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Biology subjects

Tinevez, J.-Y.

Publications and source records attributed to Tinevez, J.-Y..

At least 19 recordsLinked to original sources

Apical adhesion of meningococci controls host cell basal traction force through Ancreopodia formation

Extracellular bacterial pathogens remodel the apical surface of host cells, but whether these local interactions are mechanically transmitted across the cell to the basal extracellular matrix remains unclear. Using a combination of in vitro infection models, high-resolution imaging, traction force microscopy and bacterial genetics, we show that Neisseria meningitidis (Nm) adhesion to endothelial cells triggers a rapid increase in traction forces and localized, colony-associated traction-force hotspots on the extracellular matrix. Formation of these hotspots is associated with a novel actin-rich structure, which we term ancreopodia, that links apical bacterial colonies to the basal substrate. Super-resolution microscopy revealed ancreopodia spanning the cell thickness, connecting apical cortical plaques to reorganized basal stress fibers and focal-adhesion components. Dynamic imaging demonstrated coordinated movements of bacterial colonies and basal mechanosensitive proteins, while analysis of pili mutants showed that pilus retraction is required to focus traction forces beneath colonies. Disruption of branched actin assembly or myosin-II activity likewise impaired apico-basal organization and vinculin recruitment. Functionally, Nm infection enhanced local anchoring while restricting single-cell migration and collective endothelial dynamics. Together, these findings identify ancreopodia as a vertical mechanotransduction structure through which an extracellular pathogen couples apical adhesion to basal force transmission and reshapes host-cell mechanics.

cell biology↗

Single-cell metabolomics reveals infection-specific metabolic reprogramming of human macrophages

During intracellular infection, host cells adopt different metabolic states that traditional bulk analyses cannot distinguish. Using single-cell spatial metabolomics of human macrophages infected with Legionella pneumophila, we show that bacterial uptake activates host metabolism, whereas the bacterial effectors secreted through the type IV secretion system counteract this response and promote a glycolytic shift. The activity of effectors also generates distinct metabolic states within the infected macrophage population.

microbiology↗

Rapid repurposing of microvillar content drives a flagellate-to-amoeboid switch in the closest relative of animals

Animal cells extensively remodel their cytoskeleton during differentiation and can notably switch between two major motility modes: flagellum-based swimming and actin-based crawling. We previously showed that choanoflagellates, the closest living relatives of animals and classically viewed as obligate flagellated swimmers, can retract their collar complex and adopt an amoeboid form within seconds under spatial confinement, independently of regulated gene expression. Here, using live imaging, ultrastructural expansion microscopy, and cryo-electron tomography in Salpingoeca rosetta, we identify rapid, cell-wide cytoskeletal remodeling as the ultrastructural basis of this switch. Unconfined choanoflagellates lack a detectable actin cortex but display an apical flagellum and cortical microtubules, with F-actin being largely restricted to microvilli. Confinement triggers calcium release from intracellular stores, which induces microvillar retraction and absorption of microvillar material into the cell body, including actin, ezrin-radixin-moesin 1, and plasma membrane. Remodeling of the internalized F-actin and repurposing of associated proteins supports de novo actin cortex formation, which is necessary for amoeboid motility. In parallel, cortical microtubules are disassembled, and the reabsorbed microvillar plasma membrane increases the surface area of the cell body, allowing the cell to flatten under confinement. Cryo-electron tomography reveals stepwise actin reorganization from internalized microvillar bundles to a cortical contractile meshwork combining bundles and scattered filaments. This work reveals considerable ultrastructural plasticity in the cytoskeletal architecture of choanoflagellates and supports an ancestral role for microvilli as reservoirs of membrane and cytoskeleton to potentiate cell phenotypic transitions.

evolutionary biology↗

Real-Time Multi-Position and Multi-ROI Tracking with LiLiTTool for Smart Light-Sheet Microscopy in Growing Samples

