Fast, single-molecule localization that achieves theoretically minimum uncertainty

Measurement-based estimation of global pupil functions in 3D localization microscopy

We report the use of a phase retrieval procedure based on maximum likelihood estimation (MLE) to produce an improved, experimentally calibrated model of a point spread function (PSF) for use in three-dimensional (3D) localization microscopy experiments. The method estimates a global pupil phase function (which includes both the PSF and system aberrations) over the full axial range from a simple calibration scan. The pupil function is used to refine the PSF model and hence enable superior localizations from experimental data. To demonstrate the utility of the procedure, we apply it to experimental data acquired with a microscope employing a tetrapod PSF with a 6 µm axial range. The phase-retrieved model demonstrates significant improvements in both accuracy and precision of 3D localizations relative to the model based on scalar diffraction theory. The localization precision of the phase-retrieved model is shown to be near the limits imposed by estimation theory, and the reproducibility of the procedure is characterized and discussed. Code which performs the phase retrieval algorithm is provided.

Tuning membrane protein mobility by confinement into nanodomains

High-speed atomic force microscopy (HS-AFM) can be used to visualize function-related conformational changes of single soluble proteins. Similar studies of single membrane proteins are, however, hampered by a lack of suitable flat, non-interacting membrane supports and by high protein mobility. Here we show that streptavidin crystals grown on mica-supported lipid bilayers can be used as porous supports for membranes containing biotinylated lipids. Using SecYEG (protein translocation channel) and GlpF (aquaglyceroporin), we demonstrate that the platform can be used to tune the lateral mobility of transmembrane proteins to any value within the dynamic range accessible to HS-AFM imaging through glutaraldehyde-cross-linking of the streptavidin. This allows HS-AFM to study the conformation or docking of spatially confined proteins, which we illustrate by imaging GlpF at sub-molecular resolution and by observing the motor protein SecA binding to SecYEG.

Cryogenic photoluminescence imaging system for nanoscale positioning of single quantum emitters

We report a photoluminescence imaging system for locating single quantum emitters with respect to alignment features. Samples are interrogated in a 4 K closed-cycle cryostat by a high numerical aperture (NA = 0.9, 100× magnification) objective that sits within the cryostat, enabling high efficiency collection of emitted photons without image distortions due to the cryostat windows. The locations of single InAs/GaAs quantum dots within a >50 μm × 50 μm field of view are determined with ≈4.5 nm uncertainty (one standard deviation) in a 1 s long acquisition. The uncertainty is determined through a combination of a maximum likelihood estimate for localizing the quantum dot emission, and a cross correlation method for determining the alignment mark center. This location technique can be an important step in the high-throughput creation of nanophotonic devices that rely upon the interaction of highly confined optical modes with single quantum emitters.

Automated tracking of colloidal clusters with sub-pixel accuracy and precision

Quantitative tracking of features from video images is a basic technique employed in many areas of science. Here, we present a method for the tracking of features that partially overlap, in order to be able to track so-called colloidal molecules. Our approach implements two improvements into existing particle tracking algorithms. Firstly, we use the history of previously identified feature locations to successfully find their positions in consecutive frames. Secondly, we present a framework for non-linear least-squares fitting to summed radial model functions and analyze the accuracy (bias) and precision (random error) of the method on artificial data. We find that our tracking algorithm correctly identifies overlapping features with an accuracy below 0.2% of the feature radius and a precision of 0.1 to 0.01 pixels for a typical image of a colloidal cluster. Finally, we use our method to extract the three-dimensional diffusion tensor from the Brownian motion of colloidal dimers.

Single-pixel interior filling function approach for detecting and correcting errors in particle tracking

We present a general method for detecting and correcting biases in the outputs of particle-tracking experiments. Our approach is based on the histogram of estimated positions within pixels, which we term the single-pixel interior filling function (SPIFF). We use the deviation of the SPIFF from a uniform distribution to test the veracity of tracking analyses from different algorithms. Unbiased SPIFFs correspond to uniform pixel filling, whereas biased ones exhibit pixel locking, in which the estimated particle positions concentrate toward the centers of pixels. Although pixel locking is a well-known phenomenon, we go beyond existing methods to show how the SPIFF can be used to correct errors. The key is that the SPIFF aggregates statistical information from many single-particle images and localizations that are gathered over time or across an ensemble, and this information augments the single-particle data. We explicitly consider two cases that give rise to significant errors in estimated particle locations: undersampling the point spread function due to small emitter size and intensity overlap of proximal objects. In these situations, we show how errors in positions can be corrected essentially completely with little added computational cost. Additional situations and applications to experimental data are explored in SI Appendix In the presence of experimental-like shot noise, the precision of the SPIFF-based correction achieves (and can even exceed) the unbiased Cramér-Rao lower bound. We expect the SPIFF approach to be useful in a wide range of localization applications, including single-molecule imaging and particle tracking, in fields ranging from biology to materials science to astronomy.

3D d STORM Imaging of Fixed Brain Tissue

Central nervous system tissue contains a high density of synapses each composed of an intricate molecular machinery mediating precise transmission of information. Deciphering the molecular nanostructure of pre- and postsynaptic specializations within such a complex tissue architecture poses a particular challenge for light microscopy. Here, we describe two approaches suitable to examine the molecular nanostructure of synapses at 20-30 nm lateral and 50-70 nm axial resolution within an area of 500 μm × 500 μm and a depth of 0.6 μm to several micrometers. We employ single-molecule localization microscopy (SMLM) on immunolabeled fixed brain tissue slices. tomoSTORM utilizes array tomography to achieve SMLM in 40 nm thick resin-embedded sections. dSTORM of cryo-sectioned slices uses optical sectioning in 0.1-4 μm thick hydrated sections. Both approaches deliver 3D nanolocalization of two or more labeled proteins within a defined tissue volume. We review sample preparation, data acquisition, analysis, and interpretation.

