Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A ) Schematic representation of the microfluidic system used to study the interactions between pancreatic ductal adenocarcinoma (PDAC) cells and endothelial cells. ( B – D ) Labeled (CellTrace) PDAC cells were perfused over an endothelial monolayer at 400 µm/s for 10 min. Samples were fixed, stained with phalloidin and DAPI, and imaged using a spinning disk confocal microscope. ( B ) A representative image shows the endothelial monolayer with attached AsPC-1 cells. The red box highlights a region of interest that is magnified. Scale bars: 100 µm (main), 30 µm (inset). ( C ) The number of attached cells was quantified for each cell line. The boxes capture the interquartile range, with the median marked by a line within each box. Data points falling outside the whiskers are depicted as individual dots ( n = 25–36 fields of view, 3–7 biological repeats). The P values were determined using a randomization test. ( D ) Frequency plot showing the overall distribution of cancer cells across the microfluidic channel from the edge (border) to the center ( n = 302–2279 cells) and highlighting the region selected for subsequent live-cell imaging. ( E – L ) AsPC-1, MIA PaCa-2, and Panc 10.05 cells were perfused over an endothelial monolayer and imaged using a brightfield microscope at 25 Hz for 8 min, with flow speeds varied at 2-min intervals: 400 µm/s (High, H), 200 µm/s (Medium, M), and 100 µm/s (Low, L). Each sequence concluded with an increased flow speed of 400 µm/s to test the stability of the adhered cells (Wash, W). ( F ) A representative brightfield image (BF) showing the detected PDAC cells at two different time points and the resulting tracks. ( G ) The number of arrested PDAC cells over time for each cell line tested. Bold lines indicate the average, and shaded areas represent the SD (4–7 biological repeats, see “Methods”). The different flow speeds are shown. ( H ) The attachment rate for each cell line at each flow speed is displayed as a bar chart (mean +/− SEM) with individual data points (4–7 biological repeats, see “Methods”). The P values were determined using a randomization test. ( I ) Percentage of AsPC-1 and MIA PaCa-2 cells arresting as single cells per movie. Here, a cluster is defined as at least two cells that arrest together (at the same time) within a cell diameter of each other (see “Methods” for details). Results from the various flow speeds are pooled ( n > 24 videos, 6–7 biological repeats; see “Methods”). ( J – L ) Analysis of track metrics for MIA PaCa-2, AsPC-1, and Panc 10.05 cells at different flow speeds. ( J ) Plot of mean, maximum, and minimum track speeds for each cell line. Data are presented as mean ± SD. ( K ) Total distance traveled by PDAC cells during perfusion. ( L ) Forward Migration Index (FMI) along the flow direction for each cell line. ( I , K , L ) Results are presented as boxplots, where the whiskers extend from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points outside the whiskers are depicted as individual dots ( n = 3011–8227 tracks, 4–7 biological repeats, see “Methods”). The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Labeling, Staining, Microscopy, Live Cell Imaging, Sequencing, Migration

Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A , B ) Adhesion of labeled PDAC cell lines to an endothelial monolayer without flow. Cells were fixed, stained with phalloidin and DAPI, and imaged using a spinning disk confocal microscope. ( A ) A representative image of the endothelial monolayer with attached PDAC cells. Scale bar: 100 µm. ( B ) The number of attached cells was quantified for each cell line. Results are presented as boxplots, where the whiskers extend from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points falling outside the whiskers are depicted as individual dots ( n = 10–27 fields of view, 2–9 biological repeats). The P values were determined using a randomization test. MIA PaCa-2 vs AsPC-1, P value = 0.0001. MIA PaCa-2/SW1990/AsPC-1 (grouped on graph) vs Panc 10.05, P value = 0.0001. ( C ) Size distribution of PDAC cell lines. Cells in suspension were imaged using a brightfield microscope, and their diameters were manually measured using Fiji. Results are presented as boxplots, where the whiskers extend from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points falling outside the whiskers are depicted as individual dots ( n = 39–40 cells). The P values were determined using a randomization test. Non-significant comparisons not shown. AsPC-1 vs MIA PaCa-2, P value = 0.0001. MIA PaCa-2 vs Panc 10.05, P value = 0.0001. BxPC-3 vs Panc 10.05, P value = 0.0001. ( D , E ) Endothelial monolayers, either untreated or treated with IL-1β (10 ng/ml for 2 h and 5 ng/ml for 16 h), were fixed and stained to visualize E-selectin, VCAM1, ICAM-1, and CD44. Stainings were performed without permeabilization to specifically label surface-accessible adhesion molecules. Images were captured using a spinning disk confocal microscope. ( D ) Representative fields of view are shown. Scale bar: 100 µm. ( E ) Quantification of the marker per field of view is presented. Intensities were normalized to the number of nuclei per field of view, as well as the average intensity measured in the control in each repeat. Results are presented as boxplots, where the whiskers extend from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points falling outside the whiskers are depicted as individual dots ( n = 45 field of view, 3 biological repeats). The P values were determined using a randomization test. E-selectin, Ctrl vs IL-1β 2 h, P value = 0.0001 Ctrl vs IL-1β 16 h, P value = 0.0001. VCAM-1, Ctrl vs IL-1β 2 h, P value = 0.0001 Ctrl vs IL-1β 16 h, P value = 0.0001. ICAM-1, Ctrl vs IL-1β 2 h, P value = 0.0001 Ctrl vs IL-1β 16 h, P value = 0.0001. CD44, Ctrl vs IL-1β 16 h, P value = 0.0001. ( F , G ) The number of arrested neutrophils ( F ) or PBMCs ( G ) over time, in the presence or absence of IL-1β stimulation (10 ng/ml for 2 h and 5 ng/ml for 16 h). Bold lines indicate the average, and shaded areas represent the SD (4–7 biological repeats, see “Methods”). ( H ) The number of arrested PDAC cells over time for each cell line tested, with (2 h) and without IL-1β stimulation (PDAC Ctrl results were already displayed in Fig. ). Bold lines indicate the average, and shaded areas represent the SD (2–7 biological repeats, see “Methods”). ( I ) The number of arrested PDAC and immune cells over time without IL-1β stimulation (PDAC Ctrl results were already displayed in Fig. ). Bold lines indicate the average, and shaded areas represent the SD (3–8 biological repeats, see “Methods”). The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (https://doi.org/10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Labeling, Staining, Microscopy, Suspension, Marker, Control

Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A , B ) Analysis pipeline for predicting and segmenting endothelial cell junctions and nuclei from brightfield videos using deep-learning-based artificial labeling. ( A ) Brightfield videos were used to detect and track perfused cells, and to predict DAPI (all nuclei) and PECAM-1 (endothelial cell–cell junction) staining using artificial labeling. Endothelial cell nuclei were segmented using StarDist based on the predicted DAPI staining. Using both predicted DAPI and PECAM-1 staining, endothelial cells were segmented with Cellpose (see “Methods” for details). The distance between tracked cells and the nearest endothelial structures (junctions and nuclei) was calculated using the Euclidean distance transform algorithm from the SciPy library. Scale bar: 100 µm. ( B ) For each condition, the average distance from the cell center to the nearest nucleus and the average distance from the cell center to the nearest endothelial cell–cell junction are plotted (mean +/− SD) as a function of the total distance traveled from Landing to the first Arrest and the End of the track ( n = 84–1139 tracks, 2–8 biological repeats, see “Methods”). ( C , D ) Labeled PDAC cell lines were perfused over an endothelial monolayer at 400 µm/s for 10 min. Samples were then fixed, stained with PECAM-1 and DAPI, and imaged using a spinning disk confocal microscope. ( C ) A representative image showing the endothelial monolayer with attached PDAC cells. Boxes highlight two regions of interest that are magnified. Scale bars: 50 µm (main), 30 µm (inset). ( D ) The ratio of PDAC cells arrested on top of junctions to those arrested on top of nuclei is displayed as a bar chart (mean +/− SD) with individual data points ( n = 19–26 field of views, 3–4 biological repeats). ( E – G ) Lifeact-mScarlet-I MIA PaCa-2 cells were injected into 48 h post-fertilization Tg(5xUAS:cdh5-EGFP) zebrafish embryos. Three hours post-injection, embryos were imaged live using an Airyscan confocal microscope. A representative image and a 3D rendering are displayed. Scale bar: 15 µm. The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Labeling, Staining, Microscopy, Injection

Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A – E ) Biophysical characterization of the endothelial monolayer using atomic force microscopy (AFM). AFM was used in both contact mode ( B , C ) and tapping mode ( D , E ) to characterize the biophysical properties of the endothelial monolayer surface. The asterisk (*) indicates a gap in the endothelial monolayer. Stiffnesses measured are outside the biological range and are represented as white squares ( D ); thus, they are removed from the analysis. ( B ) A representative image of the monolayer’s height is displayed. Note that the x-y and height axes are of different scales to exaggerate the 3D topology of the layer. A representative height profile between two adjacent nuclei is also displayed. ( C ) The height difference between (b/w) nuclei and adjacent cell–cell junctions, and the distance between two adjacent nuclei, were manually extracted from AFM imaging data and are displayed as a boxplot ( n = 124 measurements, 3 biological repeats). ( D ) Representative image showing AFM results acquired in contact mode. Nuclei (black) and EC junctions (red) manual segmentation. Scale bar: 10 µm. ( E ) The stiffness (Young’s modulus) measured over the cell body and at the cell junctions was manually extracted from the AFM data and displayed as a boxplot ( n = 190–399 measurements, >3 biological repeats). ( F , G ) Spatial relationship between fibronectin (FN) and endothelial cell–cell junctions. Endothelial cell monolayers were fixed and stained without permeabilization for FN, PECAM-1, and DAPI, then imaged using a spinning disk confocal microscope. Endothelial junctions and FN patches were automatically segmented, and the distance between the FN patches and the closest endothelial cell–cell junction was analyzed (edge-to-edge distance). ( F ) A representative max projection image and associated segmentation labels are displayed. Scale bar: 50 µm. ( G ) Frequency plot showing the number of FN patches as a function of the distance to the closest endothelial cell–cell junction. The data distribution is also shown as a boxplot (n = 1867 patches, 65 fields of view, one experiment). ( H , I ) The spatial relationship between FN patches and arrested PDAC cells (MIA PaCa-2 and AsPC-1). Lifeact-mScarlet-I expressing PDAC cell lines were perfused over an endothelial monolayer at 400 µm/s for 10 min, fixed, and stained to visualize FN, thrombospondin (THSD), and DAPI, then imaged using a spinning disk confocal microscope. PDAC cells and FN/THSD patches were automatically segmented, and the distance between the PDAC cells and the closest patches was analyzed (edge-to-edge distance). ( H ) Representative images showing the endothelial monolayer with attached MIA PaCa-2 cells as segmentation labels. Scale bar: 50 µm. ( I ) The proportion of PDAC cells on top, near, or away from visible FN/THSD patches is displayed as a stacked histogram ( n = 162–2462 cells, 69–80 fields of view, 3 biological repeats). The shuffled conditions indicate that FN and THSD fluorescent channel images were randomly paired with cancer cell images from the same group before performing the distance analysis to generate randomized controls for distance measurement. ( J ) Structured illumination microscopy images of MIA PaCa-2 cells attached to an endothelial monolayer. Lifeact-mNeonGreen MIA PaCa-2 cells were perfused over an endothelial monolayer at 400 µm/s for 30 min, fixed, stained to visualize FN and F-actin, and imaged using a structured illumination microscope. Representative images of 3D renderings as well as selected projections are displayed. Scale bars: 5 µm and 1 µm. ( C , E , G ) Results are presented as boxplots, with whiskers representing the 10th to 90th percentiles and boxes indicating the interquartile range, with the median value marked. Outliers are displayed as individual data points. The P values were determined using a randomization test. ( E ) P value = 0.0001. ( G ) P value = 0.0001. The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Microscopy, Imaging, Staining, Expressing

Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A , B ) Spatial analysis of arrested PDAC cells and immune cells on endothelial cell monolayers. Using our tracking data (Figs. and ), we recorded all the events where cells were arrested in each field of view (instantaneous speed below 5 µm/s). Modified Ripley’s L functions and Monte Carlo simulations were employed to quantify the spatial density of arrested cell events, comparing the observed density to what is expected under a random distribution. ( A ) Representative images showing the accumulation of arrest events in a field of view for each condition. ( B ) Ripley’s L scores for each condition (CTRL and IL-1β are combined) are presented as a heatmap ( n = 8–12 fields of view, 8–12 biological repeats; see “Methods”). ( C , D ) Spatial relationship between arrested PDAC cells (MIA PaCa-2 and AsPC-1) and endothelial adhesion molecules. Labeled PDAC cells were perfused over an endothelial monolayer for 10 min, fixed, and stained to visualize E-selectin (E-select), VCAM1, ICAM-1, ICAM-2, CD44, and fibronectin (FN). Stainings were performed without permeabilization to label specifically surface-accessible adhesion molecules. Images were captured using a spinning disk confocal microscope. ( C ) Representative fields of view are displayed. Scale bar: 100 µm. ( D ) PDAC cells were automatically segmented, and the positivity of the endothelial cells in contact with the arrested PDAC cells for each specific marker was manually scored. The percentage of PDAC cells in contact with marker-positive areas is shown (observed). The expected rate of cells in contact with each marker was calculated using Monte Carlo simulations, which took into account the cell diameter and the area of the field of view covered by each marker (see “Methods” for details) ( n = 71–143 fields of view, 3 biological replicates). ( E ) Simulations conducted using our cell adhesion simulator to explore the factors contributing to PDAC cell clustering. We examined the effects of flow speed, PDAC adhesion strength, and the characteristics of the endothelial adhesion background. The uniform background features a constant attachment probability throughout the simulation space, while the CD44 background utilizes CD44 images to modulate attachment probabilities spatially. A static flow field indicates that cell attachment does not influence flow dynamics. In contrast, a dynamic flow field indicates that the local flow dynamics are recomputed across the whole simulation space by solving the Navier-Stokes equations after each attachment event. For each parameter tested, Ripley’s L score was calculated only when at least two cells were attached in the simulation space. Results are presented as heatmaps. ( B , D ) Results are presented as boxplots, with whiskers extending from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points outside the whiskers are depicted as individual dots. The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Modification, Labeling, Staining, Microscopy, Marker, Cell Attachment Assay

