Biology subjects

Koike, Y.

Publications and source records attributed to Koike, Y..

14 recordsLinked to original sources

bioRxiv2026

Extracting interpretable single-cell metabolic states with graph-guided representation learning

Metabolism shapes cellular function and state, yet measuring single-cell metabolic states at scale remains a challenge. We present Metabolic Representation Net (MeRN), a graph-guided variational autoencoder that leverages prior metabolic knowledge as a topology graph to learn latent representations of metabolic state and reaction activity from single-cell transcriptomes. MeRN's scalable estimation of reaction activity enables the definition of data-driven pathways (DDPs): context-specific metabolic modules supported by transcriptomic evidence and agnostic of standard pathway definitions. Using DDPs, we introduce the weakest link analysis to identify metabolic network rewiring. MeRN recovers metabolic zonation in the mouse intestine, links a folate deficiency-induced break in de novo purine synthesis to embryonic neural tube defects, shows cytokines with similar non-metabolic effects can elicit divergent T cell metabolism, and identifies metabolic drivers of T cell exhaustion and therapy response in human cancers. Our results establish MeRN as a unified method for metabolic analysis of single-cell transcriptomes.

bioinformatics↗

bioRxiv2025

Chlamydomonas γ-tubulin mutations reveal a critical role of γ-TuRC in maintaining the stability of centriolar microtubules

The centriolar triplet microtubule consists of an A-tubule with 13 protofilaments, and B-and C-tubules, each with 10 protofilaments. Although the formation of the triplets has been shown to require {gamma}-tubulin, its specific role in the formation of each tubule remains elusive. We isolated two novel Chlamydomonas reinhardtii mutants, bld13-1 and bld13-2, each expressing {gamma}-tubulin with a single amino-acid substitution (T292I or E89D). Similar to known centriole-deficient mutants, both mutants exhibited defects in ciliary assembly, nuclear number, as well as the number and orientation of cytoplasmic microtubules. Genetic analyses of the mutants, along with the expression of the mutant {gamma}-tubulins in the wild-type cells, suggested that both mutants exert dominant-negative effects over wild-type {gamma}-tubulin. Interestingly, although the centrioles in these mutants retained the typical nine triplet structure, their triplets frequently lacked several protofilaments in specific regions of the A- and C-tubules. The protofilament loss occurs more frequently in the proximal region of the centriole. These structural defects suggest a critical role for {gamma}-tubulin in maintaining the stability of the A- and C-tubules of centriolar triplets. Summary statementNovel Chlamydomonas {gamma}-tubulin mutations cause a partial loss of protofilaments in centriolar microtubules, indicating a critical role of {gamma}-tubulin in structural stabilization of triplet microtubules.

cell biology↗

bioRxiv2025

Characterizing lipoprotein profiles in coronary atherosclerosis development through quantitative lipidomics and proteomics approaches

Lipoproteins, which are synthesized in hepatic cells and secreted into the blood, play an important role in lipid transport. The quality of lipoproteins, including small dense low-density lipoproteins and the cholesterol efflux capacity of high-density lipoproteins, influences cardiovascular outcomes, although the relationship between lipid changes and lipoprotein quality remains unclear. This study characterized lipid molecules and apolipoproteins in lipoprotein particles during the development of coronary atherosclerosis in myocardial infarction-prone rabbits. Using quantitative lipidomics and proteomics techniques, the lipid composition in lipoprotein particles was evaluated by normalizing lipidomics data with lipoprotein particle numbers estimated by apolipoprotein B-100 concentration. While apolipoproteins and common risk factors for abnormal lipid metabolism, including cholesterol and triacylglycerol, did not change across stages of coronary atherosclerosis, ceramide molecules in lipoprotein particles were significantly associated with early stage progression. This study provides a perspective on the role of lipid composition in the progression of coronary atherosclerosis.

bioengineering↗

bioRxiv2024

Impaired central pattern generators due to abnormal EPHA4 signaling leads to idiopathic scoliosis

