FMRP regulates MFF translation to locally direct mitochondrial fission in neurons.

Fragile X messenger ribonucleoprotein (FMRP) is a critical regulator of translation, whose dysfunction causes fragile X syndrome. FMRP dysfunction disrupts mitochondrial health in neurons, but it is unclear how FMRP supports mitochondrial homoeostasis. Here we demonstrate that FMRP granules are recruited to the mitochondrial midzone, where they mark mitochondrial fission sites in axons and dendrites.

Heterogeneity of late endosome/lysosomes shown by multiplexed DNA-PAINT imaging.

Late endosomes/lysosomes (LELs) are crucial for numerous physiological processes and their dysfunction is linked to many diseases. Proteomic analyses have identified hundreds of LEL proteins; however, whether these proteins are uniformly present on each LEL, or if there are cell-type-dependent LEL subpopulations with unique protein compositions is unclear. We employed quantitative, multiplexed DNA-PAINT super-resolution imaging to examine the distribution of seven key LEL proteins (LAMP1, LAMP2, CD63, Cathepsin D, TMEM192, NPC1, and LAMTOR4).

Simultaneous multicolor fluorescence imaging using PSF splitting.

We present a way to encode more information in fluorescence imaging by splitting the original point spread function (PSF), which offers broadband operation and compatibility with other PSF engineering modalities and existing analysis tools. We demonstrate the approach using the 'Circulator', an add-on that encodes the fluorophore emission band into the PSF, enabling simultaneous multicolor super-resolution and single-molecule microscopy using essentially the full field of view.

Super-Resolution Imaging Uncovers Nanoscale Tau Aggregate Hyperphosphorylation Patterns in Human Alzheimer's Disease Brain Tissue.

Tau aggregation plays a critical role in Alzheimer's Disease (AD), where tau neurofibrillary tangles (NFTs) are a key pathological hallmark. While much attention has been given to NFTs, emerging evidence underscores nano-sized pre-NFT tau aggregates as potentially toxic entities in AD. By leveraging DNA-PAINT super-resolution microscopy, we visualized and quantified nanoscale tau aggregates (nano-aggregates) in human postmortem brain tissues from intermediate and advanced AD, and Primary Age-Related Tauopathy (PART).

Multiplexed DNA-PAINT Imaging of the Heterogeneity of Late Endosome/Lysosome Protein Composition.

Unlabelled: Late endosomes/lysosomes (LELs) are crucial for numerous physiological processes and their dysfunction is linked to many diseases. Proteomic analyses have identified hundreds of LEL proteins, however, whether these proteins are uniformly present on each LEL, or if there are cell-type dependent LEL sub-populations with unique protein compositions is unclear. We employed a quantitative, multiplexed DNA-PAINT super-resolution approach to examine the distribution of six key LEL proteins (LAMP1, LAMP2, CD63, TMEM192, NPC1 and LAMTOR4) on individual LELs.

Interplay between stochastic enzyme activity and microtubule stability drives detyrosination enrichment on microtubule subsets.

Microtubules in cells consist of functionally diverse subpopulations carrying distinct post-translational modifications (PTMs). Akin to the histone code, the tubulin code regulates a myriad of microtubule functions, ranging from intracellular transport to chromosome segregation. However, how individual PTMs only occur on subsets of microtubules to contribute to microtubule specialization is not well understood.

ECLiPSE: A Versatile Classification Technique for Structural and Morphological Analysis of Super-Resolution Microscopy Data.

We introduce a new automated machine learning analysis pipeline to precisely classify cellular structures captured through single molecule localization microscopy, which we call ECLiPSE (Enhanced Classification of Localized Pointclouds by Shape Extraction). ECLiPSE leverages 67 comprehensive shape descriptors encompassing geometric, boundary, skeleton and other properties, the majority of which are directly extracted from the localizations to accurately characterize individual structures. We validate ECLiPSE through unsupervised and supervised classification on a dataset featuring five distinct cellular structures, achieving exceptionally high classification accuracies nearing 100%.

