Gap junctions (GJs) represent connexin-rich membrane domains that connect interiors of adjoining cells in mammalian tissues. How fast GJs can respond to bacterial pathogens has not been known previously. Using Bessel beam plane illumination and confocal spinning disk microscopy, we found fast ( 500 ms) formation of connexin-depleted regions (CDRs) inside GJ plaques between cells exposed to AB5 toxins. CDR formation appears as a fast redistribution of connexin channels within GJ plaques with minor changes in outline or geometry. CDR formation does not depend on membrane trafficking or submembrane cytoskeleton and has no effect on GJ conductance. However, CDR responses depend on membrane lipids, can be modified by cholesterol-clustering agents and extracellular K(+) ion concentration, and influence cAMP signaling. The CDR response of GJ plaques to bacterial toxins is a phenomenon observed for all tested connexin isoforms. Through signaling, the CDR response may enable cells to sense exposure to AB5 toxins. CDR formation may reflect lipid-phase separation events in the biological membrane of the GJ plaque, leading to increased connexin packing and lipid reorganization. Our data demonstrate very fast dynamics (in the millisecond-to-second range) within GJ plaques, which previously were considered to be relatively stable, long-lived structures.

Gap junctions (GJs) represent connexin-rich membrane domains that connect interiors of adjoining cells in mammalian tissues. How fast GJs can respond to bacterial pathogens has not been known previously. Using Bessel beam plane illumination and confocal spinning disk microscopy, we found fast (~500 ms) formation of connexin-depleted regions (CDRs) inside GJ plaques between cells exposed to AB5 toxins. CDR formation appears as a fast redistribution of connexin channels within GJ plaques with minor changes in outline or geometry. CDR formation does not depend on membrane trafficking or submembrane cytoskeleton and has no effect on GJ conductance. However, CDR responses depend on membrane lipids, can be modified by cholesterol-clustering agents and extracellular K(+) ion concentration, and influence cAMP signaling. The CDR response of GJ plaques to bacterial toxins is a phenomenon observed for all tested connexin isoforms. Through signaling, the CDR response may enable cells to sense exposure to AB5 toxins. CDR formation may reflect lipid-phase separation events in the biological membrane of the GJ plaque, leading to increased connexin packing and lipid reorganization. Our data demonstrate very fast dynamics (in the millisecond-to-second range) within GJ plaques, which previously were considered to be relatively stable, long-lived structures.

Cortical information processing is under state-dependent control of subcortical neuromodulatory systems. Although this modulatory effect is thought to be mediated mainly by slow nonsynaptic metabotropic receptors, other mechanisms, such as direct synaptic transmission, are possible. Yet, it is currently unknown if any such form of subcortical control exists. Here, we present direct evidence of a strong, spatiotemporally precise excitatory input from an ascending neuromodulatory center. Selective stimulation of serotonergic median raphe neurons produced a rapid activation of hippocampal interneurons. At the network level, this subcortical drive was manifested as a pattern of effective disynaptic GABAergic inhibition that spread throughout the circuit. This form of subcortical network regulation should be incorporated into current concepts of normal and pathological cortical function.

The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (i) generality by reconstructing cell lineages in four-dimensional, terabyte-sized image data sets of fruit fly, zebrafish and mouse embryos acquired with three types of fluorescence microscopes, (ii) scalability by analyzing advanced stages of development with up to 20,000 cells per time point at 26,000 cells min(-1) on a single computer workstation and (iii) ease of use by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities. Using our system, we performed the first cell lineage reconstruction of early Drosophila melanogaster nervous system development, revealing neuroblast dynamics throughout an entire embryo.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful patterns embedded within complex and rich data sources. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a range of biosensors (calcium, norepinephrine, ATP, acetylcholine, dopamine), cell types (astrocytes, oligodendrocytes, microglia, neurons), organs (brains and spinal cords), animal models (zebrafish and mouse), and imaging modalities (confocal, two-photon, light sheet). As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce activity quantification and analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine-learning techniques. It decomposes complex live-imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, microscopy techniques, and imaging approaches. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, as well as distinct sensorimotor signal propagation patterns in the mouse spinal cord.

Preprint: https://doi.org/10.1101/2024.05.02.592259

Recording light-microscopy images of large, nontransparent specimens, such as developing multicellular organisms, is complicated by decreased contrast resulting from light scattering. Early zebrafish development can be captured by standard light-sheet microscopy, but new imaging strategies are required to obtain high-quality data of late development or of less transparent organisms. We combined digital scanned laser light-sheet fluorescence microscopy with incoherent structured-illumination microscopy (DSLM-SI) and created structured-illumination patterns with continuously adjustable frequencies. Our method discriminates the specimen-related scattered background from signal fluorescence, thereby removing out-of-focus light and optimizing the contrast of in-focus structures. DSLM-SI provides rapid control of the illumination pattern, exceptional imaging quality, and high imaging speeds. We performed long-term imaging of zebrafish development for 58 h and fast multiple-view imaging of early Drosophila melanogaster development. We reconstructed cell positions over time from the Drosophila DSLM-SI data and created a fly digital embryo.

Understanding genetic and cellular bases of adult form remains a fundamental goal at the intersection of developmental and evolutionary biology. The skin pigment cells of vertebrates, derived from embryonic neural crest, are a useful system for elucidating mechanisms of fate specification, pattern formation, and how particular phenotypes impact organismal behavior and ecology. In a survey of fishes, including the zebrafish , we identified two populations of white pigment cells-leucophores-one of which arises by transdifferentiation of adult melanophores and another of which develops from a yellow-orange xanthophore or xanthophore-like progenitor. Single-cell transcriptomic, mutational, chemical, and ultrastructural analyses of zebrafish leucophores revealed cell-type-specific chemical compositions, organelle configurations, and genetic requirements. At the organismal level, we identified distinct physiological responses of leucophores during environmental background matching, and we showed that leucophore complement influences behavior. Together, our studies reveal independently arisen pigment cell types and mechanisms of fate acquisition in zebrafish and illustrate how concerted analyses across hierarchical levels can provide insights into phenotypes and their evolution.

Fatty acids (FAs) provide cellular energy under starvation, yet how they mobilize and move into mitochondria in starved cells, driving oxidative respiration, is unclear. Here, we clarify this process by visualizing FA trafficking with a fluorescent FA probe. The labeled FA accumulated in lipid droplets (LDs) in well-fed cells but moved from LDs into mitochondria when cells were starved. Autophagy in starved cells replenished LDs with FAs, increasing LD number over time. Cytoplasmic lipases removed FAs from LDs, enabling their transfer into mitochondria. This required mitochondria to be highly fused and localized near LDs. When mitochondrial fusion was prevented in starved cells, FAs neither homogeneously distributed within mitochondria nor became efficiently metabolized. Instead, FAs reassociated with LDs and fluxed into neighboring cells. Thus, FAs engage in complex trafficking itineraries regulated by cytoplasmic lipases, autophagy, and mitochondrial fusion dynamics, ensuring maximum oxidative metabolism and avoidance of FA toxicity in starved cells.