resolved fluorescence imaging, and in situ affinity constant in cells

A new fluorescent marker for CRHR1 shows an antagonist effect and suitability for super resolution fluorescence microscopy.

Label-free monitoring of ambient oxygenation and redox conditions using the photodynamics of flavin compounds and transient state (TRAST) spectroscopy

Transient state (TRAST) monitoring can determine population dynamics of long-lived, dark transient states of fluorescent molecules, detecting only the average fluorescence intensity from a sample, when subject to different excitation pulse trains. Like Fluorescence Correlation Spectroscopy (FCS), TRAST unites the detection sensitivity of fluorescence with the environmental sensitivity of long-lived non-fluorescent states, but does not rely on detection of stochastic fluorescence fluctuations from individual molecules. Relaxed requirements on noise suppression, detection quantum yield and time-resolution of the instrument, as well as on fluorescence brightness of the molecules studied, make TRAST broadly applicable, opening also for investigations based on less bright, auto-fluorescent molecules. In this work, we applied TRAST to study the transient state population dynamics within the auto-fluorescent coenzymes flavin adenine dinucleotide (FAD) and flavin-mononucleotide (FMN). From the experimental TRAST data, we defined state models, and determined rate parameters for triplet state and redox transitions within FMN and FAD, stacking and un-stacking rates of external redox active quenching agents and by the adenine moiety of FAD itself. TRAST experiments were found to be well capable to resolve these transitions in FMN and FAD, and to track how the transitions are influenced by ambient oxygenation and redox conditions. This work demonstrates that TRAST provides a useful tool to follow local oxygenation and redox conditions via FMN and FAD fluorescence, and forms the basis for measurements on flavo-proteins and of redox and metabolic conditions in more complex environments, such as in live cells.

Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.

The ability to quantify the organization of cell membrane molecules is limited by the density of labeling and experimental conditions. Here, the authors use super-resolution optical fluctuation (SOFI) for molecular density and clustering analyses, and investigate nanoscale distribution of CD4 glycoprotein.

Reduced Fluorescent Protein Switching Fatigue by Binding-Induced Emissive State Stabilization

Reversibly switchable fluorescent proteins (RSFPs) enable advanced fluorescence imaging, though the performance of this imaging crucially depends on the properties of the labels. We report on the use of an existing small binding peptide, named Enhancer, to modulate the spectroscopic properties of the recently developed rsGreen series of RSFPs. Fusion constructs of Enhancer with rsGreen1 and rsGreenF revealed an increased molecular brightness and pH stability, although expression in living E. coli or HeLa cells resulted in a decrease of the overall emission. Surprisingly, Enhancer binding also increased off-switching speed and resistance to switching fatigue. Further investigation suggested that the RSFPs can interconvert between fast- and slow-switching emissive states, with the overall protein population gradually converting to the slow-switching state through irradiation. The Enhancer modulates the spectroscopic properties of both states, but also preferentially stabilizes the fast-switching state, supporting the increased fatigue resistance. This work demonstrates how the photo-physical properties of RSFPs can be influenced by their binding to other small proteins, which opens up new horizons for applications that may require such modulation. Furthermore, we provide new insights into the photoswitching kinetics that should be of general consideration when developing new RSFPs with improved or different photochromic properties.

Correcting for photodestruction in super-resolution optical fluctuation imaging

Super-resolution optical fluctuation imaging overcomes the diffraction limit by analyzing fluctuations in the fluorophore emission. A key assumption of the imaging is that the fluorophores are independent, though this is invalidated in the presence of photodestruction. In this work, we evaluate the effect of photodestruction on SOFI imaging using theoretical considerations and computer simulations. We find that photodestruction gives rise to an additional signal that does not present an easily interpretable view of the sample structure. This additional signal is strong and the resulting images typically exhibit less noise. Accordingly, these images may be mis-interpreted as being more visually pleasing or more informative. To address this uncertainty, we develop a procedure that can robustly estimate to what extent any particular experiment is affected by photodestruction. We also develop a detailed assessment methodology and use it to evaluate the performance of several correction algorithms. We identify two approaches that can correct for the presence of even strong photodestruction, one of which can be implemented directly in the SOFI calculation software.

