Biology subjects

Jacquemet, G.

Publications and source records attributed to Jacquemet, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Mapping bioimage-analysis software adoption in microscopy

Most quantitative microscopy measurements pass through image-analysis software, and different programs can return different measurements from the same images. Which programs researchers rely on therefore matters for reproducibility; however, this information lies scattered across the methods sections of the microscopy literature. In this analysis, we show how mentions of 30 software packages changed across 1.7 million full-text microscopy papers published between 2010 and 2025. In 2010, 12% of these papers mentioned at least one of the 22 analysis packages we tracked; by 2025, 30% did. Mentions stayed concentrated on a few general-purpose platforms, led by ImageJ/Fiji. Newer packages are mentioned more often in particular fields, such as QuPath in pathology and napari in electron microscopy. Deep-learning methods are usually mentioned alongside an established platform; papers often run StarDist inside Fiji and Cellpose on its own. Many papers mention a package without citing it, so citation counts understate how often packages appear in published work; authors should make that use visible by citing each package and reporting how they ran it.

bioinformatics↗

bioRxiv2026

Pancreatic cancer cells breach endothelial barriers through protrusion-driven invasion or endothelial retraction

Extravasation, the exit of circulating cancer cells from blood vessels, is a critical yet poorly understood step in metastatic dissemination. Here we show that pancreatic ductal adenocarcinoma (PDAC) cells can breach endothelial barriers through two mechanistically distinct modes of extravasation. MIA PaCa-2 cells breach endothelial junctions via filopodia-like protrusions, enabling access to and spread across the basal extracellular matrix (ECM). By contrast, AsPC-1 cells remain rounded atop the endothelium and cross the barrier by triggering rapid retraction of neighbouring endothelial cells. These distinct extravasation modes were also observed in zebrafish larvae. In the mouse lung, AsPC-1 cells arrest, survive, induce endothelial detachment from the basal lamina, and extravasate through this retraction mechanism before metastatic outgrowth. Mechanistically, AsPC-1-secreted factors are sufficient to destabilise endothelial monolayers, and AsPC-1 cells also induce endothelial apoptosis; however, blocking apoptosis does not prevent barrier disruption. By contrast, treatment with saracatinib, a Src-family kinase inhibitor, protects endothelial barriers, limits early vascular disruption in the lung, and delays metastatic outgrowth. Together, these findings reveal that PDAC cells can extravasate via mechanistically distinct routes, suggesting that effective anti-metastatic strategies may need to target multiple modes of endothelial barrier breach rather than a single pathway.

cell biology↗

bioRxiv2026

NucleiSky enables cross-scale multimodal registration of microscopy data using nuclei constellations

Integrating tissue-level organisation with sub-cellular resolution and molecular information often requires combining multiple microscopy modalities and scales. However, aligning images acquired with different modalities, settings, or instruments remains challenging. Here, we introduce NucleiSky, a microscopy image registration framework that utilises the spatial arrangement of nuclei or other landmarks as an intrinsic biological fingerprint. NucleiSky represents images as constellations of centroids and aligns them using geometric algorithms and spatial consensus scoring. In benchmark datasets, NucleiSky could localise query regions within larger reference images using as few as five nuclei. We show that NucleiSky can locate high-magnification fields of view within low-magnification overview scans, map these alignments to additional channels, support live brightfield-to-fixed registration using synthetic nuclear labels, and guide microscope retargeting. We further show that the same constellation-matching principle can be extended to 3D localisation and to non-nuclear landmarks. These findings establish local landmark geometry as an intrinsic spatial fingerprint that enables localisation and registration across imaging scales, modalities and microscopy platforms. NucleiSky is available as an open-source Python package and as notebook-based applications.

