Fast, single-molecule localization that achieves theoretically minimum uncertainty

Three dimensional single molecule localization using a phase retrieved pupil function

Localization-based superresolution imaging is dependent on finding the positions of individual fluorophores in a sample by fitting the observed single-molecule intensity pattern to the microscope point spread function (PSF). For three-dimensional imaging, system-specific aberrations of the optical system can lead to inaccurate localizations when the PSF model does not account for these aberrations. Here we describe the use of phase-retrieved pupil functions to generate a more accurate PSF and therefore more accurate 3D localizations. The complex-valued pupil function contains information about the system-specific aberrations and can thus be used to generate the PSF for arbitrary defocus. Further, it can be modified to include depth dependent aberrations. We describe the phase retrieval process, the method for including depth dependent aberrations, and a fast fitting algorithm using graphics processing units. The superior localization accuracy of the pupil function generated PSF is demonstrated with dual focal plane 3D superresolution imaging of biological structures.

Superresolution localization methods

Superresolution localization microscopy methods produce nanoscale images via a combination of intermittently active fluorescent probes and algorithms that can precisely determine the positions of these probes from single-molecule or few-molecule images. These algorithms vary widely in their underlying principles, complexity, and accuracy. In this review, we begin by surveying the principles of localization microscopy and describing the fundamental limits to localization precision. We then examine several different families of fluorophore localization algorithms, comparing their complexity, performance, and range of applicability (e.g., whether they require particular types of experimental information, are optimized for specific situations, or are more general). Whereas our focus is on the localization of single isotropic emitters in two dimensions, we also consider oriented dipoles, three-dimensional localization, and algorithms that can handle overlapping images of several nearby fluorophores. Throughout the review, we try to highlight practical advice for users of fluorophore localization algorithms, as well as open questions.

Localization microscopy using noncovalent fluorogen activation by genetically encoded fluorogen-activating proteins

The noncovalent equilibrium activation of a fluorogenic malachite green dye and its cognate fluorogen-activating protein (FAP) can produce a sparse labeling distribution of densely tagged genetically encoded proteins, enabling single molecule detection and super-resolution imaging in fixed and living cells. These sparse labeling conditions are achieved by control of the dye concentration in the milieu, and do not require any photoswitching or photoactivation. The labeling is achieved by using physiological buffers and cellular media, in which additives and switching buffers are not required to obtain super-resolution images. We evaluate the super-resolution properties and images obtained from a selected FAP clone fused to actin, and show that the photon counts per object are between those typically reported for fluorescent proteins and switching-dye pairs, resulting in 10-30 nm localization precision per object. This labeling strategy complements existing approaches, and may simplify multicolor labeling of cellular structures.

Efficient parallel Levenberg-Marquardt model fitting towards real-time automated parametric imaging microscopy

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy.

4Pi fluorescence detection and 3D particle localization with a single objective

Coherent detection through two opposing objectives (4Pi configuration) improves the precision of three-dimensional (3D) single-molecule localization substantially along the axial direction, but suffers from instrument complexity and maintenance difficulty. To address these issues, we have realized 4Pi fluorescence detection by sandwiching the sample between the objective and a mirror, and create interference of direct incidence and mirror-reflected signal at the camera with a spatial light modulator. Multifocal imaging using this single-objective mirror interference scheme offers improvement in the axial localization similar to the traditional 4Pi method. We have also devised several PSF engineering schemes to enable 3D localization with a single emitter image, offering better axial precision than normal single-objective localization methods such as astigmatic imaging.

Superresolution imaging of amyloid fibrils with binding-activated probes

Protein misfolding into amyloid-like aggregates underlies many neurodegenerative diseases. Thus, insights into the structure and function of these amyloids will provide valuable information on the pathological mechanisms involved and aid in the design of improved drugs for treating amyloid-based disorders. However, determining the structure of endogenous amyloids at high resolution has been difficult. Here we employ binding-activated localization microscopy (BALM) to acquire superresolution images of α-synuclein amyloid fibrils with unprecedented optical resolution. We propose that BALM imaging can be extended to study the structure of other amyloids, for differential diagnosis of amyloid-related diseases and for discovery of drugs that perturb amyloid structure for therapy.

