Simultaneous multiplane imaging-based localization encoded (SMILE) microscopy for super-resolution volume imaging

Fortunate molecules boost signal to background ratio and localization precision in correlation based single molecule localization microscopy

Single-molecule localization microscopy (SMLM) can decipher fine details that are otherwise impossible using diffraction-limited microscopy. Often, the reconstructed super-resolved images suffer from noise, strong background and are prone to false detections that may impact quantitative imaging. To overcome these limitations, we propose a technique (corrSMLM) that recognizes and detects fortunate molecules (molecules with long blinking cycles) from the recorded data. The method uses correlation between two or more consecutive frames to identify and isolate fortunate molecules that blink longer than the standard blinking period of a molecule. The corrSMLM is based on the fact that random fluctuations (noise) do not last longer (usually limited to a single frame). In contrast, fortunate molecules consistently fluoresce for extended periods and hence appear on more than one frame. Accordingly, strongly correlated spots (representing fortunate molecules) are compared in the consecutive frames, followed by data integration to determine their position and localization precision. The technique addresses two significant problems that plague existing SMLM : (1) false detection due to random noise that contributes to a strong background and (2) poor localization leading to overall low resolution. To demonstrate, corrSMLM is used for imaging fixed NIH3T3 cells (transfected with Dendra2-Actin, Dendra2-Tubulin, and mEos-Tom20 plasmid DNA). The super-resolved images show a significant reduction in background noise ( > 1.5 fold boost in SBR) and  > 2-fold improvement in localization precision as compared to standard SMLM. Intensity analysis based on the number of molecules suggests that corrSMLM better corroborates the raw data and preserves finer features (e.g., edges), which are wiped out in standard SMLM. Overall, an improvement is noted in the localization precision and spatial resolution. The proposed technique is anticipated to advance SMLM and is expected to contribute to a better understanding of single-molecule dynamics in a cellular environment.

Scanning single molecule localization microscopy (scanSMLM) for super-resolution volume imaging

Over the last decade, single-molecule localization microscopy (SMLM) has developed into a set of powerful techniques that have improved spatial resolution over diffraction-limited microscopy and demonstrated the ability to resolve biological features down to a few tens of nanometers. We introduce a single molecule-based scanning SMLM (scanSMLM) system that enables rapid volume imaging. Along with epi-illumination, the system employs a scanning-based 4f detection for volume imaging. The 4f system comprises a combination of an electrically-tunable lens and high NA detection objective lens. By rapidly changing the aperture (or equivalently the focus) of an electrically-tunable lens (ETL) in a 4f detection system, the selectivity of the axial object plane is achieved, for which the image forms in the image/detector plane. So, in principle, one can scan the object volume by just altering the aperture of ETL. Two schemes were adopted to carry out volume imaging: cyclic scan and conventional scan. The cyclic scheme scans the volume in each scan cycle, whereas plane-wise scanning is performed in the conventional scheme. Hence, the cyclic scan ensures uniform dwell time on each frame during data collection, thereby evenly distributing photobleaching throughout the cell volume. With a minimal change in the system hardware (requiring the addition of an ETL lens and related electronics for step-voltage generation) in the existing SMLM system, volume scanning (along the z-axis) can be achieved. To calibrate and derive critical system parameters, we imaged fluorescent beads embedded in a gel-matrix 3D block as a test sample. Subsequently, scanSMLM is employed to visualize the architecture of actin-filaments and the distribution of Meos-Tom20 molecules on the mitochondrial membrane. The technique is further exploited to understand the clustering of Hemagglutinin (HA) protein single molecules in a transfected cell for studying Influenza-A disease progression. The system, for the first time, enabled 3D visualization of HA distribution that revealed HA cluster formation spanning the entire cell volume, post 24 hrs of transfection. Critical biophysical parameters related to HA clusters (density, the number of HA molecules per cluster, axial span, fraction of clustered molecules, and others) are also determined, giving an unprecedented insight into Influenza-A disease progression at the single-molecule level.

Temporally resolved SMLM (with large PAR shift) enabled visualization of dynamic HA cluster formation and migration in a live cell

The blinking properties of a single molecule are critical for single-molecule localization microscopy (SMLM). Typically, SMLM techniques involve recording several frames of diffraction-limited bright spots of single-molecules with a detector exposure time close to the blinking period. This sets a limit on the temporal resolution of SMLM to a few tens of milliseconds. Realizing that a substantial fraction of single molecules emit photons for time scales much shorter than the average blinking period, we propose accelerating data collection to capture these fast emitters. Here, we put forward a short exposure-based SMLM (shortSMLM) method powered by sCMOS detector for understanding dynamical events (both at single molecule and ensemble level). The technique is demonstrated on an Influenza-A disease model, where NIH3T3 cells (both fixed and live cells) were transfected by Dendra2-HA plasmid DNA. Analysis shows a 2.76-fold improvement in the temporal resolution that comes with a sacrifice in spatial resolution, and a particle resolution shift PAR-shift (in terms of localization precision) of [Formula: see text] 11.82  nm compared to standard SMLM. We visualized dynamic HA cluster formation in transfected cells post 24 h of DNA transfection. It is noted that a reduction in spatial resolution does not substantially alter cluster characteristics (cluster density, [Formula: see text] molecules/cluster, cluster spread, etc.) and, indeed, preserves critical features. Moreover, the time-lapse imaging reveals the dynamic formation and migration of Hemagglutinin (HA) clusters in a live cell. This suggests that [Formula: see text] using a synchronized high QE sCMOS detector (operated at short exposure times) is excellent for studying temporal dynamics in cellular system.

