Biology subjects

Ohno, K.

Publications and source records attributed to Ohno, K..

11 recordsLinked to original sources

bioRxiv2025

PhenoDEL as a Novel Screening Strategy Based on Intracellular Protein Degradation Activity

Targeted protein degradation (TPD), including proteolysis targeting chimeras (PROTACs) and molecular glue degraders (MGDs), is a promising therapeutic approach. However, systematic discovery of such small molecules remains a major challenge. Here, we present PhenoDEL, a novel phenotypic DNA-encoded library (DEL) screening platform that integrates one-bead one-compound DEL (OBOC-DEL) with the Beacon(R) optofluidic system for high-throughput, single-cell analysis. By co-culturing individual OBOC-DEL beads and engineered reporter cells in nanoliter-scale chambers, PhenoDEL enables direct observation of compound-induced protein degradation at single-cell resolution. We demonstrate this approach by identifying compounds that induce degradation of FKBP12F36V-EGFP fusion proteins in PC-3 cells. The workflow allows precise linkage between compound identity and cellular phenotype via DNA barcoding and next-generation sequencing. PhenoDEL overcomes limitations of conventional screening methods, offering high sensitivity, spatial control, and scalability. This platform holds significant potential for mechanism-driven drug discovery, including identification of novel PROTACs and MGDs. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/690606v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@fe27bforg.highwire.dtl.DTLVardef@1e38ef5org.highwire.dtl.DTLVardef@be958aorg.highwire.dtl.DTLVardef@4bc48a_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Exercising with virtual reality is potentially better for the working memory and positive mood than cycling alone

Although virtual reality (VR) exercise has attracted attention as a factor in exercise habituation due to its mood-enhancing effects, its impact on brain function remains unclear. This study, involving 23 healthy university students, used functional magnetic resonance imaging (fMRI) to explore how VR exercise affects working memory, a key executive function, and its underlying neural mechanisms. Our findings indicate that a 10-min VR exercise session improved mood (arousal and vitality level) and working memory task performance (3-back task) more effectively than exercise or rest alone. Furthermore, the results confirmed that increased vitality from exercise and VR exercise interventions was associated with improved 3-back task performance. However, specific brain regions contributing to this enhancement remain unidentified. These results highlight VR exercise as the optimal exercise program for enhancing working memory function by increasing vitality level. These insights underscore VRs potential as a novel exercise modality with benefits extending beyond exercise adherence to potentially preventing dementia and depression.

neuroscience↗

bioRxiv2024

Neuroestrogens facilitate male-typical behaviors by potentiating androgen receptor signaling in medaka

In rodents, estrogens aromatized from androgens in the brain are essential for the development of male-typical behaviors. In many other vertebrates including humans and teleost fish, however, androgens facilitate these behaviors directly via the androgen receptor without aromatization into estrogens. Here we report that mutagenesis-derived male medaka fish lacking Cyp19a1b (a subtype of aromatase predominantly expressed in the brain) exhibit severely impaired male-typical mating and aggression, despite elevated brain androgen levels. These phenotypes can be rescued by estrogen administration, indicating that brain-derived estrogens are pivotal for male-typical behaviors even in teleosts. Our results further suggest that these estrogens facilitate male-typical behaviors by potentiating androgen action in the brain via the direct stimulation of androgen receptor transcription. Taken together, these findings reveal a previously unappreciated mode of action of brain-derived estrogens in shaping male-typical behaviors.

physiology↗

bioRxiv2023

RNPS1 in PSAP complex controls cyclical pre-mRNA splicing over the cell cycle

Cell cycle progression requires periodic gene expression through splicing control. However, the splicing factor that directly controls this cell cycle-dependent splicing remain unknown. Cell cycle-dependent expression of the AURKB (aurora kinase B) gene is essential for chromosome segregation and cytokinesis. We previously reported that RNPS1 is essential to maintain precise splicing in AURKB intron 5. Here we show that RNPS1 plays this role in PSAP complex with PNN and SAP18, but not ASAP complex with ACIN1 and SAP18. Whole-transcriptome sequencing of RNPS1- and PNN-deficient cells indicated that RNPS1, either alone or as PSAP complex, is an essential splicing factor for a subset of introns. Remarkably, protein expression of RNPS1, but not PNN, is coordinated with cyclical splicing in PSAP-controlled introns including AURKB intron 5. The ubiquitin-proteasome pathway is involved in the periodic decrease of RNPS1 protein level. RNPS1 is a key factor that controls periodic splicing during the cell cycle. O_FIG O_LINKSMALLFIG WIDTH=185 HEIGHT=200 SRC="FIGDIR/small/567984v3_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@84475dorg.highwire.dtl.DTLVardef@693637org.highwire.dtl.DTLVardef@16678feorg.highwire.dtl.DTLVardef@917ee0_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe AURKB gene encodes a protein kinase essential for cytokinesis and cell cycle C_LIO_LIPSAP complex (RNPS1, PNN, SAP18) is required for precise splicing in AURKB intron 5 C_LIO_LIRNPS1 protein in PSAP complex controls periodical splicing during the cell cycle C_LIO_LICyclical decrease of RNPS1 protein is mediated by the ubiquitin-proteasome pathway C_LI

molecular biology↗

bioRxiv2023

Pseudoirreversible inhibition elicits persistent efficacy of a sphigosine-1-phosphate receptor-1 antagonist