Idiopathic scoliosis (IS) is the most common form of spinal deformity with unclear pathogenesis. In this study, we firstly reanalyzed the loci associated with IS, drawing upon previous studies. Subsequently, we mapped these loci to candidate genes using either location-based or function-based strategies. To further substantiate our findings, we verified the enrichment of variants within these candidate genes across several large IS cohorts encompassing Chinese, East Asian, and European populations. Consequently, we identified variants in the EPHA4 gene as compelling candidates for IS. To confirm their pathogenicity, we generated zebrafish mutants of epha4a. Remarkably, the zebrafish epha4a mutants exhibited pronounced scoliosis during later stages of development, effectively recapitulating the IS phenotype. We observed that the epha4a mutants displayed defects in left-right coordination during locomotion, which arose from disorganized neural activation in these mutants. Our subsequent experiments indicated that the disruption of the central pattern generator (CPG) network, characterized by abnormal axon guidance of spinal cord interneurons, contributed to the disorganization observed in the mutants. Moreover, when knocked down efnb3b, the ligand for Epha4a, we observed similar CPG defects and disrupted left-right locomotion. These findings strongly suggested that ephrin B3-Epha4 signaling is vital for the proper functioning of CPGs, and defects in this pathway could lead to scoliosis in zebrafish. Furthermore, we identified two cases of IS in NGEF, a downstream molecule in the EPHA4 pathway. Collectively, our data provide compelling evidence that neural patterning impairments and disruptions in CPGs may underlie the pathogenesis of IS.

genetics↗

bioRxiv2023

Association of an estrogen-sensitive Pax1-Col11a1-Mmp3 signaling axis with adolescent idiopathic scoliosis

Adolescent idiopathic scoliosis (AIS) is a common and progressive spinal deformity in children that exhibits striking sexual dimorphism, with girls at more than five-fold greater risk of severe disease compared to boys. Despite its medical impact, the molecular mechanisms that drive AIS are largely unknown. We previously defined a female-specific AIS genetic risk locus in an enhancer near the PAX1 gene. Here we sought to define the roles of PAX1 and newly-identified AIS-associated genes in the developmental mechanism of AIS. In a genetic study of 10,519 individuals with AIS and 93,238 unaffected controls, significant association was identified with a variant in COL11A1 encoding collagen (1) XI (rs3753841; NM_080629.2_c.4004C>T; p.(Pro1335Leu); P=7.07e-11, OR=1.118). Using CRISPR mutagenesis we generated Pax1 knockout mice (Pax1-/-). In postnatal spines we found that PAX1 and collagen (1) XI protein both localize within the intervertebral disc (IVD)-vertebral junction region encompassing the growth plate, with less collagen (1) XI detected in Pax1-/- spines compared to wildtype. By genetic targeting we found that wildtype Col11a1 expression in costal chondrocytes suppresses expression of Pax1 and of Mmp3, encoding the matrix metalloproteinase 3 enzyme implicated in matrix remodeling. However, this suppression was abrogated in the presence of the AIS-associated COL11A1P1335L mutant. Further, we found that either knockdown of the estrogen receptor gene Esr2, or tamoxifen treatment, significantly altered Col11a1 and Mmp3 expression in chondrocytes. We propose a new molecular model of AIS pathogenesis wherein genetic variation and estrogen signaling increase disease susceptibility by altering a Pax1-Col11a1-Mmp3 signaling axis in spinal chondrocytes.

genetics↗

bioRxiv2023

Mis-spliced transcripts generate de novo proteins in TDP-43-related ALS/FTD

Functional loss of TDP-43, an RNA-binding protein genetically and pathologically linked to ALS and FTD, leads to inclusion of cryptic exons in hundreds of transcripts during disease. Cryptic exons can promote degradation of affected transcripts, deleteriously altering cellular function through loss-of-function mechanisms. However, the possibility of de novo protein synthesis from cryptic exon transcripts has not been explored. Here, we show that mRNA transcripts harboring cryptic exons generate de novo proteins both in TDP-43 deficient cellular models and in disease. Using coordinated transcriptomic and proteomic studies of TDP-43 depleted iPSC-derived neurons, we identified numerous peptides that mapped to cryptic exons. Cryptic exons identified in iPSC models were highly predictive of cryptic exons expressed in brains of patients with TDP-43 proteinopathy, including cryptic transcripts that generated de novo proteins. We discovered that inclusion of cryptic peptide sequences in proteins altered their interactions with other proteins, thereby likely altering their function. Finally, we showed that these de novo peptides were present in CSF from patients with ALS. The demonstration of cryptic exon translation suggests new mechanisms for ALS pathophysiology downstream of TDP-43 dysfunction and may provide a strategy for novel biomarker development. One Sentence SummaryLoss of TDP-43 function results in the expression of de novo proteins from mis-spliced mRNA transcripts.

