Visualizing the native cellular organization by coupling cryofixation with expansion microscopy (Cryo-ExM)

Cryofixation has proven to be the gold standard for efficient preservation of native cell ultrastructure compared to chemical fixation, but this approach is not widely used in fluorescence microscopy owing to implementation challenges. Here, we develop Cryo-ExM, a method that preserves native cellular organization by coupling cryofixation with expansion microscopy. This method bypasses artifacts associated with chemical fixation and its simplicity will contribute to its widespread use in super-resolution microscopy.

NNeurite: artificial neuronal networks for the unsupervised extraction of axonal and dendritic time-lapse signals

Fluorescence microscopy of Ca2+ transients in small neurites of the behaving mouse provides an unprecedented view of the micrometer-scale mechanisms supporting neuronal communication and computation, and therefore opens the way to understanding their role in cognition. However, the exploitation of this growing and precious experimental data is impeded by the scarcity of methods dedicated to the analysis of images of neurites activity in vivo. We present NNeurite, a set of mathematical and computational techniques specialized for the analysis of time-lapse microscopy images of neurite activity in small behaving animals. Starting from noisy and unstable microscopy images containing an unknown number of small neurites, NNeurite simultaneously aligns images, denoises signals and extracts the location and the temporal activity of the sources of Ca2+ transients. At the core of NNeurite is a novel artificial neuronal network(NN) which we have specifically designed to solve the non-negative matrix factorization (NMF)problem modeling source separation in fluorescence microscopy images. For the first time, we have embedded non-rigid image alignment in the NMF optimization procedure, hence allowing to stabilize images based on the transient and weak neurite signals. NNeurite processing is free of any human intervention as NN training is unsupervised and the unknown number of Ca2+ sources is automatically obtained by the NN-based computation of a low-dimensional representation of time-lapse images. Importantly, the spatial shapes of the sources of Ca2+ fluorescence are not constrained in NNeurite, which allowed to automatically extract the micrometer-scale details of dendritic and axonal branches, such dendritic spines and synaptic boutons, in the cortex of behaving mice. We provide NNeurite as a free and open-source library to support the efforts of the community in advancing in vivo microscopy of neurite activity.

Fluorescence Microscopy-Based Quantitation of GLUT4 Translocation

Postprandial insulin-stimulated glucose uptake into target tissue is crucial for the maintenance of normal blood glucose homeostasis. This step is rate-limited by the number of facilitative glucose transporters type 4 (GLUT4) present in the plasma membrane. Since insulin resistance and impaired GLUT4 translocation are associated with the development of metabolic disorders such as type 2 diabetes, this transporter has become an important target of antidiabetic drug research. The application of screening approaches that are based on the analysis of GLUT4 translocation to the plasma membrane to identify substances with insulinomimetic properties has gained global research interest in recent years. Here, we review methods that have been implemented to quantitate the translocation of GLUT4 to the plasma membrane. These methods can be broadly divided into two sections: microscopy-based technologies (e.g., immunoelectron, confocal or total internal reflection fluorescence microscopy) and biochemical and spectrometric approaches (e.g., membrane fractionation, photoaffinity labeling or flow cytometry). In this review, we discuss the most relevant approaches applied to GLUT4 thus far, highlighting the advantages and disadvantages of these approaches, and we provide a critical discussion and outlook into new methodological opportunities.