Quantitative Single-Molecule Localization Microscopy.

Super-resolution fluorescence microscopy allows the investigation of cellular structures at nanoscale resolution using light. Current developments in super-resolution microscopy have focused on reliable quantification of the underlying biological data. In this review, we first describe the basic principles of super-resolution microscopy techniques such as stimulated emission depletion (STED) microscopy and single-molecule localization microscopy (SMLM), and then give a broad overview of methodological developments to quantify super-resolution data, particularly those geared toward SMLM data.

Actin polymerization promotes invagination of flat clathrin-coated lattices in mammalian cells by pushing at lattice edges.

Clathrin-mediated endocytosis (CME) requires energy input from actin polymerization in mechanically challenging conditions. The roles of actin in CME are poorly understood due to inadequate knowledge of actin organization at clathrin-coated structures (CCSs). Using platinum replica electron microscopy of mammalian cells, we show that Arp2/3 complex-dependent branched actin networks, which often emerge from microtubule tips, assemble along the CCS perimeter, lack interaction with the apical clathrin lattice, and have barbed ends oriented toward the CCS.

Multilinear Slicing for curve resolution of fluorescence imaging with sequential illumination.

Fluorescence microscopy is an extremely powerful technique that allows to distinguish multiple labels based on their emission color or other properties, such as their photobleaching and fluorescence recovery kinetics. These kinetics are ideally assumed to be mono-exponential in nature, where the time constants intrinsic to each fluorophore can be used to quantify their presence in the sample. However, these time constants also depend on the specifics of the illumination and sample conditions, meaning that identifying the different contributions in a mixture using a single-channel detection may not be straightforward.

Separation of spectrally overlapping fluorophores using intra-exposure excitation modulation.

Multicolor fluorescence imaging is an excellent method for the simultaneous visualization of multiple structures, although it is limited by the available spectral window. More labels can be measured by distinguishing these on properties, such as their fluorescence dynamics, but usually these dynamics must be directly resolvable by the instrument. We propose an approach to distinguish emitters over a much broader range of light-induced dynamics by combining fast modulation of the light source with the detection of the time-integrated fluorescence.

Self-contained and modular structured illumination microscope.

We present a modular implementation of structured illumination microscopy (SIM) that is fast, largely self-contained and that can be added onto existing fluorescence microscopes. Our strategy, which we call HIT-SIM, can theoretically deliver well over 50 super-resolved images per second and is readily compatible with existing acquisition software packages. We provide a full technical package consisting of schematics, a list of components and an alignment scheme that provides detailed specifications and assembly instructions.

Design of experiments for the optimization of SOFI super-resolution microscopy imaging.

Super-resolution optical fluctuation imaging (SOFI) is a well-known super-resolution technique appreciated for its versatility and broad applicability. However, even though an extended theoretical description is available, it is still not fully understood how the interplay between different experimental parameters influences the quality of a SOFI image. We investigated the relationship between five experimental parameters (measurement time, on-time , off-time , probe brightness, and out of focus background) and the quality of the super-resolved images they yielded, expressed as Signal to Noise Ratio (SNR).

Spectral imaging for characterization and detection of plastic substances in branded teabags.

The addition of plastic substances in teabags is of increasing concern for conscious consumers due to the harmful effects on the environment and the potential threats to human health. This work introduces an innovative and cost-effective approach to detect and quantify plastic substances in teabags by applying near infrared hyperspectral imaging (951-2496 nm) coupled with multivariate analysis. Teabags from 6 popular brands were investigated and categorized into three classes based on spectral unmixing and target detection results: 1) the plastic teabag primarily made of nylon 6/6; 2) those made of a composite with various polypropylene and cellulose ratios; 3) biodegradable teabags free from any plastic traces.

Smoothness correction for better SOFI imaging.

Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals.

Simultaneous readout of multiple FRET pairs using photochromism.