Nanoscopy of bacterial cells immobilized by holographic optical tweezers

Imaging non-adherent cells by super-resolution far-field fluorescence microscopy is currently not possible because of their rapid movement while in suspension. Holographic optical tweezers (HOTs) enable the ability to freely control the number and position of optical traps, thus facilitating the unrestricted manipulation of cells in a volume around the focal plane. Here we show that immobilizing non-adherent cells by optical tweezers is sufficient to achieve optical resolution well below the diffraction limit using localization microscopy. Individual cells can be oriented arbitrarily but preferably either horizontally or vertically relative to the microscope's image plane, enabling access to sample sections that are impossible to achieve with conventional sample preparation and immobilization. This opens up new opportunities to super-resolve the nanoscale organization of chromosomal DNA in individual bacterial cells.

Efficient homogeneous illumination and optical sectioning for quantitative single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) relies on the switching of fluorescent molecules between a fluorescent and a dark state to achieve super resolution. This process is inherently dependent on the intensity distribution of the laser light used for both activation from the dark state and excitation of the bright state. Typically, laser light is coupled directly or via a single-mode fiber into the microscope, which leads to a Gaussian intensity profile in total internal reflection (TIR) or epi illumination. As a result, switching dynamics and brightness of the fluorescent molecules vary strongly across the field of view, impacting their localization precision and impeding quantitative analysis. Here we present a simple illumination scheme based on the use of a multimode fiber and a laser speckle-reducer, which results in a flat, homogeneous and speckle-free illumination across the entire field of view. In addition, we combined homogeneous multimode excitation of the sample with single-mode based TIR activation to simultaneously obtain the advantages of both approaches: uniform brightness of single fluorophores and TIR-like optical sectioning.

TrackNTrace: A simple and extendable open-source framework for developing single-molecule localization and tracking algorithms

Super-resolution localization microscopy and single particle tracking are important tools for fluorescence microscopy. Both rely on detecting, and tracking, a large number of fluorescent markers using increasingly sophisticated computer algorithms. However, this rise in complexity makes it difficult to fine-tune parameters and detect inconsistencies, improve existing routines, or develop new approaches founded on established principles. We present an open-source MATLAB framework for single molecule localization, tracking and super-resolution applications. The purpose of this software is to facilitate the development, distribution, and comparison of methods in the community by providing a unique, easily extendable plugin-based system and combining it with a novel visualization system. This graphical interface incorporates possibilities for quick inspection of localization and tracking results, giving direct feedback of the quality achieved with the chosen algorithms and parameter values, as well as possible sources for errors. This is of great importance in practical applications and even more so when developing new techniques. The plugin system greatly simplifies the development of new methods as well as adapting and tailoring routines towards any research problem’s individual requirements. We demonstrate its high speed and accuracy with plugins implementing state-of-the-art algorithms and show two biological applications.

Smart-aggregation imaging for single molecule localisation with SPAD cameras

Single molecule localisation microscopy (SMLM) has become an essential part of the super-resolution toolbox for probing cellular structure and function. The rapid evolution of these techniques has outstripped detector development and faster, more sensitive cameras are required to further improve localisation certainty. Single-photon avalanche photodiode (SPAD) array cameras offer single-photon sensitivity, very high frame rates and zero readout noise, making them a potentially ideal detector for ultra-fast imaging and SMLM experiments. However, performance traditionally falls behind that of emCCD and sCMOS devices due to lower photon detection efficiency. Here we demonstrate, both experimentally and through simulations, that the sensitivity of a binary SPAD camera in SMLM experiments can be improved significantly by aggregating only frames containing signal, and that this leads to smaller datasets and competitive performance with that of existing detectors. The simulations also indicate that with predicted future advances in SPAD camera technology, SPAD devices will outperform existing scientific cameras when capturing fast temporal dynamics.

Extracting quantitative information from single-molecule super-resolution imaging data with LAMA - LocAlization Microscopy Analyzer

Super-resolution fluorescence microscopy revolutionizes cell biology research and provides novel insights on how proteins are organized at the nanoscale and in the cellular context. In order to extract a maximum of information, specialized tools for image analysis are necessary. Here, we introduce the LocAlization Microscopy Analyzer (LAMA), a comprehensive software tool that extracts quantitative information from single-molecule super-resolution imaging data. LAMA allows characterizing cellular structures by their size, shape, intensity, distribution, as well as the degree of colocalization with other structures. LAMA is freely available, platform-independent and designed to provide direct access to individual analysis of super-resolution data.

Nanoscopic compartmentalization of membrane protein motion at the axon initial segment

A diffusion barrier impeding membrane molecule motion between the axon and the somatodendritic compartment develops as neurons mature and the axon initial segment (AIS) is enriched in specific molecules. Albrecht et al. analyze the mobility of lipid-anchored molecules in the AIS using single-particle tracking time course experiments and propose a new mechanistic model for the AIS diffusion barrier.

The axon initial segment (AIS) is enriched in specific adaptor, cytoskeletal, and transmembrane molecules. During AIS establishment, a membrane diffusion barrier is formed between the axonal and somatodendritic domains. Recently, an axonal periodic pattern of actin, spectrin, and ankyrin forming 190-nm-spaced, ring-like structures has been discovered. However, whether this structure is related to the diffusion barrier function is unclear. Here, we performed single-particle tracking time-course experiments on hippocampal neurons during AIS development. We analyzed the mobility of lipid-anchored molecules by high-speed single-particle tracking and correlated positions of membrane molecules with the nanoscopic organization of the AIS cytoskeleton. We observe a strong reduction in mobility early in AIS development. Membrane protein motion in the AIS plasma membrane is confined to a repetitive pattern of ∼190-nm-spaced segments along the AIS axis as early as day in vitro 4, and this pattern alternates with actin rings. Mathematical modeling shows that diffusion barriers between the segments significantly reduce lateral diffusion along the axon.

