Updated on 2024/05/23

写真b

 
MARUYAMA Ryuto
 
*Items subject to periodic update by Rikkyo University (The rest are reprinted from information registered on researchmap.)
Affiliation*
College of Science Department of Life Science
Title*
Assistant Professor
Degree
博士 ( 東京大学大学院 )
Campus Career*
  • 4 2023 - Present 
    College of Science   Department of Life Science   Assistant Professor
 

Papers

  • Correction: ER Stress Decreases Gene Expression Of Transmembrane Protein 117 Via Activation of PKR-like ER Kinase. International journal

    Ryuto Maruyama, Tomoyasu Sugiyama

    Cell biochemistry and biophysics81 ( 4 ) 853 - 853   12 2023

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  • A new strategy for screening novel functional genes involved in reduction of lipid droplet accumulation. International journal

    Ryuto Maruyama, Yasuhiro Kudo, Tomoyasu Sugiyama

    BioFactors (Oxford, England)   20 11 2023

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    Language:English   Publishing type:Research paper (scientific journal)  

    Lipid droplets (LDs) are organelles that store excess lipids and provide fatty acids for energy production during starvation. LDs are also essential for cellular maintenance, but excessive accumulation of LDs triggers various cancers in addition to metabolic diseases such as diabetes. In this study, we aimed to develop a strategy to identify new genes that reduces accumulation of LDs in cancer cells using an RNA interference (RNAi) screening system employing artificial sequence-enriched shRNA libraries. Monitoring LDs by fluorescent activated cell sorting, the subsequently collected cumulative LDs cells, and shRNA sequence analysis identified a clone that potentially functioned to accumulate LDs. The clone showed no identical sequence to human Refseq. It showed very similar sequence to seven genes by allowing three mismatches. Among these genes, we identified the mediator complex subunit 6 (MED6) gene as a target of this shRNA. Silencing of MED6 led to an increase in LD accumulation and expression of the marker genes, PLIN2 and DGAT1, in fatty cells. MED6 is a member of the mediator complex that regulates RNA polymerase II transcription through transcription factor II. Some mediator complexes play important roles in both normal and pathophysiological transcription processes. These results suggest that MED6 transcriptionally regulates the genes involved in lipid metabolism and suppresses LD accumulation.

    DOI: 10.1002/biof.2019

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  • ER Stress Decreases Gene Expression Of Transmembrane Protein 117 Via Activation of PKR-like ER Kinase. International journal

    Ryuto Maruyama, Tomoyasu Sugiyama

    Cell biochemistry and biophysics81 ( 3 ) 459 - 468   9 2023

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    Language:English   Publishing type:Research paper (scientific journal)  

    Stress response is an inherent mechanism in the endoplasmic reticulum (ER). The inducers of ER cause a specific cascade of reactions, leading to gene expression. Transmembrane protein 117 (TMEM117) is in the ER and plasma membrane. In our previous study, TMEM117 protein expression was found to be decreased by an ER stress inducer. However, the mechanism underlying this decrease in TMEM117 protein expression remains unclear. This study aimed to elucidate the mechanism underlying the decrease in TMEM117 protein expression during ER stress and identify the unfolded protein response (UPR) pathway related to decreased TMEM117 protein expression. We showed that the gene expression levels of TMEM117 were decreased by ER stress inducers and were regulated by PKR-like ER kinase (PERK), indicating that TMEM117 protein expression was regulated by the signaling pathway. Surprisingly, gene knockdown of activating transcription factor 4 (ATF4) downstream of PERK did not affect the gene expression of TMEM117. These results suggest that TMEM117 protein expression during ER stress is transcriptionally regulated by PERK but not by ATF4. TMEM117 has a potential to be a new therapeutic target against ER stress-related diseases.