"Supertrap" at Work: Extremely Efficient Nonradiative Recombination Channels in MAPbI3 Perovskites Revealed by Luminescence Super-Resolution Imaging and Spectroscopy

Organo-metal halide perovskites are some of the most promising materials for the new generation of low-cost photovoltaic and light-emitting devices. Their solution processability is a beneficial trait, although it leads to a spatial inhomogeneity of perovskite films with a variation of the trap state density at the nanoscale. Comprehending their properties using traditional spectroscopy therefore becomes difficult, calling for a combination with microscopy in order to see beyond the ensemble-averaged response. We studied photoluminescence (PL) blinking of micrometer-sized individual methylammonium lead iodide (MAPbI₃) perovskite polycrystals, as well as monocrystalline microrods up to 10 μm long. We correlated their PL dynamics with structure employing scanning electron and optical super-resolution microscopy. Combining super-resolution localization imaging and super-resolution optical fluctuation imaging (SOFI), we could detect and quantify preferential emitting regions in polycrystals exhibiting different types of blinking. We propose that blinking in MAPbI₃ occurs by the activation/passivation of a "supertrap" which presumably is a donor-acceptor pair able to trap both electrons and holes. As such, nonradiative recombination via supertraps, in spite being present at a rather low concentrations (10¹²-10¹⁵ cm^-3), is much more efficient than via all other defect states present in the material at higher concentrations (10¹⁶-10¹⁸ cm^-3). We speculate that activation/deactivation of a supertrap occurs by its temporary dissociation into free donor and acceptor impurities. We found that supertraps are most efficient in structurally homogeneous and large MAPbI₃ crystals where carrier diffusion is efficient, which may therefore pose limitations on the efficiency of perovskite-based devices.

Effect of probe diffusion on the SOFI imaging accuracy

Live-cell super-resolution fluorescence imaging is becoming commonplace for exploring biological systems, though sample dynamics can affect the imaging quality. In this work we evaluate the effect of probe diffusion on super-resolution optical fluctuation imaging (SOFI), using a theoretical model and numerical simulations based on the imaging of live cells labelled with photochromic fluorescent proteins. We find that, over a range of physiological conditions, fluorophore diffusion results in a change in the amplitude of the SOFI signal. The magnitude of this change is approximately proportional to the on-time ratio of the fluorophores. However, for photochromic fluorescent proteins this effect is unlikely to present a significant distortion in practical experiments in biological systems. Due to this lack of distortions, probe diffusion strongly enhances the SOFI imaging by avoiding spatial undersampling caused by the limited labeling density.

Achromatic light patterning and improved image reconstruction for parallelized RESOLFT nanoscopy

Fluorescence microscopy is rapidly turning into nanoscopy. Among the various nanoscopy methods, the STED/RESOLFT super-resolution family has recently been expanded to image even large fields of view within a few seconds. This advance relies on using light patterns featuring substantial arrays of intensity minima for discerning features by switching their fluorophores between 'on' and 'off' states of fluorescence. Here we show that splitting the light with a grating and recombining it in the focal plane of the objective lens renders arrays of minima with wavelength-independent periodicity. This colour-independent creation of periodic patterns facilitates coaligned on- and off-switching and readout with combinations chosen from a range of wavelengths. Applying up to three such periodic patterns on the switchable fluorescent proteins Dreiklang and rsCherryRev1.4, we demonstrate highly parallelized, multicolour RESOLFT nanoscopy in living cells for ~100 × 100 μm² fields of view. Individual keratin filaments were rendered at a FWHM of ~60-80 nm, with effective resolution for the filaments of ~80-100 nm. We discuss the impact of novel image reconstruction algorithms featuring background elimination by spatial bandpass filtering, as well as strategies that incorporate complete image formation models.

Single-Molecule Localization Microscopy in Eukaryotes

Super-resolution fluorescence imaging by photoactivation or photoswitching of single fluorophores and position determination (single-molecule localization microscopy, SMLM) provides microscopic images with subdiffraction spatial resolution. This technology has enabled new insights into how proteins are organized in a cellular context, with a spatial resolution approaching virtually the molecular level. A unique strength of SMLM is that it delivers molecule-resolved information, along with super-resolved images of cellular structures. This allows quantitative access to cellular structures, for example, how proteins are distributed and organized and how they interact with other biomolecules. Ultimately, it is even possible to determine protein numbers in cells and the number of subunits in a protein complex. SMLM thus has the potential to pave the way toward a better understanding of how cells function at the molecular level. In this review, we describe how SMLM has contributed new knowledge in eukaryotic biology, and we specifically focus on quantitative biological data extracted from SMLM images.