Optical imaging of individual biomolecules in densely packed clusters

Recent advances in fluorescence super-resolution microscopy have allowed subcellular features and synthetic nanostructures down to 10-20 nm in size to be imaged. However, the direct optical observation of individual molecular targets (∼5 nm) in a densely packed biomolecular cluster remains a challenge. Here, we show that such discrete molecular imaging is possible using DNA-PAINT (points accumulation for imaging in nanoscale topography)-a super-resolution fluorescence microscopy technique that exploits programmable transient oligonucleotide hybridization-on synthetic DNA nanostructures. We examined the effects of a high photon count, high blinking statistics and an appropriate blinking duty cycle on imaging quality, and developed a software-based drift correction method that achieves <1 nm residual drift (root mean squared) over hours. This allowed us to image a densely packed triangular lattice pattern with ∼5 nm point-to-point distance and to analyse the DNA origami structural offset with ångström-level precision (2 Å) from single-molecule studies. By combining the approach with multiplexed exchange-PAINT imaging, we further demonstrated an optical nanodisplay with 5 × 5 nm pixel size and three distinct colours with <1 nm cross-channel registration accuracy.

Centroid precision and orientation precision of planar localization microscopy

The concept of localization precision, which is essential to localization microscopy, is formally extended from optical point sources to microscopic rigid bodies. Measurement functions are presented to calculate the planar pose and motion of microscopic rigid bodies from localization microscopy data. Physical lower bounds on the associated uncertainties - termed centroid precision and orientation precision - are derived analytically in terms of the characteristics of the optical measurement system and validated numerically by Monte Carlo simulations. The practical utility of these expressions is demonstrated experimentally by an analysis of the motion of a microelectromechanical goniometer indicated by a sparse constellation of fluorescent nanoparticles. Centroid precision and orientation precision, as developed here, are useful concepts due to the generality of the expressions and the widespread interest in localization microscopy for super-resolution imaging and particle tracking.

Generalized recovery algorithm for 3D super-resolution microscopy using rotating point spread functions

Super-resolution microscopy with phase masks is a promising technique for 3D imaging and tracking. Due to the complexity of the resultant point spread functions, generalized recovery algorithms are still missing. We introduce a 3D super-resolution recovery algorithm that works for a variety of phase masks generating 3D point spread functions. A fast deconvolution process generates initial guesses, which are further refined by least squares fitting. Overfitting is suppressed using a machine learning determined threshold. Preliminary results on experimental data show that our algorithm can be used to super-localize 3D adsorption events within a porous polymer film and is useful for evaluating potential phase masks. Finally, we demonstrate that parallel computation on graphics processing units can reduce the processing time required for 3D recovery. Simulations reveal that, through desktop parallelization, the ultimate limit of real-time processing is possible. Our program is the first open source recovery program for generalized 3D recovery using rotating point spread functions.

Multifluorophore localization as a percolation problem: limits to density and precision

We show that the maximum desirable density of activated fluorophores in a superresolution experiment can be determined by treating the overlapping point spread functions as a problem in percolation theory. We derive a bound on the density of activated fluorophores, taking into account the desired localization accuracy and precision, as well as the number of photons emitted. Our bound on density is close to that reported in experimental work, suggesting that further increases in the density of imaged fluorophores will come at the expense of localization accuracy and precision.

Fisher information theory for parameter estimation in single molecule microscopy: tutorial

Estimation of a parameter of interest from image data represents a task that is commonly carried out in single molecule microscopy data analysis. The determination of the positional coordinates of a molecule from its image, for example, forms the basis of standard applications such as single molecule tracking and localization-based super-resolution image reconstruction. Assuming that the estimator used recovers, on average, the true value of the parameter, its accuracy, or standard deviation, is then at best equal to the square root of the Cramér-Rao lower bound. The Cramér-Rao lower bound can therefore be used as a benchmark in the evaluation of the accuracy of an estimator. Additionally, as its value can be computed and assessed for different experimental settings, it is useful as an experimental design tool. This tutorial demonstrates a mathematical framework that has been specifically developed to calculate the Cramér-Rao lower bound for estimation problems in single molecule microscopy and, more broadly, fluorescence microscopy. The material includes a presentation of the photon detection process that underlies all image data, various image data models that describe images acquired with different detector types, and Fisher information expressions that are necessary for the calculation of the lower bound. Throughout the tutorial, examples involving concrete estimation problems are used to illustrate the effects of various factors on the accuracy of parameter estimation and, more generally, to demonstrate the flexibility of the mathematical framework.

From single-molecule spectroscopy to super-resolution imaging of the neuron: a review

For more than 20 years, single-molecule spectroscopy has been providing invaluable insights into nature at the molecular level. The field has received a powerful boost with the development of the technique into super-resolution imaging methods, ca. 10 years ago, which overcome the limitations imposed by optical diffraction. Today, single molecule super-resolution imaging is routinely used in the study of macromolecular function and structure in the cell. Concomitantly, computational methods have been developed that provide information on numbers and positions of molecules at the nanometer-scale. In this overview, we outline the technical developments that have led to the emergence of localization microscopy techniques from single-molecule spectroscopy. We then provide a comprehensive review on the application of the technique in the field of neuroscience research.

Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.

Optimal channels for channelized quadratic estimators

We present a new method for computing optimized channels for estimation tasks that is feasible for high-dimensional image data. Maximum-likelihood (ML) parameter estimates are challenging to compute from high-dimensional likelihoods. The dimensionality reduction from M measurements to L channels is a critical advantage of channelized quadratic estimators (CQEs), since estimating likelihood moments from channelized data requires smaller sample sizes and inverting a smaller covariance matrix is easier. The channelized likelihood is then used to form ML estimates of the parameter(s). In this work we choose an imaging example in which the second-order statistics of the image data depend upon the parameter of interest: the correlation length. Correlation lengths are used to approximate background textures in many imaging applications, and in these cases an estimate of the correlation length is useful for pre-whitening. In a simulation study we compare the estimation performance, as measured by the root-mean-squared error (RMSE), of correlation length estimates from CQE and power spectral density (PSD) distribution fitting. To abide by the assumptions of the PSD method we simulate an ergodic, isotropic, stationary, and zero-mean random process. These assumptions are not part of the CQE formalism. The CQE method assumes a Gaussian channelized likelihood that can be a valid for non-Gaussian image data, since the channel outputs are formed from weighted sums of the image elements. We have shown that, for three or more channels, the RMSE of CQE estimates of correlation length is lower than conventional PSD estimates. We also show that computing CQE by using a standard nonlinear optimization method produces channels that yield RMSE within 2% of the analytic optimum. CQE estimates of anisotropic correlation length estimation are reported to demonstrate this technique on a two-parameter estimation problem.

