Biology subjects

Miyoshi, K.

Publications and source records attributed to Miyoshi, K..

17 recordsLinked to original sources

bioRxiv2026

Evaluating non-oxidative glycolysis using 13C metabolic flux analysis

Non-oxidative glycolysis (NOG) converts glucose to acetyl-CoA without emitting CO2 during Escherichia coli bioproduction. Although 13C-metabolic flux analysis (13C-MFA) has the potential to evaluate NOG flux distribution in vivo, the precision of these estimates depends on the labeling patterns of glucose tracers. Because E. coli has multiple native glycolysis pathways, selecting the optimal glucose tracer is important for precise estimates. This study used simulations to evaluate the performance of 18 commercially available glucose tracers in precisely predicting NOG flux. We artificially generated flux distributions of central metabolic pathways, including three types of NOG pathways, and obtained 13C labeling patterns of amino acids metabolized from each glucose tracer. Using these data, we then calculated 95% confidence intervals (CIs) for NOG pathway fluxes. Comparing the sum of CI widths from three NOG fluxes showed that estimation with [1,3-13C]-glucose yielded the narrowest CIs. Several tracers, including [2,3-13C]glucose, were capable of determining fluxes with high precision, but [1-13C]glucose was not one of them, despite often being used for estimating glycolytic fluxes. We then experimentally evaluated [2,3-13C]- and [1-13C]glucose as tracers in E. coli strains with and without the expression of phosphoketolase, which is required for NOG pathways to function. The results suggested that [1-13C]glucose could not detect NOG fluxes, whereas [2,3-13C]glucose estimated the fluxes of all three NOG pathways with narrow CIs.

microbiology↗

bioRxiv2026

DiverScan: attention-guided exploratory analysis of animal behaviour across diverse comparative experiments

High-throughput tracking yields rich time-series data of animal behaviour, yet extracting biological insight remains a bottleneck, even for simple control--treatment comparisons. Existing analyses struggle to pinpoint the multiple, nonlinearly intertwined differences hidden in the data and fail to generalise across diverse recording set-ups. Here we present DiverScan, a deep-learning framework for attention-guided exploratory analysis of behavioural time series. DiverScan disentangles condition-dependent behavioural differences by pairing a loss function tailored to data exploration with an attention-branch architecture, and highlights condition-specific behavioural features visually and with explanatory text generated by a large language model. DiverScan is validated on a synthetic benchmark and on datasets from seven laboratories spanning multiple species and both single- and multi-animal behaviour. Beyond recovering known phenotypes, we demonstrate that DiverScan helps researchers generate new hypotheses across these diverse datasets. Available as Jupyter notebooks with a graphical user interface and flexible input formats, DiverScan can integrate into existing behavioural-analysis pipelines.

animal behavior and cognition↗

bioRxiv2026

On-demand surround suppression explains the spatiotemporal window of the tilt illusion

What we see at one location depends on what surrounds it. Such contextual e[ff]ects are thought to arise from neural signals that travel across the retinotopic representations.Because these signals need more time to travel longer distances, a more distant surround should influence perception most strongly when presented earlier, compensating for its delay. We tested this prediction in human observers using a visual illusion in which a central target appears tilted away from the orientation of its surround (tilt illusion). Measuring the temporal window of this illusion using psychophysical reverse correlation revealed the opposite: the most e[ff]ective surround occurred progressively later as distance increased. Computational modelling demonstrated that this reversal is explained if the visual system sends out a query that recruits contextual information on demand. Perceptual appearance may thus be constructed through temporally unfolding interactions in which context is actively gathered, not passively received.

neuroscience↗

bioRxiv2026

Characterization of central carbon metabolism of Acinetobacter sp. Tol 5 based on 13C-metabolic flux analysis

