Biology subjects

Iino, Y.

Publications and source records attributed to Iino, Y..

15 recordsLinked to original sources

bioRxiv2026

SIK3 links synaptic strength to sleep pressure through RhoA signaling

Sleep is regulated by homeostatic sleep pressure, which accumulates during wakefulness, triggering sleep, and dissipates during sleep, leading to wakefulness. Although recent evidence suggests that synaptic potentiation encodes sleep pressure, the intracellular mechanisms linking synaptic strength to sleep pressure remain unclear. Here we demonstrate that the sleep-promoting kinase SIK3 links synaptic strength and sleep pressure through RhoA signalling. We found that SIK3 is required for dendritic spine enlargement induced by chemical long-term potentiation (cLTP) in cultured cortical pyramidal neurons and positively regulates spine size in the prefrontal cortex in vivo. cLTP reduced RhoA activity in an SIK3-dependent manner during spine enlargement, whereas activation of RhoA reduced EEG delta density in vivo during non-rapid eye movement sleep (NREMS), an indicator of sleep pressure. SIK3 substrate screening identified several RhoA regulators including GEF-H1, and further biochemical analyses found that phosphorylation by SIK3 activates GEF-H1. However, contrary to our expectation, RhoA facilitation through pharmacological activation of GEF-H1 enlarged spine size in cultured neurons, and expression of constitutively active GEF-H1 increased NREMS delta density in a RhoA-dependent fashion. Together, these results indicate that SIK3 enlarges spine size and enhances NREMS delta density through two RhoA-dependent pathways, driving mutually opposing intermediate phenotypes. Our findings identify two clashing SIK3-RhoA signalling pathways that couple synaptic regulation to sleep homeostasis.

neuroscience↗

bioRxiv2026

Reactivating a schizophrenia risk gene-enriched prefrontal ensemble suppresses decision noise

Schizophrenia genetics and single-cell transcriptomics implicate prefrontal excitatory neurons and synaptic programs, but how these vulnerabilities alter circuit dynamics, behavior, and pharmacological targetability remains unclear. We identify a clozapine-responsive prefrontal ensemble enriched for schizophrenia risk genes that stabilizes value-guided choice. NMDA receptor hypofunction increased value-independent decision noise and weakened the ensembles pre-choice transient, while clozapine rescued both. Chemogenetic inhibition of the ensemble increased decision noise, demonstrating causality. By integrating receptor affinities with mouse and human single-cell transcriptomes, we designed a rational multi-receptor antagonist cocktail that reactivated the ensemble and rescued decision noise without increasing NREM sleep time or NREM delta power, in contrast to clozapine. These findings link schizophrenia genetics to cortical ensemble dynamics and establish ensemble-targeted pharmacology as a strategy for ameliorating pathological computations. One-Sentence SummaryTargeting a schizophrenia risk gene-enriched prefrontal ensemble suppresses decision noise without clozapine-like sedation.

neuroscience↗

bioRxiv2026

Image-scanning light-sheet microscopy for high-speed volumetric imaging of complex biological dynamics

Volumetric fluorescence microscopy is a powerful method for studying complex biological systems because it enables comprehensive observation of structural and physiological dynamics. In particular, light-sheet microscopy (LSM) is a leading option for real-time volumetric fluorescence imaging as it combines high imaging speed, low phototoxicity, minimal photobleaching, high spatiotemporal resolution, and low computational burden. To capture fast biological events, various efforts have been made to improve the imaging speed of volumetric fluorescence microscopy, including LSM. However, existing approaches entail significant trade-offs that make routine volumetric imaging at and beyond video rates challenging under practical conditions. Here, we introduce image-scanning LSM, a method that substantially increases the volumetric imaging speed achievable with LSM while preserving key performance metrics, such as spatial resolution and photon efficiency, as well as accessibility. Our implementation, termed image-scanning oblique plane (ISOP) microscopy, enables volumetric fluorescence imaging at up to 1,000 volumes per second with submicrometer lateral spatial resolution. We demonstrate the broad utility of ISOP microscopy by recording and analyzing the dynamics of behaving and rapidly moving organisms.