Cell Biology↗

bioRxiv2026

Scaffold protein SHANK3 regulates endothelial cell motility and tissue mechanics

SHANK3 is a multidomain scaffolding protein critical for neuronal function, which has been linked to neurodevelopmental disorders such as autism spectrum disorder. More recently, SHANK3 has been shown to play a role in cell survival and actin dynamics outside the nervous system. Here, we show that SHANK3 is widely expressed in endothelial cells across different tissues, where its role is not well understood. SHANK3 localised to endothelial cell-cell junctions in cultured endothelial cells, and its depletion compromised endothelial barrier function. SHANK silencing altered cell mechanics including elongated cell morphology, reduced cell-matrix traction forces and alteration of cell migration rate. It further triggered dynamic heterogeneity in endothelial monolayers, with regions of coordinated long-range migration interspersed with areas exhibiting only local velocity fluctuations, consistent with a transition toward more fluid-like tissue behaviour. This change in collective dynamics was accompanied by increased spheroid spreading and fusion, suggestive of altered tissue viscosity, and coincided with disrupted cell-cell junction morphology and mechanical forces in SHANK3-depleted cells. In vivo, SHANK3 depletion impaired endothelial cell migration, resulting in delayed sprouting of intersegmental vessels and disruption of the vascular network in zebrafish embryos. Furthermore, inducible endothelial-specific deletion of SHANK3 in postnatal mice impaired angiogenic sprouting and reduced vascular complexity in the developing retina. Overall, we demonstrate that SHANK3 plays a role in endothelial cell motility and tissue mechanics, with implications for vascular processes during development.

cell biology↗

bioRxiv2026

Filopodia-mediated trans-endocytosis

Cell-cell communication in tissues is influenced by contact geometry and molecular signalling. Here, we demonstrate that epithelial intercellular filopodia can penetrate neighbouring cells to form micrometre-long, double-membrane "impact sites" and, in some instances, initiate trans-endocytosis. Using super-resolution live imaging and three-dimensional electron microscopy in cell models, xenografts, and patient-derived tissues, we observe widespread intercellular filopodia and extensive interdigitation at the cell-cell interface. Filopodia impact sites in the recipient cell recruit PACSIN2 into dynamic "PACSIN2 fingers" and are specifically enriched for caveolin-1 and dynamin-2, while clathrin and CLIC pathway markers are not enriched. Most contacts are transient and resolved by retraction, but some undergo scission, with recipient cells internalising filopodial tips across both homotypic and heterotypic interactions, including cancer-endothelium contacts. Correlative light and FIB-SEM analysis reveals that internalised tips are often double-membraned, closely associated with endoplasmic reticulum tubules, and can traffic to lysosomes. These findings define a protrusion-driven, curvature-dependent uptake pathway at cell-cell interfaces and identify filopodia as exchange organelles in epithelial collectives.

cell biology↗

bioRxiv2025

Filopodome proteomics identifies CCT8 as a MYO10 interactor critical for filopodia functions

Cancer cells utilize filopodia to explore, adhere to, and invade their surrounding microenvironment, yet the protein networks that organize these protrusions remain incompletely defined. To uncover the molecular machinery underlying MYO10-positive filopodia, we targeted the fast biotin ligase TurboID to the filopo-dia tip-localized motor protein MYO10. Proximity biotinylation in two cell types revealed hundreds of potential MYO10 interactors. Surprisingly, there was limited overlap between the cell lines, indicating a previously unknown level of cell-type specificity in filopodia composition. A targeted microscopy and siRNA screen identified MINK1, SCRIB, CSNK1A1, and CCT8 as new regulators of filopodia formation. Focusing on one common interactor between cell lines, CCT8, known as a subunit of the chaperonin TRiC (TCP1 Ring Complex), we found that CCT8 associates with the MYO10 motor domain and regulates MYO10 filopodia independently of TRiC. Depleting CCT8 affected filopodia dynamics and impaired cell spreading, migration, and invasion in breast cancer cells. These findings establish CCT8 as a TRiC-independent regulator of MYO10 filopodia across different cancer cell types, highlight the surprising cell-type-specificity of filopodia composition, and provide a strategy and resource for studying filopodia in various biological contexts.

cell biology↗

bioRxiv2025

Customizable FDM-based zebrafish embryo mold for live imaging

Accurate and reproducible orientation of zebrafish embryos is crucial for high-resolution live imaging but remains challenging with standard agarose mounting. Here, we introduce an orientation tool made using fused deposition modeling (FDM), enhanced with a thin resin coating to improve surface smoothness and performance. This design creates reproducible, embryo-shaped wells that hold larvae in a dorsoventral orientation. The molds, designed to fit standard glass-bottom imaging dishes, are inexpensive to produce on common desktop 3D printers and can be easily modified to fit different imaging setups using the open-source design files. This method enables consistent, long-term live imaging of multiple embryos and broadens the use of low-cost additive manufacturing in zebrafish imaging workflows.

cell biology↗

bioRxiv2025

LSD1 serine 166 is a phosphorylation switch for chromatinlandscaping, gene activation, and tissue remodeling