Quantitative Analysis of Intracellular Fluorescent Foci in Live Bacteria

Fluorescence microscopy has revolutionized in vivo cellular biology. Through the specific labeling of a protein of interest with a fluorescent protein, one is able to study movement and colocalization, and even count individual proteins in a live cell. Different algorithms exist to quantify the total intensity and position of a fluorescent focus. Although these algorithms have been rigorously studied for in vitro conditions, which are greatly different than the in-homogenous and variable cellular environments, their exact limits and applicability in the context of a live cell have not been thoroughly and systematically evaluated. In this study, we quantitatively characterize the influence of different background subtraction algorithms on several focus analysis algorithms. We use, to our knowledge, a novel approach to assess the sensitivity of the focus analysis algorithms to background removal, in which simulated and experimental data are combined to maintain full control over the sensitivity of a focus within a realistic background of cellular fluorescence. We demonstrate that the choice of algorithm and the corresponding error are dependent on both the brightness of the focus, and the cellular context. Expectedly, focus intensity estimation and localization accuracy suffer in all algorithms at low focus to background ratios, with the bacteroidal background subtraction in combination with the median excess algorithm, and the region of interest background subtraction in combination with a two-dimensional Gaussian fit algorithm, performing the best. We furthermore show that the choice of background subtraction algorithm is dependent on the expression level of the protein under investigation, and that the localization error is dependent on the distance of a focus from the bacterial edge and pole. Our results establish a set of guidelines for what signals can be analyzed to give a targeted spatial and intensity accuracy within a bacterial cell.

Super-resolved insights into human immunodeficiency virus biology

The recent development of fluorescence microscopy approaches overcoming the diffraction limit of light microscopy opened possibilities for studying small-scale cellular processes. The spatial resolution achieved by these novel techniques, together with the possibility to perform live-cell and multicolor imaging, make them ideally suited for visualization of native viruses and subviral structures within the complex environment of a host cell or organ, thus providing fundamentally new possibilities for investigating virus-cell interactions. Here, we review the use of super-resolution microscopy approaches to study virus-cell interactions, and discuss recent insights into human immunodeficiency virus biology obtained by exploiting these novel techniques.

Estimation of the diffusion constant from intermittent trajectories with variable position uncertainties

The movement of a particle described by Brownian motion is quantified by a single parameter, D, the diffusion constant. The estimation of D from a discrete sequence of noisy observations is a fundamental problem in biological single-particle tracking experiments since it can provide information on the environment and/or the state of the particle itself via the hydrodynamic radius. Here, we present a method to estimate D that takes into account several effects that occur in practice, important for the correct estimation of D, and that have hitherto not been combined together for an estimation of D. These effects are motion blur from the finite integration time of the camera, intermittent trajectories, and time-dependent localization uncertainty. Our estimation procedure, a maximum-likelihood estimation with an information-based confidence interval, follows directly from the likelihood expression for a discretely observed Brownian trajectory that explicitly includes these effects. We begin with the formulation of the likelihood expression and then present three methods to find the exact solution. Each method has its own advantages in either computational robustness, theoretical insight, or the estimation of hidden variables. The Fisher information for this likelihood distribution is calculated and analyzed to show that localization uncertainties impose a lower bound on the estimation of D. Confidence intervals are established and then used to evaluate our estimator on simulated data with experimentally relevant camera effects to demonstrate the benefit of incorporating variable localization errors.

Dual-color 3D superresolution microscopy by combined spectral-demixing and biplane imaging

Multicolor three-dimensional (3D) superresolution techniques allow important insight into the relative organization of cellular structures. While a number of innovative solutions have emerged, multicolor 3D techniques still face significant technical challenges. In this Letter we provide a straightforward approach to single-molecule localization microscopy imaging in three dimensions and two colors. We combine biplane imaging and spectral-demixing, which eliminates a number of problems, including color cross-talk, chromatic aberration effects, and problems with color registration. We present 3D dual-color images of nanoscopic structures in hippocampal neurons with a 3D compound resolution routinely achieved only in a single color.

Simultaneous measurement of emission color and 3D position of single molecules

We show that the position of single molecules in all three spatial dimensions can be estimated alongside its emission color by diffractive optics based design of the Point Spread Function (PSF). The phase in a plane conjugate to the aperture stop of the objective lens is modified by a diffractive structure that splits the spot on the camera into closely spaced diffraction orders. The distance between and the size of these sub-spots are a measure of the emission color. Estimation of the axial position is enabled by imprinting aberrations such as astigmatism and defocus onto the orders. The overall spot shape is fitted with a fully vectorial PSF model. Proof-of-principle experiments on quantum dots indicate that a spectral precision of 10 to 20 nm, an axial localization precision of 25 to 50 nm, and a lateral localization precision of 10 to 30 nm can be achieved over a 1 μm range of axial positions for on average 800 signal photons and 17 background photons/pixel. The method appears to be rather sensitive to PSF model errors such as aberrations, giving in particular rise to biases in the fitted wavelength of up to 15 nm.

Deciphering the Structure and Function of Nuclear Pores Using Single-Molecule Fluorescence Approaches

Due to its central role in macromolecular trafficking and nucleocytoplasmic information transfer, the nuclear pore complex (NPC) has been studied in great detail using a wide spectrum of methods. Consequently, many aspects of its architecture, general function, and role in the life cycle of a cell are well understood. Over the last decade, fluorescence microscopy methods have enabled the real-time visualization of single molecules interacting with and transiting through the NPC, allowing novel questions to be examined with nanometer precision. While initial single-molecule studies focused primarily on import pathways using permeabilized cells, it has recently proven feasible to investigate the export of mRNAs in living cells. Single-molecule assays can address questions that are difficult or impossible to answer by other means, yet the complexity of nucleocytoplasmic transport requires that interpretation be based on a firm genetic, biochemical, and structural foundation. Moreover, conceptually simple single-molecule experiments remain technically challenging, particularly with regard to signal intensity, signal-to-noise ratio, and the analysis of noise, stochasticity, and precision. We discuss nuclear transport issues recently addressed by single-molecule microscopy, evaluate the limits of existing assays and data, and identify open questions for future studies. We expect that single-molecule fluorescence approaches will continue to be applied to outstanding nucleocytoplasmic transport questions, and that the approaches developed for NPC studies are extendable to additional complex systems and pathways within cells.

