Biology subjects

Hirayama, M.

Publications and source records attributed to Hirayama, M..

8 recordsLinked to original sources

bioRxiv2025

MBD8 is required for LDL2-mediated transcriptional repression downstream of H3K9me2 in Arabidopsis

Histone H3 lysine 9 methylation (H3K9me) is a conserved epigenetic mark for transcriptional gene repression. In Arabidopsis, H3K9 dimethylation (H3K9me2) promotes the removal of a transcription-associated mark, H3K4 monomethylation (H3K4me1), and this process within genes requires the histone demethylase LDL2. However, how LDL2 specifically functions in genes that accumulate H3K9me2 remains unknown. Here, we show that methyl-CpG-binding domain protein 8 (MBD8) binds to LDL2 and plays a role in H3K4me1 removal and transcriptional gene repression downstream of H3K9me2. MBD8 preferentially binds GC-poor DNA, regardless of its cytosine methylation status. Interestingly, LDL2 protein levels were significantly reduced in the mbd8 mutant background, suggesting that MBD8 stabilizes the LDL2 protein, facilitating H3K4me1 removal and the transcriptional repression of H3K9me-marked genes. The domain necessary for the MBD8-LDL2 interaction is conserved among plants. We propose that MBD proteins have diverse functions beyond their methylated DNA-binding capabilities.

plant biology↗

bioRxiv2024

CD34-positive monocytes are highly susceptible to HIV-1

HIV-1 persists in cellular reservoirs despite effective combined antiretroviral therapy (cART). CD4+ T cells are a well-known reservoir, but there is evidence suggesting that myeloid cells, including circulating monocytes, are also a clinically relevant reservoir. However, it is not fully understood which subsets of monocytes are preferentially infected in vivo. Here, we show that a monocyte fraction expressing a stem cell marker CD34 is more susceptible to HIV-1 infection than the CD34-negative major subset. In cART-untreated viremic individuals, the CD34+ fraction increased in the percentage in total monocytes, and harbored higher copies of proviral DNA than the major subset. Consistent with this, the CD34+ fraction expressed HIV-1 receptors CD4 and CCR5 at higher levels and HIV-1 restriction factors MX2 and SAMHD1 at lower levels. Interestingly, proviral DNA was still detectable in the CD34+ fraction of cART-treated virologically suppressed individuals. CD34+ monocytes were also present in lymph nodes, and expressed CD4 and CCR5 at higher levels than the major subset, as observed in peripheral blood. Moreover, CD34+ monocytes present in peripheral blood and lymph nodes highly expressed CCR7 and sphingosine-1-phosphate receptor 1 (S1PR1), critical regulators of in vivo cellular trafficking. Collectively, our findings raise the new possibility that lymph node CD34+ monocytes, which originate from the circulation, are infected with HIV-1 owing to their high susceptibility to HIV-1, and return to circulation, which explains the detection of proviral DNA in peripheral CD34+ monocytes even after long-term cART.

immunology↗

bioRxiv2023

H3K9me regulates heterochromatin silencing through incoherent feedforward loops

Histone H3 lysine-9 methylation (H3K9me) is associated with condensed and transcriptionally inactive heterochromatin1. Although it has long been known that H3K9me silences transcription to control a wide variety of biological phenomena in many eukaryotic species2,3, how the silencing is regulated under the control of H3K9me is still largely unclear. Moreover, how cells delimit regions with H3K9me to avoid silencing essential genes remains unexplored. Here, using Arabidopsis genetic systems that induce H3K9me2 and its associated non-CG DNA methylation (mCH) in the transcribed region of genes de novo, we show that the accumulation of H3K9me2/mCH paradoxically also leads to the deposition of the euchromatic mark H3K36me3. This induction of H3K36me3 depends on a SET domain methyltransferase, ASHH3, and brings about anti-silencing by preventing the demethylation of H3K4me1 by LDL2, which mediates transcriptional silencing downstream of H3K9me2/mCH4. H3K9me2/mCH-driven antagonistic actions of ASHH3-H3K36me3 and LDL2-H3K4me1-loss also regulate the de novo silencing of reactivated transposable elements (TEs). These results demonstrate that H3K9me2 both facilitates and impedes silencing, and the incoherent feedforward loops fine-tune the fate of genes and TEs. Our results illuminate a novel elaborate mechanism for partitioning chromatin domains and provide insights into the molecular basis underlying natural epigenetic variation.

genetics↗

bioRxiv2021

Hidden pathway for cytokine receptor activation: Structural insights into a marine sponge-derived lectin that activates the thrombopoietin receptor via recognition of the fucose moiety

N-glycan-mediated activation of the thrombopoietin receptor (MPL) under pathological conditions has been implicated in myeloproliferative neoplasms induced by mutant calreticulin, which forms an endogenous receptor-agonist complex that constitutively activates the receptor. However, the molecular basis for this mechanism has not been studied because no external agonists existed. We describe the structure and function of a marine sponge-derived MPL agonist, thrombocorticin (ThC), a homodimerized lectin with calcium-dependent fucose-binding properties. ThC-induced activation persists due to limited receptor internalization. The strong synergy between ThC and thrombopoietin suggests that ThC catalyzes the formation of receptor dimers on the cell surface. MPL is subject to sugar-mediated activation, where the kinetics differ from those of cytokines. This result suggests the presence of diverse receptor activation pathways in human thrombopoiesis. One-sentence summaryA marine sponge lectin catalyzes thrombopoietin receptor dimerization and activation, exhibiting strong synergy with thrombopoietin, and modulates internalization of the receptor.

cell biology↗

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↗

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

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↗