Acinetobacter sp. strain Tol 5 is an attractive microorganism because of its ability to utilize various aromatic compounds, including toluene. However, because Tol 5 is a non-model microorganism, the utilization of carbon sources in central carbon metabolism remains unclear. In this study, the activity of the central carbon metabolism was characterized using 13C-metabolic flux analysis (13C-MFA). Tol 5 was cultured in synthetic medium using ethanol or acetate as the sole carbon source. In addition, because toluene is degraded into pyruvate and acetyl-CoA via the toluene dioxygenase pathway, this situation was mimicked by culturing with ethanol and lactate as co-substrates. The 13C-MFA confirmed flux through the glyoxylate shunt, which bypasses part of the TCA cycle when either ethanol or acetate was used as the sole carbon source. In ethanol, the flux ratio of isocitrate dehydrogenase at the isocitrate branch point decreased markedly. Unlike acetate, the conversion of ethanol to acetyl-CoA is accompanied by NADH production. Therefore, the observed change in this flux ratio was influenced by the excess NADH generated. Under ethanol-lactate conditions, Tol 5 simultaneously utilized ethanol and lactate. The ethanol consumption rate decreased to less than half of that observed when ethanol was the sole carbon source. Most of the lactate uptake was converted to pyruvate and metabolized via the TCA cycle. The glyoxylate shunt flux was lower than that in ethanol. These metabolic characteristics provide valuable insights into the use of Tol 5 as a next-generation microbial cell factory.

microbiology↗

bioRxiv2026

m1A58 governs two steps of human initiator-methionine tRNA metabolism: maturation and XRN2-mediated decay

N{superscript 1}-methyladenosine at position 58 (m{superscript 1}A58), installed by the TRMT6/TRMT61A complex, is a highly conserved structural modification implicated in tRNA stability and human disease. In yeast, loss of m{superscript 1}A58 disrupts initiator methionine tRNA (tRNA) metabolism through defects in precursor processing and rapid tRNA decay, but whether these mechanisms operate in human cells has remained unclear. Here, using acute degron-mediated depletion of TRMT6 in human HCT116 cells combined with precursor-resolved tRNA sequencing, we show that m{superscript 1}A58 controls two distinct steps of tRNA metabolism. TRMT6 depletion selectively reduces mature tRNA while causing accumulation of precursor species retaining both 5'-leader and 3'-trailer sequences, consistent with impaired maturation. In parallel, the nuclear 5'[->]3' exonuclease XRN2 selectively degrades the residual mature hypomodified tRNA pool without affecting precursor accumulation. Loss of mature tRNA activates the integrated stress response and impairs proliferation, which is restored by XRN2 co-depletion. Together, our findings identify m{superscript 1}A58 as a coordinator of human initiator-tRNA maturation and surveillance, establishing a two-step pathway that maintains tRNA homeostasis in human cells.

biochemistry↗

bioRxiv2026

Deep-learning-based fMRI decoding of real-world size for hand-held objects

Real-world object size is a fundamental dimension of visual cognition, supporting effective interaction with the environment and object manipulation. However, neural mechanisms encoding size have largely been inferred from extreme size comparisons, leaving the neural representation of subtle size differences within a manipulable, "hand-scale" range poorly understood. Here, we applied a three-dimensional deep neural network (3D DNN) to decode real-world size from whole-brain fMRI data (N = 50) using objects that all fall within a graspable range. The 3D DNN successfully decoded subtle size differences, achieving predictive accuracies comparable to multivariate pattern analysis. Crucially, Guided Gradient-weighted Class Activation Mapping (Guided Grad-CAM) revealed that discriminative size information was not confined to the ventral occipito-temporal cortex but extended to a distributed network. Notably, these regions spatially overlap with the specific brain areas implicated in size-perception distortions following brain damage. Our findings suggest that the brain represents subtle variations in object size through a non-linear, distributed network that transcends the traditional visual hierarchy. Specifically, this system likely orchestrates the integration of visual properties with semantic scaling and the multimodal convergence of vision, space, and memory.

neuroscience↗

bioRxiv2025

The mammalian rapid tRNA decay pathway is critical for N⁷-methylguanosine-hypomodified tRNA degradation under physiological conditions