Förster resonant energy transfer (FRET) is a powerful mechanism to probe associations in situ. Simultaneously performing more than one FRET measurement can be challenging due to the spectral bandwidth required for the donor and acceptor fluorophores. We present an approach to distinguish overlapping FRET pairs based on the photochromism of the donor fluorophores, even if the involved fluorophores display essentially identical absorption and emission spectra.

Fluorophore unmixing based on bleaching and recovery kinetics using MCR-ALS.

Fluorescence microscopy is a key technology in the life sciences, though its performance is constrained by the number of labels that can be recorded. We propose to use the kinetics of fluorophore photodestruction and subsequent fluorescence recovery to distinguish multiple spectrally-overlapping emitters in fixed cells, thus enhancing the information that can be obtained from a single measurement. We show that the data can be directly processed using multivariate curve resolution - alternating least squares (MCR-ALS) to deliver distinct images for each fluorophore in their local environment, and apply this methodology to membrane imaging using DiBAC(3) and concanavalin A - Alexa Fluor 488 as the fluorophores.

Structure-Function Dataset Reveals Environment Effects within a Fluorescent Protein Model System.

Anisotropic environments can drastically alter the spectroscopy and photochemistry of molecules, leading to complex structure-function relationships. We examined this using fluorescent proteins as easy-to-modify model systems. Starting from a single scaffold, we have developed a range of 27 photochromic fluorescent proteins that cover a broad range of spectroscopic properties, including the determination of 43 crystal structures.

Deep learning for classification of time series spectral images using combined multi-temporal and spectral features.

Time series spectral imaging facilitates a comprehensive understanding of the underlying dynamics of multi-component systems and processes. Most existing classification strategies focus exclusively on the spectral features and they tend to fail when spectra between classes closely resemble each other. This work proposes a hybrid approach of principal component analysis (PCA) and deep learning (i.

A spatial constraint to model and extract texture components in Multivariate Curve Resolution of near-infrared hyperspectral images.

This article highlights the importance of properly taking into account spatial structures and features to better resolve near-infrared (NIR) hyperspectral images by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS), especially when highly mixed components (in terms of spatial and spectral overlap) underlying the systems under study are dealt with. As in the NIR domain these components can explain both chemical properties and physical phenomena, their improved unravelling can therefore represent an alternative or a complement to more standard approaches for, e.g.

Mechanistic investigation of mEos4b reveals a strategy to reduce track interruptions in sptPALM.

Green-to-red photoconvertible fluorescent proteins repeatedly enter dark states, causing interrupted tracks in single-particle-tracking localization microscopy (sptPALM). We identified a long-lived dark state in photoconverted mEos4b that results from isomerization of the chromophore and efficiently absorbs cyan light. Addition of weak 488-nm light swiftly reverts this dark state to the fluorescent state.

Effect of image processing constraints on the extent of rotational ambiguity in MCR-ALS of hyperspectral images.

Hyperspectral imaging is a way to explore the spatial and spectral information of the different compounds in chemical or biological samples. In addition, multivariate curve resolution - alternating least squares (MCR-ALS) can be used to extract this information based on the bilinearity assumption. However, it is well-known that using proper constraints can reduce the amount of uncertainty in the results of MCR, which is called rotational ambiguity.

Superhydrophobic polypyrene films to prevent Staphylococcus aureus and Pseudomonas aeruginosa biofilm adhesion on surfaces: high efficiency deciphered by fluorescence microscopy.

A blue luminescent and superhydrophobic coating based on an electropolymerized fluorinated-pyrene monomer and its planktonic bacteria and biofilm repellent properties are reported. Two different pathogenic bacterial strains (Gram-positive and Gram-negative) at two different incubation times (2 h planktonic bacterial and 24 h biofilm adhesion) were studied and monitored (analyzed) using multicolor scanning confocal fluorescence microscopy. The coating was proved to reduce bacterial adhesion by 65%.