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The migration of many cell types relies on the formation of actomyosin-dependent protrusions called blebs, but the mechanisms responsible for focusing this kind of protrusive activity to the cell front are largely unknown. Here, we employ zebrafish primordial germ cells (PGCs) as a model to study the role of cell-cell adhesion in bleb-driven single-cell migration in vivo. Utilizing a range of genetic, reverse genetic and mathematical tools, we define a previously unknown role for E-cadherin in confining bleb-type protrusions to the leading edge of the cell. We show that E-cadherin-mediated frictional forces impede the backwards flow of actomyosin-rich structures that define the domain where protrusions are preferentially generated. In this way, E-cadherin confines the bleb-forming region to a restricted area at the cell front and reinforces the front-rear axis of migrating cells. Accordingly, when E-cadherin activity is reduced, the bleb-forming area expands, thus compromising the directional persistence of the cells. The arrival of migratory cells at their targets relies on following precise routes within tissues. Here the authors demonstrate that the cell adhesion molecule E-cadherin can control the path of cell migration by confining the site where bleb-type protrusions form within the cell front.

G-protein-coupled receptors (GPCR) are present at the cell surface in different conformational and oligomeric states. However, how these states impact GPCRs biological function and therapeutic targeting remains incompletely known. Here, we investigated this issue in living cells for the CC chemokine receptor 5 (CCR5), a major receptor in inflammation and the principal entry co-receptor for Human Immunodeficiency Viruses type 1 (HIV-1). We used TIRF microscopy and a statistical method to track and classify the motion of different receptor subpopulations. We showed a diversity of ligand-free forms of CCR5 at the cell surface constituted of various oligomeric states and exhibiting transient Brownian and restricted motions. These forms were stabilized differently by distinct ligands. In particular, agonist stimulation restricted the mobility of CCR5 and led to its clustering, a feature depending on β-arrestin, while inverse agonist stimulation exhibited the opposite effect. These results suggest a link between receptor activation and immobilization. Applied to HIV-1 envelope glycoproteins gp120, our quantitative analysis revealed agonist-like properties of gp120s. Distinct gp120s influenced CCR5 dynamics differently, suggesting that they stabilize different CCR5 conformations. Then, using a dimerization-compromized mutant, we showed that dimerization (i) impacts CCR5 precoupling to G proteins, (ii) is a pre-requisite for the immobilization and clustering of receptors upon activation, and (iii) regulates receptor endocytosis, thereby impacting the fate of activated receptors. This study demonstrates that tracking the dynamic behavior of a GPCR is an efficient way to link GPCR conformations to their functions, therefore improving the development of drugs targeting specific receptor conformations.

One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules' interactions and physical interplay with their environment. The standard tool for analyzing molecules' distribution statistically is the Ripley's K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles' computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters' size from the maxima of the Ripley's K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of 2 μm, which suggests distinct physical mechanisms and cellular functions for each pathway.

is the anaerobic protozoan parasite responsible for human amoebiasis, the third most deadly parasitic disease worldwide. This highly motile eukaryotic cell invades human tissues and constitutes an excellent experimental model of cell motility and cell shape deformation. The absence of extranuclear microtubules in means that the actin-rich cytoskeleton takes on a crucial role in not only amoebic motility but also other processes sustaining pathogenesis, such as the phagocytosis of human cells and the parasite's resistance of host immune responses. Actin is highly conserved among eukaryotes, although diverse isoforms exist in almost all organisms studied to date. However, has a single actin protein, the structure of which differs significantly from those of its human homologs. Here, we studied the expression, structure and dynamics of actin in . We used molecular and cellular approaches to evaluate actin gene expression during intestinal invasion by trophozoites. Based on a three-dimensional structural bioinformatics analysis, we characterized protein domains differences between amoebic actin and human actin. Fine-tuned molecular dynamics simulations enabled us to examine protein motion and refine the three-dimensional structures of both actins, including elements potentially accounting for differences changes in the affinity properties of amoebic actin and deoxyribonuclease I. The dynamic, multifunctional nature of the amoebic cytoskeleton prompted us to examine the pleiotropic forms of actin structures within live cells; we observed the cortical cytoskeleton, stress fibers, \"dot-like\" structures, adhesion plates, and macropinosomes. In line with these data, a proteomics study of actin-binding proteins highlighted the Arp2/3 protein complex as a crucial element for the development of macropinosomes and adhesion plaques.

Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on standard co-localisation techniques. Our method considers cellular geometry and densities of molecules to provide statistical maps of isolated and associated (coupled) molecules. We use SODA with three-colour structured-illumination microscopy (SIM) images of hippocampal neurons, and statistically characterise spatial organisation of thousands of synapses. We show that presynaptic synapsin is arranged in asymmetric triangle with the 2 postsynaptic markers homer and PSD95, indicating a deeper localisation of homer. We then determine stoichiometry and distance between localisations of two synaptic vesicle proteins with 3D-STORM. These findings give insights into the protein organisation at the synapse, and prove the efficiency of SODA to quantitatively assess the geometry of molecular assemblies. Elucidating molecular organisation requires precise localisation and analysis. Here the authors develop SODA software for automatic and quantitative mapping of statistically coupled molecules, and use it to unravel spatial organisation of thousands of synaptic proteins in SIM and 3DSTORM microscopy.