Sphingosine 1-phosphate receptor 1 (S1PR1), a G protein-coupled receptor, is required for lymphocyte trafficking, and is a promising therapeutic target in inflammatory diseases. We synthesized a competitive antagonist, KSI-6666, that persistently inhibits S1PR1 activity and effectively suppresses pathogenic inflammation. Metadynamics simulation proposed that the interaction of KSI-6666 with a methionine residue in the ligand-binding pocket of S1PR1 may inhibit the dissociation of KSI-6666 from S1PR1. Consistently, in vitro functional and mutational analyses revealed that KSI-6666 causes pseudoirreversible inhibition of S1PR1, dependent on the methionine residue of the protein and substituents on the distal benzene ring of KSI-6666. Moreover, in vivo study suggested that this pseudoirreversible inhibition is responsible for the persistent activity of KSI-6666. In this study, we discover that KSI-6666 is a potent S1PR1 antagonist, achieving pseudoirreversible inhibition of S1PR1 activity through interacting with a specific methionine residue.

pharmacology and toxicology↗

bioRxiv2020

Rapid-Eye-Movement Sleep Behavior Disorder Exhibits Similar but Distinct Gut Dysbiosis Compared to Parkinson's Disease

Gut dysbiosis has been reported repeatedly in Parkinsons disease (PD), but once in rapid-eye-movement sleep behavior disorder (RBD) from Germany. Abnormal aggregation of -synuclein fibrils causing PD possibly starts from the intestine. RBD patients frequently develop PD. Early-stage gut dysbiosis that is causally associated with PD is thus expected to be observed in RBD. We analyzed gut microbiota in 26 RBD patients and 137 controls by 16S rRNA-seq. Our RBD dataset was meta-analyzed with the German RBD dataset, and was compared with gut microbiota in 223 PD patients. Unsupervised clustering of gut microbiota by LIGER, a topic model-based tool for single-cell RNA-seq analysis, revealed four enterotypes in controls, RBD, and PD. Short-chain fatty acid (SCFA)-producing bacteria were conserved in an enterotype observed in controls and RBD, whereas they were less in enterotypes observed in PD. Genus Akkermansia and family Akkermansiaceae were consistently increased in both RBD in two countries and PD in five countries. No short-chain fatty acid (SCFA)-producing bacteria were significantly changed in RBD in two counties. In contrast, we previously reported that recognized and putative SCFA-producing genera Faecalibacterium, Roseburia, and Lachnospiraceae ND3007 group were consistently decreased in PD in five countries. Increased mucin-layer-degrading genus Akkermansia possibly accounts for the development of RBD, and an additional decrease of SCFA-producing genera is likely to be associated with the transition from RBD to PD. ImportanceNineteen studies have been reported on gut microbiota in PD, whereas only one study has been reported in RBD from Germany. RBD has the highest likelihood ratio to develop PD. Our meta-analysis of RBD in Japan and Germany revealed increased mucin-layer-degrading genus Akkermansia in RBD. Genus Akkermansia may increase the intestinal permeability, as we previously observed in PD patients, and make the intestinal neural plexus exposed to oxidative stress, which can lead to abnormal aggregation of prion-like -synuclein fibrils in the intestine. In contrast to PD, SCFA-producing bacteria were not decreased in RBD. As SCFA induces Treg cells, a decrease of SCFA-producing bacteria may be a prerequisite for the development of PD. We propose that prebiotic and/or probiotic therapeutic strategies to increase the intestinal mucin layer and to increase intestinal SCFA potentially retard the development of RBD and PD.

microbiology↗

bioRxiv2020

Subepidermal blisters are healed by wedge-shaped keratinocytes of hair follicle origin

Injury in adult tissue generally reactivates developmental programs to foster regeneration, but it is not known whether this paradigm applies to growing tissue. Here, by employing blisters, we show that epidermal wounds heal at the expense of skin development. The regenerated epidermis suppresses the expression of tissue morphogenesis genes accompanied by delayed hair follicle (HF) growth. Lineage tracing experiments, cell proliferation dynamics, and mathematical modeling reveal that the progeny of HF junctional zone stem cells, which undergo a morphological transformation, repair the blisters while not promoting HF development. In contrast, the contribution of interfollicular stem cell progeny to blister healing is small. These findings demonstrate that tissue development can be sacrificed for the sake of wound regeneration and suggest that tissue repair does not coincide with the reactivation of developmental programs in all regenerative contexts. Our study elucidates the key cellular mechanism of wound healing in skin blistering diseases.

cell biology↗

bioRxiv2019

Hierarchical non-negative matrix factorization using clinical information for microbial communities.