Chemical modifications of transfer RNAs (tRNAs) are integral to their stability and to translation. Loss of N7-methylguanosine (m7G) on specific tRNAs reduces their steady-state abundance and impairs translation in mammals, but whether these decreases reflect active degradation under physiological growth conditions is unresolved. Here, using human HCT116 cells, we show that knockdown of the 5'[->]3' exonuclease, XRN2, restores tRNA levels diminished by METTL1 depletion. Leveraging conditional protein knockdown, we performed time-resolved measurements of mature tRNA levels and directly quantified decay kinetics. We show that in the absence of heat stress, mG-hypomodified tRNAs undergo XRN2-dependent accelerated decay. Finally, partial loss of the Drosophila XRN2 ortholog, Rat1, genetically rescues male sterility of mettl1 mutants, demonstrating organismal relevance. These findings define a conserved constitutive rapid tRNA decay pathway in mammals and indicate inhibition of tRNA decay as a potential therapeutic strategy in disorders caused by tRNA hypomodification.

molecular biology↗

bioRxiv2025

Cellular fitness is determined by ribosomal protein S12-mediated release of a truncated Xrp1

Multicellular tissues require continuous optimization to maintain their structure and function by actively eliminating viable, yet unfit cells via a mechanism known as cell competition. During this process, unfit loser cells commonly upregulate the C/EBP family transcription factor Xrp1, which causes their elimination, indicating that intracellular Xrp1 levels determine cellular fitness. However, despite its central role, the mechanism by which Xrp1 is upregulated in unfit cells remains unknown. Here, we show that Xrp1 is upregulated through a previously unrecognized post-transcriptional regulatory mechanism mediated by the ribosomal protein S12 (RpS12). Surprisingly, Xrp1 mRNA is abundantly expressed even in wild-type cells, yet it is not translated. This is due to an upstream open reading frame (uORF) located in the 5UTR of the initial coding exon of Xrp1 mRNA, which inhibits the translation of the main Xrp1 ORF. Intriguingly, in unfit cells, RpS12 causes splicing-mediated skipping of this initial exon, leading to the use of an alternate start codon that generates a short isoform of Xrp1 protein, causing cell death. Notably, protein structural analysis reveals that RpS12 is highly homologous to that of a spliceosomal component SNU13, suggesting the role of RpS12 in directly regulating alternative splicing of Xrp1 mRNA. Our findings thus provide not only a mechanistic insights into how cellular fitness is determined but also how tissue optimization is achieved.

cell biology↗

bioRxiv2024

Osiris gene family defines the cuticle nano-patterns of Drosophila

Nanostructures of pores and protrusions in the insect cuticle modify molecular permeability and surface wetting and help insects sense a variety of environmental cues. The cellular mechanism specifying cuticle nanostructures is poorly understood. Here, we show that insect-specific Osiris family genes are expressed in various cuticle-secreting cells in the Drosophila head in the early stage of cuticle secretion and collectively cover nearly the entire surface of the head epidermis. We show that each sense organ cell with various cuticular nanostructures expresses a unique combination of Osiris genes. Osiris gene mutations caused various cuticle defects in the corneal nipples of the eye and pores of the chemosensory sensilla. Osiris genes provide an entry point for investigating cuticle nanopatterning in insects.

developmental biology↗

bioRxiv2023

Mettl1-dependent m7G tRNA modification is essential for maintaining spermatogenesis and fertility in Drosophila melanogaster

N7-methylguanosine (m7G) in the variable loop region of tRNA is catalyzed by METTL1/WDR4 heterodimer and stabilizes target tRNA. Here, we reveal essential functions of Mettl1 in Drosophila fertility. Knockout of Mettl1 (Mettl1-KO) lost the elongated spermatids and mature sperm, which was fully rescued by a Mettl1-transgene expression, but not a catalytic-dead Mettl1 transgene. This demonstrates that Mettl1-dependent m7G is required for spermatogenesis. Mettl1-KO resulted in a loss of m7G modification on a subset of tRNAs and a decreased level of tRNA expression. Strikingly, overexpression of the translational elongation factor, EF11, which can compete with the rapid tRNA decay (RTD) pathway in S. cerevisiae, significantly counteracted the sterility of Mettl1-KO males, supporting a critical role of m7G modification of tRNAs in spermatogenesis. Ribosome profiling showed that Mettl1-KO led to the ribosome stalling at codons decoded by tRNAs that were reduced in expression. Mettl1-KO also significantly reduced the translation efficiency of genes involved in elongated spermatid formation and sperm stability. These findings reveal a developmental role for m7G tRNA modifications and indicate that m7G modification-dependent tRNA stability differs among tissues.

