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Deep-learning techniques have enabled a breakthrough in robustness and execution time in automated cell detection in live fluorescence microscopy datasets. However, the heterogeneity, dimensionality and ever-growing size of 3D+time datasets challenge the evaluation of measurements. Here we propose a quality score for the accuracy of cell segmentation maps that is detector-independent and does not need any groundtruth nor priors on object appearance. Our method learns the dynamic parameters of each cell to detect inconsistencies in local displacements induced by segmentation errors. Using simulations that approximate the dynamics of cellular aggregates, we demonstrate the score ability to rank the performance of detectors up to 40% of false positives. On live volumetric imaging of organoids, our score is able to appropriately rank two stateof-the-art pre-trained deep-learning detectors (Stardist3D and Cellpose).; Les techniques d'apprentissage profond ont permis une percée dans la robustesse et le temps d'exécution de la détection automatisée des cellules dans les ensembles de données de microscopie à fluorescence en direct. Cependant, l'hétérogénéité, la dimensionnalité et la taille toujours croissante des ensembles de données 3D+temps compliquent l'évaluation des mesures. Nous proposons ici un score de qualité pour la précision des cartes de segmentation cellulaire qui est indépendant du détecteur et ne nécessite aucune vérité de base ni aucun a priori sur l'apparence de l'objet. Notre méthode apprend les paramètres dynamiques de chaque cellule pour détecter les incohérences dans les déplacements locaux induits par les erreurs de segmentation. En utilisant des simulations qui se rapprochent de la dynamique des agrégats cellulaires, nous démontrons la capacité du score à classer la performance des détecteurs jusqu'à 40% de faux positifs. Sur l'imagerie volumétrique en direct d'organoïdes, notre score est capable de classer de manière appropriée deux détecteurs d'apprentissage profond pré-entraînés de l'état de l'art (Stardist3D et Cellpose).

Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a challenge. We present a quantitative high-resolution imaging assay of single cancer cells in zebrafish xenografts to probe functional adaptation to variable cell-extrinsic cues and molecular interventions. Using cell morphology as a surrogate readout of cell functional states, we examine environmental influences on the morphotype distribution of Ewing Sarcoma, a pediatric cancer associated with the oncogene EWSR1-FLI1 and whose plasticity is thought to determine disease outcome through non-genomic mechanisms. Computer vision analysis reveals systematic shifts in the distribution of 3D morphotypes as a function of cell type and seeding site, as well as tissue-specific cellular organizations that recapitulate those observed in human tumors. Reduced expression of the EWSR1-FLI1 protein product causes a shift to more protrusive cells and decreased tissue specificity of the morphotype distribution. Overall, this work establishes a framework for a statistically robust study of cancer cell plasticity in diverse tissue microenvironments.

Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a significant challenge. We present a quantitative high-resolution imaging assay of cancer cell morphology in zebrafish xenografts to probe functional adaptation to variable cell extrinsic cues and molecular interventions. We focus on Ewing Sarcoma, a pediatric cancer driven by a single oncogenic fusion protein EWSR1-FLI1, and with little to no additional somatic mutations, making it a prototypical form of cancer whose adaptation to microenvironments is likely driven by acute, non-genomic mechanisms. Using computer vision analysis of 3D cell shapes, we find systematic shifts in the distribution of cell morphotypes between distinct sites in the fish embryo. We also find site-specific morphological responses to differential expression of EWSR1-FLI1. Combining these data we propose a model where Ewing Sarcoma cancer cell plasticity is sensitive both to expression fluctuation of EWSR1-FLI1 and signals from the surrounding tissue microenvironment, with either or both factors possibly contributing to the oncogenic potential of these cells.

Azoitei, Noh, et al. engineer fluorescent biosensors to measure activation at the subcellular level and with subsecond kinetics of GEF-H1, a Rho GTPase that regulates cytoskeletal dynamics. In combination with computational image time series analysis, the biosensors reveal the synergistic role of microtubule dynamics and Src phosphorylation in regulating GEF-H1 activity locally during cell migration., Rho family GTPases are activated with precise spatiotemporal control by guanine nucleotide exchange factors (GEFs). Guanine exchange factor H1 (GEF-H1), a RhoA activator, is thought to act as an integrator of microtubule (MT) and actin dynamics in diverse cell functions. Here we identify a GEF-H1 autoinhibitory sequence and exploit it to produce an activation biosensor to quantitatively probe the relationship between GEF-H1 conformational change, RhoA activity, and edge motion in migrating cells with micrometer- and second-scale resolution. Simultaneous imaging of MT dynamics and GEF-H1 activity revealed that autoinhibited GEF-H1 is localized to MTs, while MT depolymerization subadjacent to the cell cortex promotes GEF-H1 activation in an ~5-µm-wide peripheral band. GEF-H1 is further regulated by Src phosphorylation, activating GEF-H1 in a narrower band ~0–2 µm from the cell edge, in coordination with cell protrusions. This indicates a synergistic intersection between MT dynamics and Src signaling in RhoA activation through GEF-H1.