Long-term live imaging of growing samples with light-sheet fluorescence microscopy provides unique insights into development, but morphogenesis often displaces features of interest outside the microscopes field of view (FOV), calling for automated methods to track these features and update the microscopes FOV in real time. Existing solutions, which typically rely on local or global intensity distributions, struggle to follow specific features robustly throughout morphogenesis, leading to truncated or incomplete datasets. Here, we present a light-sheet live tracking tool (LiLiTTool) that maintains user-defined regions of interest (ROI) within the FOV throughout extended imaging sessions. LiLiTTool uses Cotracker3, a state-of-the art deep learning-based motion predictor, augmented by sensor fusion with a trained object-detector. This enables robust compensation for drift, rotation, and deformation during morphogenesis, while meeting the timing constraints of live acquisition. We validated LiLiTool by integrating with the Viventis LS1 microscope, achieving sub-second processing and stable tracking of growing zebrafish embryos over many hours. LiLiTTool supports multi-ROI tracking in 3D, enabling simultaneous monitoring of multiple features within the same embryo and in multiple embryos during a single acquisition. LiLiTTool is modular and openly available on GitHub and as a napari plugin for post-acquisition tracking. By enabling precise, adaptive, and scalable real-time imaging, LiLiTTool advances smart microscopy approaches and provides the developmental biology community with a practical tool for capturing reliable spatio-temporal information in growing embryos or other morphogenetic systems.

developmental biology↗

EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation

Investigating single-cell dynamics and morphology in tissues and embryos requires highly accurate quantitative analysis of microscopy images. Despite significant advances in the field of bioimage analysis, even the most sophisticated segmentation and tracking algorithms inevitably produce errors (e.g. : over segmentation, missing objects, miss-connected objects). Although error rate may be small, their propagation throughout a time-lapse sequence has catastrophic effects on the accuracy of tracking and extraction of single cell parameters. Extracting single cell temporal information in the context of tissue/embryo requires thus expert curation to identify and correct segmentation errors. In the movies commonly used in developmental biology and stem cell research, both the number of imaged cells and the duration of recording are large, making this manual correction task extremely time-consuming. This has now become a major bottleneck in the fields of development, stem cell biology and bioimage analysis. We present here EpiCure (Epithelial Curation), a versatile tool designed to streamline and accelerate manual curation of segmentation and tracking in 2D movies of large epithelial tissues. EpiCure uses temporal information and morphometric parameters to automatically identify segmentation and tracking errors and provides user-friendly tools to correct them. It focuses on ergonomics and offers several visualization options to help navigating in movies of tissue covering a large number of cells, speeding up the detection of errors and their curation. EpiCure is highly interoperable and supports input from a wide range of segmentation tools. It also includes multiple export filters, enabling seamless integration with downstream analysis pipelines. In this paper, using movies from several animal models, we highlight the importance of curating cell segmentation and tracking for accurate downstream analysis, and demonstrate how EpiCure helps the curation process for extracting accurate single cell dynamics and cellular events detection, making it faster and amenable on large dataset.

developmental biology↗

Stress-responsive Mycobacterium tuberculosis subpopulations manipulate macrophage polarization and can be targeted to limit inflammation

Tuberculosis is characterized by broad clinical heterogeneity that hinders infection control, with differences in lesion development, progression, and treatment outcomes. This complexity is likely associated with Mycobacterium tuberculosis inherent phenotypic variation and its capacity to diversify under host microenvironmental and antimicrobial stressors. Here, we analyze M. tuberculosis at the single-cell and subpopulation level using fluorescent reporters, imaging, transcriptomic, and functional assays. We identify RNA signatures specific to stress-responsive bacilli with translational potential. Focusing on the clinically validated chaperone GroEL2, we find that it correlates with M. tuberculosis growth rate and stress tolerance in vitro and intracellularly. Furthermore, GroEL2 phenotypic diversity influences innate responses in macrophages, which experience different polarization, in turn affecting GroEL2 expression. We also show that targeting GroEL2 impairs pathogen survival and dampens inflammation. This study provides a link between pathogen phenotypic variation and macrophage fates, with implications for early infection outcomes, local disease progression, and subpopulation-targeted interventions.

microbiology↗

A general methodology for liver sinusoid fenestration analysis based on 3D electron microscopy data