Light-sheet confined super-resolution using two-photon photoactivation

Light-sheet microscopy is a useful tool for performing biological investigations of thick samples and it has recently been demonstrated that it can also act as a suitable architecture for super-resolution imaging of thick biological samples by means of individual molecule localization. However, imaging in depth is still limited since it suffers from a reduction in image quality caused by scattering effects. This paper sets out to investigate the advantages of non-linear photoactivation implemented in a selective plane illumination configuration when imaging scattering samples. In particular, two-photon excitation is proven to improve imaging capabilities in terms of imaging depth and is expected to reduce light-sample interactions and sample photo-damage. Here, two-photon photoactivation is coupled to individual molecule localization methods based on light-sheet illumination (IML-SPIM), allowing super-resolution imaging of nuclear pH2AX in NB4 cells.

STED microscopy of living cells--new frontiers in membrane and neurobiology

Recent developments in fluorescence far-field microscopy such as STED microscopy have accomplished observation of the living cell with a spatial resolution far below the diffraction limit. Here, we briefly review the current approaches to super-resolution optical microscopy and present the implementation of STED microscopy for novel insights into live cell mechanisms, with a focus on neurobiology and plasma membrane dynamics.

Dual-color superresolution microscopy reveals nanoscale organization of mechanosensory podosomes

Podosomes are multimolecular mechanosensory assemblies that coordinate mesenchymal migration of tissue-resident dendritic cells. They have a protrusive actin core and an adhesive ring of integrins and adaptor proteins, such as talin and vinculin. We recently demonstrated that core actin oscillations correlate with intensity fluctuations of vinculin but not talin, suggesting different molecular rearrangements for these components. Detailed information on the mutual localization of core and ring components at the nanoscale is lacking. By dual-color direct stochastic optical reconstruction microscopy, we for the first time determined the nanoscale organization of individual podosomes and their spatial arrangement within large clusters formed at the cell-substrate interface. Superresolution imaging of three ring components with respect to actin revealed that the cores are interconnected and linked to the ventral membrane by radiating actin filaments. In core-free areas, αMβ2 integrin and talin islets are homogeneously distributed, whereas vinculin preferentially localizes proximal to the core and along the radiating actin filaments. Podosome clusters appear as self-organized contact areas, where mechanical cues might be efficiently transduced and redistributed. Our findings call for a reevaluation of the current "core-ring" model and provide a novel structural framework for further understanding the collective behavior of podosome clusters.

Fast and efficient molecule detection in localization-based super-resolution microscopy by parallel adaptive histogram equalization

In localization-based super-resolution microscopy, individual fluorescent markers are stochastically photoactivated and subsequently localized within a series of camera frames, yielding a final image with a resolution far beyond the diffraction limit. Yet, before localization can be performed, the subregions within the frames where the individual molecules are present have to be identified-oftentimes in the presence of high background. In this work, we address the importance of reliable molecule identification for the quality of the final reconstructed super-resolution image. We present a fast and robust algorithm (a-livePALM) that vastly improves the molecule detection efficiency while minimizing false assignments that can lead to image artifacts.

Ultrafast, accurate, and robust localization of anisotropic dipoles

The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms. However, the commonly used Gaussian function is not appropriate for anisotropic dipoles because it is not the true point spread function. We derived the theoretical point spread function of tilted dipoles with restricted mobility and developed an algorithm based on an artificial neural network for estimating the localization, orientation and mobility of individual dipoles. Compared with fitting-based methods, our algorithm demonstrated ultrafast speed and higher accuracy, reduced sensitivity to defocusing, strong robustness and adaptability, making it an optimal choice for both two-dimensional and three-dimensional super-resolution imaging analysis.