LSD1 is a histone 3 (H3) demethylase that can either repress or activate gene expression. We discover here that the so far enigmatic balance between these two activities in non-hormonal cancer cells is regulated by phosphorylation of serine 166 (S166) on LSD1. SET-mediated Protein Phosphatase 2A (PP2A) inhibition in KRAS mutant cells promotes S166 phosphorylation. Endogenous LSD1 S166 alanine mutant (S166A) cells display H3 lysine 9 demethylation and acetylation, euchromatin, and gene activation. Mechanistically this is explained by the impaired interaction of S166A mutant LSD1 with repressor proteins SNAI2 and MYBP1. Functionally LSD1 S166A mutant cells display augmented beta1 integrin activity and stress fiber formation, and the mutant xenograft tumors have altered tumor microenvironment associated with increased macrophage recruitment. Collectively, PP2A-regulated S166 of LSD1 is a phosphorylation switch for epigenetic gene activation in non-hormonal cancer cells. Conceptually we demonstrate how dephosphorylation of one amino acid on a non-histone protein shapes chromatin landscape in cancer cells, and modify tumor stroma, and immune cell content. Highlights* Mechanism for gene activation by LSD1 in non-hormonal cancers * Single phosphorylation switch in a non-histone protein controls epigenetic landscape * Epigenetic protein phosphorylation in cancer cells shapes tumour immune microenvironment * Novel function for Protein Phosphatase 2A (PP2A) in epigenome regulation via LSD1 Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/653937v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@19548b3org.highwire.dtl.DTLVardef@1d7fd4dorg.highwire.dtl.DTLVardef@13707b3org.highwire.dtl.DTLVardef@1da7b71_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Fast label-free live imaging reveals key roles of flow dynamics and CD44-HA interaction in cancer cell arrest on endothelial monolayers

Leukocyte extravasation is a key component of the innate immune response, while circulating tumor cell extravasation is a critical step in metastasis formation. Despite their importance, the mechanisms underlying leukocyte and tumor cell extravasation remain incompletely understood. Here, we developed an imaging pipeline that integrates fast, label-free live-cell imaging with deep learning-based image analysis to quantitatively track and compare the initial steps of extravasation--cell landing and arrest on an endothelial monolayer--under physiological flow conditions. We find that pancreatic ductal adenocarcinoma (PDAC) cells exhibit variable adhesion strength and flow sensitivity. Remarkably, some PDAC cells demonstrate comparable endothelial engagement as leukocytes, preferentially arresting at endothelial junctions, potentially due to increased stiffness at these sites, which leads to exposure to the underlying basal extracellular matrix. PDAC cells also tend to cluster in regions with high, heterogeneous expression of the endothelial CD44 receptor. Simulations suggest that clustering results from the combination of CD44-mediated attachment and localized flow disturbances that facilitate subsequent cell attachment. Targeting CD44 using siRNA or function-blocking antibodies, or degrading its ligand hyaluronic acid (HA), almost completely abolishes PDAC cell attachment. Overall, we demonstrate that cancer and immune cells share both common and unique features in endothelial adhesion under flow, and identify CD44 and HA as key mediators of PDAC cell arrest.

cell biology↗

bioRxiv2024

Structural Repetition Detector: multi-scale quantitative mapping of molecular complexes through microscopy

From molecules to organelles, cells exhibit recurring structural motifs across multiple scales. Understanding these structures provides insights into their functional roles. While super-resolution microscopy can visualise such patterns, manual detection in large datasets is challenging and biased. We present the Structural Repetition Detector (SReD), an unsupervised computational framework that identifies repetitive biological structures by exploiting local texture repetition. SReD formulates structure detection as a similarity-matching problem between local image regions. It detects recurring patterns without prior knowledge or constraints on the imaging modality. We demonstrate SReDs capabilities on various fluorescence microscopy images. Quantitative analyses of three datasets highlight SReDs utility: estimating the periodicity of spectrin rings in neurons, detecting HIV-1 viral assembly, and evaluating microtubule dynamics modulated by EB3. Our open-source ImageJ and Fiji plugin enables unbiased analysis of repetitive structures across imaging modalities in diverse biological contexts.

cell biology↗

bioRxiv2024

PhotoFiTT: A Quantitative Framework for Assessing Phototoxicity in Live-Cell Microscopy Experiments