bioengineering↗

bioRxiv2025

Noradrenaline and microglia maintain plasticity-rigidity balance to safeguard rapid emotional learning in the prefrontal cortex

Synaptic plasticity is governed by rules that determine how patterns of neural activity are converted into changes in synaptic weights. While neocortical plasticity rules appear to shift from Hebbian to three-factor forms during development, the cellular mechanisms underlying this transition remain unclear. Here, we show that microglia mediate the developmental transition of plasticity rules at individual dendritic spines in the medial prefrontal cortex (mPFC) during juvenile-to-adolescent maturation. After maturation, microglia suppressed Hebbian activity-induced spine enlargement via a humoral factor. This suppression was relieved by noradrenaline through microglia-intrinsic cAMP signaling, thereby enabling a three-factor rule for gating plasticity. The adolescent mPFC required three-factor plasticity signaling for the acquisition of socially learned fear. Local microglial ablation enhanced learning efficiency but also altered pain sensitivity in a learning-dependent manner, suggesting that microglial suppression safeguards pre-existing emotional circuits. Together, these findings identify microglia as critical regulators of developmental plasticity-rule transitions in the mPFC.

neuroscience↗

bioRxiv2024

CGC1, a new reference genome for Caenorhabditis elegans

The original 100.3 Mb reference genome for Caenorhabditis elegans, generated from the wild-type laboratory strain N2, has been crucial for analysis of C. elegans since 1998 and has been considered complete since 2005. Unexpectedly, this long-standing reference was shown to be incomplete in 2019 by a genome assembly from the N2-derived strain VC2010. Moreover, genetically divergent versions of N2 have arisen over decades of research and hindered reproducibility of C. elegans genetics and genomics. Here we provide a 106.4 Mb gap-free, telomere-to-telomere genome assembly of C. elegans, generated from CGC1, an isogenic derivative of the N2 strain. We used improved long-read sequencing and manual assembly of 43 recalcitrant genomic regions to overcome deficiencies of prior N2 and VC2010 assemblies, and to assemble tandem repeat loci including a 772-kb sequence for the 45S rRNA genes. While many differences from earlier assemblies came from repeat regions, unique additions to the genome were also found. Of 19,972 protein-coding genes in the N2 assembly, 19,790 (99.1%) encode products that are unchanged in the CGC1 assembly. The CGC1 assembly also may encode 183 new protein-coding and 163 new ncRNA genes. CGC1 thus provides both a completely defined reference genome and corresponding isogenic wild-type strain for C. elegans, allowing unique opportunities for model and systems biology.

genomics↗

bioRxiv2023

WormTracer: A precise method for worm posture analysis using temporal continuity

This study introduces WormTracer, a novel algorithm designed to accurately quantify temporal evolution of worm postures. Unlike conventional methods that analyze individual images separately, WormTracer estimates worm centerlines within a sequence of images concurrently. This process enables the resolution of complex postures that are difficult to assess when treated as isolated images. The centerlines obtained through WormTracer exhibit higher accuracy compared to those acquired using conventional methods. By applying principal component analysis to the centerlines obtained by WormTracer, we successfully generated new eigenworms, a basic set of postures, that enables a more precise representation of worm postures than existing eigenworms. Author summaryC. elegans is a valuable model organism for comprehensive understanding of genes, neurons and behavior. Quantification of behavior is essential for clarifying these relationships, and posture information plays a crucial role in the analyses. However, accurately quantifying the posture of C. elegans from video images of worms is challenging, and while various methods have been developed to date, they have their own limitations. In this study, we developed an analytical tool called WormTracer, which can obtain worm centerlines more accurately than conventional methods, even when worms assume complex postures. Using this tool, we successfully obtained new eigenworms, basis postures of a worm, that can more accurately reproduce various postures than conventional eigenworms. WormTracer and the new eigenworms will be valuable assets for future quantitative studies on worm locomotion and sensorimotor behaviors.