The liver has a complex architecture composed of millions of lobules. Within these lobules, hepatocytes, the main hepatic cells, are organized in rows separated by blood capillaries known as sinusoids. These capillaries are lined by liver sinusoidal endothelial cells (LSEC) that form a very specific fenestrated endothelium essential for the exchange of metabolites and proteins between the blood and hepatocytes. Alterations in the size and number of LSEC fenestrations are associated with the onset and the progression of various liver diseases. The analysis of liver architecture is thus of utmost importance for advancing our knowledge of liver ultrastructure and its alterations. Liver architecture has been studied since decades, mainly using 2D electron microscopy, and more recently using advanced super-resolution fluorescence microscopy. In recent years, volume electron microscopy techniques, including focused ion beam-scanning electron microscopy (FIB-SEM) progressed and nowadays enable the 3D reconstruction of biological ultrastructures down to nanometer resolution. However, the analysis of large volumes (e.g., several tens of {micro}m3) remains challenging due to various constraints in the segmentation of large datasets. In the current study, we developed a workflow to semi-automatically segment hepatic sinusoids from FIB-SEM mice liver datasets using the CNN-based (convolutional neural network) tool known as "nnU-Net", after fine-tuning a ground truth model. We also implemented tools for semi-automatic quantification of LSEC fenestrae diameters and sinusoid porosity from segmented datasets. This workflow enabled us to compare the distribution of LSEC fenestrae diameters in wild-type versus Bmp9-deleted mice, a hepatic factor known to be involved in fenestration maintenance. Our results confirm the importance of BMP9 for LSEC differentiation. Therefore, the developed methodology represents a valuable tool for characterizing the fenestrated endothelium under various physiological and pathological conditions.

cell biology↗

Automated Optimization of Bacterial Tracking Pipelines with TrackMate 8

Quantitative analysis of bacterial dynamics in time-lapse microscopy requires robust tracking pipelines, yet selecting and optimizing algorithms for specific experiments remains challenging. Indeed, Microbiologists are confronted with numerous algorithms that must be carefully chosen and parameterized to achieve optimal tracking for their experiments. We present an automated methodology to determine optimal tracking configurations for microbiological applications. It is based on TrackMate 8, a novel version of the TrackMate Fiji plugin extended with microbiology-specific tools. Our approach systematically evaluates algorithm-parameter combinations optimizing biologically relevant metrics (e.g., cell-cycle accuracy, bacteria morphology) and includes: (1) integration of deep-learning algorithms (Omnipose, YOLO, Trackastra) adequate for bacteria images in TrackMate, (2) a TrackMate-Helper extension for parameter optimization, and (3) a tracking and segmentation editor for tracking ground-truth generation. We demonstrate the effectiveness of the methodology on two use cases showing its adaptability to diverse experimental conditions. This methodology enables microbiologists with a widely applicable, automated framework to optimize tracking pipelines, facilitating quantitative analysis in bacterial imaging.

microbiology↗

Mastodon: the Command Center for Large-Scale Lineage-Tracing Microscopy Datasets

Understanding development in living organisms requires following the divisions, movements, and fates of cells across developing systems. While advances in microscopy have enabled whole-embryo imaging at the cellular level, extracting and analyzing cell lineages from these massive datasets remains a significant computational challenge. We present Mastodon, a scalable, extensible software platform for manual, semi-automated, and automated cell tracking in large images. A purpose-built graph model supports responsive performance for datasets with millions of annotations, making Mastodon a future-proof platform for cell lineage analysis. Built as a Fiji plugin, Mastodon enables interactive visualization, editing, and analysis of complex lineage trees, seamlessly integrated with the raw image data. Comprehension of cell lineages in complex three-dimensional geometries is facilitated by interoperability with the powerful open-source render engine Blender. In three distinct developmental contexts, we demonstrate how Mastodon will accelerate biological insights by providing user-friendly navigation and explorative analysis in complex lineage datasets.

bioinformatics↗

Adhesion-Controlled Mechanics of the Glial Niche Regulate Neural Stem Cell Proliferative Potential

Controlled proliferation of neural stem cells (NSCs) builds a functional nervous system during development. While their cellular niche is recognized as a signalling hub, the contribution of its structure and mechanics in regulating neurogenesis remains unexplored. The Drosophila larval central nervous system contains self-renewing NSCs in close contact with cortex glial cells. Transcriptomics identified a triad of immunoglobulin superfamily cell adhesion molecules (Dpr10/Dpr6 in glia and DIP- in NSCs) which physically and mechanically connect the NSC and glial membranes, acting as mechanoregulators. Their disruption increases glial cortical tension, causing non-autonomous mitotic defects in NSCs, characterized by abnormal spindle morphologies and impaired mitotic progression. Additionally, elevated glial tensile forces increase Lamin content in NSCs, a protective response also resulting in nuclear deformation. Ultimately NSC proliferative potential and genome integrity are compromised. Our study reveals that the native mechanical properties of the niche are transmitted to NSCs and regulate their function. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/628019v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@18137f8org.highwire.dtl.DTLVardef@819740org.highwire.dtl.DTLVardef@1f0ed0forg.highwire.dtl.DTLVardef@5ba0e4_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Backtracking Metabolic Dynamics in Single Cells Predicts Bacterial Replication in Human Macrophages