BackgroundThe human microbiome forms very complex communities that consist of hundreds to thousands of different microorganisms that not only affect the host, but also participate in disease processes. Several state-of-the-art methods have been proposed for learning the structure of microbial communities and to investigate the relationship between microorganisms and host environmental factors. However, these methods were mainly designed to model and analyze single microbial communities that do not interact with or depend on other communities. Such methods therefore cannot comprehend the properties between interdependent systems in communities that affect host behavior and disease processes.\n\nResultsWe introduce a novel hierarchical Bayesian framework, called BALSAMICO (BAyesian Latent Semantic Analysis of MIcrobial COmmunities), which uses microbial metagenome data to discover the underlying microbial community structures and the associations between microbiota and their environmental factors. BALSAMICO models mixtures of communities in the framework of nonnegative matrix factorization, taking into account environmental factors. This method first proposes an efficient procedure for estimating parameters. A simulation then evaluates the accuracy of the estimated parameters. Finally, the method is used to analyze clinical data. In this analysis, we successfully detected bacteria related to colorectal cancer. These results show that the method not only accurately estimates the parameters needed to analyze the connections between communities of microbiota and their environments, but also allows for the effective detection of these communities in real-world circumstances.

bioinformatics↗

bioRxiv2018

Comprehensive analysis of miRNA and protein profiles within exosomes derived from canine lymphoid tumour cell lines

Exosomes are small extracellular vesicles released from almost all cell types, which play roles in cell-cell communication. Recent studies have suggested that microenvironmental crosstalk mediated by exosomes is an important factor in the escape of tumour cells from the anti-tumour immune system in human haematopoietic malignancies. Here, we conducted comprehensive analysis of the miRNA and protein profiles within the exosomes released from four canine lymphoid tumour cell lines as a model of human lymphoid tumours. The results showed that the miRNAs and proteins abundantly contained in exosomes were similar among the four cell lines. However, the profiles of miRNA within exosomes differed among the cell lines and reflected the expression pattern of miRNAs of the parent cells. In the comparison of the amounts of miRNAs and proteins among the cell lines, those of three miRNAs (miR-151, miR-8908a-3p, and miR-486) and CD82 protein differed between exosomes derived from vincristine-sensitive and resistant cell lines. Further investigations are needed to elucidate the biological functions of the exosomal contents in the microenvironmental crosstalk of lymphoid tumours.

cancer biology↗

bioRxiv2018

A Latent Allocation Model for the Analysis of Microbial Composition and Disease

BackgroundEstablishing the relationship between microbiota and specific disease is important but requires appropriate statistical methodology. A specialized feature of microbiome count data is the presence of a large number of zeros, which makes it difficult to analyze in case-control studies. Most existing approaches either add a small number called a pseudo-count or use probability models such as the multinomial and Dirichlet-multinomial distributions to explain the excess zero counts, which may produce unnecessary biases and impose a correlation structure taht is unsuitable for microbiome data.\n\nResultsThe purpose of this article is to develop a new probabilistic model, called BERMUDA (BERnoulli and MUltinomial Distribution-based latent Allocation), to address these problems. BERMUDA enables us to describe the differences in bacteria composition and a certain disease among samples. We also provide a simple and efficient learning procedure for the proposed model using an annealing EM algorithm.\n\nConclusionWe illustrate the performance of the proposed method both through both the simulation and real data analysis. BERMUDA is implemented with R and is available from GitHub (https://github.com/abikoushi/Bermuda).

bioinformatics↗

bioRxiv2018

ENIGMA: An Enterotype-Like Unigram Mixture Model for Microbial Association Analysis

BackgroundOne of the major challenges in microbial studies is to discover associations between microbial communities and a specific disease. A specialized feature of microbiome count data is that intestinal bacterial communities have clusters reffered as enterotype characterized by differences in specific bacterial taxa, which makes it difficult to analyze these data under health and disease conditions. Traditional probabilistic modeling cannot distinguish dysbiosis of interest with the individual differences.\n\nResultsWe propose a new probabilistic model, called ENIGMA (Enterotype-like uNIGram mixture model for Microbial Association analysis), to address these problems. ENIGMA enables us to simultaneously estimate enterotype-like clusters characterized by the abundances of signature bacterial genera and environmental effects associated with the disease.\n\nConclusionWe illustrate the performance of the proposed method both through the simulation and clinical data analysis. ENIGMA is implemented with R and is available from GitHub (https://github.com/abikoushi/enigma).

bioinformatics↗