Fluorescence nanoscopy. Methods and applications

Fluorescence nanoscopy refers to the experimental techniques and analytical methods used for fluorescence imaging at a resolution higher than conventional, diffraction-limited, microscopy. This review explains the concepts behind fluorescence nanoscopy and focuses on the latest and promising developments in acquisition techniques, labelling strategies to obtain highly detailed super-resolved images and in the quantitative methods to extract meaningful information from them.

Measuring image resolution in optical nanoscopy

Resolution in optical nanoscopy (or super-resolution microscopy) depends on the localization uncertainty and density of single fluorescent labels and on the sample's spatial structure. Currently there is no integral, practical resolution measure that accounts for all factors. We introduce a measure based on Fourier ring correlation (FRC) that can be computed directly from an image. We demonstrate its validity and benefits on two-dimensional (2D) and 3D localization microscopy images of tubulin and actin filaments. Our FRC resolution method makes it possible to compare achieved resolutions in images taken with different nanoscopy methods, to optimize and rank different emitter localization and labeling strategies, to define a stopping criterion for data acquisition, to describe image anisotropy and heterogeneity, and even to estimate the average number of localizations per emitter. Our findings challenge the current focus on obtaining the best localization precision, showing instead how the best image resolution can be achieved as fast as possible.

Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms

Newly developed scientific complementary metal–oxide–semiconductor (sCMOS) cameras have the potential to dramatically accelerate data acquisition in single-molecule switching nanoscopy (SMSN) while simultaneously increasing the effective quantum efficiency. However, sCMOS-intrinsic pixel-dependent readout noise substantially reduces the localization precision and introduces localization artifacts. Here we present algorithms that overcome these limitations and provide unbiased, precise localization of single molecules at the theoretical limit. In combination with a multi-emitter fitting algorithm, we demonstrate single-molecule localization super-resolution imaging at up to 32 reconstructed images/second (recorded at 1,600–3,200 camera frames/second) in both fixed and living cells.

Multi-color quantum dot tracking using a high-speed hyperspectral line-scanning microscope

Many cellular signaling processes are initiated by dimerization or oligomerization of membrane proteins. However, since the spatial scale of these interactions is below the diffraction limit of the light microscope, the dynamics of these interactions have been difficult to study on living cells. We have developed a novel high-speed hyperspectral microscope (HSM) to perform single particle tracking of up to 8 spectrally distinct species of quantum dots (QDs) at 27 frames per second. The distinct emission spectra of the QDs allows localization with ∼10 nm precision even when the probes are clustered at spatial scales below the diffraction limit. The capabilities of the HSM are demonstrated here by application of multi-color single particle tracking to observe membrane protein behavior, including: 1) dynamic formation and dissociation of Epidermal Growth Factor Receptor dimers; 2) resolving antigen induced aggregation of the high affinity IgE receptor, FcεR1; 3) four color QD tracking while simultaneously visualizing GFP-actin; and 4) high-density tracking for fast diffusion mapping.

Imaging cells at the nanoscale

Recently developed super-resolution techniques in optical microscopy have pushed the length scale at which cellular structure can be observed down to tens of nanometres. A wide array of methods have been described that fall under the umbrella term of super-resolution microscopy and each of these methods has different requirements for acquisition speed, experimental complexity, fluorophore requirements and post-processing of data. For example, experimental complexity can be decreased by using a standard widefield microscope for acquisition, but this requires substantial processing of the data to extract the super-resolution information. These powerful techniques are bringing new insights into the nanoscale structure of sub-cellular assemblies such as podosomes, which are an ideal system to observe with super-resolution microscopy as the structures are relatively thin and they form and dissociate over a period of several minutes. Here we discuss the major classes of super-resolution microscopy techniques, and demonstrate their relative performance by imaging podosomes.