bioinformatics↗

bioRxiv2023

Multiple p38/JNK Mitogen-activated protein kinase (MAPK) signaling pathways mediate salt chemotaxis learning in C. elegans

Animals are able to adapt their behaviors to their environment. In order to achieve this, the nervous system plays integrative roles, such as perception of external signals, sensory processing, and behavioral regulations via various signal transduction pathways. Here genetic analyses of C. elegans found that mutants of components of JNK and p38 Mitogen-activated protein kinase (MAPK) signaling pathways, also known as stress-activated protein kinase (SAPK) signaling pathways, exhibit various types of defects in the learning of salt chemotaxis. C. elegans homologues of JNK MAPKKK and MAPKK, MLK-1 and MEK-1, respectively, are required to avoid salt concentrations experienced during starvation. In contrast, homologues of p38 MAPKKK and MAPKK, NSY-1 and SEK-1, respectively, are required for high-salt chemotaxis after conditioning. Genetic interaction analyses suggest that a JNK family MAPK, KGB-1, functions downstream of both signaling pathways to regulate salt chemotaxis learning. Furthermore, we found that the NSY-1/SEK-1 pathway functions in sensory neurons, ASH, ADF, and ASER, to regulate the learned high-salt chemotaxis. A neuropeptide, NLP-3, expressed in ASH, ADF, and ASER neurons, and a neuropeptide receptor, NPR-15, expressed in AIA interneurons that receive synaptic input from these sensory neurons, function in the same genetic pathway as NSY-1 / SEK-1 signaling. These findings suggest that this MAPK pathway may affect neuropeptide signaling between sensory neurons and interneurons, thus promoting high-salt chemotaxis after conditioning.

genetics↗

bioRxiv2023

Antagonistic regulation of salt and sugar chemotaxis plasticity by a single chemosensory neuron in Caenorhabditis elegans

The nematode Caenorhabditis elegans memorizes various external chemicals, such as ions and odorants, during feeding. Here we find that C. elegans is attracted to the monosaccharides glucose and fructose after exposure to these monosaccharides in the presence of food; however, it avoids them without conditioning. The attraction to glucose requires a left-sided ASE gustatory neuron called ASEL. ASEL activity increases when glucose concentration decreases. Optogenetic ASEL stimulation promotes forward movements; however, after glucose conditioning, it promotes turning, suggesting that after glucose conditioning, the behavioral output of ASEL activation switches toward glucose. We previously reported that chemotaxis toward sodium ion (Na+), which is sensed by ASEL, increases after Na+ conditioning in the presence of food. Interestingly, glucose conditioning decreases Na+ chemotaxis, and conversely, Na+ conditioning decreases glucose chemotaxis, suggesting the reciprocal inhibition of learned chemotaxis to distinct chemicals. The activation of PKC-1, an nPKC {varepsilon}/{eta} ortholog, in ASEL promotes glucose chemotaxis and decreases Na+ chemotaxis after glucose conditioning. Furthermore, genetic screening identified ENSA-1, an ortholog of the protein phosphatase inhibitor ARPP-16/19, which functions in parallel with PKC-1 in glucose-induced chemotactic learning toward distinct chemicals. These findings suggest that kinase-phosphatase signaling regulates the balance between learned behaviors based on glucose conditioning in ASEL, which might contribute to migration toward chemical compositions where the animals were previously fed. Author summaryCaenorhabditis elegans responds to compounds that taste salty, bitter, sour, etc. However, its response to sweet compounds is unclear. Here, we show that C. elegans responds to glucose through a chemosensory neuron called ASEL. C. elegans avoids high concentrations of glucose and learns to approach glucose after feeding in the presence of high glucose, dependent on the action of ASEL. The ASEL neuron has been reported to respond to salt and promotes salt attraction after feeding in the presence of high salt. We find that the feeding-associated attractive responses to glucose and salt are antagonistic. When encountered with a mixture of salt and glucose during feeding, C. elegans changes its chemotactic response toward those chemicals according to the balance of each chemical in the mixture. C. elegans may memorize the concentrations of the chemical mixture during feeding and migrates to the chemical composition previously fed, which may promote opportunities obtaining food. Furthermore, we find that kinase-phosphatase signaling, which modulates neurotransmission, in ASEL is required for chemotaxis based on information processing of salt and glucose.