Live-cell monochromatic dual-label sub-diffraction microscopy by mt-pcSOFI

We present mt-pcSOFI, live-cell monochromatic sub-diffraction imaging and illustrate the method with existing RSFPs and the newly developed ffDronpa-F.

Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions

Live-cell imaging of focal adhesions requires a sufficiently high temporal resolution, which remains a challenge for super-resolution microscopy. Here we address this important issue by combining photoactivated localization microscopy (PALM) with super-resolution optical fluctuation imaging (SOFI). Using simulations and fixed-cell focal adhesion images, we investigate the complementarity between PALM and SOFI in terms of spatial and temporal resolution. This PALM-SOFI framework is used to image focal adhesions in living cells, while obtaining a temporal resolution below 10 s. We visualize the dynamics of focal adhesions, and reveal local mean velocities around 190 nm min⁻¹. The complementarity of PALM and SOFI is assessed in detail with a methodology that integrates a resolution and signal-to-noise metric. This PALM and SOFI concept provides an enlarged quantitative imaging framework, allowing unprecedented functional exploration of focal adhesions through the estimation of molecular parameters such as fluorophore densities and photoactivation or photoswitching kinetics.

Live cell super-resolution imaging requires a high temporal resolution, which remains a challenge. Here the authors combine photo-activated localization microscopy (PALM) with super-resolution optical fluctuation imaging (SOFI) to achieve high spatiotemporal resolution and quantitative imaging of focal adhesion dynamics.

SOFI Simulation Tool: A Software Package for Simulating and Testing Super-Resolution Optical Fluctuation Imaging

Super-resolution optical fluctuation imaging (SOFI) allows one to perform sub-diffraction fluorescence microscopy of living cells. By analyzing the acquired image sequence with an advanced correlation method, i.e. a high-order cross-cumulant analysis, super-resolution in all three spatial dimensions can be achieved. Here we introduce a software tool for a simple qualitative comparison of SOFI images under simulated conditions considering parameters of the microscope setup and essential properties of the biological sample. This tool incorporates SOFI and STORM algorithms, displays and describes the SOFI image processing steps in a tutorial-like fashion. Fast testing of various parameters simplifies the parameter optimization prior to experimental work. The performance of the simulation tool is demonstrated by comparing simulated results with experimentally acquired data.

Super Resolution Imaging of Nanoparticles Cellular Uptake and Trafficking

Understanding the interaction between synthetic nanostructures and living cells is of crucial importance for the development of nanotechnology-based intracellular delivery systems. Fluorescence microscopy is one of the most widespread tools owing to its ability to image multiple colors in native conditions. However, due to the limited resolution, it is unsuitable to address individual diffraction-limited objects. Here we introduce a combination of super-resolution microscopy and single-molecule data analysis to unveil the behavior of nanoparticles during their entry into mammalian cells. Two-color Stochastic Optical Reconstruction Microscopy (STORM) addresses the size and positioning of nanoparticles inside cells and probes their interaction with the cellular machineries at nanoscale resolution. Moreover, we develop image analysis tools to extract quantitative information about internalized particles from STORM images. To demonstrate the potential of our methodology, we extract previously inaccessible information by the direct visualization of the nanoparticle uptake mechanism and the intracellular tracking of nanoparticulate model antigens by dendritic cells. Finally, a direct comparison between STORM, confocal microscopy, and electron microscopy is presented, showing that STORM can provide novel and complementary information on nanoparticle cellular uptake.

Model-free uncertainty estimation in stochastical optical fluctuation imaging (SOFI) leads to a doubled temporal resolution

Stochastic optical fluctuation imaging (SOFI) is a super-resolution fluorescence imaging technique that makes use of stochastic fluctuations in the emission of the fluorophores. During a SOFI measurement multiple fluorescence images are acquired from the sample, followed by the calculation of the spatiotemporal cumulants of the intensities observed at each position. Compared to other techniques, SOFI works well under conditions of low signal-to-noise, high background, or high emitter densities. However, it can be difficult to unambiguously determine the reliability of images produced by any superresolution imaging technique. In this work we present a strategy that enables the estimation of the variance or uncertainty associated with each pixel in the SOFI image. In addition to estimating the image quality or reliability, we show that this can be used to optimize the signal-to-noise ratio (SNR) of SOFI images by including multiple pixel combinations in the cumulant calculation. We present an algorithm to perform this optimization, which automatically takes all relevant instrumental, sample, and probe parameters into account. Depending on the optical magnification of the system, this strategy can be used to improve the SNR of a SOFI image by 40% to 90%. This gain in information is entirely free, in the sense that it does not require additional efforts or complications. Alternatively our approach can be applied to reduce the number of fluorescence images to meet a particular quality level by about 30% to 50%, strongly improving the temporal resolution of SOFI imaging.

