Real-time volumetric microscopy of in vivo dynamics and large-scale samples with SCAPE 2.0.

The limited per-pixel bandwidth of most microscopy methods requires compromises between field of view, sampling density and imaging speed. This limitation constrains studies involving complex motion or fast cellular signaling, and presents a major bottleneck for high-throughput structural imaging. Here, we combine high-speed intensified camera technology with a versatile, reconfigurable and dramatically improved Swept, Confocally Aligned Planar Excitation (SCAPE) microscope design that can achieve high-resolution volumetric imaging at over 300 volumes per second and over 1.2 GHz pixel rates. We demonstrate near-isotropic sampling in freely moving Caenorhabditis elegans, and analyze real-time blood flow and calcium dynamics in the beating zebrafish heart. The same system also permits high-throughput structural imaging of mounted, intact, cleared and expanded samples. SCAPE 2.0's significantly lower photodamage compared to point-scanning techniques is also confirmed. Our results demonstrate that SCAPE 2.0 is a powerful, yet accessible imaging platform for myriad emerging high-speed dynamic and high-throughput volumetric microscopy applications.

Neuraminidase inhibition promotes the collective migration of neurons and recovery of brain function.

In the injured brain, new neurons produced from endogenous neural stem cells form chains and migrate to injured areas and contribute to the regeneration of lost neurons. However, this endogenous regenerative capacity of the brain has not yet been leveraged for the treatment of brain injury. Here, we show that in healthy brain chains of migrating new neurons maintain unexpectedly large non-adherent areas between neighboring cells, allowing for efficient migration. In instances of brain injury, neuraminidase reduces polysialic acid levels, which negatively regulates adhesion, leading to increased cell-cell adhesion and reduced migration efficiency. The administration of zanamivir, a neuraminidase inhibitor used for influenza treatment, promotes neuronal migration toward damaged regions, fosters neuronal regeneration, and facilitates functional recovery. Together, these findings shed light on a new mechanism governing efficient neuronal migration in the adult brain under physiological conditions, pinpoint the disruption of this mechanism during brain injury, and propose a promising therapeutic avenue for brain injury through drug repositioning.

Optical Control of Cell Signaling with Red/Far-Red Light-Responsive Optogenetic Tools in Caenorhabditis elegans.

Optogenetic techniques have been intensively applied to the nematode Caenorhabditis elegans to investigate its neural functions. However, as most of these optogenetics are responsive to blue light and the animal exhibits avoidance behavior to blue light, the application of optogenetic tools responsive to longer wavelength light has been eagerly anticipated. In this study, we report the implementation in C. elegans of a phytochrome-based optogenetic tool that responds to red/near-infrared light and manipulates cell signaling. We first introduced the SynPCB system, which enabled us to synthesize phycocyanobilin (PCB), a chromophore for phytochrome, and confirmed the biosynthesis of PCB in neurons, muscles, and intestinal cells. We further confirmed that the amount of PCBs synthesized by the SynPCB system was sufficient for photoswitching of phytochrome B (PhyB)-phytochrome interacting factor 3 (PIF3). In addition, optogenetic elevation of intracellular Ca2+ levels in intestinal cells induced a defecation motor program. These SynPCB system and phytochrome-based optogenetic techniques would be of great value in elucidating the molecular mechanisms underlying C. elegans behaviors.

Seg2Link: an efficient and versatile solution for semi-automatic cell segmentation in 3D image stacks.

Recent advances in microscopy techniques, especially in electron microscopy, are transforming biomedical studies by acquiring large quantities of high-precision 3D cell image stacks. To examine cell morphology and connectivity in organs such as the brain, scientists need to conduct cell segmentation, which extracts individual cell regions of different shapes and sizes from a 3D image. This is challenging due to the indistinct images often encountered in real biomedical research: in many cases, automatic segmentation methods inevitably contain numerous mistakes in the segmentation results, even when using advanced deep learning methods. To analyze 3D cell images effectively, a semi-automated software solution is needed that combines powerful deep learning techniques with the ability to perform post-processing, generate accurate segmentations, and incorporate manual corrections. To address this gap, we developed Seg2Link, which takes deep learning predictions as inputs and use watershed 2D + cross-slice linking to generate more accurate automatic segmentations than previous methods. Additionally, it provides various manual correction tools essential for correcting mistakes in 3D segmentation results. Moreover, our software has been optimized for efficiently processing large 3D images in diverse organisms. Thus, Seg2Link offers an practical solution for scientists to study cell morphology and connectivity in 3D image stacks.

