HIV-1 budding requires cortical actin disassembly by the oxidoreductase MICAL1.

Many enveloped viruses bud from the plasma membrane that is tightly associated with a dense and thick actin cortex. This actin network represents a significant challenge for membrane deformation and scission, and how it is remodeled during the late steps of the viral cycle is largely unknown. Using superresolution microscopy, we show that HIV-1 buds in areas of the plasma membrane with low cortical F-actin levels.

Homebuilt Imaging-Based Spatial Transcriptomics: Tertiary Lymphoid Structures as a Case Example.

Spatial transcriptomics methods provide insight into the cellular heterogeneity and spatial architecture of complex, multicellular systems. Combining molecular and spatial information provides important clues to study tissue architecture in development and disease. Here, we present a comprehensive do-it-yourself (DIY) guide to perform such experiments at reduced costs leveraging open-source approaches.

Monitoring RVFV Infection Using Bioluminescent Reporter Viruses In Vivo.

Rift Valley fever virus is able to infect multiple organs and cell types, and the course of infection varies between viral strains and between individuals in particular according to age, genetic background, and physiological status. Studies on viral and host factors involve detecting and quantifying viral load at multiple time points and in multiple tissues. While this is classically performed by genome quantification or viral titration, in vivo imaging techniques using recombinant viruses expressing a bioluminescent or fluorescent protein allow noninvasive longitudinal studies on the same group of mice over the entire course of disease and the detection of unsuspected sites of infection.

Staying on track - Keeping things running in a high-end scientific imaging core facility.

Modern life science research is a collaborative effort. Few research groups can single-handedly support the necessary equipment, expertise and personnel needed for the ever-expanding portfolio of technologies that are required across multiple disciplines in today's life science endeavours. Thus, research institutes are increasingly setting up scientific core facilities to provide access and specialised support for cutting-edge technologies.

Caveolin-1 protects endothelial cells from extensive expansion of transcellular tunnel by stiffening the plasma membrane.

Large transcellular pores elicited by bacterial mono-ADP-ribosyltransferase (mART) exotoxins inhibiting the small RhoA GTPase compromise the endothelial barrier. Recent advances in biophysical modeling point toward membrane tension and bending rigidity as the minimal set of mechanical parameters determining the nucleation and maximal size of transendothelial cell macroaperture (TEM) tunnels induced by bacterial RhoA-targeting mART exotoxins. We report that cellular depletion of caveolin-1, the membrane-embedded building block of caveolae, and depletion of cavin-1, the master regulator of caveolae invaginations, increase the number of TEMs per cell.

Decolonization of asymptomatic carriage of multi-drug resistant bacteria by bacteriophages?

Antimicrobial resistance is a major threat to human and animal health and accounted for up to 4.5 million deaths worldwide in 2019. Asymptomatic colonization of the digestive tract by multidrug resistant (multi-resistant) bacteria such as extended-spectrum beta-lactamase-, or carbapenemase- producing is (i) a risk factor for infection by these multi-resistant bacteria, (ii) a risk factor of dissemination of these multi-resistant bacteria among patients and in the community, and (iii) allows the exchange of resistance genes between bacteria.

Deep learning in image-based phenotypic drug discovery.

Modern drug discovery approaches often use high-content imaging to systematically study the effect on cells of large libraries of chemical compounds. By automatically screening thousands or millions of images to identify specific drug-induced cellular phenotypes, for example, altered cellular morphology, these approaches can reveal 'hit' compounds offering therapeutic promise. In the past few years, artificial intelligence (AI) methods based on deep learning (DL) [a family of machine learning (ML) techniques] have disrupted virtually all image analysis tasks, from image classification to segmentation.