Lens-based fluorescence nanoscopy

The majority of studies of the living cell rely on capturing images using fluorescence microscopy. Unfortunately, for centuries, diffraction of light was limiting the spatial resolution in the optical microscope: structural and molecular details much finer than about half the wavelength of visible light (~200 nm) could not be visualized, imposing significant limitations on this otherwise so promising method. The surpassing of this resolution limit in far-field microscopy is currently one of the most momentous developments for studying the living cell, as the move from microscopy to super-resolution microscopy or 'nanoscopy' offers opportunities to study problems in biophysical and biomedical research at a new level of detail. This review describes the principles and modalities of present fluorescence nanoscopes, as well as their potential for biophysical and cellular experiments. All the existing nanoscopy variants separate neighboring features by transiently preparing their fluorescent molecules in states of different emission characteristics in order to make the features discernible. Usually these are fluorescent 'on' and 'off' states causing the adjacent molecules to emit sequentially in time. Each of the variants can in principle reach molecular spatial resolution and has its own advantages and disadvantages. Some require specific transitions and states that can be found only in certain fluorophore subfamilies, such as photoswitchable fluorophores, while other variants can be realized with standard fluorescent labels. Similar to conventional far-field microscopy, nanoscopy can be utilized for dynamical, multi-color and three-dimensional imaging of fixed and live cells, tissues or organisms. Lens-based fluorescence nanoscopy is poised for a high impact on future developments in the life sciences, with the potential to help solve long-standing quests in different areas of scientific research.

Investigating the usage of point spread functions in point source and microsphere localization

Using a point spread function (PSF) to localize a point-like object, such as a fluorescent molecule or microsphere, represents a common task in single molecule microscopy image data analysis. The localization may differ in purpose depending on the application or experiment, but a unifying theme is the importance of being able to closely recover the true location of the point-like object with high accuracy. We present two simulation studies, both relating to the performance of object localization via the maximum likelihood fitting of a PSF to the object's image. In the first study, we investigate the integration of the PSF over an image pixel, which represents a critical part of the localization algorithm. Specifically, we explore how the fineness of the integration affects how well a point source can be localized, and find the use of too coarse a step size to produce location estimates that are far from the true location, especially when the images are acquired at relatively low magnifications. We also propose a method for selecting an appropriate step size. In the second study, we investigate the suitability of the common practice of using a PSF to localize a microsphere, despite the mismatch between the microsphere's image and the fitted PSF. Using criteria based on the standard errors of the mean and variance, we find the method suitable for microspheres up to 1 μm and 100 nm in diameter, when the localization is performed, respectively, with and without the simultaneous estimation of the width of the PSF.

Nanoscopic cell-wall architecture of an immunogenic ligand in Candida albicans during antifungal drug treatment

Candida albicans evades immunity by limiting cell-wall β-glucan exposure. dSTORM imaging reveals that “unmasking”of glucan by an antifungal drug occurs through nanoscale reorganization of glucan exposure geometry. Nanostructuring of glucan might play a role in innate immune activation and provides insights into the physical regulation of glucan exposure.

The cell wall of Candida albicans is composed largely of polysaccharides. Here we focus on β-glucan, an immunogenic cell-wall polysaccharide whose surface exposure is often restricted, or “masked,” from immune recognition by Dectin-1 on dendritic cells (DCs) and other innate immune cells. Previous research suggested that the physical presentation geometry of β-glucan might determine whether it can be recognized by Dectin-1. We used direct stochastic optical reconstruction microscopy to explore the fine structure of β-glucan exposed on C. albicans cell walls before and after treatment with the antimycotic drug caspofungin, which alters glucan exposure. Most surface-accessible glucan on C. albicans yeast and hyphae is limited to isolated Dectin-1–binding sites. Caspofungin-induced unmasking caused approximately fourfold to sevenfold increase in total glucan exposure, accompanied by increased phagocytosis efficiency of DCs for unmasked yeasts. Nanoscopic imaging of caspofungin-unmasked C. albicans cell walls revealed that the increase in glucan exposure is due to increased density of glucan exposures and increased multiglucan exposure sizes. These findings reveal that glucan exhibits significant nanostructure, which is a previously unknown physical component of the host–Candida interaction that might change during antifungal chemotherapy and affect innate immune activation.

Super-Resolution Microscopy and Tracking of DNA-Binding Proteins in Bacterial Cells

The ability to detect individual fluorescent molecules inside living cells has enabled a range of powerful microscopy techniques that resolve biological processes on the molecular scale. These methods have also transformed the study of bacterial cell biology, which was previously obstructed by the limited spatial resolution of conventional microscopy. In the case of DNA-binding proteins, super-resolution microscopy can visualize the detailed spatial organization of DNA replication, transcription, and repair processes by reconstructing a map of single-molecule localizations. Furthermore, DNA-binding activities can be observed directly by tracking protein movement in real time. This allows identifying subpopulations of DNA-bound and diffusing proteins, and can be used to measure DNA-binding times in vivo. This chapter provides a detailed protocol for super-resolution microscopy and tracking of DNA-binding proteins in Escherichia coli cells. The protocol covers the construction of cell strains and describes data acquisition and analysis procedures, such as super-resolution image reconstruction, mapping single-molecule tracks, computing diffusion coefficients to identify molecular subpopulations with different mobility, and analysis of DNA-binding kinetics. While the focus is on the study of bacterial chromosome biology, these approaches are generally applicable to other molecular processes and cell types.