Vertebrate cells assemble mitotic spindles through multiple pathways. It is shown that Augmin-dependent, noncentrosomal nucleation generates the vast majority of microtubules in metaphase spindles. This results in a strong directional bias of microtubule growth toward individual kinetochores., Dividing cells reorganize their microtubule cytoskeleton into a bipolar spindle, which moves one set of sister chromatids to each nascent daughter cell. Early spindle assembly models postulated that spindle pole–derived microtubules search the cytoplasmic space until they randomly encounter a kinetochore to form a stable attachment. More recent work uncovered several additional, centrosome-independent microtubule generation pathways, but the contributions of each pathway to spindle assembly have remained unclear. Here, we combined live microscopy and mathematical modeling to show that most microtubules nucleate at noncentrosomal regions in dividing human cells. Using a live-cell probe that selectively labels aged microtubule lattices, we demonstrate that the distribution of growing microtubule plus ends can be almost entirely explained by Augmin-dependent amplification of long-lived microtubule lattices. By ultrafast 3D lattice light-sheet microscopy, we observed that this mechanism results in a strong directional bias of microtubule growth toward individual kinetochores. Our systematic quantification of spindle dynamics reveals highly coordinated microtubule growth during kinetochore fiber assembly.

Particle tracking is a ubiquitous task in the study of dynamic molecular and cellular processes by live microscopy. Light-sheet microscopy has recently opened a path to acquiring complete cell volumes for investigation in 3-dimensions (3D). However, hypothesis formulation and quantitative analysis have remained difficult due to fundamental challenges in the visualization and the verification of large sets of 3D particle trajectories. Here we describe u-track 3D, a software package that addresses these two challenges with three algorithmic innovations. Building on the established framework of globally optimal particle association in space and time implemented in the u-track package and recent advances in gaining association robustness in the case of erratic motion, we first report a complete and versatile pipeline for particle tracking. We then present the concept of dynamic region of interest (dynROI), which allows an experimenter to interact with dynamic 3D processes in 2D views amenable to visual inspection. Third, we present an estimator of trackability, which provides for every trajectory a confidence score, thereby overcoming the challenges of visual validation of trajectories in dense particle fields. With these combined strategies, u-track 3D provides a framework for the unbiased study of molecular processes in complex volumetric sequences.

We introduce a cost-effective and easily implemented scan unit which enables any camera-based microscope to perform projection imaging from diverse viewing angles. We demonstrate this capability on Lattice Light-Sheet and Oblique Plane Microscopy by rapidly delivering projection images with an uncompromised lateral resolution and high optical contrast. By imaging the sample from one or multiple perspectives, our method enables visualization of rapid biological processes, real time stereoscopic imaging as well as three-dimensional particle localization throughout a cellular volume from just two images. Furthermore, because our projection imaging technique provides intuitive three-dimensional renderings in real-time, it improves microscope usability, allows users to more-readily optimize instrument performance and identify biological phenomena of interest on-the-fly, while also reducing data overhead by a factor of >100. We leverage our rapid projection method to image cancer cell morpho-dynamics and calcium signaling in cultured neurons, to perform three-dimensional localization of genetically encoded nanoparticles, as well as to image orthogonal views of an embryonic Zebrafish heart simultaneously.

International audience; We present a 3D optical flow method for 3D fluorescence image sequences which preserves discontinuities in the computed flow field. We propose to minimize an energy function composed of a linearized 3D Census signature-based data term and a total variational (TV) regularizer. To demonstrate the efficiency of our method, we have applied it to real sequences depicting collagen network, where the motion field is expected to be discontinuous. We also favorably compare our results with two other motion estimation methods.

Contains fulltext : 220755.pdf (Publisher’s version ) (Open Access) Cell migration research has become a high-content field. However, the quantitative information encapsulated in these complex and high-dimensional datasets is not fully exploited owing to the diversity of experimental protocols and non-standardized output formats. In addition, typically the datasets are not open for reuse. Making the data open and Findable, Accessible, Interoperable, and Reusable (FAIR) will enable meta-analysis, data integration, and data mining. Standardized data formats and controlled vocabularies are essential for building a suitable infrastructure for that purpose but are not available in the cell migration domain. We here present standardization efforts by the Cell Migration Standardisation Organisation (CMSO), an open community-driven organization to facilitate the development of standards for cell migration data. This work will foster the development of improved algorithms and tools and enable secondary analysis of public datasets, ultimately unlocking new knowledge of the complex biological process of cell migration.