To respond to the urgent need for COVID-19 testing, countries perform nucleic acid amplification tests (NAAT) for the detection of SARS-CoV-2 in centralized laboratories. Real-time RT—PCR (Reverse transcription—Polymerase Chain Reaction), used to amplify and detect the viral RNA., is considered, as the current gold standard for diagnostics. It is an efficient process, but the complex engineering required for automated RNA extraction and temperature cycling makes it incompatible for use in point of care settings [1]. In the present work, by harnessing progress made in the past two decades in isothermal amplification and paper microfluidics, we created a portable test, in which SARS-CoV-2 RNA is extracted, amplified isothermally by RT—LAMP (Loop-mediated Isothermal Amplification), and detected using intercalating dyes or fluorescent probes. Depending on the viral load in the tested samples, the detection takes between twenty minutes and one hour. Using a set of 16 pools of naso-pharyngal swab eluates, we estimated a limit of detection comparable to real-time RT-PCR (i.e. 1 genome copies per microliter of clinical sample) and no cross‐reaction with eight major respiratory viruses currently circulating in Europe. We designed and fabricated an easy-to-use portable device called “COVIDISC” to carry out the test at the point of care. The low cost of the materials along with the absence of complex equipment will expedite the widespread dissemination of this device. What is proposed here is a new efficient tool to help managing the pandemics.

The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris . We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron’s calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra , and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.

Advances in tissue labeling, imaging, and automated cell identification now enable the visualization of immune cell types in human tumors. However, a framework for analyzing spatial patterns within the tumor microenvironment (TME) is still lacking. To address this, we develop Spatiopath , a null-hypothesis framework that distinguishes statistically significant immune cell associations from random distributions. Using embedding functions to map cell contours and tumor regions, Spatiopath extends Ripley’s K function to analyze both cell-cell and cell-tumor interactions. We validate the method with synthetic simulations and apply it to multi-color images of lung tumor sections, revealing significant spatial patterns such as mast cells accumulating near T cells and the tumor epithelium. These patterns highlight differences in spatial organization, with mast cells clustering near the epithelium and T cells positioned farther away. Spatiopath enables a better understanding of immune responses and may help identify biomarkers for patient outcomes. Immunotherapy is transforming cancer treatment, with immune cell distribution in the tumour microenvironment key to predicting outcomes. Here, authors provide a robust framework to analyse spatial patterns, distinguishing true immune associations from random accumulations, offering insights into immunotherapy responses.

The interleukin-2 receptor (IL-2R) is a cytokine receptor essential for immunity that transduces proliferative signals regulated by its uptake and degradation. IL-2R is a well-known marker of clathrin-independent endocytosis (CIE), a process devoid of any coat protein, raising the question of how the CIE vesicle is generated. Here, we investigated the impact of IL-2Rγ clustering in its endocytosis. Combining total internal reflection fluorescence (TIRF) live imaging of a CRISPR-edited T cell line endogenously expressing IL-2Rγ taggedwith green fluorescent protein (GFP), with multichannel imaging, single-molecule tracking, and quantitative analysis, we were able to decipher IL-2Rγ stoichiometry at the plasma membrane in real time. We identified three distinct IL-2Rγ cluster populations. IL-2Rγ is secreted to the cell surface as a preassembled small cluster of three molecules maximum, rapidly diffusing at the plasma membrane. A medium-sized cluster composed of four to six molecules is key for IL-2R internalization and is promoted by interleukin 2 (IL-2) binding, while larger clusters (more than six molecules) are static and inefficiently internalized. Moreover, we identified membrane cholesterol and the branched actin cytoskeleton as key regulators of IL-2Rγ clustering and IL-2–induced signaling. Both cholesterol depletion and Arp2/3 inhibition lead to the assembly of large IL-2Rγ clusters, arising from the stochastic interaction of receptor molecules in close correlation with their enhanced lateral diffusion at the membrane, thus resulting in a default in IL-2R endocytosis. Despite similar clustering outcomes, while cholesterol depletion leads to a sustained IL-2–dependent signaling, Arp2/3 inhibition prevents signal initiation. Taken together, our results reveal the importance of cytokine receptor clustering for CIE initiation and signal transduction.

Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time analysis of the behaviour of mice housed in groups of up to four over several days and in enriched environments. The method combines computer vision through a depth-sensing infrared camera, machine learning for animal and posture identification, and radio-frequency identification to monitor the quality of mouse tracking. It tracks multiple mice accurately, extracts a list of behavioural traits of both individuals and the groups of mice, and provides a phenotypic profile for each animal. We used the method to study the impact of Shank2 and Shank3 gene mutations—mutations that are associated with autism—on mouse behaviour. Characterization and integration of data from the behavioural profiles of Shank2 and Shank3 mutant female mice revealed their distinctive activity levels and involvement in complex social interactions. A method that combines a depth-sensing camera and machine learning can track the movements of up to four mice in real time and for several days, extracting both individual and group behavioural traits.