In vivo single-particle imaging of nuclear mRNA export in budding yeast demonstrates an essential role for Mex67p

Many messenger RNA export proteins have been identified; yet the spatial and temporal activities of these proteins and how they determine directionality of messenger ribonucleoprotein (mRNP) complex export from the nucleus remain largely undefined. Here, the bacteriophage PP7 RNA-labeling system was used in Saccharomyces cerevisiae to follow single-particle mRNP export events with high spatial precision and temporal resolution. These data reveal that mRNP export, consisting of nuclear docking, transport, and cytoplasmic release from a nuclear pore complex (NPC), is fast (∼ 200 ms) and that upon arrival in the cytoplasm, mRNPs are frequently confined near the nuclear envelope. Mex67p functions as the principal mRNP export receptor in budding yeast. In a mex67-5 mutant, delayed cytoplasmic release from NPCs and retrograde transport of mRNPs was observed. This proves an essential role for Mex67p in cytoplasmic mRNP release and directionality of transport.

Label-free multi-color superlocalization of plasmonic emission within metallic nano-interstice using femtosecond chirp-manipulated four wave mixing

We demonstrate an as yet unused method to sieve, localize, and steer plasmonic hot spot within metallic nano-interstices close to percolation threshold. Multicolor superlocalization of plasmon mode within 60 nm was constantly achieved by chirp-manipulated superresolved four wave mixing (FWM) images. Since the percolated film is strongly plasmonic active and structurally multiscale invariant, the present method provides orders of magnitude enhanced light localization within single metallic nano-interstice, and can be universally applied to any region of the random film. The result, verified by the maximum likelihood estimation (MLE) and deconvolution stochastic optical reconstruction microscopy (deconSTORM) algorithm, may contribute to label-free multiplex superlocalized spectroscopy of single molecule and sub-cellular activity monitoring combining hot spot steering capability.

Cramér-Rao Lower Bound for Point Based Image Registration With Heteroscedastic Error Model for Application in Single Molecule Microscopy

The Cramér-Rao lower bound for the estimation of the affine transformation parameters in a multivariate heteroscedastic errors-in-variables model is derived. The model is suitable for feature-based image registration in which both sets of control points are localized with errors whose covariance matrices vary from point to point. With focus given to the registration of fluorescence microscopy images, the Cramér-Rao lower bound for the estimation of a feature's position (e.g., of a single molecule) in a registered image is also derived. In the particular case where all covariance matrices for the localization errors are scalar multiples of a common positive definite matrix (e.g., the identity matrix), as can be assumed in fluorescence microscopy, then simplified expressions for the Cramér-Rao lower bound are given. Under certain simplifying assumptions these expressions are shown to match asymptotic distributions for a previously presented set of estimators. Theoretical results are verified with simulations and experimental data.

A review of progress in single particle tracking: from methods to biophysical insights

Optical microscopy has for centuries been a key tool to study living cells with minimum invasiveness. The advent of single molecule techniques over the past two decades has revolutionized the field of cell biology by providing a more quantitative picture of the complex and highly dynamic organization of living systems. Amongst these techniques, single particle tracking (SPT) has emerged as a powerful approach to study a variety of dynamic processes in life sciences. SPT provides access to single molecule behavior in the natural context of living cells, thereby allowing a complete statistical characterization of the system under study. In this review we describe the foundations of SPT together with novel optical implementations that nowadays allow the investigation of single molecule dynamic events with increasingly high spatiotemporal resolution using molecular densities closer to physiological expression levels. We outline some of the algorithms for the faithful reconstruction of SPT trajectories as well as data analysis, and highlight biological examples where the technique has provided novel insights into the role of diffusion regulating cellular function. The last part of the review concentrates on different theoretical models that describe anomalous transport behavior and ergodicity breaking observed from SPT studies in living cells.

Single-molecule spectroscopy and imaging over the decades

As of 2015, it has been 26 years since the first optical detection and spectroscopy of single molecules in condensed matter. This area of science has expanded far beyond the early low temperature studies in crystals to include single molecules in cells, polymers, and in solution. The early steps relied upon high-resolution spectroscopy of inhomogeneously broadened optical absorption profiles of molecular impurities in solids at low temperatures. Spectral fine structure arising directly from the position-dependent fluctuations of the number of molecules in resonance led to the attainment of the single-molecule limit in 1989 using frequency-modulation laser spectroscopy. In the early 1990s, a variety of fascinating physical effects were observed for individual molecules, including imaging of the light from single molecules as well as observations of spectral diffusion, optical switching and the ability to select different single molecules in the same focal volume simply by tuning the pumping laser frequency. In the room temperature regime, researchers showed that bursts of light from single molecules could be detected in solution, leading to imaging and microscopy by a variety of methods. Studies of single copies of the green fluorescent protein also uncovered surprises, especially the blinking and photoinduced recovery of emitters, which stimulated further development of photoswitchable fluorescent protein labels. All of these early steps provided important fundamentals underpinning the development of super-resolution microscopy based on single-molecule localization and active control of emitting concentration. Current thrust areas include extensions to three-dimensional imaging with high precision, orientational analysis of single molecules, and direct measurements of photodynamics and transport properties for single molecules trapped in solution by suppression of Brownian motion. Without question, a huge variety of studies of single molecules performed by many talented scientists all over the world have extended our knowledge of the nanoscale and many microscopic mechanisms previously hidden by ensemble averaging.

Quantitative analysis and modeling probe polarity establishment in C. elegans embryos

Cell polarity underlies many aspects of metazoan development and homeostasis, and relies notably on a set of PAR proteins located at the cell cortex. How these proteins interact in space and time remains incompletely understood. We performed a quantitative assessment of polarity establishment in one-cell stage Caenorhabditis elegans embryos by combining time-lapse microscopy and image analysis. We used our extensive data set to challenge and further specify an extant mathematical model. Using likelihood-based calibration, we uncovered that cooperativity is required for both anterior and posterior PAR complexes. Moreover, we analyzed the dependence of polarity establishment on changes in size or temperature. The observed robustness of PAR domain dimensions in embryos of different sizes is in agreement with a model incorporating fixed protein concentrations and variations in embryo surface/volume ratio. In addition, we quantified the dynamics of polarity establishment over most of the viable temperatures range of C. elegans. Modeling of these data suggests that diffusion of PAR proteins is the process most affected by temperature changes, although cortical flows appear unaffected. Overall, our quantitative analytical framework provides insights into the dynamics of polarity establishment in a developing system.

