Biology subjects

Irie, K.

Publications and source records attributed to Irie, K..

15 recordsLinked to original sources

bioRxiv2026

Evaluation of Retinal Safety of Hypoxia-Inducible Factor Prolyl Hydroxylase Inhibitors

Hypoxia-inducible factor prolyl hydroxylase (HIF-PH) inhibitors are widely used for the treatment of renal anemia; however, their effects on intraocular vascular endothelial growth factor (VEGF) expression remain unclear. In this study, we examined the effects of all five HIF-PH inhibitors --roxadustat, daprodustat, vadadustat, enarodustat, and molidustat--on Vegfa expression in the retina in mice. C57BL/6J mice were orally administered each inhibitor. Six hours after administration, the kidney, retina, and liver were collected, and transcription levels were quantified by real-time quantitative reverse transcription PCR. Renal Epo transcription was significantly increased by molidustat (P < 0.01), roxadustat (P < 0.01), and enarodustat (P < 0.05). Retinal Vegfa transcription was significantly increased by four inhibitors (P < 0.01), with molidustat showing no significant effect. In the liver, Vegfa transcription was increased by daprodustat (P < 0.05) and vadadustat (P < 0.01). Furthermore, renal Epo and retinal Vegfa transcription levels showed a moderate positive correlation with a marginal trend toward statistical significance (r = 0.37, P = 0.08). These findings indicate that HIF-PH inhibitors differentially regulate hypoxia-responsive genes across tissues and suggest that retinal VEGF upregulation should be considered when evaluating the safety of these agents.

pharmacology and toxicology↗

bioRxiv2025

Conformational dynamics underlying slow inactivation in voltage-gated sodium channels

Voltage-gated sodium (Nav) channels initiate and propagate action potentials in many excitable cells. Upon repetitive activation, the conductance of Nav channels gradually decreases on a timescale ranging from seconds to minutes, a phenomenon known as slow inactivation, which is crucial for regulating the excitability of many cells. Many studies indicated that slow inactivation is associated with conformational changes at the selectivity filter, but the underlying mechanisms remain unclear. By examining the conformational dynamics of a prokaryotic NavAb channel using single-molecule FRET (smFRET), our work revealed the transitions of its selectivity filter among three distinct conformational states and showed that activating voltages enriched the high-FRET conformations, potentially associated with slow inactivation. We further identified L176 in the selectivity filter P1 helix and T206 in the pore-forming S6 helix as residues coupling the primary and slow inactivation gates by showing that the additional L176F mutation stabilizes the S6 C-terminal deletion opening mutant in the closed state. Consistently, our smFRET results also indicated that the high FRET conformation of the selectivity filter was markedly attenuated in the S6 C-terminal deletion opening mutant, but reverted by the L176F mutation. Open-pore blocker lidocaine has been shown to prevent eukaryotic Nav channels from entering the slow inactivation state. Moreover, our smFRET studies showed that it diminished the high FRET conformation of the NavAb selectivity filter in a dose-dependent manner, while the L176F mutation, again, markedly reversed the lidocaine effects. Collectively, our studies suggested that slow inactivation in the NavAb channel results from the collapse of the selectivity filter pore, as revealed by the high FRET conformation in our smFRET measurements. The L176 in the selectivity filter and T206 in the pore-forming S6 helix coordinate conformational changes of the slow inactivation gate at the selectivity filter and the primary gate at the helix bundle crossing, providing the structural basis for slow inactivation in prokaryotic voltage-gated sodium channels.

biophysics↗

bioRxiv2025

Entorhinal cortex signals dimensions of past experience that can be generalised in a novel environment

