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Henriques, R.

Publications and source records attributed to Henriques, R..

10 recordsLinked to original sources

Fix your membrane receptor imaging: Actin cytoskeleton and CD4 membrane organization disruption by chemical fixation

Single-molecule localization microscopy (SMLM) techniques allow near molecular scale resolution (~ 20nm) as well as precise and robust analysis of protein organization at different scales. SMLM hardware, analytics and probes have been the focus of a variety of studies and are now commonly used in laboratories across the world. Protocol reliability and artefact identification are increasingly seen as important aspects of super-resolution microscopy. The reliability of these approaches thus requires in-depth evaluation so that biological findings are based on solid foundations. Here we explore how different fixation approaches that disrupt or preserve the actin cytoskeleton affect membrane protein organization. Using CD4 as a model, we show that fixation-mediated disruption of the actin cytoskeleton correlates with changes in CD4 membrane organization. We highlight how these artefacts are easy to overlook and how careful sample preparation is essential for extracting meaningful results from super-resolution microscopy.

cell biology

NanoJ: a high-performance open-source super-resolution microscopy toolbox

Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was de-veloped for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image re-construction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

bioinformatics

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

With the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. To guide researchers on the optimal analytical software for their experiments, we have designed, in a large community effort, a competition to extensively characterise and rank these options. 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 single molecule localization microscopy software, provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions, and ultimately provides insight into the current limits of the field.

biophysics

Nanoscale Polarization of the Vaccinia Virus Entry Fusion Complex Drives Efficient Fusion

The spatial distribution of binding and fusion proteins on most viruses and the functional relevance of this organization remains largely unexplored. Employing super-resolution microscopy we define the nanoscale membrane architecture of the prototypic poxvirus, vaccinia. We show that binding and entry fusion complex (EFC) proteins are organized into distinct functional domains with fusion proteins polarized to the tips of virions. Repression of individual EFC components disrupted fusion protein polarization, correlating with a loss of fusion activity. Repression of vaccinia A27, a non-EFC protein implicated in fusion, revealed that disruption of EFC localization impacts virus fusion pore formation. We propose that the polarized distribution of EFCs is essential for poxvirus fusion efficiency.

microbiology

Automating multimodal microscopy with NanoJ-Fluidics

Fluorescence microscopy can reveal all aspects of cellular mechanisms, from molecular details to dynamics, thanks to approaches such as super-resolution and live-cell imaging. Each of its modalities requires specific sample preparation and imaging conditions to obtain high-quality, artefact-free images, ultimately providing complementary information. Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows involving multiple sample preparation steps. We present a robust fluidics approach to automate complex sequences of treatment, labelling and imaging of live and fixed cells. Our open-source NanoJ-Fluidics system is based on low-cost LEGO hardware controlled by ImageJ-based software and can be directly adapted to any microscope, providing easy-to-implement high-content, multimodal imaging with high reproducibility. We demonstrate its capacity to carry out complex sequences of experiments such as super-resolved live-to-fixed imaging to study actin dynamics; highly-multiplexed STORM and DNA-PAINT acquisitions of multiple targets; and event-driven fixation microscopy to study the role of adhesion contacts in mitosis.

cell biology

Nanoscale colocalization of NK cell activating and inhibitory receptors controls signal integration

NK cell responses depend on the balance of signals from inhibitory and activating receptors. However, how the integration of antagonistic signals occurs upon NK cell-target cell interaction is not fully understood. Here, we provide evidence that NK cell inhibition via the inhibitory receptor Ly49A is dependent on its relative colocalization at the nanometer scale with the activating receptor NKG2D upon immune synapse (IS) formation. NKG2D and Ly49A signal integration and colocalization was studied using NKG2D-GFP and Ly49A-RFP-expressing primary NK cells, forming ISs with NIH3T3 target cells, with or without expression of single chain trimer (SCT) H2-Dd and an extended form of SCT H2-Dd-CD4 MHC-I molecules. Nanoscale colocalization was assessed by Forster resonance energy transfer (FRET) between NKG2D-GFP and Ly49A-RFP and measured for each synapse. In the presence of their respective cognate ligands, NKG2D and Ly49A colocalize at a nanometer scale leading to NK cell inhibition. However, increasing the size of the Ly49A ligand reduced the nanoscale colocalization with NKG2D consequently impairing Ly49A-mediated inhibition. Thus, our data shows NK cell signal integration is critically dependent on the dimensions of NK cell ligand-receptor pairs by affecting their relative nanometer-scale colocalization at the IS. Together, our results suggest the balance of NK cell signals, and NK cell responses, are determined by the relative nanoscale colocalization of activating and inhibitory receptors in the immune synapse.