Accurately tracking dynamic state transitions is crucial for modeling and predicting biological outcomes, as it captures heterogeneity of cellular responses. To build a model to predict bacterial infection in single cells, we have monitored in parallel infection progression and metabolic parameters in thousands of human primary macrophages infected with the intracellular pathogen Legionella pneumophila. By combining livecell imaging with a novel tool for classifying cells based on infection outcomes, we were able to trace the specific evolution of metabolic parameters linked to distinct outcomes, such as bacterial replication or cell death. Our findings revealed that early changes in mitochondrial membrane potential ({Delta}{psi}m) and in the production of mitochondrial Reactive Oxygen Species (mROS) are associated with macrophages that will later support bacterial growth. We used these data to train an explainable machine-learning model and achieved 83% accuracy in predicting L. pneumophila replication in single, infected cells before bacterial replication starts. Our results highlight backtracking as a valuable tool to gain new insights in host-pathogen interactions and identify early mitochondrial alterations as key predictive markers of success of bacterial infection.

microbiology↗

Bacterial growth under confinement requires transcriptional adaptation to resist metabolite-induced turgor pressure build-up

Bacterial proliferation often occurs in confined spaces, during biofilm formation, within host cells, or in specific niches during infection, creating mechanical constraints. We investigated how spatial confinement and growth-induced mechanical pressure affect bacterial physiology. Here, we found that, when proliferating in a confining microfluidic-based device with access to nutrients, Escherichia coli cells generate forces in the hundreds of kPa range. This pressure decouples growth and division, producing shorter bacteria with higher protein concentrations. This leads to cytoplasmic crowding, which ultimately arrests division and stalls protein synthesis. In this arrested state, the pressure produced by bacteria keeps increasing. A minimal theoretical model of bacterial growth predicts this novel regime of steady pressure increase in the absence of protein production, that we named overpressurization. In this regime, the Rcs pathway is activated and that abnormal shapes appear in rcs mutant populations only when they reach the overpressurized state. A uropathogenic strain of E. coli displayed the same confined growth phenotypes in vitro and requirement for Rcs in a mice model of urinary tract infection, suggesting that these pressurized regimes are relevant to understand the physiopathology of bacterial infections.

microbiology↗

TYPE THREE SECRETION SYSTEM-INDUCED MECHANOPORATION OF VACUOLAR MEMBRANES

SO_SCPLOWUMMARYC_SCPLOWEndomembrane breaching is a crucial strategy employed by intracellular pathogens enclosed within vacuoles to access the nutrient-rich cytosol for intracellular replication. While bacteria use various mechanisms to compromise host membranes, the specific processes and factors involved are often unknown. Shigella flexneri, a major human pathogen, accesses the cytosol relying on the Type Three Secretion System (T3SS) and secreted effectors. Using in-cell correlative light and electron microscopy, we tracked the sequential steps of Shigella host cell entry. Moreover, we captured the T3SS, which projects a needle from the bacterial surface, in the process of puncturing holes in the vacuolar membrane. This initial puncture ensures disruption of the vacuolar membrane. Together this introduces the concept of mechanoporation via a bacterial secretion system as a crucial process for bacterial pathogen-induced membrane damage. GO_SCPLOWRAPHICALC_SCPLOW AO_SCPLOWBSTRACTC_SCPLOW O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/613840v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1669028org.highwire.dtl.DTLVardef@8259cborg.highwire.dtl.DTLVardef@1d522caorg.highwire.dtl.DTLVardef@1df0f2d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Universal dynamics of cohesin-mediated loop extrusion