No two situations are identical. They can be similar in some aspects but different in others. This poses a key challenge when attempting to generalise our experience from one situation to another. How do we distinguish the aspects that transfer across situations from those that do not? One hypothesis is that the entorhinal cortex (EC) meets this challenge by forming factorised representations that allow for increased neural similarity between events that share generalisable features. We tested this hypothesis using functional magnetic resonance imaging. Female and male participants (n=40) were trained to report behavioural sequences based on an underlying graph structure. Participants then made decisions in a new environment where some, but not all graph transitions from the previous structure could be generalised. Behavioural results showed that participants distinguished the generalisable transition information. Accuracy was significantly higher in blocks where sequence transitions were shared across environments, than those in which transitions differed. This boost in accuracy was especially pronounced during early exposure to the novel environment. Throughout this early phase, neural patterns in EC showed a corresponding differentiation of the generalisable aspects. Neural patterns representing starting locations in familiar and novel environments were significantly more similar in EC on trials where sequences could be generalised from prior experience, compared to trials with new sequential transitions. This signalling was associated with improved performance when prior sequence knowledge could be reused. Our results suggest that during early exposure to novel environments, EC may signal dimensions of past experience that can be generalised. Significance StatementGeneralisation is the process of using our experience to solve new challenges. A central problem we face when attempting to generalise is determining which aspects of a new situation are similar to what we have experienced before and which are different. This allows us to generalise our knowledge selectively, transferring insights to the aspects that are similar and relevant in novel scenarios, while avoiding over-generalisation to the aspects that differ. The results from this experiment suggest that the entorhinal cortex may distinguish these aspects during early exposure to new environments, supporting complex generalisation behaviour.

neuroscience↗

bioRxiv2025

Model-informed Deep Q-Networks to Guide Infliximab Dosing in Pediatric Crohn's Disease

Model-informed precision dosing (MIPD) utilizes pharmacokinetic/pharmacodynamic (PK/PD) models to optimize drug therapy. However, conventional MIPD often requires manual simulation and regimen selection, which are time-consuming and demand specialized expertise. Reinforcement learning (RL), in which an agent learns optimal decisions through iterative interactions with an environment, offers a scalable and automated alternative. In this study, we developed a model-informed Deep Q-Network (DQN) to personalize infliximab dosing for patients with Crohns disease. The DQN was trained in a simulation environment incorporating a population PK model, inter-individual variability, and assay error. Virtual patients with randomly sampled covariates were used to explore dosing strategies at infusions 1, 3, and 4. Doses ranged from 1 to 10 mg/kg at infusion 1 and from 1 to 20 mg/kg thereafter, with intervals of 4 to 12 weeks. The reward function prioritized achieving trough concentrations of 18-26 {micro}g/mL before infusion 3 and 5-10 {micro}g/mL before infusions 4 and 5, while penalizing overtreatment and additional infusions. The DQN policy converged after 80,000 episodes, yielding target attainment probabilities (PTAs) of 92.9% and 98.4% at infusions 4 and 5, respectively, in 1,000 virtual patients. High doses (11-20 mg/kg) were selected in only 0.2% of cases. At infusion 4, 66.8% of patients received an 8-week interval, and 57.3% at infusion 5. Retrospective real-world validation showed that patients whose actual doses matched DQN recommendations had trough levels significantly closer to target ranges. These findings support the feasibility of using DQN-based agents to enhance and automate infliximab individualized dosing in pediatric populations.

pharmacology and toxicology↗

bioRxiv2025

Deep Learning Pipeline for Segmentation and Quantification of Overlapping Membranes in 2D Image

Quantitative morphological analysis is crucial for understanding cellular processes. While 3D Z-stack imaging offers high-resolution data, the complexity of 3D structures makes direct interpretation and manual annotation challenging and time-consuming, especially for large datasets. Maximum Intensity Projection (MIP) is a common strategy to create more interpretable 2D representations, but this inevitably leads to artificial overlaps between structures, significantly hindering accurate automated segmentation of individual instances by conventional methods or standard deep learning tools. To address this critical challenge in 2D projection analysis, we developed DeMemSeg, a deep learning pipeline based on Mask R-CNN, specifically designed to segment overlapping membrane structures, called prospore membranes (PSMs) during yeast sporulation. DeMemSeg was trained on a custom-annotated dataset, leveraging a systematic image processing workflow. Our optimized model accurately identifies and delineates individual, overlapping PSMs, achieving segmentation performance and derived morphological measurements that are statistically indistinguishable from expert manual annotation. Notably, DeMemSeg successfully generalized to segment PSMs from unseen data acquired from gip1{Delta} mutant cells, capturing the distinct morphological defects in PSMs. DeMemSeg thus provides a robust, automated solution for objective quantitative analysis of complex, overlapping membrane morphologies directly from widely used 2D MIP images, offering a practical tool and adaptable workflow to advance cell biology research.

cell biology↗

bioRxiv2025

Structure-function analysis of lithium-ion selectivity of voltage-gated sodium channel