Dynamics and Interactions of Individual Proteins in the Membrane of Single, Living Cells

Total internal reflection fluorescence (TIRF) microscopy is a powerful technique for interrogating protein dynamics in the membranes of living single cells. Receptor-ligand interactions are of particular interest for improving our understanding of cell signaling networks in a variety of applications. Here, we describe methods for fluorescently labeling individual receptors and their ligands, conducting single-molecule TIRF microscopy of receptors and ligands in single, living cells, and importantly, performing image analysis on the resulting time sequence of images to extract quantitative dynamics. While we use Toll-like receptor 4 and its ligand lipopolysaccharide as a specific example, the methods are general and readily extendable to other receptor-ligand systems of importance in cellular biology.

Single-molecule microscopy of molecules tagged with GFP or RFP derivatives in mammalian cells using nanobody binders

With the recent development of single-molecule localization-based superresolution microscopy, the imaging of cellular structures at a resolution below the diffraction-limit of light has become a widespread technique. While single fluorescent molecules can be resolved in the nanometer range, the delivery of these molecules to the authentic structure in the cell via traditional antibody-mediated techniques can add substantial error due to the size of the antibodies. Accurate and quantitative labeling of cellular molecules has thus become one of the bottlenecks in the race for highest resolution of target structures. Here we illustrate in detail how to use small, high affinity nanobody binders against GFP and RFP family proteins for highly generic labeling of fusion constructs with bright organic dyes. We provide detailed protocols and examples for their application in superresolution imaging and single particle tracking and demonstrate advantages over conventional labeling approaches.

Probability-based particle detection that enables threshold-free and robust in vivo single-molecule tracking

Any single-molecule study starts with finding those single-molecule signals in recorded images. Currently, parameters such as filter and thresholds are user set, and errors are unknown and not observed or controlled. A framework is presented in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test.

Single-molecule detection in fluorescence nanoscopy has become a powerful tool in cell biology but can present vexing issues in image analysis, such as limited signal, unspecific background, empirically set thresholds, image filtering, and false-positive detection limiting overall detection efficiency. Here we present a framework in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test. Our method delivers robust and threshold-free signal detection with a defined error estimate and improved detection of weaker signals. The probability value has consequences for downstream data analysis, such as weighing a series of detections and corresponding probabilities, Bayesian propagation of probability, or defining metrics in tracking applications. We show that the method outperforms all current approaches, yielding a detection efficiency of >70% and a false-positive detection rate of <5% under conditions down to 17 photons/pixel background and 180 photons/molecule signal, which is beneficial for any kind of photon-limited application. Examples include limited brightness and photostability, phototoxicity in live-cell single-molecule imaging, and use of new labels for nanoscopy. We present simulations, experimental data, and tracking of low-signal mRNAs in yeast cells.

Nanoscale Landscape of Phosphoinositides Revealed by Specific Pleckstrin Homology (PH) Domains Using Single-molecule Superresolution Imaging in the Plasma Membrane

Both phosphatidylinositol 4-phosphate (PI4P) and phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) are independent plasma membrane (PM) determinant lipids that are essential for multiple cellular functions. However, their nanoscale spatial organization in the PM remains elusive. Using single-molecule superresolution microscopy and new photoactivatable fluorescence probes on the basis of pleckstrin homology domains that specifically recognize phosphatidylinositides in insulin-secreting INS-1 cells, we report that the PI(4,5)P2 probes exhibited a remarkably uniform distribution in the major regions of the PM, with some sparse PI(4,5)P2-enriched membrane patches/domains of diverse sizes (383 ± 14 nm on average). Quantitative analysis revealed a modest concentration gradient that was much less steep than previously thought, and no densely packed PI(4,5)P2 nanodomains were observed. Live-cell superresolution imaging further demonstrated the dynamic structural changes of those domains in the flat PM and membrane protrusions. PI4P and phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3) showed similar spatial distributions as PI(4,5)P2. These data reveal the nanoscale landscape of key inositol phospholipids in the native PM and imply a framework for local cellular signaling and lipid-protein interactions at a nanometer scale.

Fast and Precise 3D Fluorophore Localization based on Gradient Fitting

Astigmatism imaging approach has been widely used to encode the fluorophore's 3D position in single-particle tracking and super-resolution localization microscopy. Here, we present a new high-speed localization algorithm based on gradient fitting to precisely decode the 3D subpixel position of the fluorophore. This algebraic algorithm determines the center of the fluorescent emitter by finding the position with the best-fit gradient direction distribution to the measured point spread function (PSF), and can retrieve the 3D subpixel position of the fluorophore in a single iteration. Through numerical simulation and experiments with mammalian cells, we demonstrate that our algorithm yields comparable localization precision to the traditional iterative Gaussian function fitting (GF) based method, while exhibits over two orders-of-magnitude faster execution speed. Our algorithm is a promising high-speed analyzing method for 3D particle tracking and super-resolution localization microscopy.

Orchestration of ErbB3 signaling through heterointeractions and homointeractions

Members of the ErbB family of receptor tyrosine kinases are capable of both homointeractions and heterointeractions. Because each receptor has a unique set of binding sites for downstream signaling partners and differential catalytic activity, subtle shifts in their combinatorial interplay may have a large effect on signaling outcomes. The overexpression and mutation of ErbB family members are common in numerous human cancers and shift the balance of activation within the signaling network. Here we report the development of a spatial stochastic model that addresses the dynamics of ErbB3 homodimerization and heterodimerization with ErbB2. The model is based on experimental measures for diffusion, dimer off-rates, kinase activity, and dephosphorylation. We also report computational analysis of ErbB3 mutations, generating the prediction that activating mutations in the intracellular and extracellular domains may be subdivided into classes with distinct underlying mechanisms. We show experimental evidence for an ErbB3 gain-of-function point mutation located in the C-lobe asymmetric dimerization interface, which shows enhanced phosphorylation at low ligand dose associated with increased kinase activity.

Enhanced dimerization drives ligand-independent activity of mutant epidermal growth factor receptor in lung cancer

Epidermal growth factor receptor kinase mutations drive oncogenesis, but the molecular mechanism of pathological signal initiation is poorly understood. Using high-resolution microscopy methods, the authors reveal that these kinase mutations induce structural changes in the receptor ectodomain that lead to enhanced, ligand-independent dimerization.