Nanoscale Study of Polymer Dynamics

The thermal motion of polymer chains in a crowded environment is anisotropic and highly confined. Whereas theoretical and experimental progress has been made, typically only indirect evidence of polymer dynamics is obtained either from scattering or mechanical response. Toward a complete understanding of the complicated polymer dynamics in crowded media such as biological cells, it is of great importance to unravel the role of heterogeneity and molecular individualism. In the present work, we investigate the dynamics of synthetic polymers and the tube-like motion of individual chains using time-resolved fluorescence microscopy. A single fluorescently labeled polymer molecule is observed in a sea of unlabeled polymers, giving access to not only the dynamics of the probe chain itself but also to that of the surrounding network. We demonstrate that it is possible to extract the characteristic time constants and length scales in one experiment, providing a detailed understanding of polymer dynamics at the single chain level. The quantitative agreement with bulk rheology measurements is promising for using local probes to study heterogeneity in complex, crowded systems.

Super-Resolution Optical Fluctuation Bio-Imaging with Dual-Color Carbon Nanodots

Success in super-resolution imaging relies on a proper choice of fluorescent probes. Here, we suggest novel easily produced and biocompatible nanoparticles-carbon nanodots-for super-resolution optical fluctuation bioimaging (SOFI). The particles revealed an intrinsic dual-color fluorescence, which corresponds to two subpopulations of particles of different electric charges. The neutral nanoparticles localize to cellular nuclei suggesting their potential use as an inexpensive, easily produced nucleus-specific label. The single particle study revealed that the carbon nanodots possess a unique hybrid combination of fluorescence properties exhibiting characteristics of both dye molecules and semiconductor nanocrystals. The results suggest that charge trapping and redistribution on the surface of the particles triggers their transitions between emissive and dark states. These findings open up new possibilities for the utilization of carbon nanodots in the various super-resolution microscopy methods based on stochastic optical switching.

A study of SeqA subcellular localization in Escherichia coli using photo-activated localization microscopy

Escherichia coli (E. coli) cells replicate their genome once per cell cycle to pass on genetic information to the daughter cells. The SeqA protein binds the origin of replication, oriC, after DNA replication initiation and sequesters it from new initiations in order to prevent overinitiation. Conventional fluorescence microscopy studies of SeqA localization in bacterial cells have shown that the protein is localized to discrete foci. In this study we have used photo-activated localization microscopy (PALM) to determine the localization of SeqA molecules, tagged with fluorescent proteins, with a localization precision of 20–30 nm with the aim to visualize the SeqA subcellular structures in more detail than previously possible. SeqA–PAmCherry was imaged in wild type E. coli, expressed from plasmid or genetically engineered into the bacterial genome, replacing the native seqA gene. Unsynchronized cells as well as cells with a synchronized cell cycle were imaged at various time points, in order to investigate the evolution of SeqA localization during the cell cycle. We found that SeqA indeed localized into discrete foci but these were not the only subcellular localizations of the protein. A significant amount of SeqA–PAmCherry molecules was localized outside the foci and in a fraction of cells we saw patterns indicating localization at the membrane. Using quantitative PALM, we counted protein copy numbers per cell, protein copy numbers per focus, the numbers of foci per cell and the sizes of the SeqA clusters. The data showed broad cell-to-cell variation and we did not observe a correlation between SeqA–PAmCherry protein numbers and the cell cycle under the experimental conditions of this study. The numbers of SeqA–PAmCherry molecules per focus as well as the foci sizes also showed broad distributions indicating that the foci are likely not characterized by a fixed number of molecules. We also imaged an E. coli strain devoid of the dam methylase (Δdam) and observed that SeqA–PAmCherry no longer formed foci, and was dispersed throughout the cell and localized to the plasma membrane more readily. We discuss our results in the context of the limitations of the technique.