N-BAR and F-BAR proteins-endophilin-A3 and PSTPIP1-control clathrin-independent endocytosis of L1CAM.

Recent advances in the field demonstrate the high diversity and complexity of endocytic pathways. In the current study, we focus on the endocytosis of L1CAM. This glycoprotein plays a major role in the development of the nervous system, and is involved in cancer development and is associated with metastases and poor prognosis. Two L1CAM isoforms are subject to endocytosis: isoform 1, described as a clathrin-mediated cargo; isoform 2, whose endocytosis has never been studied. Deciphering the molecular machinery of isoform 2 internalisation should contribute to a better understanding of its pathophysiological role. First, we demonstrated in our cellular context that both isoforms of L1CAM are mainly a clathrin-independent cargo, which was not expected for isoform 1. Second, the mechanism of L1CAM endocytosis is specifically mediated by the N-BAR domain protein endophilin-A3. Third, we discovered PSTPIP1, an F-BAR domain protein, as a novel actor in this endocytic process. Finally, we identified galectins as endocytic partners and negative regulators of L1CAM endocytosis. In summary, the interplay of the BAR proteins endophilin-A3 and PSTPIP1, and galectins fine tune the clathrin-independent endocytosis of L1CAM.

SPITFIR(e): a supermaneuverable algorithm for fast denoising and deconvolution of 3D fluorescence microscopy images and videos.

Modern fluorescent microscopy imaging is still limited by the optical aberrations and the photon budget available in the specimen. A direct consequence is the necessity to develop flexible and "off-road" algorithms in order to recover structural details and improve spatial resolution, which is critical when restraining the illumination to low levels in order to limit photo-damages. Here, we report SPITFIR(e) a flexible method designed to accurately and quickly restore 2D-3D fluorescence microscopy images and videos (4D images). We designed a generic sparse-promoting regularizer to subtract undesirable out-of-focus background and we developed a primal-dual algorithm for fast optimization. SPITFIR(e) is a "swiss-knife" method for practitioners as it adapts to any microscopy techniques, to various sources of signal degradation (noise, blur), to variable image contents, as well as to low signal-to-noise ratios. Our method outperforms existing state-of-the-art algorithms, and is more flexible than supervised deep-learning methods requiring ground truth datasets. The performance, the flexibility, and the ability to push the spatiotemporal resolution limit of sub-diffracted fluorescence microscopy techniques are demonstrated on experimental datasets acquired with various microscopy techniques from 3D spinning-disk confocal up to lattice light sheet microscopy.

Challenges of intracellular visualization using virtual and augmented reality.

Microscopy image observation is commonly performed on 2D screens, which limits human capacities to grasp volumetric, complex, and discrete biological dynamics. With the massive production of multidimensional images (3D + time, multi-channels) and derived images (e.g., restored images, segmentation maps, and object tracks), scientists need appropriate visualization and navigation methods to better apprehend the amount of information in their content. New modes of visualization have emerged, including virtual reality (VR)/augmented reality (AR) approaches which should allow more accurate analysis and exploration of large time series of volumetric images, such as those produced by the latest 3D + time fluorescence microscopy. They include integrated algorithms that allow researchers to interactively explore complex spatiotemporal objects at the scale of single cells or multicellular systems, almost in a real time manner. In practice, however, immersion of the user within 3D + time microscopy data represents both a paradigm shift in human-image interaction and an acculturation challenge, for the concerned community. To promote a broader adoption of these approaches by biologists, further dialogue is needed between the bioimaging community and the VR&AR developers.

STracking: a free and open-source Python library for particle tracking and analysis.

SUMMARY: Analysis of intra- and extracellular dynamic like vesicles transport involves particle tracking algorithms. The design of a particle tracking pipeline is a routine but tedious task. Therefore, particle dynamics analysis is often performed by combining several pieces of software (filtering, detection, tracking, etc.) requiring many manual operations, and thus leading to poorly reproducible results. Given the new segmentation tools based on deep learning, modularity and interoperability between software have become essential in particle tracking algorithms. A good synergy between a particle detector and a tracker is of paramount importance. In addition, a user-friendly interface to control the quality of estimated trajectories is necessary. To address these issues, we developed STracking, a Python library that allows combining algorithms into standardized particle tracking pipelines. AVAILABILITY AND IMPLEMENTATION: STracking is available as a Python library using 'pip install' and the source code is publicly available on GitHub (https://github.com/sylvainprigent/stracking). A graphical interface is available using two napari plugins: napari-stracking and napari-tracks-reader. These napari plugins can be installed via the napari plugins menu or using 'pip install'. The napari plugin source codes are available on GitHub (https://github.com/sylvainprigent/napari-tracks-reader, https://github.com/sylvainprigent/napari-stracking). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

4polar-STORM polarized super-resolution imaging of actin filament organization in cells.

