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

Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learning

Microscopy images often suffer from high levels of noise, which can hinder further analysis and interpretation. Content-aware image restoration (CARE) methods have been proposed to address this issue, but they often require large amounts of training data and suffer from over-fitting. To overcome these challenges, we propose a novel framework for few-shot microscopy image denoising. Our approach combines a generative adversarial network (GAN) trained via contrastive learning (CL) with two structure preserving loss terms (Structural Similarity Index and Total Variation loss) to further improve the quality of the denoised images using little data. We demonstrate the effectiveness of our method on three well-known microscopy imaging datasets, and show that we can drastically reduce the amount of training data while retaining the quality of the denoising, thus alleviating the burden of acquiring paired data and enabling few-shot learning. The proposed framework can be easily extended to other image restoration tasks and has the potential to significantly advance the field of microscopy image analysis

Non-parametric regression for patch-based fluorescence microscopy image sequence denoising

We present a non-parametric regression method for denoising 3D image sequences acquired in fluorescence microscopy. The proposed method exploits 3D+time information to improve the signal-to-noise ratio of images corrupted by mixed Poisson-Gaussian noise. A variance stabilization transform is first applied to the image-data to introduce independence between the mean and variance. This pre-processing requires the knowledge of parameters related to the acquisition system, also estimated in our approach. In a second step, we propose an original statistical patch-based framework for noise reduction and preservation of space-time discontinuities. In our study, discontinuities are related to small moving spots with high velocity observed in fluorescence video-microscopy. The idea is to minimize an objective nonlocal energy functional involving spatio-temporal image patches. The minimizer has a simple form and is defined as the weighted average of input data taken in spatially-varying neighborhoods. The size of each neighborhood is optimized to improve the performance of the pointwise estimator. The performance of the algorithm which requires no motion estimation, is then demonstrated on both synthetic and real image sequences using qualitative and quantitative criteria

The interaction of IQGAP1 with the exocyst complex is required for tumor cell invasion downstream of Cdc42 and RhoA

Invadopodia are actin-based membrane protrusions formed at contact sites between invasive tumor cells and the extracellular matrix with matrix proteolytic activity. Actin regulatory proteins participate in invadopodia formation, whereas matrix degradation requires metalloproteinases (MMPs) targeted to invadopodia. In this study, we show that the vesicle-tethering exocyst complex is required for matrix proteolysis and invasion of breast carcinoma cells. We demonstrate that the exocyst subunits Sec3 and Sec8 interact with the polarity protein IQGAP1 and that this interaction is triggered by active Cdc42 and RhoA, which are essential for matrix degradation. Interaction between IQGAP1 and the exocyst is necessary for invadopodia activity because enhancement of matrix degradation induced by the expression of IQGAP1 is lost upon deletion of the exocyst-binding site. We further show that the exocyst and IQGAP1 are required for the accumulation of cell surface membrane type 1 MMP at invadopodia. Based on these results, we propose that invadopodia function in tumor cells relies on the coordination of cytoskeletal assembly and exocytosis downstream of Rho guanosine triphosphatases

A tessellation-based colocalization analysis approach for single-molecule localization microscopy

International audienceMulticolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner

Single-particle tracking uncovers dynamics of glutamate-induced retrograde transport of NF-κB p65 in living neurons

Retrograde transport of NF-κB from the synapse to the nucleus in neurons is mediated by the dynein/dynactin motor complex and can be triggered by synaptic activation. The calibre of axons is highly variable ranging down to 100 nm, aggravating the investigation of transport processes in neurites of living neurons using conventional light microscopy. In this study we quantified for the first time the transport of the NF-κB subunit p65 using high-density single-particle tracking in combination with photoactivatable fluorescent proteins in living mouse hippocampal neurons. We detected an increase of the mean diffusion coefficient (Dmean) in neurites from 0.12 ± 0.05 µm2/s to 0.61 ± 0.03 µm2/s after stimulation with glutamate. We further observed that the relative amount of retrogradely transported p65 molecules is increased after stimulation. Glutamate treatment resulted in an increase of the mean retrograde velocity from 10.9 ± 1.9 to 15 ± 4.9 µm/s, whereas a velocity increase from 9 ± 1.3 to 14 ± 3 µm/s was observed for anterogradely transported p65. This study demonstrates for the first time that glutamate stimulation leads to an increased mobility of single NF-κB p65 molecules in neurites of living hippocampal neurons

Heterogeneity of AMPA receptor trafficking and molecular interactions revealed by superresolution analysis of live cell imaging

Simultaneous tracking of many thousands of individual particles in live cells is possible now with the advent of high-density superresolution imaging methods. We present an approach to extract local biophysical properties of cell-particle interaction from such newly acquired large collection of data. Because classical methods do not keep the spatial localization of individual trajectories, it is not possible to access localized biophysical parameters. In contrast, by combining the high-density superresolution imaging data with the present analysis, we determine the local properties of protein dynamics. We specifically focus on AMPA receptor (AMPAR) trafficking and estimate the strength of their molecular interaction at the subdiffraction level in hippocampal dendrites. These interactions correspond to attracting potential wells of large size, showing that the high density of AMPARs is generated by physical interactions with an ensemble of cooperative membrane surface binding sites, rather than molecular crowding or aggregation, which is the case for the membrane viral glycoprotein VSVG. We further show that AMPARs can either be pushed in or out of dendritic spines. Finally, we characterize the recurrent step of influenza trajectories. To conclude, the present analysis allows the identification of the molecular organization responsible for the heterogeneities of random trajectories in cells

The actin-based motor protein myosin II regulates MHC class II trafficking and BCR-driven antigen presentation

Antigen (Ag) capture and presentation onto major histocompatibility complex (MHC) class II molecules by B lymphocytes is mediated by their surface Ag receptor (B cell receptor [BCR]). Therefore, the transport of vesicles that carry MHC class II and BCR–Ag complexes must be coordinated for them to converge for processing. In this study, we identify the actin-associated motor protein myosin II as being essential for this process. Myosin II is activated upon BCR engagement and associates with MHC class II–invariant chain complexes. Myosin II inhibition or depletion compromises the convergence and concentration of MHC class II and BCR–Ag complexes into lysosomes devoted to Ag processing. Accordingly, the formation of MHC class II–peptides and subsequent CD4 T cell activation are impaired in cells lacking myosin II activity. Therefore, myosin II emerges as a key motor protein in BCR-driven Ag processing and presentation

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software

With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3D SMLM software packages. We generated realistic simulated datasets for popular imaging modalities—2D, astigmatic 3D, biplane 3D and double-helix 3D—and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D SMLM software and provides a holistic view of how the latest 2D and 3D SMLM packages perform in realistic conditions. This resource allows researchers to identify optimal analytical software for their experiments, allows 3D SMLM software developers to benchmark new software against the current state of the art, and provides insight into the current limits of the field