Motivation The revolution in light sheet microscopy enables the concurrent observation of thousands of dynamic processes, from single molecules to cellular organelles, with high spatiotemporal resolution. However, challenges in the interpretation of multidimensional data requires the fully automatic measurement of those motions to link local processes to cellular functions. This includes the design and the implementation of image processing pipelines able to deal with diverse motion types, and 3D visualization tools adapted to the human visual system. Results Here, we describe a new method for 3D motion estimation that addresses the aforementioned issues. We integrate 3D matching and variational approach to handle a diverse range of motion without any prior on the shape of moving objects. We compare different similarity measures to cope with intensity ambiguities and demonstrate the effectiveness of the Census signature for both stages. Additionally, we present two intuitive visualization approaches to adapt complex 3D measures into an interpretable 2D view, and a novel way to assess the quality of flow estimates in absence of ground truth. Availability and implementation https://team.inria.fr/serpico/data/3d-optical-flow-data/ Supplementary information Supplementary data are available at Bioinformatics online.

Actin assembly supplies the structural framework for cell morphology and migration. Beyond structure, this actin framework can also be engaged to drive biochemical signaling programs. Here, we describe how the hyperactivation of Rac1 via the P29S mutation (Rac1(P29S)) in melanoma hijacks branched actin network assembly to coordinate proliferative cues that facilitate metastasis and drug resistance. Upon growth challenge, Rac1(P29S)-harboring melanoma cells massively upregulate lamellipodia formation by dendritic actin polymerization. These extended lamellipodia form a signaling microdomain that sequesters and phospho-inactivates the tumor suppressor NF2/Merlin, driving Rac1(P29S) cell proliferation in growth suppressive conditions. These biochemically active lamellipodia require cell-substrate attachment but not focal adhesion assembly and drive proliferation independently of the ERK/MAPK pathway. These data suggest a critical link between cell morphology and cell signaling and reconcile the dichotomy of Rac1’s regulation of both proliferation and actin assembly by revealing a mutual signaling axis wherein actin assembly drives proliferation in melanoma.

We present cleared tissue Axially Swept Light-Sheet Microscopy (ctASLM), which achieves sub-micron isotropic resolution, high optical sectioning capability, and large field of view imaging (870×870 μm2) over a broad range of immersion media. ctASLM can image live, expanded, and both aqueous and organic chemically cleared tissue preparations and provides 2- to 5-fold better axial resolution than confocal or other reported cleared tissue light-sheet microscopes. We image millimeter-sized tissues with sub-micron 3D resolution, which enabled us to perform automated detection of cells and subcellular features such as dendritic spines.

We present cleared-tissue axially swept light-sheet microscopy (ctASLM), which enables isotropic, subcellular resolution imaging with high optical sectioning capability and a large field of view over a broad range of immersion media. ctASLM can image live, expanded, and both aqueous and non-aqueous chemically cleared tissue preparations. Depending on the optical configuration, ctASLM provides up to 260 nm of axial resolution, a three to tenfold improvement over confocal and other reported cleared-tissue light-sheet microscopes. We imaged millimeter-scale cleared tissues with subcellular three-dimensional resolution, which enabled automated detection of multicellular tissue architectures, individual cells, synaptic spines and rare cell–cell interactions. Cleared-tissue axially swept light-sheet microscopy (ctASLM) enables high-speed, refraction index-independent imaging of live, cleared and expanded samples with isotropic, submicron resolution.

Dividing cells reorganize their microtubule cytoskeleton into a bipolar spindle, which moves one set of sister chromatids to each nascent daughter cell. Early spindle assembly models postulated that spindle-pole-derived microtubules search the cytoplasmic space until they randomly encounter a kinetochore to form a stable attachment. More recent work uncovered several additional, centrosome-independent microtubule generation pathways, but the contributions of each pathway to spindle assembly have remained unclear. Here, we combined live microscopy and mathematical modeling to show that most microtubules nucleate at non-centrosomal regions in dividing human cells. Using a live-cell probe that selectively labels aged microtubule lattices, we demonstrate that the distribution of growing microtubule plus-ends can be almost entirely explained by Augmin-dependent amplification of long-lived microtubules. By ultra-fast 3D lattice light-sheet microscopy, we observed that this mechanism results in a strong directional bias of microtubule growth towards individual kinetochores. Our systematic quantification of spindle dynamics reveals highly coordinated microtubule growth during kinetochore-fiber assembly.