Detection of fortunate molecules induce particle resolution shift (PAR-shift) toward single-molecule limit in SMLM: A technique for resolving molecular clusters in cellular system

Molecules capable of emitting a large number of photons (also known as fortunate molecules) are crucial for achieving a resolution close to single molecule limit (the actual size of a single molecule). We propose a long-exposure single molecule localization microscopy (leSMLM) technique that enables detection of fortunate molecules, which is based on the fact that detecting a relatively small subset of molecules with large photon emission increases its localization precision (∼r₀/N). Fortunate molecules have the ability to emit a large burst of photons over a prolonged time (> average blinking lifetime). So, a long exposure time allows the time window necessary to detect these elite molecules. The technique involves the detection of fortunate molecules to generate enough statistics for a quality reconstruction of the target protein distribution in a cellular system. Studies show a significant PArticle Resolution Shift (PAR-shift) of about 6 and 11 nm toward single-molecule-limit (far from diffraction-limit) for an exposure time window of 60 and 90 ms, respectively. In addition, a significant decrease in the fraction of fortunate molecules (single molecules with small localization precision) is observed. Specifically, 8.33% and 3.43% molecules are found to emit in 30-60  ms and >60 ms, respectively, when compared to single molecule localization microscopy (SMLM). The long exposure has enabled better visualization of the Dendra2HA molecular cluster, resolving sub-clusters within a large cluster. Thus, the proposed technique leSMLM facilitates a better study of cluster formation in fixed samples. Overall, leSMLM technique offers a spatial resolution improvement of ~ 10 nm compared to traditional SMLM at the cost of marginally poor temporal resolution.

Single-Molecule Clustering for Super-Resolution Optical Fluorescence Microscopy

Molecular assembly in a complex cellular environment is vital for understanding underlying biological mechanisms. Biophysical parameters (such as single-molecule cluster density, cluster-area, pairwise distance, and number of molecules per cluster) related to molecular clusters directly associate with the physiological state (healthy/diseased) of a cell. Using super-resolution imaging along with powerful clustering methods (K-means, Gaussian mixture, and point clustering), we estimated these critical biophysical parameters associated with dense and sparse molecular clusters. We investigated Hemaglutinin (HA) molecules in an Influenza type A disease model. Subsequently, clustering parameters were estimated for transfected NIH3T3 cells. Investigations on test sample (randomly generated clusters) and NIH3T3 cells (expressing Dendra2-Hemaglutinin (Dendra2-HA) photoactivable molecules) show a significant disparity among the existing clustering techniques. It is observed that a single method is inadequate for estimating all relevant biophysical parameters accurately. Thus, a multimodel approach is necessary in order to characterize molecular clusters and determine critical parameters. The proposed study involving optical system development, photoactivable sample synthesis, and advanced clustering methods may facilitate a better understanding of single molecular clusters. Potential applications are in the emerging field of cell biology, biophysics, and fluorescence imaging.

Probabilistic Optically-Selective Single-molecule Imaging Based Localization Encoded (POSSIBLE) microscopy for ultra-superresolution imaging

To be able to resolve molecular-clusters it is crucial to access vital information (such as, molecule density, cluster-size, and others) that are key in understanding disease progression and the underlying mechanism. Traditional single-molecule localization microscopy (SMLM) techniques use molecules of variable sizes (as determined by its localization precision (LP)) to reconstruct a super-resolution map. This results in an image with overlapping and superimposing PSFs (due to a wide size-spectrum of single-molecules) that undermine image resolution. Ideally, it should be possible to identify the brightest molecules (also termed as the fortunate molecules) to reconstruct ultra-superresolution map, provided sufficient statistics is available from the recorded data. Probabilistic Optically-Selective Single-molecule Imaging Based Localization Encoded (POSSIBLE) microscopy explores this possibility by introducing a narrow probability size-distribution of single-molecules (narrow size-spectrum about a predefined mean-size). The reconstruction begins by presetting the mean and variance of the narrow distribution function (Gaussian function). Subsequently, the dataset is processed and single-molecules are filtered by the Gaussian function to remove unfortunate molecules. The fortunate molecules thus retained are then mapped to reconstruct an ultra-superresolution map. In-principle, the POSSIBLE microscopy technique is capable of infinite resolution (resolution of the order of actual single-molecule size) provided enough fortunate molecules are experimentally detected. In short, bright molecules (with large emissivity) holds the key. Here, we demonstrate the POSSIBLE microscopy technique and reconstruct single-molecule images with an average PSF sizes of σ ± Δσ = 15 ± 10 nm, 30 ± 2 nm & 50 ± 2 nm. Results show better-resolved Dendra2-HA clusters with large cluster-density in transfected NIH3T3 fibroblast cells as compared to the traditional SMLM techniques. Cluster analysis indicates densely-packed HA molecules, HA-HA interaction, and a surge in the number of HA molecules per cluster post 24 Hrs of transfection. The study using POSSIBLE microscopy introduces new insights in influenza biology. We anticipate exciting applications in the multidisciplinary field of disease biology, oncology, and biomedical imaging.