Electric shock causes a fleeing-like persistent behavioral response in the nematode Caenorhabditis elegans.

Behavioral persistency reflects internal brain states, which are the foundations of multiple brain functions. However, experimental paradigms enabling genetic analyses of behavioral persistency and its associated brain functions have been limited. Here, we report novel persistent behavioral responses caused by electric stimuli in the nematode Caenorhabditis elegans. When the animals on bacterial food are stimulated by alternating current, their movement speed suddenly increases 2- to 3-fold, persisting for more than 1 minute even after a 5-second stimulation. Genetic analyses reveal that voltage-gated channels in the neurons are required for the response, possibly as the sensors, and neuropeptide signaling regulates the duration of the persistent response. Additional behavioral analyses implicate that the animal's response to electric shock is scalable and has a negative valence. These properties, along with persistence, have been recently regarded as essential features of emotion, suggesting that C. elegans response to electric shock may reflect a form of emotion, akin to fear.

Neural mechanism of experience-dependent sensory gain control in C. elegans.

Animals' sensory systems adjust their responsiveness to environmental stimuli that vary greatly in their intensity. Here we report the neural mechanism of experience-dependent sensory adjustment, especially gain control, in the ASH nociceptive neurons in Caenorhabditis elegans. Using calcium imaging under gradual changes in stimulus intensity, we find that the ASH neurons of naive animals respond to concentration increases in a repulsive odor 2-nonanone regardless of the magnitude of the concentration increase. However, after preexposure to the odor, the ASH neurons exhibit significantly weak responses to a small gradual increase in odor concentration while their responses to a large gradual increase remain strong. Thus, preexposure changes the slope of stimulus-response relationships (i.e., gain control). Behavioral analysis suggests that this gain control contributes to the preexposure-dependent enhancement of odor avoidance behavior. Mathematical analysis reveals that the ASH response consists of fast and slow components, and that the fast component is specifically suppressed by preexposure for the gain control. In addition, genetic analysis suggests that G protein signaling may be required for the regulation of fast component. We propose how prior experience dynamically and specifically modulates stimulus-response relationships in sensory neurons, eventually leading to adaptive modulation of behavior.

Ultradian rhythm in the intestine of Caenorhabditis elegans is controlled by the C-terminal region of the FLR-1 ion channel and the hydrophobic domain of the FLR-4 protein kinase.

Defecation behavior in Caenorhabditis elegans is driven by an endogenous ultradian clock in the intestine. Its periods are positively regulated by FLR-1, an ion channel of the epithelial sodium channel/degenerin superfamily, and FLR-4, a protein kinase with a hydrophobic domain at the carboxyl terminus. FLR-1 has many putative phosphorylation sites in the C-terminal intracellular region. This structure implies that the periods may be regulated by the phosphorylation of FLR-1 by FLR-4, but it remains to be clarified. Here, we show that a truncated FLR-1 lacking the C-terminal intracellular region resulted in longer periods, suggesting that this region is involved in the negative regulation of defecation cycle periods. Contrary to our expectation, FLR-4 was still necessary for the function of the truncated FLR-1. Furthermore, FLR-4 containing a kinase-dead mutation or lacking the whole kinase domain was sufficient for normal defecation cycle periods. FLR-4 was necessary for the stable expression of FLR-1::GFP, and its hydrophobic domain was sufficient also for this function. FLR-1 and FLR-4 are often colocalized in the plasma membrane. These data showed an unexpected role of FLR-4: its hydrophobic domain stabilizes the FLR-1 ion channel, a key regulator of defecation cycle periods in the intestine.

Tracking Moving Cells in 3D Time Lapse Images Using 3DeeCellTracker.