Real-time analysis and visualization for single-molecule based super-resolution microscopy

Accurate multidimensional localization of isolated fluorescent emitters is a time consuming process in single-molecule based super-resolution microscopy. We demonstrate a functional method for real-time reconstruction with automatic feedback control, without compromising the localization accuracy. Compatible with high frame rates of EM-CCD cameras, it relies on a wavelet segmentation algorithm, together with a mix of CPU/GPU implementation. A combination with Gaussian fitting allows direct access to 3D localization. Automatic feedback control ensures optimal molecule density throughout the acquisition process. With this method, we significantly improve the efficiency and feasibility of localization-based super-resolution microscopy.

Super-resolution imaging by localization microscopy

Photoactivated localization microscopy (PALM) and the related technique of Stochastic optical reconstruction microscopy (STORM) are super-resolution imaging methods based on the precise localization of single molecules. Instruments based on these techniques are now commercially available and are capable of generating images with lateral resolutions in the tens of nanometers range. Here, we give an overview of the current state of this technology including live-cell and 3D PALM and provide an in-depth protocol for performing PALM experiments in a fixed cell monolayer. This includes both the instrumentation/acquisition aspects and the data analysis required for generating quantitative, super-resolution data of molecular distributions. In this example, the system under investigation will be fixed HeLa cells transfected with the photo-switchable fluorescent protein PS-CFP2 targeted to the plasma membrane by fusion to the N-terminus of the protein kinase Lck.

Visualizing cell structure and function with point-localization superresolution imaging

Fundamental to the success of cell and developmental biology is the ability to tease apart molecular organization in cells and tissues by localizing specific proteins with respect to one another in a native cellular context. However, many key cellular structures (from mitochondrial cristae to nuclear pores) lie below the diffraction limit of visible light, precluding analysis of their organization by conventional approaches. Point-localization superresolution microscopy techniques, such as PALM and STORM, are poised to resolve, with unprecedented clarity, the organizational principles of macromolecular complexes within cells, thus leading to deeper insights into cellular function in both health and disease.

Quantifying spatial organization in point-localization superresolution images using pair correlation analysis

The distinctive distributions of proteins within subcellular compartments both at steady state and during signaling events have essential roles in cell function. Here we describe a method for delineating the complex arrangement of proteins within subcellular structures visualized using point-localization superresolution (PL-SR) imaging. The approach, called pair correlation photoactivated localization microscopy (PC-PALM), uses a pair-correlation algorithm to precisely identify single molecules in PL-SR imaging data sets, and it is used to decipher quantitative features of protein organization within subcellular compartments, including the existence of protein clusters and the size, density and number of proteins in these clusters. We provide a step-by-step protocol for PC-PALM, illustrating its analysis capability for four plasma membrane proteins tagged with photoactivatable GFP (PAGFP). The experimental steps for PC-PALM can be carried out in 3 d and the analysis can be done in ∼6-8 h. Researchers need to have substantial experience in single-molecule imaging and statistical analysis to conduct the experiments and carry out this analysis.

Quantum dot-based single-molecule microscopy for the study of protein dynamics

Real-time microscopic visualization of single molecules in living cells provides a molecular perspective of cellular dynamics, which is difficult to be observed by conventional ensemble techniques. Among various classes of fluorescent tags used in single-molecule tracking, quantum dots are particularly useful due to their unique photophysical properties. This chapter provides an overview of single quantum dot tracking for protein dynamic studies. First, we review the fundamental diffraction limit of conventional optical systems and recent developments in single-molecule detection beyond the diffraction barrier. Second, we describe methods to prepare water-soluble quantum dots for biological labeling and single-molecule microscopy experimental design. Third, we provide detailed methods to perform quantum dot-based single-molecule microscopy. This technical section covers three protocols including (1) imaging system calibration using spin-coated single quantum dots, (2) single quantum dot labeling in living cells, and (3) tracking algorithms for single-molecule analysis.