immunology

TMEM16F activation by Ca2+ triggers plasmalemma expansion and directs PD-1 trafficking

TMEM16F, an ion channel gated by high cytoplasmic Ca2+, is required for cell surface phosphatidylserine exposure during platelet aggregation and T cell activation. Here we demonstrate in Jurkat T cells and HEK293 cells that TMEM16F activation triggers large-scale surface membrane expansion in parallel with lipid scrambling. Following TMEM16F mediated scrambling and surface expansion, cells undergo extensive membrane shedding. The membrane compartment that expands the cell surface does not involve endoplasmic reticulum or acidified lysosomes. Surprisingly, T cells lacking TMEM16F expression not only fail to expand surface membrane, but instead rapidly internalize membrane via massive endocytosis (MEND). The T cell co-receptor PD-1 is selectively shed when TMEM16F triggers membrane expansion, while it is selectively internalized in the absence of TMEM16F. Its participation in this trafficking is determined by its single transmembrane domain. Thus, we establish a fundamental role for TMEM16F as a regulator of Ca2+-activated membrane trafficking.

cell biology

Content-Aware Image Restoration: Pushing the Limits of Fluorescence Microscopy

Fluorescence microscopy is a key driver of discoveries in the life-sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how image restoration based on deep learning extends the range of biological phenomena observable by microscopy. On seven concrete examples we demonstrate how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to 10-fold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times higher frame-rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FO_SCPLOWIJIC_SCPLOW, and KO_SCPLOWNIMEC_SCPLOW.

bioinformatics

A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores

Fluorescing molecules (fluorophores) that stochastically switch between photon-emitting and dark states underpin some of the most celebrated advancements in super-resolution microscopy. While this stochastic behavior has been heavily exploited, full characterization of the underlying models can potentially drive forward further imaging methodologies. Under the assumption that fluorophores move between fluorescing and dark states as continuous time Markov processes, the goal is to use a sequence of images to select a model and estimate the transition rates. We use a hidden Markov model to relate the observed discrete time signal to the hidden continuous time process. With imaging involving several repeat exposures of the fluorophore, we show the observed signal depends on both the current and past states of the hidden process, producing emission probabilities that depend on the transition rate parameters to be estimated. To tackle this unusual coupling of the transition and emission probabilities, we conceive transmission (transition-emission) matrices that capture all dependencies of the model. We provide a scheme of computing these matrices and adapt the forward-backward algorithm to compute a likelihood which is readily optimized to provide rate estimates. When confronted with several model proposals, combining this procedure with the Bayesian Information Criterion provides accurate model selection.

biophysics

NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts

Most super-resolution microscopy methods depend on steps that contribute to the formation of image artefacts. Here we present NanoJ-SQUIRREL, an ImageJ-based analytical approach providing a quantitative assessment of super-resolution image quality. By comparing diffraction-limited images and super-resolution equivalents of the same focal volume, this approach generates a quantitative map of super-resolution defects, as well as methods for their correction. To illustrate its broad applicability to super-resolution approaches we apply our method to Localization Microscopy, STED and SIM images of a variety of in-cell structures including microtubules, poxviruses, neuronal actin rings and clathrin coated pits. We particularly focus on single-molecule localisation microscopy, where super-resolution reconstructions often feature imperfections not present in the original data. By showing the quantitative evolution of data quality over these varied sample preparation, acquisition and super-resolution methods we display the potential of NanoJ-SQUIRREL to guide optimization of superresolution imaging parameters.

biophysics