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes, yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT (Phototoxicity Fitness Time Trial), an integrated framework combining a standardised experimental protocol with advanced image analysis to quantify light-induced cellular stress in label-free settings. PhotoFiTT leverages machine learning and cell cycle dynamics to analyse mitotic timing, cell size changes, and overall cellular activity in response to controlled light exposure. Using adherent mammalian cells, we demonstrate PhotoFiTTs ability to detect wavelength- and dose-dependent effects, showcasing that near-UV light induces significant mitotic delays at doses as low as 0.6 J/cm2, while longer wavelengths require higher doses for comparable effects. PhotoFiTT enables researchers to establish quantitative benchmarks for acceptable levels of photodamage, facilitating the optimisation of imaging protocols that balance image quality with sample health.

cell biology↗

bioRxiv2023

DL4MicEverywhere: Deep learning for microscopy made flexible, shareable, and reproducible

Deep learning has revolutionised the analysis of extensive microscopy datasets, yet challenges persist in the widespread adoption of these techniques. Many lack access to training data, computing resources, and expertise to develop complex models. We introduce DL4MicEverywhere, advancing our previous ZeroCostDL4Mic platform, to make deep learning more accessible. DL4MicEverywhere uniquely allows flexible training and deployment across diverse computational environments by encapsulating methods in interactive Jupyter notebooks within Docker containers -a standalone virtualisation of required packages and code to reproduce a computational environment-. This enhances reproducibility and convenience. The platform includes twice as many techniques as originally provided by ZeroCostDL4Mic and enables community contributions via automated build pipelines. DL4MicEverywhere empowers participatory innovation and aims to democratise deep learning for bioimage analysis.

bioinformatics↗

bioRxiv2023

CellTracksColab, A platform for compiling, analyzing, and exploring tracking data

In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches. Here, we introduce CellTracksColab, a platform tailored to simplify the exploration and analysis of tracking data. CellTracksColab facilitates the compiling and analysis of results across multiple fields of view, conditions, and repeats, ensuring a holistic dataset overview. CellTracksColab also harnesses the power of high-dimensional data reduction and clustering, enabling researchers to identify distinct behavioral patterns and trends without bias. Finally, CellTracksColab also includes specialized analysis modules enabling spatial analyses (clustering, proximity to specific regions of interest). We demonstrate CellTracksColab capabilities with three use cases, including T-cells and cancer cell migration, as well as filopodia dynamics. CellTracksColab is available for the broader scientific community at https://github.com/CellMigrationLab/CellTracksColab.

bioinformatics↗

bioRxiv2023

TLNRD1 is a CCM complex component and regulates endothelial barrier integrity

We previously identified talin rod domain-containing protein 1 (TLNRD1) as a potent actin-bundling protein in vitro. Here, we report that TLNRD1 is primarily expressed in the vasculature in vivo and that its depletion leads to vascular abnormalities in vivo and loss of barrier integrity in cultured endothelial cells. We demonstrate that TLNRD1 is a component of the cerebral cavernous malformations (CCM) complex through its direct, high-affinity interaction with CCM2. Modeling and functional testing of TLNRD1 and CCM2 mutants reveal that their interaction is mediated by a hydrophobic C-terminal helix in CCM2 that attaches to a hydrophobic groove on the 4-helix domain of TLNRD1. Disruption of this binding interface leads to CCM2 and TLNRD1 accumulation in the nucleus and actin fibers. Notably, a CCM2 pathogenic mutation linked to vascular dementia in patients maps to the interface and disrupts the interaction. Our findings indicate that CCM2 controls TLNRD1 localization to the cytoplasm and inhibits its actin-bundling activity. Based on these results, we propose a new pathway by which the CCM complex modulates the actin cytoskeleton and vascular integrity by controlling TLNRD1 bundling activity.

cell biology↗

bioRxiv2023

NanoPyx: super-fast bioimage analysis powered by adaptive machine learning

To overcome the challenges posed by large and complex microscopy datasets, we have developed NanoPyx, an adaptive bioimage analysis framework designed for high-speed processing. At the core of NanoPyx is the Liquid Engine, an agent-based machine-learning system that predicts acceleration strategies for image analysis tasks. Unlike traditional single-algorithm methods, the Liquid Engine generates multiple CPU and GPU code variations using a meta-programming system, creating a competitive environment where different algorithms are benchmarked against each other to achieve optimal performance under the user"s computational environment. In initial experiments focusing on super-resolution analysis methods, the Liquid Engine demonstrated an over 10-fold computational speed improvement by accurately predicting the ideal scenarios to switch between algorithmic implementations. NanoPyx is accessible to users through a Python library, code-free Jupyter notebooks, and a napari plugin, making it suitable for individuals regardless of their coding proficiency. Furthermore, the optimisation principles embodied by the Liquid Engine have broader implications, extending their applicability to various high-performance computing fields.