neuroscience↗

bioRxiv2022

Deducing ensemble dynamics and information flow from the whole-brain imaging data

Recent development of large-scale activity imaging of neuronal ensembles provides opportunities for understanding how activity patterns are generated in the brain and how information is transmitted between neurons or neuronal ensembles. However, methodologies for extracting the component properties that generate overall dynamics are still limited. In this study, the results of time-lapse 3D imaging (4D imaging) of head neurons of the nematode C. elegans were analyzed by hitherto unemployed methodologies. By combining time-delay embedding with independent component analysis, the whole-brain activities were decomposed to a small number of component dynamics. Results from multiple samples, where different subsets of neurons were observed, were further combined by matrix factorization, revealing common dynamics from neuronal activities that are apparently divergent across sampled animals. By this analysis, we could identify components that show common relationships across different samples and those that show relationships distinct between individual samples. We also constructed a network model building on time-lagged prediction models of synaptic communications. This was achieved by dimension reduction of 4D imaging data using the general framework gKDR (gradient kernel dimension reduction). The model is able to decompose basal dynamics of the network. We further extended the model by incorporating probabilistic distribution, resulting in models that we call gKDR-GMM and gKDR-GP. The models capture the overall relationships of neural activities and reproduce the stochastic but coordinated dynamics in the neural network simulation. By virtual manipulation of individual neurons and synaptic contacts in this model, information flow could be estimated from whole-brain imaging results.

neuroscience↗

bioRxiv2022

Insulin/IGF Signaling Regulates Presynaptic Glutamate Release in Aversive Olfactory Learning

Information flow through neural circuits is continuously modified by context-dependent learning. In the nematode Caenorhabditis elegans, pairing specific odors with food deprivation results in aversion to the odor. Here we identify cell-specific mechanisms of insulin/IGF receptor signaling that integrate sensory information with food context during aversive olfactory learning. Using a conditional allele of the insulin/IGF receptor DAF-2, we show that aversive learning to butanone, an odor sensed only by the AWCON olfactory neuron, requires DAF-2 in AWCON. Learning requires an axonally-localized DAF-2c isoform and the insulin receptor substrate (IRS) protein IST-1, but is partly independent of the FoxO transcription factor DAF-16. Upon food deprivation, the unconditioned stimulus for learning, DAF-2 expression increases post-transcriptionally through an insulin- and ist-1-dependent process. Aversive learning suppresses odor-regulated glutamate release from AWCON in wild-type animals but not in ist-1 mutants, suggesting that localized insulin signaling drives presynaptic depression to generate an aversive memory.

neuroscience↗

bioRxiv2020

Roles of the ClC chloride channel CLH-1 in food-associated salt chemotaxis behavior of C. elegans

The ability of animals to process dynamic sensory information facilitates foraging in an ever changing environment. However, molecular and neural mechanisms underlying such ability remain elusive. The ClC anion channels/transporters play a pivotal role in cellular ion homeostasis across all phlya. Here we find a ClC chloride channel is involved in salt concentration chemotaxis of C. elegans. Genetic screening identified two altered-function mutations of clh-1 that disrupt experience-dependent salt chemotaxis. Using genetically encoded fluorescent sensors, we demonstrate that CLH-1 contributes to regulation of chloride and calcium dynamics of salt-sensing neuron, ASER. The mutant CLH-1 reduced responsiveness of ASER to salt stimuli in terms of both temporal resolution and intensity, which could disrupt navigation strategies for approaching preferred salt concentration. Furthermore, other ClC genes appeared to act redundantly in salt chemotaxis. These findings provide insights into the regulatory mechanism of neuronal responsivity by ClCs that contribute to modulation of navigation behavior.