Voltage-gated sodium channels (Navs) selectively conduct Na+ to generate action potentials. Na+ permeates Navs with significantly higher efficiency than many other cations, but Li+ can also permeate Navs to a comparable extent as Na+. It had been known that Li+ in blood enters cell via Navs and effects beneficially on various neuropathies. However, the molecular basis of the high Li+ selectivity of Navs had been unclear. In this study, using a prokaryotic Nav, we successfully created the first Nav mutant that is more selective for Li+ than for Na+. Electrophysiological and crystallographic analyses revealed the critical determinants of high Li+ selectivity: the strong electrostatic interaction between the ion pathway and hydrated ions, and the smaller number of hydration water exchanges within the ion pathway. Additionally, the extensive interactions around the ion pathway were shown to support monovalent cation selectivity. New drug directions based on the molecular basis for Li+ permeation may target various neurological disorders and clarify the broader biological effects of lithium.

biophysics↗

bioRxiv2025

Hybrid Population PK-Machine Learning Modeling to Predict Infliximab Pharmacokinetics in Pediatric and Young Adult Patients with Crohn's Disease

Population pharmacokinetic (PK) model-based Bayesian estimation is widely used for dose individualization, particularly when sample availability is limited. However, its predictive accuracy can be compromised by factors such as misspecified prior information, intra-patient variability, and uncertainties in PK variations. In this study, we developed a hybrid approach that combines machine learning (ML) with population PK-based Bayesian methods to improve the prediction of infliximab concentrations in children with Crohns disease. We calculated prediction errors between Bayesian-estimated and observed infliximab concentrations from 292 measurements across 93 patients. Incorporating clinical patient features, we explored various ML algorithms, including linear regression, random forest, support vector regression, neural networks, and XGBoost to correct the Bayesian-based prediction errors. The predictive performance of these ML models was assessed using root mean square error (RMSE) and mean prediction error (MPE) with 5-fold cross-validation. For Bayesian estimation alone, the RMSE and MPE were 4.8 {micro}g/mL and -0.67 {micro}g/mL, respectively. Among the ML algorithms, the XGBoost model demonstrated the best performance, achieving an RMSE of 3.78 {+/-} 0.85 {micro}g/mL and an MPE of -0.03 {+/-} 0.69 {micro}g/mL in 5-fold cross-validation. The ML-corrected Bayesian estimation significantly reduced the absolute prediction error compared to Bayesian estimation alone. This hybrid population PK-ML approach provides a promising framework for improving the predictive performance of Bayesian estimation, with the potential for continuous learning from new clinical data to enhance dose individualization. Key pointsO_LIA new hybrid model combining population pharmacokinetic model-based Bayesian estimation and machine learning significantly improved the accuracy of infliximab concentration predictions in young adult and pediatric patients with Crohns disease. C_LIO_LIThe developed hybrid model can facilitate infliximab individualized dosing by accounting for changes in clinical conditions and patient-specific factors that the conventional Bayesian estimation approach may not address, and can be integrated into precision dosing dashboards, such as RoadMAB, for real-world clinical application. C_LIO_LIThis study indicates that model predictive accuracy can be enhanced by combining the Bayesian method with machine learning, even with a relatively small amount of clinical data. This is particularly encouraging for specific populations, such as pediatric patients, where obtaining rich clinical data is challenging. C_LI

pharmacology and toxicology↗

bioRxiv2025

MeCP2 controls dendritic morphogenesis via miR-199a-mediated Qki downregulation

Rett syndrome (RTT) (OMIM: 312750) is a severe neurodevelopmental disorder caused by mutations in the MECP2 gene. Although decreased dendritic morphogenesis has been observed in the brain of RTT patients and mouse models, the molecular mechanisms underlying these dendritic anomalies remain unclear. We have previously shown that MeCP2 facilitates specific microRNA (miRNA) processing by associating with the miRNA microprocessor Drosha complex. In this study, we show that MeCP2 positively regulates dendritic formation via miR-199a, a specific target of the MeCP2-Drosha complex. Overexpression of MeCP2 and miR-199a promotes dendritic development such as increases in dendrite length, branching number, and complexity. In contrast, blocking miR-199a inhibited dendrite formation and abolished enhanced dendritic development induced by MeCP2 expression. We also demonstrate that the decreased dendrite outgrowth observed in MeCP2-deficient neurons could be rescued by miR-199a expression. In addition, we found that miR-199a targets the 3 untranslated region of quaking (Qki), a negative regulator of dendritic development, and downregulates its protein expression level. Furthermore, we report an increase in the Qki protein expression level in miR-199a-2-deficient brains and show that Qki knockdown restores the dendritic morphology of miR-199a-2-Knockout (KO) neurons. Taken together, these results suggest that the MeCP2/miR-199a/Qki axis is critical for proper dendritic development and its dysregulation contributes to the dendritic pathology in RTT.