Most animal genomes are partitioned into Topologically Associating Domains (TADs), created by cohesin-mediated loop extrusion and defined by convergently oriented CTCF sites. The dynamics of loop extrusion and its regulation remains poorly characterized in vivo. Here, we tracked TAD anchors in living human cells to visualize and quantify cohesin-dependent loop extrusion across multiple endogenous genomic regions. We show that TADs are dynamic structures whose anchors are brought in proximity about once per hour and for 6-19 min ([~]16% of the time). TADs are continuously subjected to extrusion by multiple cohesin complexes, extruding loops at [~]0.1 kb/s. Remarkably, despite strong differences of Hi-C patterns between the chromatin regions, their dynamics is consistent with the same density, residence time and speed of cohesin. Our results suggest that TAD dynamics is governed primarily by CTCF site location and affinity, which allows genome-wide predictive models of cohesin-dependent interactions.

genetics↗

Pulsatile dynamics propagate crystalline order in the developing Drosophila eye

Pattern formation in developing tissues often involves self-organization guided by positional information. In most tissues, however, its dynamics, and therefore the underlying logic, remain unknown. Examining self-organized patterning of the fly eye, we combine experiments and modeling to elucidate how rows of light-receiving units emerge in the wake of a traveling differentiation front to form a crystal-like array. Live imaging of the proneural factor Atonal reveals unanticipated oscillations at the front, which are produced by the successive activation of two distinct enhancers and associated with pulsatile Notch signaling. Our observations are inconsistent with current models of eye patterning, whereby each row of differentiating cells provides a negative template for the next. Instead, they inform a new relay model in which transient Notch signaling from differentiating cells provides a positive template for the onset of differentiation two rows ahead, conveying both temporal and spatial information to propagate oscillations and crystal-like order.

developmental biology↗

Clostridioides difficile binary toxin CDT induces biofilm-like persisting microcolonies

Clinical symptoms of Clostridioides difficile infection (CDI) range from diarrhea to pseudomembranous colitis. A major challenge in managing CDI is the high rate of relapse. Several studies correlate production of CDT binary toxin by clinical strains of Clostridioides difficile with higher relapse rates. Although the mechanism of action of CDT on host cells is known, its exact contribution to CDI is still unclear. To understand the physiological role of CDT during CDI, we established two hypoxic relevant intestinal models, Transwell and Microfluidic Intestine-on-Chip systems. Both were challenged with the epidemic strain UK1 CDT+ and its isogenic CDT- mutant. We report that CDT binary toxin induces mucin-associated microcolonies that increase C. difficile colonization and display biofilm-like properties by enhancing C. difficile resistance to vancomycin but not to fidaxomicin, a biofilm disrupting antibiotic. Importantly, biofilm- like CDT-dependent microcolonies were also observed in the caecum and colon of infected mice. Hence, our study shows that CDT toxin induces biofilm-like microcolonies, increasing C. difficile colonization and persistence.

microbiology↗

MiniBAR/KIAA0355 is a dual Rac and Rab effector required for ciliogenesis

Cilia protrude from the cell surface and play critical roles in in-tracellular signaling, environmental sensing and development. Actin-dependent contractility and intracellular trafficking are both required for ciliogenesis, but little is known about how these processes are coordinated. Here, we identified a Rac1-and Rab35-binding protein with a truncated BAR domain that we named MiniBAR (aka KIAA0355/GARRE) which plays a key role in ciliogenesis. MiniBAR colocalizes with Rac1 and Rab35 at the plasma membrane and on intracellular vesicles traffick-ing to the ciliary base and exhibits remarkable fast pulses at the ciliary membrane. MiniBAR depletion leads to short cilia resulting from abnormal Rac-GTP/Rho-GTP levels, increased acto-myosin-II-dependent contractility together with defective trafficking of IFT88 and ARL13B into cilia. MiniBAR-depleted zebrafish embryos display dysfunctional short cilia and hall-marks of ciliopathies including left-right asymmetry defects. Thus, MiniBAR is a unique dual Rac and Rab effector that con-trols both actin cytoskeleton and membrane trafficking for cili-ogenesis.

cell biology↗

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy

Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective anti-microbial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. To address this, we developed a flow-controlled multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells, compressed inside separate microchambers by a soft hydro-pneumatic membrane. With this platform, we implemented a dynamic single-cell screening for compounds that induce a phenotypic change while decreasing cell-to-cell variation, aiming to undermine the bacterial population, making it more vulnerable to other drugs. We first applied this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our top hit impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that pheno-tuning compounds represent a successful approach to tackle pathogens that are increasingly difficult to treat.

microbiology↗