molecular biology↗

bioRxiv2022

GGSDT: A unified signal detection framework for confidence data analysis

Human decision behavior entails a graded awareness of its certainty, known as a feeling of confidence. Until now, considerable interest has been paid to behavioral and computational dissociations of decision and confidence, which has raised an urgent need for measurement frameworks that can quantify the efficiency of confidence rating relative to decision accuracy (metacognitive efficiency). As a unique addition to such frameworks, we have developed a new signal detection theory paradigm utilizing the generalized gaussian distribution (GGSDT). This framework evaluates the observers internal standard deviation ratio and metacognitive efficiency through the scale and shape parameters respectively. The shape parameter quantifies the kurtosis of internal distributions and can practically be understood in reference to the proportion of the gaussian ideal observers confidence being disrupted with random guessing (metacognitive lapse rate). This interpretation holds largely irrespective of the contaminating effects of decision accuracy or operating characteristic asymmetry. Thus, the GGSDT enables hitherto unexplored research protocols (e.g., direct comparison of yes/no versus forced-choice metacognitive efficiency), expected to find applications in various fields of behavioral science. This paper provides a detailed walkthrough of the GGSDT analysis with an accompanying R package (ggsdt).

neuroscience↗

bioRxiv2022

Multi-modal deep neural decoding of visual object representation in humans

Perception and categorization of objects in a visual scene are essential to grasp the surrounding situation. However, it is unclear how neural activities in spatially distributed brain regions, especially in terms of temporal dynamics, represent visual objects. To address this issue, we explored the spatial and temporal organization of visual object representations using concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), combined with neural decoding using deep neural networks (DNNs). Visualization of the fMRI DNN revealed that visual categorization (faces or non-face objects) occurred in brain-wide cortical regions, including the ventral temporal cortex. Interestingly, the EEG DNN valued the earlier phase of neural responses for categorization and the later phase of neural responses for sub-categorization. Combination of the two DNNs improved the classification performance for both categorization and sub-categorization. These deep learning-based results demonstrate a categorization principle in which visual objects are represented in a spatially organized and coarse-to-fine manner.

neuroscience↗

bioRxiv2022

Mechanistic insights into intramembrane proteolysis by E. coli site-2 protease homolog RseP

Site-2 proteases are a conserved family of intramembrane proteases that cleave transmembrane substrates to regulate signal transduction and maintain proteostasis. Here, we elucidated crystal structures of inhibitor-bound forms of bacterial site-2 proteases including E. coli RseP. Our observations are consistent with a rearrangement of the RseP domains surrounding the active center to expose the substrate-binding site where a conserved electrostatic linkage between the transmembrane and membrane-associated domains mediates the conformational changes, suggesting that RseP has a gating mechanism to regulate substrate entry. Mutational analysis also supports that the substrate transmembrane helix is unwound by strand addition to the intramembrane {beta} sheet and is clamped at the active center for efficient cleavage. Furthermore, this substrate accommodation mechanism appears to be common across distinct intramembrane proteases.

biochemistry↗

bioRxiv2021

Performance-optimized neural networks as an explanatory framework for decision confidence

Previous work has sought to understand decision confidence as a prediction of the probability that a decision will be correct, leading to debate over whether these predictions are optimal, and whether they rely on the same decision variable as decisions themselves. This work has generally relied on idealized, low-dimensional models, necessitating strong assumptions about the representations over which confidence is computed. To address this, we used deep neural networks to develop a model of decision confidence that operates directly over high-dimensional, naturalistic stimuli. The model accounts for a number of puzzling dissociations between decisions and confidence, reveals a rational explanation of these dissociations in terms of optimization for the statistics of sensory inputs, and makes the surprising prediction that, despite these dissociations, decisions and confidence depend on a common decision variable.

neuroscience↗

bioRxiv2020

Naturally mutated spike proteins of SARS-CoV-2 variants show differential levels of cell entry