Journal: The EMBO Journal

Article Title: Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers

doi: 10.1038/s44318-025-00678-9

Figure Lengend Snippet: ( A , B ) Validation of hyaluronidase (HA digestion; HA dig.) treatment in PDAC cells. MIA PaCa-2 and AsPC-1 were treated with hyaluronidase and plated on poly-Lysine-coated coverslip, fixed, stained, and imaged using a spinning disk confocal microscope. ( A ) Representative SUM projections and single planes are displayed. Note that the Hyaluronic signal in the digested sample is inside the cell. ( B ) The HA signal per cell was quantified from the SUM projections ( n = 601–1542, 3 biological repeats). Scale bar: 20 µm. ( C – E ) Impact of hyaluronidase treatments in PDAC cells or endothelial cells (ECs) on PDAC cell attachment to the endothelial monolayer. PDAC or ECs were pre-treated with hyaluronidase. PDAC cells were then perfused over endothelial monolayers, and cell attachment was recorded as in Fig. . The number of arrested MIA PaCa-2 ( C ) and AsPC-1 ( D ) cells over time is displayed, with bold lines indicating the average and shaded areas representing the SD (2–3 biological repeats, see “Methods”). The data is shown for different flow speeds. ( E ) The attachment rate for each cell line and condition at the medium (M) flow speed is displayed as a bar chart (mean ± SEM) with individual data points (2–3 biological repeats, see “Methods”). ( F – H ) Effect of hyaluronidase treatments on the spatial clustering of PDAC cells. ( F ) Using the tracking data from ( C – E ) and as in Fig. , we recorded all arrest events within each field of view. Modified Ripley’s L functions were applied to quantify the spatial density of arrested cells. Ripley’s L scores for each condition are presented as boxplots ( n = 8–12 fields of view, 2–3 biological repeats, see “Methods”). ( G , H ) As in Fig. , the analysis was refined to include only cell trajectories showing a definitive arrest pattern. ( G ) The total distance traveled from the point of arrest to the end of the track is displayed for each condition. ( H ) The number of detachment peaks per condition is shown ( n = 20–1055 tracks). ( B , F – H ) Results are presented as boxplots, with whiskers extending from the 10th to the 90th percentiles. The boxes capture the interquartile range, with the median marked by a line within each box. Data points falling outside the whiskers are depicted as individual dots. The P values were determined using a randomization test. ( B ) MIA PaCa-2, P value = 0.0001. AsPC-1, P value = 0.0001. ( F ) MIA PaCa-2, Untreated vs EC, P value = 0.0001. ( G ) MIA PaCa-2, Untreated vs MIA PaCa-2, P value = 0.0001. Untreated vs EC, P value = 0.0001. ( H ) MIA PaCa-2, Untreated vs MIA PaCa-2, P value = 0.0001. Untreated vs EC, P value = 0.0001. The numerical data and images used for this figure, as well as statistical summaries including pairwise Cohen’s d values and results from statistical tests, have been archived on Zenodo (10.5281/zenodo.17232437).

Article Snippet: Marianas spinning-disk imaging system with a Yokogawa CSU-W1 scanning unit on an inverted Zeiss Axio Observer Z1 , Intelligent Imaging Innovations , .