Recent advancements in 3D microscopy have enabled scientists to monitor signals of multiple cells in various animals/organs. However, segmenting and tracking the moving cells in three-dimensional time-lapse images (3D + T images), to extract their dynamic positions and activities, remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline called 3DeeCellTracker, which precisely tracks cells with large movements in 3D + T images, obtained from different animals or organs, using highly divergent optical systems. In this protocol, we explain how to set up the computational environment, the required data, and the procedures to segment and track cells with 3DeeCellTracker. Our protocol will help scientists to analyze cell activities/movements in 3D + T image datasets that have been difficult to analyze. Graphic abstract: The flowchart illustrating how to use 3DeeCellTracker. See the Equipment and Procedure sections for detailed explanations.

Enhancement of odor avoidance regulated by dopamine signaling in Caenorhabditis elegans.

The enhancement of sensory responses after prior exposure to a stimulus is a fundamental mechanism of neural function in animals. Its molecular basis, however, has not been studied in as much depth as the reduction of sensory responses, such as adaptation or habituation. We report here that the avoidance behavior of the nematode Caenorhabditis elegans in response to repellent odors (2-nonanone or 1-octanol) is enhanced rather than reduced after preexposure to the odors. This enhancement effect of preexposure was maintained for at least 1 h after the conditioning. The enhancement of 2-nonanone avoidance was not dependent on the presence or absence of food during conditioning, which generally functions as a strong positive or negative unconditioned stimulus in the animals. These results suggest that the enhancement is acquired as a type of nonassociative learning. In addition, genetic and pharmacological analyses revealed that the enhancement of 2-nonanone avoidance requires dopamine signaling via D(2)-like dopamine receptor DOP-3, which functions in a pair of RIC interneurons to regulate the enhancement. Because dopamine signaling has been tightly linked with food-related information to modulate various behaviors of C. elegans, it may play different role in the regulation of the enhancement of 2-nonanone avoidance. Thus, our data suggest a new genetic and pharmacological paradigm for nonassociative enhancement of neural responses that is regulated by dopamine signaling.

Calcium Imaging of Neuronal Activity under Gradually Changing Odor Stimulation in Caenorhabditis elegans.

Olfactory behavior is among the most fundamental animal behaviors both in the wild and in the laboratory. To elucidate the neural mechanisms underlying olfactory behavior, it is critical to measure neural responses to odorant concentration changes resembling those that animals actually sense during olfactory behavior. However, reproducing the dynamically changing olfactory stimuli to an animal during such measurements of neural activity is technically challenging. Here, we describe technical details and protocols for odor stimulation during calcium imaging of the sensory neurons of the nematode Caenorhabditis elegans. In this system, the neuronal activity of C. elegans is measured using ratiometric calcium imaging during exposure to quantitatively controlled olfactory stimuli over time. Temporal changes in odor concentrations around the animal are precisely controlled according to a predesigned temporal odor gradient to reproduce a realistic odor concentration change during olfactory behavior in a behavioral arena. By monitoring neural activity in response to the realistic olfactory stimulus, it is possible to elucidate the mechanisms by which olfactory input is processed by neural activities and reflected in behavioral output.

Cross-species behavior analysis with attention-based domain-adversarial deep neural networks.

Since the variables inherent to various diseases cannot be controlled directly in humans, behavioral dysfunctions have been examined in model organisms, leading to better understanding their underlying mechanisms. However, because the spatial and temporal scales of animal locomotion vary widely among species, conventional statistical analyses cannot be used to discover knowledge from the locomotion data. We propose a procedure to automatically discover locomotion features shared among animal species by means of domain-adversarial deep neural networks. Our neural network is equipped with a function which explains the meaning of segments of locomotion where the cross-species features are hidden by incorporating an attention mechanism into the neural network, regarded as a black box. It enables us to formulate a human-interpretable rule about the cross-species locomotion feature and validate it using statistical tests. We demonstrate the versatility of this procedure by identifying locomotion features shared across different species with dopamine deficiency, namely humans, mice, and worms, despite their evolutionary differences.

3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.

Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.