genomics↗

bioRxiv2019

Evaluation of 3D markerless motion capture accuracy using OpenPose with multiple video cameras

There is a need within human movement sciences for a markerless motion capture system, which is easy to use and suffciently accurate to evaluate motor performance. This study aims to develop a 3D markerless motion capture technique, using OpenPose with multiple synchronized video cameras, and examine its accuracy in comparison with optical marker-based motion capture. Participants performed three motor tasks (walking, countermovement jumping, and ball throwing), with these movements measured using both marker-based optical motion capture and OpenPose-based markerless motion capture. The differences in corresponding joint positions, estimated from the two different methods throughout the analysis, were presented as a mean absolute error (MAE). The results demonstrated that, qualitatively, 3D pose estimation using markerless motion capture could correctly reproduce the movements of participants. Quantitatively, of all the mean absolute errors calculated, approximately 47% were less than 20 mm and 80% were less than 30 mm. However, 10% were greater than 40 mm. The primary reason for mean absolute errors exceeding 40mm was that OpenPose failed to track the participants pose in 2D images owing to failures, such as recognition of an object as a human body segment, or replacing one segment with another depending on the image of each frame. In conclusion, this study demonstrates that, if an algorithm that corrects all apparently wrong tracking can be incorporated into the system, OpenPose-based markerless motion capture can be used for human movement science with an accuracy of 30mm or less.

neuroscience↗

bioRxiv2019

An annotation dataset facilitates automatic annotation of whole-brain activity imaging of C. elegans

Annotation of cell identity is an essential process in neuroscience that allows for comparing neural activities across different animals. In C. elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal is limited in practice and comprehensive methods for cell annotation are required. Here we propose an efficient annotation method that can be integrated with the whole-brain imaging technique. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. The large positional variations illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters to tackle this problem. We also developed an automatic annotation method with human interaction functionality that facilitates annotation for whole-brain imaging.

neuroscience↗

bioRxiv2019

The minimal behavioral time window for reward conditioning in the nucleus accumbens of mice

The temporal precision of reward-reinforcement learning is determined by the minimal time window of the reward action--theoretically known as the eligibility trace. In animal studies, however, such a minimal time window and its origin have not been well understood. Here, we used head-restrained mice to accurately control the timing of sucrose water as an unconditioned stimulus (US); we found that the reinforcement effect of the US occurred only within 1 s after a short tone of a conditioned stimulus (CS). The conditioning required the dopamine D1 receptor and CaMKII signaling in the nucleus accumbens (NAc). The time window was not reduced by replacing CS with optogenetic stimulation of the synaptic inputs to the NAc, which is in agreement with previous reports on the effective dopamine timing of NAc synapses. Thus, our data suggest that the minimal reward time window is 1 s, and is formed in the NAc.

neuroscience↗

bioRxiv2017

An ensemble learning approach to auto-annotation for whole-brain C. elegans imaging

Shifting from individual neuron analysis to whole-brain neural network analysis opens up new research opportunities for Caenorhabditis elegans (C. elegans). An automated data processing pipeline, including neuron detection, segmentation, tracking and annotation, will significantly improve the efficiency of analyzing whole-brain C. elegans imaging. The resulting large data sets may motivate new scientific discovery by exploiting many promising analysis tools for big data. In this study, we focus on the development of an automated annotation procedure. With only around 180 neurons in the central nervous system of a C. elegans, the annotation of each individual neuron still remains a major challenge because of the high density in space, similarity in neuron shape, unpredictable distortion of the worms head during motion, intrinsic variations during worm development, etc. We use an ensemble learning approach to achieve around 25% error for a test based on real experimental data. Also, we demonstrate the importance of exploring extra source of information for annotation other than the neuron positions.

bioinformatics↗