Single quantum dot imaging in living cells

Direct visualization of biological processes at single-molecule level provides a detailed perspective which conventional bulk measurements are hard to achieve. Among various classes of fluorescent tags used in single-molecule tracking, quantum dots are particularly useful due to their unique photophysical properties. In this chapter, we describe the principles, methodologies, and experimental protocols for qdot-based single-molecule imaging. The first half provides an overview of fluorescent microscopy and advances in single-molecule tracking using quantum dots. The remainder of this chapter describes methods to carry out qdot-based single-molecule experiments. Detailed protocols including qdot labeling, microscopy setup, and single-molecule analysis using appropriate computational programs are given.

Single-molecule localization super-resolution microscopy: deeper and faster

For over a decade fluorescence microscopy has demonstrated the capacity to achieve single-molecule localization accuracies of a few nanometers, well below the ≈ 200 nm lateral and ≈ 500 nm axial resolution limit of conventional microscopy. Yet, only the recent development of new fluorescence labeling modalities, the increase in sensitivity of imaging hardware, and the creation of novel image analysis tools allow for the emergence of single-molecule-based super-resolution imaging techniques. Novel methods such as photoactivated localization microscopy and stochastic optical reconstruction microscopy can typically reach a tenfold increase in resolution compared to standard microscopy methods. Their implementation is relatively easy only requiring minimal changes to a conventional wide-field or total internal reflection fluorescence microscope. The recent translation of these two methods into commercial imaging systems has made them further accessible to researchers in biology. However, these methods are still evolving rapidly toward imaging live samples with high temporal resolution and depth. In this review, we recall the roots of single-molecule localization microscopy, summarize major recent developments, and offer perspective on potential applications.

Flexural rigidity measurements of biopolymers using gliding assays

Microtubules are cytoskeletal polymers which play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires microtubules that are stiff and straight enough to span a significant fraction of the cell diameter. As a result, the microtubule persistence length, a measure of stiffness, has been actively studied for the past two decades(1). Nonetheless, open questions remain: short microtubules are 10-50 times less stiff than long microtubules(2-4), and even long microtubules have measured persistence lengths which vary by an order of magnitude(5-9). Here, we present a method to measure microtubule persistence length. The method is based on a kinesin-driven microtubule gliding assay(10). By combining sparse fluorescent labeling of individual microtubules with single particle tracking of individual fluorophores attached to the microtubule, the gliding trajectories of single microtubules are tracked with nanometer-level precision. The persistence length of the trajectories is the same as the persistence length of the microtubule under the conditions used(11). An automated tracking routine is used to create microtubule trajectories from fluorophores attached to individual microtubules, and the persistence length of this trajectory is calculated using routines written in IDL. This technique is rapidly implementable, and capable of measuring the persistence length of 100 microtubules in one day of experimentation. The method can be extended to measure persistence length under a variety of conditions, including persistence length as a function of length along microtubules. Moreover, the analysis routines used can be extended to myosin-based acting gliding assays, to measure the persistence length of actin filaments as well.

Single-molecule super-resolution imaging in bacteria

Bacteria have evolved complex, multi-component cellular machineries to carry out fundamental cellular processes such as cell division/separation, locomotion, protein secretion, DNA transcription/replication, or conjugation/competence. Diffraction of light has so far restricted the use of conventional fluorescence microscopy to reveal the composition, internal architecture and dynamics of these important machineries. This review describes some of the more recent advances on single-molecule super-resolution microscopy methods applied to bacteria and highlights their application to chemotaxis, cell division, DNA segregation, and DNA transcription machineries. Finally, we discuss some of the lessons learned from this approach, and future perspectives.