Mutations within the epidermal growth factor receptor (EGFR/erbB1/Her1) are often associated with tumorigenesis. In particular, a number of EGFR mutants that demonstrate ligand-independent signaling are common in non–small cell lung cancer (NSCLC), including kinase domain mutations L858R (also called L834R) and exon 19 deletions (e.g., ΔL747-P753insS), which collectively make up nearly 90% of mutations in NSCLC. The molecular mechanisms by which these mutations confer constitutive activity remain unresolved. Using multiple subdiffraction-limit imaging modalities, we reveal the altered receptor structure and interaction kinetics of NSCLC-associated EGFR mutants. We applied two-color single quantum dot tracking to quantify receptor dimerization kinetics on living cells and show that, in contrast to wild-type EGFR, mutants are capable of forming stable, ligand-independent dimers. Two-color superresolution localization microscopy confirmed ligand-independent aggregation of EGFR mutants. Live-cell Förster resonance energy transfer measurements revealed that the L858R kinase mutation alters ectodomain structure such that unliganded mutant EGFR adopts an extended, dimerization-competent conformation. Finally, mutation of the putative dimerization arm confirmed a critical role for ectodomain engagement in ligand-independent signaling. These data support a model in which dysregulated activity of NSCLC-associated kinase mutants is driven by coordinated interactions involving both the kinase and extracellular domains that lead to enhanced dimerization.

Classification of dynamical diffusion states in single molecule tracking microscopy

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins.

Bax monomers form dimer units in the membrane that further self-assemble into multiple oligomeric species

Bax is a key regulator of apoptosis that mediates the release of cytochrome c to the cytosol via oligomerization in the outer mitochondrial membrane before pore formation. However, the molecular mechanism of Bax assembly and regulation by other Bcl-2 members remains obscure. Here, by analysing the stoichiometry of Bax oligomers at the single-molecule level, we find that Bax binds to the membrane in a monomeric state and then self-assembles in <1 min. Strikingly, active Bax does not exist in a unique oligomeric state, but as several different species based on dimer units. Moreover, we show that cBid activates Bax without affecting its assembly, while Bcl-xL induces the dissociation of Bax oligomers. On the basis of our experimental data and theoretical modelling, we propose a new mechanism for the molecular pathway of Bax assembly to form the apoptotic pore.

Co-Orientation: Quantifying Simultaneous Co-Localization and Orientational Alignment of Filaments in Light Microscopy

Co-localization analysis is a widely used tool to seek evidence for functional interactions between molecules in different color channels in microscopic images. Here we extend the basic co-localization analysis by including the orientations of the structures on which the molecules reside. We refer to the combination of co-localization of molecules and orientational alignment of the structures on which they reside as co-orientation. Because the orientation varies with the length scale at which it is evaluated, we consider this scale as a separate informative dimension in the analysis. Additionally we introduce a data driven method for testing the statistical significance of the co-orientation and provide a method for visualizing the local co-orientation strength in images. We demonstrate our methods on simulated localization microscopy data of filamentous structures, as well as experimental images of similar structures acquired with localization microscopy in different color channels. We also show that in cultured primary HUVEC endothelial cells, filaments of the intermediate filament vimentin run close to and parallel with microtubuli. In contrast, no co-orientation was found between keratin and actin filaments. Co-orientation between vimentin and tubulin was also observed in an endothelial cell line, albeit to a lesser extent, but not in 3T3 fibroblasts. These data therefore suggest that microtubuli functionally interact with the vimentin network in a cell-type specific manner.

Investigation of the numerics of point spread function integration in single molecule localization

The computation of point spread functions, which are typically used to model the image profile of a single molecule, represents a central task in the analysis of single molecule microscopy data. To determine how the accuracy of the computation affects how well a single molecule can be localized, we investigate how the fineness with which the point spread function is integrated over an image pixel impacts the performance of the maximum likelihood location estimator. We consider both the Airy and the two-dimensional Gaussian point spread functions. Our results show that the point spread function needs to be adequately integrated over a pixel to ensure that the estimator closely recovers the true location of the single molecule with an accuracy that is comparable to the best possible accuracy as determined using the Fisher information formalism. Importantly, if integration with an insufficiently fine step size is carried out, the resulting estimates can be significantly different from the true location, particularly when the image data is acquired at relatively low magnifications. We also present a methodology for determining an adequate step size for integrating the point spread function.

SNSMIL, a real-time single molecule identification and localization algorithm for super-resolution fluorescence microscopy

Single molecule localization based super-resolution fluorescence microscopy offers significantly higher spatial resolution than predicted by Abbe's resolution limit for far field optical microscopy. Such super-resolution images are reconstructed from wide-field or total internal reflection single molecule fluorescence recordings. Discrimination between emission of single fluorescent molecules and background noise fluctuations remains a great challenge in current data analysis. Here we present a real-time, and robust single molecule identification and localization algorithm, SNSMIL (Shot Noise based Single Molecule Identification and Localization). This algorithm is based on the intrinsic nature of noise, i.e., its Poisson or shot noise characteristics and a new identification criterion, QSNSMIL, is defined. SNSMIL improves the identification accuracy of single fluorescent molecules in experimental or simulated datasets with high and inhomogeneous background. The implementation of SNSMIL relies on a graphics processing unit (GPU), making real-time analysis feasible as shown for real experimental and simulated datasets.

Quantitative evaluation of software packages for single-molecule localization microscopy

The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.

Precise Three-Dimensional Scan-Free Multiple-Particle Tracking over Large Axial Ranges with Tetrapod Point Spread Functions

We employ a novel framework for information-optimal microscopy to design a family of point spread functions (PSFs), the Tetrapod PSFs, which enable high-precision localization of nanoscale emitters in three dimensions over customizable axial (z) ranges of up to 20 μm with a high numerical aperture objective lens. To illustrate, we perform flow profiling in a microfluidic channel and show scan-free tracking of single quantum-dot-labeled phospholipid molecules on the surface of living, thick mammalian cells.