Microscopes have been used to decrypt the tiny details of life since the 17th century. Now, the advent of 3D microscopy allows scientists to build up detailed pictures of living cells and tissues. In that effort, automation is becoming increasingly important so that scientists can analyze the resulting images and understand how bodies grow, heal and respond to changes such as drug therapies. In particular, algorithms can help to spot cells in the picture (called cell segmentation), and then to follow these cells over time across multiple images (known as cell tracking). However, performing these analyses on 3D images over a given period has been quite challenging. In addition, the algorithms that have already been created are often not user-friendly, and they can only be applied to a specific dataset gathered through a particular scientific method. As a response, Wen et al. developed a new program called 3DeeCellTracker, which runs on a desktop computer and uses a type of artificial intelligence known as deep learning to produce consistent results. Crucially, 3DeeCellTracker can be used to analyze various types of images taken using different types of cutting-edge microscope systems. And indeed, the algorithm was then harnessed to track the activity of nerve cells in moving microscopic worms, of beating heart cells in a young small fish, and of cancer cells grown in the lab. This versatile tool can now be used across biology, medical research and drug development to help monitor cell activities.

FLR-2, the glycoprotein hormone alpha subunit, is involved in the neural control of intestinal functions in Caenorhabditis elegans.

The intestine plays an essential role in organism-wide regulatory networks in both vertebrates and invertebrates. In Caenorhabditis elegans, class 1 flr genes (flr-1, flr-3 and flr-4) act in the intestine and control growth rates and defecation cycle periods, while class 2 flr genes (flr-2, flr-5, flr-6 and flr-7) are characterized by mutations that suppress the slow growth of class 1 flr mutants. This study revealed that flr-2 gene controls antibacterial defense and intestinal color, confirming that flr-2 regulates intestinal functions. flr-2 encoded the only glycoprotein hormone alpha subunit in C. elegans and was expressed in certain neurons. Furthermore, FLR-2 bound to another secretory protein GHI-1, which belongs to a family of lipid- and lipopolysaccharide-binding proteins. A ghi-1 deletion mutation partially suppressed the short defecation cycle periods of class 1 flr mutants, and this effect was enhanced by flr-2 mutations. Thus, FLR-2 acts as a signaling molecule for the neural control of intestinal functions, which is achieved in a functional network involving class 1 and class 2 flr genes as well as ghi-1. These results are informative to studies of glycoprotein hormone signaling in higher animals.

Deep learning-assisted comparative analysis of animal trajectories with DeepHL.

A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficult for them to contrast group differences manually. This study introduces DeepHL, a deep learning-assisted platform for the comparative analysis of animal movement data, i.e., trajectories. This software uses a deep neural network based on an attention mechanism to automatically detect segments in trajectories that are characteristic of one group. It then highlights these segments in visualized trajectories, enabling biologists to focus on these segments, and helps them reveal the underlying meaning of the highlighted segments to facilitate formulating new hypotheses. We tested the platform on a variety of trajectories of worms, insects, mice, bears, and seabirds across a scale from millimeters to hundreds of kilometers, revealing new movement features of these animals.

Neuronal, mathematical, and molecular bases of perceptual decision-making in C. elegans.

Animals process sensory information from the environment to make behavioral decisions. Although environmental information may be ambiguous or gradually changing, animals can still choose one behavioral option among several through perceptual decision-making. Perceptual decision-making has been intensively studied in primates and rodents, and neural activity that accumulates sensory information has been shown to be crucial. However, it remains unclear how the accumulating neural activity is generated, and whether such activity is a conserved decision-making strategy across the animal kingdom. Here, we review the previous perceptual decision-making studies in vertebrates and invertebrates and our recent achievement in an invertebrate model animal, the nematode Caenorhabditis elegans. In the study, we analyzed temporal dynamics of neuronal activity during perceptual decision-making in navigational behavior of C. elegans. We identified neural activity that accumulates sensory information and elucidated the molecular mechanism for the accumulating activity, which may be relevant to decision-making across the animal kingdom.

STEFTR: A Hybrid Versatile Method for State Estimation and Feature Extraction From the Trajectory of Animal Behavior.

Animal behavior is the final and integrated output of brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient prior knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach for behavioral state estimation and feature extraction (STEFTR) only from low-content animal trajectory data. To demonstrate the effectiveness of the proposed method, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales-from mm to 1,000 km in space and from sub-seconds to days in time. We successfully estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.

FLR-4, a novel serine/threonine protein kinase, regulates defecation rhythm in Caenorhabditis elegans.