neuroscience↗

bioRxiv2022

Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks

An essential aspect of human motor learning is the formation of inverse models, which map desired actions to motor commands. Inverse models can be learned by adjusting parameters in neural circuits to minimize errors in the performance of motor tasks through gradient descent. However, the theory of gradient descent establishes an upper limit on the learning speed, above which learning becomes unstable. Specifically, the eigenvalues of the Hessian of the error surface around a minimum determine the maximum speed of learning in a given task. Here, we use this theoretical framework to analyze the speed of learning in different inverse model learning architectures in a set of isometric arm-reaching tasks. We show theoretically that, for these isometric tasks, the error surface and, thus the speed of learning, are determined by the shapes of 1) the force manipulability ellipsoid of the arm and 2) the distribution of targets in the task. In particular, rounder manipulability ellipsoids generate a rounder error surface, allowing for faster learning of the inverse model. Rounder target distributions have a similar effect. We tested these predictions experimentally in a virtual quasi-isometric reaching task with a visuomotor transformation. The experimental results were consistent with our theoretical predictions. Furthermore, our analysis accounts for the speed of learning in previous experiments with incompatible and compatible virtual surgery tasks, and in visuomotor rotation tasks with different numbers of targets. By identifying aspects of a task that influence the speed of learning, our results provide theoretical principles for the design of motor tasks that allow for faster learning. Author SummaryWhen facing a new or changing environment, humans need to learn a new internal inverse model to generate fast and accurate movements. Different computational architectures based on supervised learning via gradient descent have been proposed to explain the acquisition of these inverse models. Although the theory of gradient descent and its results regarding the speed of learning are well developed in Machine Learning, this framework has seldom been applied to computational models of human motor learning. In this study, we found that applying this theoretical framework to a set of isometric reaching tasks clearly reveals aspects of the motor task that can speed up or slow down learning. In particular, we found that, in isometric tasks, the force manipulability ellipsoid of the arm and the distribution of force targets determine the speed of learning. These theoretical results allowed us to generate testable hypotheses about the speed of learning in different motor task conditions, which we successfully confirmed experimentally. We believe that our methods and results could open new lines of research to systematically identify aspects of motor learning tasks that can be exploited to enhance the speed of learning and to design new tasks that are easy to learn.

neuroscience↗

bioRxiv2022

A model predictive control strategy to regulate movements and interactions

Humans are adept at moving the arm to interact with objects and surfaces. The brain is thought to regulate motion and interactions using two different controllers, one specialized for movements and the other for force regulation. However, it remains unclear whether different control mechanisms are necessary. Here we show that the brain can employ a single high-level control strategy for both movement and interaction control. The Model Predictive Control (MPC) strategy introduced in this paper uses an internal model of the environment to plan the arms muscle activity whilst updating its predictions using periodic feedback. Computer simulations demonstrate MPCs ability to produce human-like movements and after-effects in free and force field environments. It can simultaneously regulate both force and stiffness during interactions, and can accomplish motor tasks demanding transitions between motion and interaction control. Model Predictive Control promises to be an important tool to test ideas of motor control as it can handle nonlinear dynamics with changing environments and goals without having to specify the movement duration.

neuroscience↗

bioRxiv2021

TDP-43 represses cryptic exon inclusion in FTD/ALS gene UNC13A

A hallmark pathological feature of neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing. Single nucleotide polymorphisms (SNPs) in UNC13A are among the strongest genome-wide association study (GWAS) hits associated with FTD/ALS in humans, but how those variants increase risk for disease is unknown. Here we show that TDP-43 represses a cryptic exon splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines, and iPSC-derived motor neurons resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. Remarkably, the top variants associated with FTD/ALS risk in humans are located in the cryptic exon harboring intron itself and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD/ALS (UNC13A genetic variants) and loss of TDP-43 function.