Techniques: Biomarker Discovery, Staining, Microscopy, Cell Attachment Assay, Modification

Journal: Cellular and Molecular Life Sciences: CMLS

Article Title: LRRK2 kinase modulates glucose-stimulated insulin secretion via RAB8 phosphorylation and ciliogenesis

doi: 10.1007/s00018-025-05810-w

Figure Lengend Snippet: LRRK2 controls the glucose-stimulated insulin secretion through its kinase activity. A Glucose-stimulated (20 mM) insulin secretion in βtc3 cells incubated in the absence (CTR - DMSO) or presence of the LRRK2 kinase inhibitors GSK (200 nM) or MLi-2 (10 nM) (n = at least 5 independent experiments). Data are expressed as percentage of insulin content and are reported as mean ± SD. Two-way ANOVA: * p < 0.05, ** p < 0.01. B Glucose-stimulated (16.7 mM) insulin secretion in isolated human islets incubated in the absence (CTR - DMSO) or presence of the LRRK2 kinase inhibitors GSK (200 nM) and MLi-2 (10 nM) ( n = 5 independent experiments). Data are expressed as percentage of insulin content and are reported as mean ± SD. Two-way ANOVA: *p<0.05, **p < 0.01, ***p < 0.005. C Representative images of insulin granules density in the TIRF zone (100 nm) under basal (1 mM glucose) and stimulated (20 mM glucose) conditions in βtc3 cells incubated with 10 nM MLi-2 or DMSO (CTR) for 45 min. After treatments, cells were fixed and stained with anti-insulin antibody. Scale bar: 5 μm. D Quantitative analysis of insulin granules in the TIRF zone in control and MLi-2 treated βtc3 cells. Data are normalized for the cell area and are reported as mean ± SD. Each dot represents the average granule density in one cell ( n = 22 cells). Two-way ANOVA: ** p < 0.01, **** p < 0.001. E Glucose-stimulated (20 mM) insulin secretion in βtc3 cells expressing LRRK2 WT or G2019S constructs. Insulin secretion was evaluated in the presence or absence of the LRRK2 kinase inhibitor GSK (200 nM) in G2019S-transfected cells ( n = 3 independent experiments). Data are expressed as percentage of insulin content and are reported as mean ± SD. Two-way ANOVA: * p < 0.05, ** p < 0.01, *** p < 0.005

Article Snippet: Samples were imaged by a TIRF microscope (Axio Observer Z1, Zeiss), equipped with a 100 × 1.45 NA, oil immersion, objective and an Argon laser.

Techniques: Activity Assay, Incubation, Isolation, Staining, Control, Expressing, Construct, Transfection

Journal: Cellular and Molecular Life Sciences: CMLS

Article Title: LRRK2 kinase modulates glucose-stimulated insulin secretion via RAB8 phosphorylation and ciliogenesis

doi: 10.1007/s00018-025-05810-w

Figure Lengend Snippet: RAB8 is phosphorylated by LRRK2, and its phosphorylation promotes insulin release. A Full-length RFP-LRRK2 was expressed in βtc3 cells, and the recombinant protein was isolated on the RFP-selector resin (RFP-resin). A control-selector resin (Ctr-Resin) was used to detect unspecific binding. Interacting proteins were resolved by western blotting analysis with the anti-RAB8 antibody. B Western blot analysis of RAB8 phosphorylation on the threonine 72 residue at different time points after glucose stimulation (20 mM), in the presence or absence of LRRK2 kinase inhibitor MLi-2 (10 nM, 45 min pre-treatment) and C relative quantification ( n = at least 3 independent experiments). Actin was used as loading control. Data are expressed as Phospho-RAB8 over RAB8 and are reported as mean ± SD. Two-way ANOVA: ** p < 0.01; **** p < 0.001. D Glucose-stimulated (20 mM) insulin secretion in βtc3 cells transfected with WT RAB8 and T72A mutant. Data are expressed as percentage of insulin content and values are reported as mean ± SD ( n = 6 experiments). Two-way ANOVA: * p < 0.05; ***p < 0.005; **** p < 0.001. E Quantitative analysis of insulin granule trafficking in the TIRF zone in βtc3 cells cotransfected with GFP-insulin and WT RAB8 and T72A mutant at different time points after glucose (20 mM) and KCl (40 mM) stimulations. Data are normalized on cell area and are reported as mean ± SD. Two-way ANOVA. ** p < 0.01; **** p < 0.001 vs WT RAB8, same time point; °° p < 0.01, vs 0’ WT RAB8 ( n = at least 3 independent experiments). F Representative immunofluorescence images of βtc3 cells triple stained with DAPI (blue), anti-RAB8 (green) and anti-insulin (red) antibodies under basal (1 mM glucose) and stimulated (20 mM glucose) conditions. Scale bar: 5 μm

Article Snippet: Samples were imaged by a TIRF microscope (Axio Observer Z1, Zeiss), equipped with a 100 × 1.45 NA, oil immersion, objective and an Argon laser.

Techniques: Phospho-proteomics, Recombinant, Isolation, Control, Binding Assay, Western Blot, Residue, Quantitative Proteomics, Transfection, Mutagenesis, Immunofluorescence, Staining