neuroscience↗

bioRxiv2024

Branched-chain amino acid metabolism is a crucial modulator of cellular senescence

Cellular senescence is a complex stress response that results in the permanent arrest of cell proliferation. The accumulation of senescent cells occurs during aging in living organisms, and contributes to tissue dysfunction. Although there are growing lines of evidence that various metabolic changes occur in senescent cells, the link between cellular metabolism and senescence is not yet fully understood. In this study, we demonstrate that alterations in the metabolism of branched-chain amino acids (BCAAs) play a crucial role in establishing cellular senescence. Furthermore, we identified mitochondrial BCAA transamination as a crucial step in this process. Our findings show that various types of cellular stress lead to a reduction in the expression of BCAA aminotransferase 2 (BCAT2), one of the BCAA catabolic enzymes, resulting in decreased catabolism of BCAAs and reduced synthesis of glutamate. The reduction of BCAA catabolites, together with the consequent limitation in glutathione production from glutamate, triggers cellular senescence. Furthermore, we demonstrate that a reduction in BCAT2 levels alone is sufficient to induce cellular senescence, both in cultured cells and in mice. Additionally, our results demonstrate that aging alters BCAA metabolism in both mice and humans. Our findings provide new insights into the metabolic mechanisms underlying cellular senescence, with a particular focus on the role of BCAAs.

cell biology↗

bioRxiv2023

Remodeling of the secretory pathway is coordinated with de novo membrane formation in budding yeast gametogenesis

Gametogenesis in budding yeast involves a large-scale rearrangement of membrane traffic to allow de novo formation of a membrane, called the prospore membrane (PSM). However, the mechanism underlying this event is not fully elucidated. Here, we show that the number of endoplasmic reticulum exit sites (ERES) per cell fluctuates and switches from decreasing to increasing upon the onset of PSM formation. Reduction in ERES number, presumably accompanying a transient stall in membrane traffic, resulting in the loss of preexisting Golgi apparatus from the cell, was followed by local ERES regeneration, leading to Golgi reassembly in nascent spores. We have revealed that protein phosphatase-1 (PP-1) and its development-specific subunit, Gip1, promote ERES regeneration through Sec16 foci formation. Furthermore, sed4{Delta}, a mutant with impaired ERES formation, showed defects in PSM growth and spore formation. Thus, ERES regeneration in nascent spores facilitates the segregation of membrane traffic organelles, leading to PSM growth.

cell biology↗

bioRxiv2022

Automation of yeast spot assays using an affordable liquid handling robot

The spot assay of the budding yeast Saccharomyces cerevisiae is an experimental method that is used to evaluate the effect of genotypes, medium conditions, and environmental stresses on cell growth and survival. Automation of the spot assay experiments from preparing a dilution series to spotting to observing spots continuously has been implemented based on large laboratory automation devices and robots, especially for high-throughput functional screening assays. However, there has yet to be an affordable solution for the automated spot assays suited to researchers in average laboratories and with high customizability for end-users. To make reproducible spot assay experiments widely available, we have automated the plate-based yeast spot assay of budding yeast using Opentrons OT-2 (OT-2), an affordable liquid-handling robot, and a flatbed scanner. We prepared a 3D-printed mount for the Petri dish to allow for precise placement of the Petri dish inside the OT-2. To account for the uneven height of the agar plates, which were made by human hands, we devised a method to adjust the z-position of the pipette tips which is based on the weight of each agar plate. During the incubation of the agar plates, a flatbed scanner was used to automatically take images of the agar plates over time, allowing researchers to quantify and compare the cell density within the spots at optimal time points a posteriori. Furthermore, the accuracy of the newly developed automated spot assay was verified by performing spot assays with human experimenters and the OT-2 and quantifying the yeast-grown area of the spots. This study will contribute to the introduction of automated spot assays and the automated acquisition of growth processes in conventional laboratories that are not adapted for high-throughput laboratory automation.