bioinformatics↗

bioRxiv2023

Proteomic profiling of isolated immune synapses from primary mouse B cells

The immune synapse (IS) is a cell-cell interaction platform critical in lymphocyte activation by specific antigens. Despite of B cells being able to also respond to soluble antigens, in particular the in vivo importance of the IS and surface-tethered antigen recognition has strongly emerged in the recent years. The IS serves as a dynamic hub for multiple cellular actions but the molecular details of these functions, especially beyond the B cell antigen receptor (BCR) signalling, remain poorly understood. Here, to address the lack in the systems level understanding of the IS, we setup methodology for comprehensive investigation of the composition of the primary mouse B cells IS at proteome level. Utilizing functionalized magnetic beads to mimic antigen presenting cells and trigger IS formation on them, we developed a method to specifically and robustly extract the cell adhesions on the beads, namely the IS or transferrin receptor mediated adhesion as a control. Our data revealed 661 proteins exclusively present in the IS at 15 minutes after BCR engagement, 13 exclusively in the control adhesions and 365 proteins shared between the samples. We got strong coverage of the known components of the IS as well as identified a plethora of unknown proteins and functional pathways with hitherto unknown roles in B cell IS. Thus, in this work, we validated the IS isolation method as a valuable tool to study early B cell activation by surface-bound antigens as well as unveil several novel proteins and pathways suggestive of new functional aspects in the IS.

immunology↗

bioRxiv2022

Vimentin supports directional cell migration by controlling focal adhesions

Persistent cell migration requires focal adhesions to assemble and disassemble locally while maintaining global front-rear alignment. The mechanism that enforces this long-range spatial coherence remains unresolved. Here we identify the intermediate filament protein vimentin as a cell-scale organizer that stabilizes focal adhesion alignment during directed fibroblast migration. Using quantitative live-cell imaging, we show that vimentin-deficient fibroblasts lose directional persistence and a complete collapse of global focal adhesion alignment. Quantitative analysis reveals that vimentin stabilizes focal adhesion alignment by constraining angular fluctuations and preserving the periodic bias of adhesion birth across the adhesion field. Loss of vimentin results in smaller, rapidly turning-over adhesions with disrupted orientation. Trajectory analysis reveals a mechanically anchored adhesion state selectively associated with vimentin recruitment, distinguishing mechanical stabilization from biochemical maturation. Super-resolution and iPALM imaging further show that vimentin integrates within the focal adhesion nanoarchitecture near the force-transduction layer. Together, our findings establish that vimentin intermediate filaments impose spatial coherence on adhesion dynamics, converting locally stochastic adhesion assembly, turnover, and disassembly into globally coordinated adhesions and persistent directional migration.

cell biology↗

bioRxiv2022

Targeting a broad spectrum of KRAS-mutant cancers by hyperactivation-induced cell death

The KRAS oncogene drives many common and highly fatal malignancies. These include pancreatic, lung, and colorectal cancer, where numerous different activating KRAS mutations have made the development of KRAS inhibitors difficult. Here we identify the scaffold protein SH3 and multiple ankyrin repeat domain 3 (SHANK3) as a RAS interactor that binds overactive mutant forms to limit oncogenic KRAS signalling and maintain RAS- activity at an optimal level. Depletion of SHANK3 results in hyperactivation of KRAS/mitogen-activated protein kinase (MAPK) signalling, which in turn selectively induces MAPK/ERK-dependent cell death in KRAS-mutant cancers. Furthermore, targeting of this therapeutic vulnerability through nanobody- or RNA interference- mediated disruption of the SHANK3-KRAS interaction reduces tumour growth in vivo. Thus, inhibition of the SHANK3-KRAS interaction represents a new pan-KRAS-mutant compatible strategy for selective killing of KRAS- mutant cancer cells through excessive signalling. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/508660v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@87e71forg.highwire.dtl.DTLVardef@56cf94org.highwire.dtl.DTLVardef@1561136org.highwire.dtl.DTLVardef@183f711_HPS_FORMAT_FIGEXP M_FIG C_FIG Schematic model of SHANK3-controlled cell fate in KRAS-mutant cancers. SHANK3 directly interacts with KRAS and competes with RAF for KRAS binding to sustain oncogenic RAS-MAPK/ERK signalling at an optimal level (i.e. below toxic oncogenic signalling) in KRAS-mutant cancers. SHANK3 silencing (1) and inhibition of SHANK3-KRAS interaction (2) drive KRAS-mutant cells into cell death.

cancer biology↗