Super-resolution imaging visualizes the eightfold symmetry of gp210 proteins around the nuclear pore complex and resolves the central channel with nanometer resolution

One of the most complex molecular machines of cells is the nuclear pore complex (NPC), which controls all trafficking of molecules in and out of the nucleus. Because of their importance for cellular processes such as gene expression and cytoskeleton organization, the structure of NPCs has been studied extensively during the last few decades, mainly by electron microscopy. We have used super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM) to investigate the structure of NPCs in isolated Xenopus laevis oocyte nuclear envelopes, with a lateral resolution of ~15 nm. By generating accumulated super-resolved images of hundreds of NPCs we determined the diameter of the central NPC channel to be 41 ± 7 nm and demonstrate that the integral membrane protein gp210 is distributed in an eightfold radial symmetry. Two-color dSTORM experiments emphasize the highly symmetric NPCs as ideal model structures to control the quality of corrections to chromatic aberration and to test the capability and reliability of super-resolution imaging methods.

Video-based tracking of single molecules exhibiting directed in-frame motion

Trajectories of individual molecules moving within complex environments such as cell cytoplasm and membranes or semiflexible polymer networks provide invaluable information on the organization and dynamics of these systems. However, when such trajectories are obtained from a sequence of microscopy images, they can be distorted due to the fact that the tracked molecule exhibits appreciable directed motion during the single-frame acquisition. We propose a new model of image formation for mobile molecules that takes the linear in-frame motion into account and develop an algorithm based on the maximum likelihood approach for retrieving the position and velocity of the molecules from single-frame data. The position and velocity information obtained from individual frames are further fed into a Kalman filter for interframe tracking of molecules that allows prediction of the trajectory of the molecule and further improves the precision of the position and velocity estimates. We evaluate the performance of our algorithm by calculations of the Cramer-Rao Lower Bound, simulations, and model experiments with a piezo-stage. We demonstrate tracking of molecules moving as fast as 7 pixels/frame (12.6 μm/s) within a mean error of 0.42 pixel (37.43 nm).

Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images

Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned to each photon, and independent distributions are joined to describe emitter location. We compare algorithms, and recommend which serves best under different conditions. At low signal-to-noise ratios, ours is 2-fold more precise than others, and 2 orders of magnitude faster; at high ratios, it closely approximates the maximum likelihood estimate.

Estimation theoretic measure of resolution for stochastic localization microscopy

One approach to super-resolution fluorescence microscopy, termed stochastic localization microscopy, relies on the nanometer scale spatial localization of individual fluorescent emitters that stochastically label specific features of the specimen. The precision of emitter localization is an important determinant of the resulting image resolution but is insufficient to specify how well the derived images capture the structure of the specimen. We address this deficiency by considering the inference of specimen structure based on the estimated emitter locations. By using estimation theory, we develop a measure of spatial resolution that jointly depends on the density of the emitter labels, the precision of emitter localization, and prior information regarding the spatial frequency content of the labeled object. The Nyquist criterion does not set the scaling of this measure with emitter number. Given prior information and a fixed emitter labeling density, our resolution measure asymptotes to a finite value as the precision of emitter localization improves. By considering the present experimental capabilities, this asymptotic behavior implies that further resolution improvements require increases in labeling density above typical current values. Our treatment also yields algorithms to enhance reliable image features. Overall, our formalism facilitates the rigorous statistical interpretation of the data produced by stochastic localization imaging techniques.

Fast and precise algorithm based on maximum radial symmetry for single molecule localization

We present an algorithm to estimate the location of single fluorescent molecule with both high speed and high precision. This algorithm is based on finding the subpixel position with maximum radial symmetry in a pixelated single molecule fluorescence image. Compared with conventional algorithms, this algorithm does not rely on point-spread-function or noise model. Through numerical simulation and experimental analysis, we found that this algorithm exhibits localization precision very close to the maximum likelihood estimator (MLE), while executes ∼1000 times faster than the MLE and ∼6 times faster than the fluoroBancroft algorithm.

