The C. elegans Thermosensory Neuron AFD Responds to Warming

AbstractThe 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 ∼0.05°C and to memorize the previously cultivated temperature [1, 2]. The AFD neuron is the only major thermosensory neuron required for the thermotaxis behavior [3]. Genetic analyses have revealed several signal transduction molecules that are required for the sensation and/or memory of temperature information in the AFD neuron [4–7], 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 [5]. 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 <i>C. elegans</i>

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

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

Abstract 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

Genetic Control of Temperature Preference in the Nematode Caenorhabditis elegans

Animals modify behavioral outputs in response to environmental changes. C. elegans exhibits thermotaxis, where well-fed animals show attraction to their cultivation temperature on a thermal gradient without food. We show here that feeding-state-dependent modulation of thermotaxis is a powerful behavioral paradigm for elucidating the mechanism underlying neural plasticity, learning, and memory in higher animals. Starved experience alone could induce aversive response to cultivation temperature. Changing both cultivation temperature and feeding state simultaneously evoked transient attraction to or aversion to the previous cultivation temperature: recultivation of starved animals with food immediately induced attraction to the temperature associated with starvation, although the animals eventually exhibited thermotaxis to the new temperature associated with food. These results suggest that the change in feeding state quickly stimulates the switch between attraction and aversion for the temperature in memory and that the acquisition of new temperature memory establishes more slowly. We isolated aho (abnormal hunger orientation) mutants that are defective in starvation-induced cultivation-temperature avoidance. Some aho mutants responded normally to changes in feeding state with respect to locomotory activity, implying that the primary thermosensation followed by temperature memory formation remains normal and the modulatory aspect of thermotaxis is specifically impaired in these mutants

Insulin-like signaling and the neural circuit for integrative behavior in C. elegans

Caenorhabditis elegans exhibits a food-associated behavior that is modulated by the past cultivation temperature. Mutations in INS-1, the homolog of human insulin, caused the defect in this integrative behavior. Mutations in DAF-2/insulin receptor and AGE-1/phosphatidylinositol 3 (PI-3)-kinase partially suppressed the defect of ins-1 mutants, and a mutation in DAF-16, a forkhead-type transcriptional factor, caused a weak defect. In addition, mutations in the secretory protein HEN-1 showed synergistic effects with INS-1. Expression of AGE-1 in any of the three interneurons, AIY, AIZ, or RIA, rescued the defect characteristic of age-1 mutants. Calcium imaging revealed that starvation induced INS-1-mediated down-regulation of AIZ activity. Our results suggest that INS-1, in cooperation with HEN-1, antagonizes the DAF-2 insulin-like signaling pathway to modulate interneuron activity required for food-associated integrative behavior

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

Data from: 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

Deep learning-assisted comparative analysis of animal trajectories with DeepHL

Comparative analysis of animal behaviour using locomotion data such as GPS data is difficult because the large amount of data makes it difficult to contrast group differences. Here the authors apply deep learning to detect and highlight trajectories characteristic of a group across scales of millimetres to hundreds of kilometres