bioengineering↗

bioRxiv2021

APOE ε4 allele advances the age-dependent decline of amyloid β clearance in the human cortex

IntroductionOur previous study indicated that the pericapillary clearance of amyloid {beta} (A{beta}) declines with age in APOE 3/3 subjects. Here, we examine whether the APOE {varepsilon}4 allele has an impact on this age-related decline. MethodsWe examined 69 autopsy brains of APOE {varepsilon}3/{varepsilon}4 or APOE {varepsilon}3/{varepsilon}3 individuals (30-65 years) for the immunohistochemical localization of intracellular, extracellular, and pericapillary A{beta} in the cerebral cortex. ResultsIn APOE {varepsilon}3/{varepsilon}4 individuals, the percentage of A{beta} positive pericapillary spaces began to decrease (p=0.030), and the number of extracellular A{beta} particles increased in the early 30s (p=0.0008). Those average values were significantly lower (p<0.0001) and higher (p<0.0001), respectively, compared to APOE {varepsilon}3/{varepsilon}3 individuals. DiscussionOur observations indicate that APOE {varepsilon}4 allele advances by one decade at the onset of age-related decline in A{beta} glymphatic clearance. This finding supports early clinical intervention and stratification by APOE genotype to prevent A{beta} deposition and AD progression.

pathology↗

bioRxiv2019

Crystal structure of a human plasma membrane phospholipid flippase

ATP11C, a member of P4-ATPase flippase, exclusively translocates phosphatidylserine from the outer to the inner leaflets of the plasma membrane, and maintains the asymmetric distribution of phosphatidylserine in the living cell. However, the mechanisms by which ATP11C translocates phosphatidylserine remain elusive. Here we show the crystal structures of a human plasma membrane flippase, ATP11C-CDC50A complex, in an outward-open E2P conformation. Two phosphatidylserine molecules are in a conduit that continues from the cell surface to the occlusion site in the middle of the membrane. Mutations in either of the phosphotidylserine binding sites or along the pathway between significantly impairs specific ATPase and transport activities. We propose a model for phosphatidylserine translocation from the outer to the inner leaflet of the plasma membrane.

biochemistry↗

bioRxiv2019

A native prokaryotic voltage-dependent calcium channel with a novel selectivity filter sequence

Voltage-dependent Ca2+ channels (Cavs) are indispensable for coupling action potentials with Ca2+ signaling in living organisms. The structure of Cavs is similar to that of voltage-dependent Na+ channels (Navs). It is known that prokaryotic Navs can obtain Ca2+ selectivity by negative charge mutations of the selectivity filter, but native prokaryotic Cavs had not yet been identified.\n\nHere, we report the first identification of a native prokaryotic Cav, CavMr, and its relative, NavPp. Although CavMr contains a smaller number of negatively charged residues in the selectivity filter than artificial prokaryotic Cavs, CavMr exhibits high Ca2+ selectivity. In contrast, NavPp, which has similar filter sequence to artificial Cavs, mainly allows Na+ to permeate. Interestingly, a NavPp mutant whose selectivity filter was replaced with that of CavMr exhibits high Ca2+ selectivity. Mutational analyses revealed that the glycine residue of the CavMr selectivity filter is a determinant for Ca2+ selectivity. This glycine residue is well conserved among subdomains I and III of eukaryotic Cavs.\n\nThese findings provide new insight into the Ca2+ selectivity mechanism conserved from prokaryotes to eukaryotes.

biophysics↗

bioRxiv2019

A single K+-binding site in the crystal structure of the gastric proton pump

The gastric proton pump (H+,K+-ATPase), a P-type ATPase responsible for gastric acidification, mediates electro-neutral exchange of H+ and K+ coupled with ATP hydrolysis, but with an as yet undetermined transport stoichiometry. Here we show crystal structures at a resolution of 2.5 [A] of the pump in the E2-P transition state, in which the counter-transporting cation is occluded. We found a single K+ bound to the cation-binding site of H+,K+-ATPase, indicating an exchange of 1H+/1K+ per hydrolysis of one ATP molecule. This fulfils the energy requirement for the generation of a six pH unit gradient across the membrane. The structural basis of K+recognition is resolved, supported by molecular dynamics simulations, and this establishes how H+,K+-ATPase overcomes the energetic challenge to generate an H+ gradient of more than a million-fold - the highest cation gradient known in any mammalian tissue - across the membrane.

biochemistry↗