neuroscience↗

bioRxiv2021

Age-related demethylation of the TDP-43 autoregulatory region in the human motor cortex

In amyotrophic lateral sclerosis (ALS), TAR DNA-binding protein 43 (TDP-43), which is encoded by TARDBP, forms aggregates in the motor cortex. This aggregate formation may be triggered by an increase in the TDP-43 level with aging. However, the amount of TDP-43 is autoregulated by alternative splicing of the TARDBP 3UTR, and how this autoregulation is affected by aging remains to be elucidated. We found that DNA demethylation in the autoregulatory region in the TARDBP 3'UTR reduced alternative splicing and increased TARDBP mRNA expression. Furthermore, in the human motor cortex, we found that this region was demethylated with aging, resulting in increased expression of TARDBP mRNA. The acceleration of DNA demethylation in the motor cortex was associated with the age of ALS onset. In summary, the dysregulation of TDP-43 autoregulation by age-related DNA demethylation in the motor cortex may explain the contribution of aging and motor system selectivity in ALS.

molecular biology↗

bioRxiv2020

MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics

Mathematical models of metabolic networks utilize simulation to study system-level mechanisms and functions. Various approaches have been used to model the steady state behavior of metabolic networks using genome-scale reconstructions, but formulating dynamic models from such reconstructions continues to be a key challenge. Here, we present the Mass Action Stoichiometric Simulation Python (MASSpy) package, an open-source computational framework for dynamic modeling of metabolism. MASSpy utilizes mass action kinetics and detailed chemical mechanisms to build dynamic models of complex biological processes. MASSpy adds dynamic modeling tools to the COnstraint-Based Reconstruction and Analysis Python (COBRApy) package to provide an unified framework for constraint-based and kinetic modeling of metabolic networks. MASSpy supports high-performance dynamic simulation through its implementation of libRoadRunner; the Systems Biology Markup Language (SBML) simulation engine. Three case studies demonstrate how to use MASSpy: 1) to simulate dynamics of detailed mechanisms of enzyme regulation; 2) to generate an ensemble of kinetic models using Monte Carlo sampling to approximate missing numerical values of parameters and to quantify uncertainty, and 3) to overcome issues that arise when integrating experimental data with the computation of functional states of detailed biological mechanisms. MASSpy represents a powerful tool to address challenge that arise in dynamic modeling of metabolic networks, both at a small and large scale. Author SummaryGenome-scale reconstructions of metabolism appeared shortly after the first genome sequences became available. Constraint-based models are widely used to compute steady state properties of such reconstructions, but the attainment of dynamic models has remained elusive. We thus developed the MASSpy software package, a framework that enables the construction, simulation, and visualization of dynamic metabolic models. MASSpy is based on the mass action kinetics for each elementary step in an enzymatic reaction mechanism. MASSpy seamlessly unites existing software packages within its framework to provide the user with various modeling tools in one package. MASSpy integrates community standards to facilitate the exchange of models, giving modelers the freedom to use the software for different aspects of their own modeling workflows. Furthermore, MASSpy contains methods for generating and simulating ensembles of models, and for explicitly accounting for biological uncertainty. MASSpy has already demonstrated success in a classroom setting. We anticipate that the suite of modeling tools incorporated into MASSpy will enhance the ability of the modeling community to construct and interrogate complex dynamic models of metabolism.

systems biology↗

bioRxiv2020

The CRP-family transcriptional regulator DevH regulates expression of heterocyst-specific genes at the later stage of differentiation in the cyanobacterium Anabaena sp. strain PCC 7120

Heterocysts are terminally differentiated cells of filamentous cyanobacteria, which are specialized for nitrogen fixation. Because nitrogenase, an enzyme for nitrogen fixation, is easily inactivated by oxygen, the intracellular environment of heterocysts is kept microoxic. In heterocysts, the oxygen-evolving photosystem II is inactivated, a heterocyst-specific envelope with an outer polysaccharide layer and an inner glycolipid layer is formed to limit oxygen entry, and oxygen consumption is activated. Heterocyst differentiation, which is accompanied by drastic morphological and physiological changes, requires strictly controlled gene expression systems. Here, we investigated the functions of a CRP-family transcriptional regulator, DevH, in the process of heterocyst differentiation. A devH-knockdown strain, devHKD, was created by replacing the original promoter with the gifA promoter, which is repressed during heterocyst differentiation. Although devHKD formed morphologically distinct cells with the heterocyst envelope polysaccharide layer, it was unable to grow diazotrophically. Genes involved in construction of the microoxic environment, such as cox operons and the hgl island, were not upregulated in devHKD. Moreover, expression of the nif gene cluster was completely abolished. Even under anaerobic conditions, the nif gene cluster was not induced in devHKD. Thus, DevH is necessary for the establishment of a microoxic environment and induction of nitrogenase in heterocysts.