In subcellular light-sheet fluorescence microscopy (LSFM) of adherent cells, glass substrates are advantageously rotated relative to the excitation and emission light paths to avoid glass-induced optical aberrations. Because cells are spread across the sample volume, three-dimensional imaging requires a light-sheet with a long propagation length, or rapid sample scanning. However, the former degrades axial resolution and/or optical sectioning, while the latter mechanically perturbs sensitive biological specimens on pliant biomimetic substrates (e.g., collagen and basement membrane). Here, we use aberration-free remote focusing to diagonally sweep a narrow light-sheet along the sample surface, enabling multicolor imaging with high spatiotemporal resolution. Further, we implement a dithered Gaussian lattice to minimize sample-induced illumination heterogeneities, significantly improving signal uniformity. Compared with mechanical sample scanning, we drastically reduce sample oscillations, allowing us to achieve volumetric imaging at speeds of up to 3.5 Hz for thousands of Z-stacks. We demonstrate the optical performance with live-cell imaging of microtubule and actin cytoskeletal dynamics, phosphoinositide signaling, clathrin-mediated endocytosis, polarized blebbing, and endocytic vesicle sorting. We achieve three-dimensional particle tracking of clathrin-associated structures with velocities up to 4.5 μm/s in a dense intracellular environment, and show that such dynamics cannot be recovered reliably at lower volumetric image acquisition rates using experimental data, numerical simulations, and theoretical modeling.

We introduce Field Synthesis, a theorem that can be used to synthesize any scanned or dithered light-sheet, including those used in lattice light-sheet microscopy (LLSM), from an incoherent superposition of one-dimensional intensity distributions. This user-friendly and modular approach offers a drastically simplified optical design, higher light-throughput, simultaneous multicolor illumination, and a 100% spatial duty cycle, thereby providing uncompromised biological imaging with decreased rates of photobleaching.

Multiple mechanisms contribute to cancer cell progression and metastatic activity, including changes in endocytic trafficking and signaling of cell surface receptors. We report that gain-of-function (GOF) mutant p53 expression enhances β integrin and EGF receptor recycling and increases cell migration by triggering a positive feedback loop involving the activation of dynamin-1 (Dyn1) and accumulation of a spatially-restricted subpopulation of APPL1-positive ‘perimeter’ endosomes. DNM1 is upregulated at both the mRNA and protein levels in a manner dependent on expression of GOF mutant p53. Perimeter APPL1 endosomes are required for rapid recycling of EGFR and β1 integrins and modulate Akt signaling and Dyn1 activation to create the positive feedback loop that culminates in increased focal adhesion turnover and cell migration. Thus, Dyn1- and Akt-dependent perimeter APPL1 endosomes function as a nexus, integrating signaling and receptor trafficking, that can be co-opted by cancer cells for mutant p53-driven migration and invasion.

Cancer cells use a variety of mechanisms to subvert growth regulation and overcome environmental challenges. Often, these same mechanisms enable cancer cells to also develop resistance to targeted therapies. Here, we describe how a hyperactivating mutation of the Rac1 GTPase (Rac1P29S) harnesses Rac1’s role as a regulator of actin polymer assembly to sustain cell cycle progression in growth limiting conditions. This proliferative advantage supports metastatic colonization of melanoma cells and confers insensitivity to inhibitors of the mitogen-activated protein kinase (MAPK) pathway, a frequent target for melanoma treatment. Rac1P29S bypasses the MAPK axis through a mechanism that necessitates cell-matrix attachment, however, does not depend on integrin-mediated focal adhesion assembly and focal adhesion kinase signaling. Even without involvement of canonical adhesion signaling, cells carrying the Rac1P29S mutation show elevated traction upon drug treatment and require mechanical resistance from their surrounding matrix to gain a proliferative advantage. We describe an alternative arm for cell mechanosensing, whereby actin polymerization against a matrix of minimal rigidity organizes biochemical cues to drive proliferative signals. Hyperactivation of Rac1 by the P29S mutation channels this pathway in melanoma through Arp 2/3-dependent formation of a constrained actin brush network that results in the inactivation of tumor suppressor NF2/Merlin. These data suggest an alternative mechanism for mechanosensitive growth regulation that can be hijacked by cancer cells to circumvent the adverse conditions of foreign microenvironments or drug treatment.

International audience; We present a two-stage 3D optical flow estimation method for light microscopy image volumes. The method takes a pair of light microscopy image volumes as input, segments the 2D slices of the source volume in superpixels and sparsely estimates the 3D displacement vectors in the volume pair. A weighted interpolation is then introduced to get a dense 3D flow field. Edges and motion boundaries are considered during the interpolation. Our experimental results show good gain in execution speed, and accuracy evaluated in computer generated 3D data. Promising results on real 3D image sequences are reported.