The causative agent of the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is steadily mutating during continuous transmission among humans. Such mutations can occur in the spike (S) protein that binds to the angiotensin-converting enzyme-2 (ACE2) receptor and is cleaved by transmembrane protease serine 2 (TMPRSS2). However, whether S mutations affect SARS-CoV-2 infectivity remains unknown. Here, we show that naturally occurring S mutations can reduce or enhance cell entry via ACE2 and TMPRSS2. A SARS-CoV-2 S-pseudotyped lentivirus exhibits substantially lower entry than SARS-CoV S. Among S variants, the D614G mutant shows the highest cell entry, as supported by structural observations. Nevertheless, the D614G mutant remains susceptible to neutralization by antisera against prototypic viruses. Taken together, these data indicate that the D614G mutation enhances viral infectivity while maintaining neutralization susceptibility.

microbiology↗

bioRxiv2019

Serum miR-379 expression is related to the development and progression of hypercholesterolemia in non-alcoholic fatty liver disease

IntroductionNon-alcoholic fatty liver disease (NAFLD) has a wide spectrum, eventually leading to cirrhosis and hepatic carcinogenesis. We previously reported that a series of microRNAs (miRNAs) mapped in the 14q32.2 maternally imprinted gene region (Dlk1-Dio3 mat) are related to NAFLD development and progression in a mouse model. We examined the suitability of miR-379, a circulating Dlk1-Dio3 mat miRNA, as a human NAFLD biomarker.\n\nMethodsEighty NAFLD patients were recruited for this study. miR-379 was selected from the putative Dlk1-Dio3 mat miRNA cluster because it exhibited the greatest expression difference between NAFLD and non-alcoholic steatohepatitis in our preliminary study. Real-time PCR was used to examine the expression levels of miR-379 and miR-16 as an internal control.\n\nResultsCompared to normal controls, serum miR-379 expression was significantly up-regulated in NAFLD patients. Receiver operating characteristic curve analysis suggested that miR-379 is a suitable marker for discriminating NAFLD patients from controls, with an area under the curve value of 0.72. Serum miR-379 exhibited positive correlations with alkaline phosphatase, total cholesterol, and low-density-lipoprotein cholesterol levels in patients with early stage NAFLD (Brunt fibrosis stage 0 to 1). The correlation between serum miR-379 and cholesterol levels was lost in early stage NAFLD patients treated with statins. Software-based predictions indicated that various energy metabolism-related genes, including insulin-like growth factor-1 (IGF-1) and IGF-1 receptor, are potential targets of miR-379.\n\nConclusionsSerum miR-379 exhibits high potential as a biomarker for NAFLD. miR-379 appears to increase cholesterol lipotoxicity, leading to the development and progression of NAFLD, via interference with the expression of target genes, including those related to the IGF-1 signaling pathway. Our results could facilitate future research into the pathogenesis, diagnosis, and treatment of NAFLD.

molecular biology↗

bioRxiv2018

Application of UV-cured resin as embedding/mounting media for practical, time-saving otolith specimen preparation

Otoliths are calcified structures located in the inner ears of fish, as in most vertebrates, that are responsible primarily for the perception of gravity, balance and movement, and secondarily of sound detection. Microstructural and chemical analyzes of the inner otolith growth layers, called increments, constitute powerful tools to estimate fish age and elucidate many life history and demographic traits of fish populations. Otolith analyzes often require the production of a thin cross section that includes in the same plane of view the otolith core and all microscopic layers formed from birth until the moment of collection (otolith edge). Here we report on the usefulness of UV-cured resins that have become recently popular among nail artists and hobbyists for otolith specimen preparation. We show that single-component UV-cured resins can replace successfully and advantageously the commonly used two-component Epoxy resins to obtain otolith cross sections suitable for both microstructural examination and chemical analysis by electron probe microanalysis. UV-cured resins provide on-demand, extremely rapid (minute-order) hardening and high transparency, while providing similar adhesion and mechanical support for the otoliths during processing and analysis as Epoxy resins. UV-cured resins may revolutionize otolith specimen preparation practically- and time-wise, and may be particularly useful in teaching and workshop situations in which time for otolith embedding is a constraint.

ecology↗