Insights into cell membrane microdomain organization from live cell single particle tracking of the IgE high affinity receptor FcϵRI of mast cells

Current models propose that the plasma membrane of animal cells is composed of heterogeneous and dynamic microdomains known variously as cytoskeletal corrals, lipid rafts and protein islands. Much of the experimental evidence for these membrane compartments is indirect. Recently, live cell single particle tracking studies using quantum dot-labeled IgE bound to its high affinity receptor FcϵRI, provided direct evidence for the confinement of receptors within micrometer-scale cytoskeletal corrals. In this study, we show that an innovative time-series analysis of single particle tracking data for the high affinity IgE receptor, FcϵRI, on mast cells provides substantial quantitative information about the submicrometer organization of the membrane. The analysis focuses on the probability distribution function of the lengths of the jumps in the positions of the quantum dots labeling individual IgE FcϵRI complexes between frames in movies of their motion. Our results demonstrate the presence, within the micrometer-scale cytoskeletal corrals, of smaller subdomains that provide an additional level of receptor confinement. There is no characteristic size for these subdomains; their size varies smoothly from a few tens of nanometers to a over a hundred nanometers. In QD-IGE labeled unstimulated cells, jumps of less than 70 nm predominate over longer jumps. Addition of multivalent antigen to crosslink the QD-IgE-FcϵRI complexes causes a rapid slowing of receptor motion followed by a long tail of mostly jumps less than 70 nm. The reduced receptor mobility likely reflects both the membrane heterogeneity revealed by the confined motion of the monomeric receptor complexes and the antigen-induced cross linking of these complexes into dimers and higher oligomers. In both cases, the probability distribution of the jump lengths is well fit, from 10 nm to over 100 nm, by a novel power law. The fit for short jumps suggests that the motion of the quantum dots can be modeled as diffusion in a fractal space of dimension less than two.

Inferring biological structures from super-resolution single molecule images using generative models

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information.

Non-bias-limited tracking of spherical particles, enabling nanometer resolution at low magnification

We present a three-dimensional tracking routine for nondiffraction-limited particles, which significantly reduces pixel bias. Our technique allows for increased resolution compared to that of previous methods, especially at low magnification or at high signal/noise ratio. This enables tracking with nanometer accuracy in a wide field of view and tracking of many particles. To reduce bias induced by pixelation, the tracking algorithm uses interpolation of the image on a circular grid to determine the x-, y-, and z-positions. We evaluate the proposed algorithm by tracking simulated images and compare it to well-known center-of-mass and cross-correlation methods. The final resolution of the described method improves up to an order of magnitude in three dimensions compared to conventional tracking methods. We show that errors in x,y-tracking can seriously affect z-tracking if interpolation is not used. We validate our results with experimental data obtained for conditions matching those used in the simulations. Finally, we show that the increased performance of the proposed algorithm uniquely enables it to extract accurate data for the persistence length and end-to-end distance of 107 DNA tethers in a single experiment.

Statistical deconvolution for superresolution fluorescence microscopy

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ∼10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame.

Rational design of true monomeric and bright photoactivatable fluorescent proteins

Monomeric (m)Eos2 is an engineered photoactivatable fluorescent protein widely used for super-resolution microscopy. We show that mEos2 forms oligomers at high concentrations and forms aggregates when labeling membrane proteins, limiting its application as a fusion partner. We solved the crystal structure of tetrameric mEos2 and rationally designed improved versions, mEos3.1 and mEos3.2, that are truly monomeric, are brighter, mature faster and exhibit higher photon budget and label density.

Optical nanoscopy: from acquisition to analysis

Recent advances in far-field microscopy have demonstrated that fluorescence imaging is possible at resolutions well below the long-standing diffraction limit. By exploiting photophysical properties of fluorescent probe molecules, this new class of methods yields a resolving power that is fundamentally diffraction unlimited. Although these methods are becoming more widely used in biological imaging, they must be complemented by suitable data analysis approaches if their potential is to be fully realized. Here we review the basic principles of diffraction-unlimited microscopy and how these principles influence the selection of available algorithms for data analysis. Furthermore, we provide an overview of existing analysis strategies and discuss their application.

