Biology subjects

Shibuya, T.

Publications and source records attributed to Shibuya, T..

8 recordsLinked to original sources

bioRxiv2026

GABAergic projection from the subiculum to the medial entorhinal cortex in mice and rats

The subiculum (SUB) is a major hippocampal output hub that routes information to cortical and subcortical targets, and its long-range projections are considered excitatory. Using enhancer-driven adeno-associated viral vectors to selectively label {gamma}-aminobutyric acid (GABA)-releasing neurons across species, here we show that the dorsal SUB also sends an inhibitory projection to the dorsal part of the medial entorhinal cortex (MEC) in mice and rats. Anterograde tracing in mice revealed that the dorsal SUB contains GABAergic neurons that project sparsely to all layers of the dorsal MEC with enrichment in superficial layers, in contrast to the glutamatergic SUB axons targeting MEC layer V. Slice electrophysiology demonstrated that these GABAergic axons form inhibitory synapses in the MEC. A subset of projecting neurons expressed parvalbumin (PV), whereas somatostatin-positive neurons were rare. Consistently, PV neuron-specific anterograde tracing recapitulated the SUB-to-MEC projection. In rats, subicular GABAergic axons were enriched in MEC layer II, and SynaptoTAG2-labeled presynaptic boutons were positive for the vesicular GABA transporter, supporting inhibitory synapse formation. Anterograde tracing of PV neurons similarly recapitulated the laminar axonal distribution in the MEC. These results identify a conserved PV-associated inhibitory SUB-to-MEC projection with species-specific laminar organization, extending the canonical excitatory view of subicular output.

neuroscience↗

bioRxiv2023

RNA editing of AZIN1 coding sites is catalyzed by ADAR1 p150 after splicing

Adenosine-to-inosine RNA editing is catalyzed by nuclear ADAR1 p110 and ADAR2, and cytoplasmic ADAR1 p150 in mammals, all of which recognize double-stranded RNAs (dsRNAs) as targets. Although its frequency is quite rare, RNA editing occurs in coding regions, which alters protein functions by exchanging amino acid sequences, and is therefore physiologically significant. In general, such coding sites are edited by ADAR1 p110 and ADAR2 prior to splicing, given that the corresponding exon forms a dsRNA structure with an adjacent intron. We previously found that RNA editing at two coding sites of antizyme inhibitor 1 (AZIN1) is sustained in Adar1 p110/Aadr2 double knockout mice. However, the molecular mechanisms underlying RNA editing of AZIN1 remain unknown. Here, we showed that Azin1 editing levels were increased upon type I interferon treatment, which activated Adar1 p150 transcription, in mouse Raw264.7 cells. Azin1 RNA editing was observed in mature mRNA but not precursor mRNA. Furthermore, we revealed that the two coding sites were editable only by ADAR1 p150 in both mouse Raw264.7 and human HEK293T cells. This unique editing was achieved by forming a dsRNA structure with a downstream exon after splicing and the intervening intron suppressed RNA editing. Therefore, deletion of a nuclear export signal from ADAR1 p150, shifting its localization to the nucleus, decreased Azin1 editing levels. Finally, we demonstrated that Azin1 RNA editing was completely absent in Adar1 p150 knockout mice. Thus, these findings indicate that RNA editing of AZIN1 coding sites is exceptionally catalyzed by ADAR1 p150 after splicing.

molecular biology↗

bioRxiv2022

Acidophilic nitrification alleviates phosphorus deficiency in hydroponics with biogas digestates

Biogas digestates can be applied to hydroponics via nitrification. However, the low solubility of phosphorus in digestates can cause phosphorus deficiency in plants. Here, we hypothesized that acidophilic nitrification might prevent this deficiency by dissolving phosphorus in the digestate. Acidophilic and neutrophilic nitrification were conducted at a pH of 3.27 and 6.25 using biogas digestates from food wastes. Acidophilic nitrification dissolved about 3.5 times more phosphorus than neutrophilic nitrification, but the increased acidity also reduced the nitrification rate, resulting in residual ammonium. We then grew lettuce hydroponically with filtrates of these digestates. The growth performance suggested that the increased phosphorus improved growth and that the residual ammonium did not inhibit it. Acidophilic nitrification was shown to be effective for use in hydroponics, particularly to alleviate phosphorus deficiency. These findings should provide new insights into resource recycling, which is essential in both urban and space environments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/522315v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@2d4e2corg.highwire.dtl.DTLVardef@675c08org.highwire.dtl.DTLVardef@1cb3139org.highwire.dtl.DTLVardef@10cd093_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2022

Privacy-Preserving Statistical Analysis of Genomic Data using Compressive Mechanism with Haar Wavelet Transform

To promote the use of personal genome information in medicine, it is important to analyze the relationship between diseases and the human genomes. Therefore, statistical analysis using genomic data is often conducted, but there is a privacy concern with respect to releasing the statistics as they are. Existing methods to address this problem using the concept of differential privacy cannot provide accurate outputs under strong privacy guarantees, making them less practical. In this study, for the first time we investigate the application of a compressive mechanism to genomic statistical data and propose two approaches. The first is to apply the normal compressive mechanism to the statistics vector along with an algorithm to determine the number of nonzero entries in a sparse representation. The second is to alter the mechanism based on the data, aiming to release significant SNPs with a high probability. In this algorithm, we apply the compressive mechanism with the input as a sparse vector for significant data and the Laplace mechanism for non-significant data. Using the Haar transform for the wavelet matrix in the compressive mechanism is advantageous to determine the number of nonzero elements and the amount of noise. In addition, we theoretically prove that our proposed method achieves{epsilon} -differential privacy. We evaluated our methods in terms of accuracy, rank error, and run time compared to the Laplace and exponential mechanisms. The results show that our second method in particular can guarantee both high privacy assurance as well as utility. The Python implementation of our experiments is available at https://github.com/ay0408/CompLaplace.