Single-molecule localization microscopy provides insights into the nanometer-scale spatial organization of proteins in cells, however it does not provide information on their conformation and orientation, which are key functional signatures. Detecting single molecules' orientation in addition to their localization in cells is still a challenging task, in particular in dense cell samples. Here, we present a polarization-splitting scheme which combines Stochastic Optical Reconstruction Microscopy (STORM) with single molecule 2D orientation and wobbling measurements, without requiring a strong deformation of the imaged point spread function. This method called 4polar-STORM allows, thanks to a control of its detection numerical aperture, to determine both single molecules' localization and orientation in 2D and to infer their 3D orientation. 4polar-STORM is compatible with relatively high densities of diffraction-limited spots in an image, and is thus ideally placed for the investigation of dense protein assemblies in cells. We demonstrate the potential of this method in dense actin filament organizations driving cell adhesion and motility.

Endophilin-A3 and Galectin-8 control the clathrin-independent endocytosis of CD166.

While several clathrin-independent endocytic processes have been described so far, their biological relevance often remains elusive, especially in pathophysiological contexts such as cancer. In this study, we find that the tumor marker CD166/ALCAM (Activated Leukocyte Cell Adhesion Molecule) is a clathrin-independent cargo. We show that endophilin-A3-but neither A1 nor A2 isoforms-functionally associates with CD166-containing early endocytic carriers and physically interacts with the cargo. Our data further demonstrates that the three endophilin-A isoforms control the uptake of distinct subsets of cargoes. In addition, we provide strong evidence that the construction of endocytic sites from which CD166 is taken up in an endophilin-A3-dependent manner is driven by extracellular galectin-8. Taken together, our data reveal the existence of a previously uncharacterized clathrin-independent endocytic modality, that modulates the abundance of CD166 at the cell surface, and regulates adhesive and migratory properties of cancer cells.

A sequential algorithm to detect diffusion switching along intracellular particle trajectories.

MOTIVATION: Recent advances in molecular biology and fluorescence microscopy imaging have made possible the inference of the dynamics of single molecules in living cells. Changes of dynamics can occur along a trajectory. Then, an issue is to estimate the temporal change-points that is the times at which a change of dynamics occurs. The number of points in the trajectory required to detect such changes will depend on both the magnitude and type of the motion changes. Here, the number of points per trajectory is of the order of 102, even if in practice dramatic motion changes can be detected with less points. RESULTS: We propose a non-parametric procedure based on test statistics computed on local windows along the trajectory to detect the change-points. This algorithm controls the number of false change-point detections in the case where the trajectory is fully Brownian. We also develop a strategy for aggregating the detections obtained with different window sizes so that the window size is no longer a parameter to optimize. A Monte Carlo study is proposed to demonstrate the performances of the method and also to compare the procedure to two competitive algorithms. At the end, we illustrate the efficacy of the method on real data in 2D and 3D, depicting the motion of mRNA complexes-called mRNA-binding proteins-in neuronal dendrites, Galectin-3 endocytosis and trafficking within the cell. AVAILABILITY AND IMPLEMENTATION: A user-friendly Matlab package containing examples and the code of the simulations used in the paper is available at http://serpico.rennes.inria.fr/doku.php? id=software:cpanalysis:index. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

EHD2 is a mechanotransducer connecting caveolae dynamics with gene transcription.

Caveolae are small invaginated pits that function as dynamic mechanosensors to buffer tension variations at the plasma membrane. Here we show that under mechanical stress, the EHD2 ATPase is rapidly released from caveolae, SUMOylated, and translocated to the nucleus, where it regulates the transcription of several genes including those coding for caveolae constituents. We also found that EHD2 is required to maintain the caveolae reservoir at the plasma membrane during the variations of membrane tension induced by mechanical stress. Metal-replica electron microscopy of breast cancer cells lacking EHD2 revealed a complete absence of caveolae and a lack of gene regulation under mechanical stress. Expressing EHD2 was sufficient to restore both functions in these cells. Our findings therefore define EHD2 as a central player in mechanotransduction connecting the disassembly of the caveolae reservoir with the regulation of gene transcription under mechanical stress.

A novel type of quantum dot-transferrin conjugate using DNA hybridization mimics intracellular recycling of endogenous transferrin.

Colloidal nanoparticles such as Quantum Dots (QDs) are promising alternatives to organic fluorophores, especially for long duration bioimaging. For specific targeting applications, QDs frequently require functionalization with selected proteins. In this regard, conjugation of proteins to QDs such that the nanobioconjugates retain the endogenous behavior of the coupled protein remains challenging. We have developed a novel method to conjugate a protein, transferrin (Tf), to QDs using DNA hybridization. These conjugates are characterized biochemically, and the trafficking properties in live cells are investigated. Although the internalization kinetics into the cells is much reduced compared to Tf labelled with organic dye, we could show that DNA hybridization-based QD-Tf conjugates are the first for which recycling from endosomes to the plasma membrane can be observed. This recycling occurs with kinetics that is similar to dye labelled Tf. We could image and follow the trajectories of recycling of individual vesicles for several tens of minutes. The conjugation of QDs to proteins mediated by DNA hybridization yields a new generation of ultra-bright and photostable probes that preserves the intracellular properties of the dye labelled protein better than previously reported QD conjugates using other surface chemistries for direct coupling.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy.

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells.