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.

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.

Many animals, including insects, are known to use visual landmarks to orient in their environment. In Drosophila melanogaster, behavioural genetics studies have identified a higher brain structure called the central complex as being required for the fly’s innate responses to vertical visual features and its short- and long-term memory for visual patterns. But whether and how neurons of the fly central complex represent visual features are unknown. Here we use two-photon calcium imaging in head-fixed walking and flying flies to probe visuomotor responses of ring neurons—a class of central complex neurons that have been implicated in landmark-driven spatial memory in walking flies and memory for visual patterns in tethered flying flies. We show that dendrites of ring neurons are visually responsive and arranged retinotopically. Ring neuron receptive fields comprise both excitatory and inhibitory subfields, resembling those of simple cells in the mammalian primary visual cortex. Ring neurons show strong and, in some cases, direction-selective orientation tuning, with a notable preference for vertically oriented features similar to those that evoke innate responses in flies. Visual responses were diminished during flight, but, in contrast with the hypothesized role of the central complex in the control of locomotion, not modulated during walking. Taken together, these results indicate that ring neurons represent behaviourally relevant visual features in the fly’s environment, enabling downstream central complex circuits to produce appropriate motor commands. More broadly, this study opens the door to mechanistic investigations of circuit computations underlying visually guided action selection in the Drosophila central complex.

Animals rely on dedicated sensory circuits to extract and encode environmental features. How individual neurons integrate and translate these features into behavioral responses remains a major question. Here, we identify a visual projection neuron type that conveys predator approach information to the Drosophila giant fiber (GF) escape circuit. Genetic removal of this input during looming stimuli reveals that it encodes angular expansion velocity, whereas other input cell type(s) encode angular size. Motor program selection and timing emerge from linear integration of these two features within the GF. Linear integration improves size detection invariance over prior models and appropriately biases motor selection to rapid, GF-mediated escapes during fast looms. Our findings suggest feature integration, and motor control may occur as simultaneous operations within the same neuron and establish the Drosophila escape circuit as a model system in which these computations may be further dissected at the circuit level.

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us to select a compact set of superior features at very low cost. We perform extensive experimental comparison of our algorithm and other methods using three different classifiers (naive Bayes, support vector machine, and linear discriminate analysis) and four different data sets (handwritten digits, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.

During courtship males attract females with elaborate behaviors. In mice, these displays include ultrasonic vocalizations. Ultrasonic courtship vocalizations were previously attributed to the courting male, despite evidence that both sexes produce virtually indistinguishable vocalizations. Because of this similarity, and the difficulty of assigning vocalizations to individuals, the vocal contribution of each individual during courtship is unknown. To address this question, we developed a microphone array system to localize vocalizations from socially interacting, individual adult mice. With this system, we show that female mice vocally interact with males during courtship. Males and females jointly increased their vocalization rates during chases. Furthermore, a female's participation in these vocal interactions may function as a signal that indicates a state of increased receptivity. Our results reveal a novel form of vocal communication during mouse courtship, and lay the groundwork for a mechanistic dissection of communication during social behavior.

The formation of complex but highly organized neural circuits requires interactions between neurons and glia. During the assembly of the olfactory circuit, 50 olfactory receptor neuron (ORN) classes and 50 projection neuron (PN) classes form synaptic connections in 50 glomerular compartments in the antennal lobe, each of which represents a discrete olfactory information-processing channel. Each compartment is separated from the adjacent compartments by membranous processes from ensheathing glia. Here we show that Thisbe, an FGF released from olfactory neurons, particularly from local interneurons, instructs ensheathing glia to wrap each glomerulus. The Heartless FGF receptor acts cell-autonomously in ensheathing glia to regulate process extension so as to insulate each neuropil compartment. Overexpressing Thisbe in ORNs or PNs causes overwrapping of the glomeruli their axons or dendrites target. Failure to establish the FGF-dependent glia structure disrupts precise ORN axon targeting and discrete glomerular formation.

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.