Symmetry breaking and fate divergence during lateral inhibition in Drosophila.

Lateral inhibition mediates alternative cell fate decision and produces regular cell fate patterns with fate symmetry breaking (SB) relying on the amplification of small stochastic differences in Notch activity via an intercellular negative feedback loop. Here, we used quantitative live imaging of endogenous Scute (Sc), a proneural factor, and of a Notch activity reporter to study the emergence of Sensory Organ Precursor cells (SOPs) in the pupal abdomen of Drosophila. SB was observed at low Sc levels and was not preceded by a phase of intermediate Sc expression and Notch activity. Thus, mutual inhibition may only be transient in this context. In support of the intercellular feedback loop model, cell-to-cell variations in Sc levels promoted fate divergence. The size of the apical area of competing cells did not detectably bias this fate choice. Surprisingly, cells that were in direct contact at the time of SB could adopt the SOP fate, albeit at low frequency (10%). These lateral inhibition defects were corrected by cellular rearrangements, not cell fate change, highlighting the role of cell-cell intercalation in pattern refinement.

TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines.

TrackMate is an automated tracking software used to analyze bioimages and is distributed as a Fiji plugin. Here, we introduce a new version of TrackMate. TrackMate 7 is built to address the broad spectrum of modern challenges researchers face by integrating state-of-the-art segmentation algorithms into tracking pipelines. We illustrate qualitatively and quantitatively that these new capabilities function effectively across a wide range of bio-imaging experiments.

nAdder: A scale-space approach for the 3D analysis of neuronal traces.

Tridimensional microscopy and algorithms for automated segmentation and tracing are revolutionizing neuroscience through the generation of growing libraries of neuron reconstructions. Innovative computational methods are needed to analyze these neuronal traces. In particular, means to characterize the geometric properties of traced neurites along their trajectory have been lacking. Here, we propose a local tridimensional (3D) scale metric derived from differential geometry, measuring for each point of a curve the characteristic length where it is fully 3D as opposed to being embedded in a 2D plane or 1D line. The larger this metric is and the more complex the local 3D loops and turns of the curve are. Available through the GeNePy3D open-source Python quantitative geometry library (https://genepy3d.gitlab.io), this approach termed nAdder offers new means of describing and comparing axonal and dendritic arbors. We validate this metric on simulated and real traces. By reanalysing a published zebrafish larva whole brain dataset, we show its ability to characterize different population of commissural axons, distinguish afferent connections to a target region and differentiate portions of axons and dendrites according to their behavior, shedding new light on the stereotypical nature of neurites' local geometry.

LPS-Induced Systemic Inflammation Affects the Dynamic Interactions of Astrocytes and Microglia with the Vasculature of the Mouse Brain Cortex.

The Neurovascular Unit (NVU), composed of glia (astrocytes, oligodendrocytes, microglia), neurons, pericytes and endothelial cells, is a dynamic interface ensuring the physiological functioning of the central nervous system (CNS), which gets affected and contributes to the pathology of several neurodegenerative diseases. Neuroinflammation is a common feature of neurodegenerative diseases and is primarily related to the activation state of perivascular microglia and astrocytes, which constitute two of its major cellular components. Our studies focus on monitoring in real time the morphological changes of perivascular astrocytes and microglia, as well as their dynamic interactions with the brain vasculature, under physiological conditions and following systemic neuroinflammation triggering both microgliosis and astrogliosis. To this end, we performed 2-photon laser scanning microscopy (2P-LSM) for intravital imaging of the cortex of transgenic mice visualizing the dynamics of microglia and astroglia following neuroinflammation induced by systemic administration of the endotoxin lipopolysaccharide (LPS). Our results indicate that following neuroinflammation the endfeet of activated perivascular astrocytes lose their close proximity and physiological cross-talk with vasculature, an event that most possibly contributes to a loss of blood-brain barrier (BBB) integrity. At the same time, microglial cells become activated and exhibit a higher extent of physical contact with the blood vessels. These dynamic responses of perivascular astrocytes and microglia are peaking at 4 days following LPS administration; however, they still persist at a lower level at 8 days after LPS injection, revealing incomplete reversal of inflammation affecting the glial properties and interactions within the NVU.

Apical size and deltaA expression predict adult neural stem cell decisions along lineage progression.

The maintenance of neural stem cells (NSCs) in the adult brain depends on their activation frequency and division mode. Using long-term intravital imaging of NSCs in the zebrafish adult telencephalon, we reveal that apical surface area and expression of the Notch ligand DeltaA predict these NSC decisions. deltaA-negative NSCs constitute a bona fide self-renewing NSC pool and systematically engage in asymmetric divisions generating a self-renewing deltaAneg daughter, which regains the size and behavior of its mother, and a neurogenic deltaApos daughter, eventually engaged in neuronal production following further quiescence-division phases. Pharmacological and genetic manipulations of Notch, DeltaA, and apical size further show that the prediction of activation frequency by apical size and the asymmetric divisions of deltaAneg NSCs are functionally independent of Notch. These results provide dynamic qualitative and quantitative readouts of NSC lineage progression in vivo and support a hierarchical organization of NSCs in differently fated subpopulations.

HaloTag-based reporters for sparse labeling and cell tracking.

Multiscale analysis of morphogenesis requires to follow and measure in real-time the in vivo behaviour of large numbers of individual cells over long period of time. Despite recent progress, the large-scale automated tracking of cells in developing embryos and tissues remains a challenge. Here we describe a genetic tool for the random and sparse labelling of individual cells in developing Drosophila tissues. This tool is based on the conditional expression of a nuclear HaloTag protein that can be fluorescently labelled upon the irreversible binding of a cell permeable synthetic ligand. While the slow maturation of genetically encoded fluorescent renders the tracking of individual cells difficult in rapidly dividing tissues, nuclear HaloTag proteins allowed for rapid labelling of individual cells in cultured imaginal discs. To study cell shape changes, we also produced an HaloTag version of the actin-bound protein LifeAct. Since sparse labelling facilitates cell tracking, nuclear HaloTag reporters will be useful for the single-cell analysis of fate dynamics in Drosophila tissues cultured ex vivo.

GeNePy3D: a quantitative geometry python toolbox for bioimaging.

The advent of large-scale fluorescence and electronic microscopy techniques along with maturing image analysis is giving life sciences a deluge of geometrical objects in 2D/3D(+t) to deal with. These objects take the form of large scale, localised, precise, single cell, quantitative data such as cells' positions, shapes, trajectories or lineages, axon traces in whole brains atlases or varied intracellular protein localisations, often in multiple experimental conditions. The data mining of those geometrical objects requires a variety of mathematical and computational tools of diverse accessibility and complexity. Here we present a new Python library for quantitative 3D geometry called GeNePy3D which helps handle and mine information and knowledge from geometric data, providing a unified application programming interface (API) to methods from several domains including computational geometry, scale space methods or spatial statistics. By framing this library as generically as possible, and by linking it to as many state-of-the-art reference algorithms and projects as needed, we help render those often specialist methods accessible to a larger community. We exemplify the usefulness of the  GeNePy3D toolbox by re-analysing a recently published whole-brain zebrafish neuronal atlas, with other applications and examples available online. Along with an open source, documented and exemplified code, we release reusable containers to allow for convenient and wide usability and increased reproducibility.