Evaluation of sCMOS cameras for detection and localization of single Cy5 molecules

The ability to detect single molecules over the electronic noise requires high performance detector systems. Electron Multiplying Charge-Coupled Device (EMCCD) cameras have been employed successfully to image single molecules. Recently, scientific Complementary Metal Oxide Semiconductor (sCMOS) based cameras have been introduced with very low read noise at faster read out rates, smaller pixel sizes and a lower price compared to EMCCD cameras. In this study, we have compared the two technologies using two EMCCD and three sCMOS cameras to detect single Cy5 molecules. Our findings indicate that the sCMOS cameras perform similar to EMCCD cameras for detecting and localizing single Cy5 molecules.

Position and orientation estimation of fixed dipole emitters using an effective Hermite point spread function model

We introduce a method for determining the position and orientation of fixed dipole emitters based on a combination of polarimetry and spot shape detection. A key element is an effective Point Spread Function model based on Hermite functions. The model offers a good description of the shape variations with dipole orientation and polarization detection channel, and provides computational advantages over the exact vectorial description of dipole image formation. The realized localization uncertainty is comparable to the free dipole case in which spots are rotationally symmetric and can be well modeled with a Gaussian. This result holds for all dipole orientations, for all practical signal levels, and for defocus values within the depth of focus, implying that the massive localization bias for defocused emitters with tilted dipole axis found with Gaussian spot fitting is eliminated.

A unique series of reversibly switchable fluorescent proteins with beneficial properties for various applications

Reversibly switchable fluorescent proteins (RSFPs) have attracted widespread interest for emerging techniques including repeated tracking of protein behavior and superresolution microscopy. Among the limited number of RSFPs available, only Dronpa is widely employed for most cell biology applications due to its monomeric and other favorable photochemical properties. Here we developed a series of monomeric green RSFPs with beneficial optical characteristics such as high photon output per switch, high photostability, a broad range of switching rate, and pH-dependence, which make them potentially useful for various applications. One member of this series, mGeos-M, exhibits the highest photon budget and localization precision potential among all green RSFPs. We propose mGeos-M as a candidate to replace Dronpa for applications such as dynamic tracking, dual-color superresolution imaging, and optical lock-in detection.

Intra-nuclear mobility and target search mechanisms of transcription factors: a single-molecule perspective on gene expression

Precise expression of specific genes in time and space is at the basis of cellular viability as well as correct development of organisms. Understanding the mechanisms of gene regulation is fundamental and still one of the great challenges for biology. Gene expression is regulated also by specific transcription factors that recognize and bind to specific DNA sequences. Transcription factors dynamics, and especially the way they sample the nucleoplasmic space during the search for their specific target in the genome, are a key aspect for regulation and it has been puzzling researchers for forty years. The scope of this review is to give a state-of-the-art perspective over the intra-nuclear mobility and the target search mechanisms of specific transcription factors at the molecular level. Going through the seminal biochemical experiments that have raised the first questions about target localization and the theoretical grounds concerning target search processes, we describe the most recent experimental achievements and current challenges in understanding transcription factors dynamics and interactions with DNA using in vitro assays as well as in live prokaryotic and eukaryotic cells. This article is part of a Special Issue entitled: Nuclear Transport and RNA Processing.

Quantum dots to tail single bio-molecules inside living cells

In the last two decades, the single particle and single molecule approach became more and more popular to investigate the activity and the mechano-chemical properties of biological molecules. The inherent limit of these assays was that the molecules of interest were observed in vitro, out of their natural environment, the cell. Several recent works have shown the possibility to overcome this limit, to extend this approach to living cells and to observe the details of many cellular processes at the molecular level. In this review we discuss the use of semiconductor quantum dots to perform single particle and single molecule tracking in the cell. We refer to other articles for the technical aspects of this method. Here, after an introduction on the advantages provided by these nanoparticles, we restrict ourselves to some examples, mainly related to intracellular transport and molecular motor activity. These will illustrate the important role played by semiconductor quantum dots as fluorescent nano-reporters in in cell single molecule approach in modern biology and biophysics.