genomics↗

bioRxiv2021

Efficient Differentially Private Methods for a Transmission Disequilibrium Test in Genome Wide Association Studies

To achieve the provision of personalized medicine, it is very important to investigate the relationship between diseases and human genomes. For this purpose, large-scale genetic studies such as genome-wide association studies are often conducted, but there is a risk of identifying individuals if the statistics are released as they are. In this study, we propose new efficient differentially private methods for a transmission disequilibrium test, which is a family-based association test. Existing methods are computationally intensive and take a long time even for a small cohort. Moreover, for approximation methods, sensitivity of the obtained values is not guaranteed. We present an exact algorithm with a time complexity of [O](nm) for a dataset containing n families and m single nucleotide polymorphisms (SNPs). We also propose an approximation algorithm that is faster than the exact one and prove that the obtained scores sensitivity is 1. From our experimental results, we demonstrate that our exact algorithm is 10, 000 times faster than existing methods for a small cohort with 5, 000 SNPs. The results also indicate that the proposed method is the first in the world that can be applied to a large cohort, such as those with 106 SNPs. In addition, we examine a suitable dataset to apply our approximation algorithm. Supplementary materials are available at https://github.com/ay0408/DP-trio-TDT.

bioinformatics↗

bioRxiv2020

Disruption of Z-RNA-binding of ADAR1 induces Aicardi-Goutieres syndrome-like encephalopathy in mice

ADAR1 p150 is an enzyme responsible for adenosine-to-inosine RNA editing. Deletion of ADAR1 p150 results in embryonic lethality with a type I interferon (IFN) signature, caused by aberrant MDA5 sensing unedited transcripts. ADAR1 p150 contains a unique Z-DNA/RNA-binding domain (Z); however, the role of this domain remains unknown. A mutation has been identified in this domain in patients with Aicardi-Goutieres syndrome (AGS), an inherited interferonopathy, suggesting an essential role in avoiding MDA5 activation. Here, we show that a mutation in the Z domain reduces the editing activity of ADAR1 p150 by comparing activity between wild-type and mutated isoforms expressed in Adar1/Adar2 knockout cells. Furthermore, we created Z domain-mutated knock-in mice, which displayed severe growth retardation with abnormal organ development, including AGS-like encephalopathy with a type I IFN signature. These abnormalities were ameliorated by the concurrent deletion of MDA5. Collectively, Z-RNA-recognition contributes to ADAR1 p150-mediated RNA editing, which prevents MDA5 activation.

immunology↗

bioRxiv2019

A comparative analysis among ADAR mutant mice reveals site-specific regulation of RNA editing

Adenosine-to-inosine RNA editing is an essential posttranscriptional modification catalyzed by adenosine deaminase acting on RNA (ADAR)1 and ADAR2 in mammals. For numerous sites in coding sequences (CDS) and microRNAs (miRNAs), editing is highly conserved and has significant biological consequences, for example, by altering amino acid residues and target recognition. However, technical limitations have prevented a comprehensive and quantitative study to determine how specific ADARs contribute to each site. Here, we developed a simple method in which each RNA region with an editing site was amplified separately and combined for deep sequencing. Using this method, we compared the editing ratios of all sites that were either definitely or possibly conserved in CDS and miRNAs in the cerebral cortex and spleen of wild-type mice, Adar1E861A/E861AIfih-/- mice expressing inactive ADAR1 (Adar1 KI) and Adar2-/-Gria2R/R (Adar2 KO) mice. We found that the editing ratio was frequently upregulated in either Adar mutant mouse strain. In contrast, we found that the presence of both ADAR1 and ADAR2 was required for the efficient editing of specific sites. In addition, some sites, such as miR-3099-3p, showed no preference for either ADAR. We further created double mutant Adar1 KI Adar2 KO mice and observed viable and fertile animals with complete absence of editing, suggesting that ADAR1 and ADAR2 are the sole enzymes responsible for all editing sites in vivo. Collectively, these findings indicate that editing is regulated in a site-specific manner by the different interplay between ADAR1 and ADAR2.

molecular biology↗

bioRxiv2019

Nanopore base-calling from a perspective of instance segmentation

BackgroundNanopore sequencing is a rapidly developing third-generation sequencing technology, which can generate long nucleotide reads of molecules within a portable device in real time. Through detecting the change of ion currency signals during a DNA/RNA fragments pass through a nanopore, genotypes are determined. Currently, the accuracy of nanopore base-calling has a higher error rate than short-read base-calling. Through utilizing deep neural networks, the-state-of-the art nanopore base-callers achieve base-calling accuracy in a range from 85% to 95%.\n\nResultIn this work, we proposed a novel base-calling approach from a perspective of instance segmentation. Different from the previous sequence labeling approaches, we formulated the base-calling problem as a multi-label segmentation task. Meanwhile, we proposed a refined U-net model which we call UR-net that can model sequential dependencies for a one-dimensional segmentation task. The experiment results show that the proposed base-caller URnano achieves competitive results compared to recently proposed CTC-featured base-caller Chiron, on the same amount of training and test data for in-domain evaluation. Our results show that formulating the base-calling problem as a one-dimensional segmentation task is a promising approach.\n\nAvailabilityThe source code and data are available at https://github.com/yaozhong/URnano\n\nContactyaozhong@ims.u-tokyo.ac.jp\n\nSupplementary informationSupplementary data are available at attachment online.

bioinformatics↗