The defecation behavior of the nematode Caenorhabditis elegans is controlled by a 45-s ultradian rhythm. An essential component of the clock that regulates the rhythm is the inositol trisphosphate receptor in the intestine, but other components remain to be discovered. Here, we show that the flr-4 gene, whose mutants exhibit very short defecation cycle periods, encodes a novel serine/threonine protein kinase with a carboxyl terminal hydrophobic region. The expression of functional flr-4::GFP was detected in the intestine, part of pharyngeal muscles and a pair of neurons, but expression of flr-4 in the intestine was sufficient for the wild-type phenotype. Furthermore, laser killing of the flr-4-expressing neurons did not change the defecation phenotypes of wild-type and flr-4 mutant animals. Temperature-shift experiments with a temperature-sensitive flr-4 mutant suggested that FLR-4 acts in a cell-functional rather than developmental aspect in the regulation of defecation rhythms. The function of FLR-4 was impaired by missense mutations in the kinase domain and near the hydrophobic region, where the latter allele seemed to be a weak antimorph. Thus, a novel protein kinase with a unique structural feature acts in the intestine to increase the length of defecation cycle periods.

Measuring Spatiotemporal Dynamics of Odor Gradient for Small Animals by Gas Chromatography.

Odor is the most fundamental chemical stimulus that delivers information regarding food, mating partners, enemies, and danger in the surrounding environment. Research on odor response in animals is widespread, although studies on experimental systems in which the gradient of odor concentration is quantitatively measured has been quite limited. Here, we describe a method for measuring a gradient of odor concentration established by volatilization and diffusion in a relatively small enclosed space, which has been used widely in laboratories to analyze small model animals such as the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster. We first vaporized known amounts of a liquid odorant 2-nonanone in a tank and subjected them to gas chromatographic analysis to obtain a calibration curve. Then, we aspirated a small amount of gas phase from a small hole on an agar plate and measured the odor concentration. By repeating this at different spatial and temporal points, we were able to detect a gradient of the odor concentration that increased over time. Furthermore, by applying these measured values to mathematical models of volatilization and diffusion, we were able to visualize an estimated dynamic change in odor concentration over an agar plate. Combining monitoring of odor concentration change in an agar plate with behavioral monitoring by machine vision will allow us to estimate how the brain computes information regarding odor concentration change in order to regulate behavior.

The C. elegans thermosensory neuron AFD responds to warming.

The mechanism of temperature sensation is far less understood than the sensory response to other environmental stimuli such as light, odor, and taste. Thermotaxis behavior in C. elegans requires the ability to discriminate temperature differences as small as approximately 0.05 degrees C and to memorize the previously cultivated temperature. The AFD neuron is the only major thermosensory neuron required for the thermotaxis behavior. Genetic analyses have revealed several signal transduction molecules that are required for the sensation and/or memory of temperature information in the AFD neuron, but its physiological properties, such as its ability to sense absolute temperature or temperature change, have been unclear. We show here that the AFD neuron responds to warming. Calcium concentration in the cell body of AFD neuron is increased transiently in response to warming, but not to absolute temperature or to cooling. The transient response requires the activity of the TAX-4 cGMP-gated cation channel, which plays an essential role in the function of the AFD neuron. Interestingly, the AFD neuron further responds to step-like warming above a threshold that is set by temperature memory. We suggest that C. elegans provides an ideal model to genetically and physiologically reveal the molecular mechanism for sensation and memory of temperature information.

Calcium dynamics regulating the timing of decision-making in C. elegans.

Brains regulate behavioral responses with distinct timings. Here we investigate the cellular and molecular mechanisms underlying the timing of decision-making during olfactory navigation in Caenorhabditis elegans. We find that, based on subtle changes in odor concentrations, the animals appear to choose the appropriate migratory direction from multiple trials as a form of behavioral decision-making. Through optophysiological, mathematical and genetic analyses of neural activity under virtual odor gradients, we further find that odor concentration information is temporally integrated for a decision by a gradual increase in intracellular calcium concentration ([Ca2+]i), which occurs via L-type voltage-gated calcium channels in a pair of olfactory neurons. In contrast, for a reflex-like behavioral response, [Ca2+]i rapidly increases via multiple types of calcium channels in a pair of nociceptive neurons. Thus, the timing of neuronal responses is determined by cell type-dependent involvement of calcium channels, which may serve as a cellular basis for decision-making.