microbiology↗

bioRxiv2019

When 90% of the variance is not enough: residual EMG from muscle synergy extraction influences task performance

Muscle synergies are usually identified via dimensionality reduction techniques, such that the identified synergies reconstruct the muscle activity to a level of accuracy defined heuristically, such as 90% of the variance explained. Here, we question the assumption that the residual muscle activity not explained by the synergies is due to noise. We hypothesize instead that the residual activity is structured and can therefore influence the execution of a motor task. Young healthy subjects performed an isometric reaching task in which surface electromyography of 10 arm muscles was mapped onto estimated two-dimensional forces used to control a cursor. Three to five synergies were extracted to account for 90% of the variance explained. We then altered the muscle-force mapping via \"hard\" and \"easy\" virtual surgeries. Whereas in both surgeries the forces associated with synergies spanned the same single dimension of the virtual environment, the muscle-force mapping was as close as possible to the initial mapping in the easy surgery and as far as possible in the hard surgery. This design therefore maximized potential differences in reaching errors attributable to the residual muscle activity. Results show that the easy surgery produced much smaller directional errors than the hard task. In addition, systematic estimations of the errors for easy and hard surgeries constructed with 1 to 10 synergies show that the errors differ significantly for up to 8 synergies, which account for 98% of the variance on average. Our study therefore indicates the need for cautious interpretations of results derived from synergy extraction techniques based on heuristics with lenient levels of accuracy.\n\nAuthor summaryThe muscle synergy hypothesis states that the central nervous system simplifies motor control by grouping muscles that share common functions into modules called muscle synergies. Current techniques use unsupervised dimensionality reduction algorithms to identify these synergies. However, these techniques rely on arbitrary criteria to determine the number of synergies, which is actually unknown. An example of such criteria is that the identified synergies must be able to reconstruct the measured muscle activity to at least a 90% level of accuracy. Thus, the residual muscle activity, the remaining 10% of the muscle activity, is often disregarded as noise. We show that residual muscle activity following muscle synergy identification has a large systematic effect on movements even when the number of synergies approaches the number of muscles. This suggests that current synergy extraction techniques may discard a component of muscle activity that is important for motor control. Therefore, current synergy extraction techniques must be updated to identify true physiological synergies.

neuroscience↗

bioRxiv2018

Plasma redox imbalance caused by albumin oxidation promotes lung-predominant NETosis and pulmonary cancer metastasis

Neutrophil extracellular traps (NETs) entrap circulating tumor cells (CTCs) and promote metastasis within distant organs in preclinical models1,2. In these models, NETosis is triggered by exogenous massive inflammatory stimuli, and thus it remains unknown whether cancer hosts under physiologic inflammation-free conditions experience NETosis and consequent cancer metastasis. Here we show that plasma redox imbalance caused by albumin oxidation promotes inflammation-independent NETosis and cancer metastasis specifically in the lungs. Albumin is the major source of free thiol that maintains redox balance in vitro and in vivo. Oxidation of albumin-derived free thiol is sufficient to trigger NETosis via accumulation of reactive oxygen species within neutrophils. The resultant NETs are found predominantly within lungs where they contribute to the colonization of CTCs leading to pulmonary metastases in mouse models. These effects are abrogated by pharmacologic inhibition of NET formation. Moreover, albumin oxidation and the resultant decline of plasma free thiol are associated with pulmonary metastasis in a cohort of head and neck cancer patients. These results implicate plasma redox balance as an endogenous and physiologic regulator of NETosis and pulmonary cancer metastasis, providing new therapeutic and diagnostic opportunities for combatting cancer progression.

cancer biology↗