International audience; One of the major challenges in multiple particle tracking is the capture of extremely heterogeneous movements of objects in crowded scenes. The presence of numerous assignment candidates in the expected range of particle motion makes the tracking ambiguous and induces false positives. Lowering the ambiguity by reducing the search range, on the other hand, is not an option, as this would increase the rate of false negatives. We propose here a piecewise-stationary motion model (PMM) for the particle transport along an iterative smoother that exploits recursive tracking in multiple rounds in forward and backward temporal directions. By fusing past and future information, our method, termed PMMS, can recover fast transitions from freely or confined diffusive to directed motions with linear time complexity. To avoid false positives we complemented recursive tracking with a robust inline estimator of the search radius for assignment (a.k.a. gating), where past and future information are exploited using only two frames at each optimization step. We demonstrate the improvement of our technique on simulated data – especially the impact of density, variation in frame to frame displacements, and motion switching probability. We evaluated our technique on the 2D particle tracking challenge dataset published by Chenouard et al in 2014. Using high SNR to focus on motion modeling challenges, we show superior performance at high particle density. On biological applications, our algorithm allows us to quantify the extremely small percentage of motor-driven movements of fluorescent particles along microtubules in a dense field of unbound, diffusing particles. We also show with virus imaging that our algorithm can cope with a strong reduction in recording frame rate while keeping the same performance relative to methods relying on fast sampling.

The use of propagation invariant Bessel beams has enabled high-resolution subcellular light sheet fluorescence microscopy. However, the energy within the concentric side lobe structure of Bessel beams increases significantly with propagation length, generating unwanted out-of-focus fluorescence that enforces practical limits on the imaging field of view size. Here, we present a light sheet fluorescence microscope that achieves 390 nm isotropic resolution and high optical sectioning strength (i.e., out-of-focus blur is strongly suppressed) over large field of views, without the need for structured illumination or deconvolution-based postprocessing. We demonstrate simultaneous dual-color, high-contrast, and high-dynamic-range time-lapse imaging of migrating cells in complex three-dimensional microenvironments, three-dimensional tracking of clathrin-coated pits, and long-term imaging spanning >10 h and encompassing >2600 time points.

In fluorescence microscopy, the serial acquisition of two-dimensional images to form a three-dimensional (3D) volume limits the maximum imaging speed. This is particularly evident when imaging adherent cells in a light-sheet fluorescence microscopy format, as their elongated morphologies require ∼200 image planes per image volume. Here, by illuminating the specimen with three light sheets, each independently detected, we present a light-efficient, crosstalk-free, and volumetrically parallelized 3D microscopy technique that is optimized for high-speed (up to 14 Hz) subcellular (300 nm lateral, 600 nm axial resolution) imaging of adherent cells. We demonstrate 3D imaging of intracellular processes, including cytoskeletal dynamics in single-cell migration and collective wound healing for 1500 and 1000 time points, respectively. Furthermore, we capture rapid biological processes, including the trafficking of early endosomes with velocities exceeding 10 μm/s and calcium signaling in primary neurons.

International audience; We propose a robust statistical framework for reconstructing lifetime map corrupted by vesicle motion in frequency domain FLIM imaging. Instrumental noise is taken into account to improve lifetime estimation. Robust M-estimators and MLestimators allow to jointly estimate motion and lifetime. Performances are demonstrated on simulated and real samples.

We propose a robust statistical framework for correcting the movements of vesicles in frequency domain FLIM imaging. Movement and lifetime are jointly estimated in a three-step procedure. Robust M-estimators are mainly used to improve accuracy in temporally-varying noisy images. The performance of the proposed method is demonstrated on both simulated and real samples.

Fluorescence lifetime is usually defined as the average nanosecond-scale delay between excitation and emission of fluorescence. It has been established that lifetime measurements yield numerous indications on cellular processes such as interprotein and intraprotein mechanisms through fluorescent tagging and Förster resonance energy transfer. In this area, frequency-domain fluorescence lifetime imaging microscopy is particularly appropriate to probe a sample noninvasively and quantify these interactions in living cells. The aim is then to measure the fluorescence lifetime in the sample at each location in space from fluorescence variations observed in a temporal sequence of images obtained by phase modulation of the detection signal. This leads to a sensitivity of lifetime determination to other sources of fluorescence variations such as intracellular motion. In this paper, we propose a robust statistical method for lifetime estimation for both background and small moving structures with a focus on intracellular vesicle trafficking.