    DOI: 10.1007/s12013-023-01150-3

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  • Effects of the anti-inflammatory drug celecoxib on cell death signaling in human colon cancer. International journal

    Ryuto Maruyama, Yuki Kiyohara, Yasuhiro Kudo, Tomoyasu Sugiyama

    Naunyn-Schmiedeberg's archives of pharmacology396 ( 6 ) 1171 - 1185   6 2023

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    Language:English   Publishing type:Research paper (scientific journal)  

    The anti-inflammatory drug celecoxib, the only inhibitor of cyclooxygenase-2 (COX-2) with anticancer activity, is used to treat rheumatoid arthritis and can cause endoplasmic reticulum (ER) stress by inhibiting sarco/ER Ca2 +-ATPase activity in cancer cells. This study aimed to investigate the correlation between celecoxib-induced ER stress and the effects of celecoxib against cell death signaling. Treatment of human colon cancer HCT116 cells with celecoxib reduced their viability and resulted in a loss of mitochondrial membrane potential ([Formula: see text]). Additionally, celecoxib treatment reduced the expression of genes involved in mitochondrial biogenesis and metabolism such as mitochondrial transcription factor A (TFAM) and uncoupling protein 2 (UCP2). Furthermore, celecoxib reduced transmembrane protein 117 (TMEM117), and RNAi-mediated knockdown of TMEM117 reduced TFAM and UCP2 expressions. These results suggest that celecoxib treatment results in the loss of [Formula: see text] by reducing TMEM117 expression and provide insights for the development of novel drugs through TMEM117 expression.

    DOI: 10.1007/s00210-023-02399-4

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  • Deep Learning of Phase-Contrast Images of Cancer Stem Cells Using a Selected Dataset of High Accuracy Value Using Conditional Generative Adversarial Networks. International journal

    Zaijun Zhang, Hiroaki Ishihata, Ryuto Maruyama, Tomonari Kasai, Hiroyuki Kameda, Tomoyasu Sugiyama

    International journal of molecular sciences24 ( 6 )   10 3 2023

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    Language:English   Publishing type:Research paper (scientific journal)  

    Artificial intelligence (AI) technology for image recognition has the potential to identify cancer stem cells (CSCs) in cultures and tissues. CSCs play an important role in the development and relapse of tumors. Although the characteristics of CSCs have been extensively studied, their morphological features remain elusive. The attempt to obtain an AI model identifying CSCs in culture showed the importance of images from spatially and temporally grown cultures of CSCs for deep learning to improve accuracy, but was insufficient. This study aimed to identify a process that is significantly efficient in increasing the accuracy values of the AI model output for predicting CSCs from phase-contrast images. An AI model of conditional generative adversarial network (CGAN) image translation for CSC identification predicted CSCs with various accuracy levels, and convolutional neural network classification of CSC phase-contrast images showed variation in the images. The accuracy of the AI model of CGAN image translation was increased by the AI model built by deep learning of selected CSC images with high accuracy previously calculated by another AI model. The workflow of building an AI model based on CGAN image translation could be useful for the AI prediction of CSCs.

    DOI: 10.3390/ijms24065323

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  • Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology International journal

    Yumi Hanai, Hiroaki Ishihata, Zaijun Zhang, Ryuto Maruyama, Tomonari Kasai, Hiroyuki Kameda, Tomoyasu Sugiyama

    Biomedicines10 ( 5 ) 941 - 941   19 4 2022

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    Deep learning is being increasingly applied for obtaining digital microscopy image data of cells. Well-defined annotated cell images have contributed to the development of the technology. Cell morphology is an inherent characteristic of each cell type. Moreover, the morphology of a cell changes during its lifetime because of cellular activity. Artificial intelligence (AI) capable of recognizing a mouse-induced pluripotent stem (miPS) cell cultured in a medium containing Lewis lung cancer (LLC) cell culture-conditioned medium (cm), miPS-LLCcm cell, which is a cancer stem cell (CSC) derived from miPS cell, would be suitable for basic and applied science. This study aims to clarify the limitation of AI models constructed using different datasets and the versatility improvement of AI models. The trained AI was used to segment CSC in phase-contrast images using conditional generative adversarial networks (CGAN). The dataset included blank cell images that were used for training the AI but they did not affect the quality of predicting CSC in phase contrast images compared with the dataset without the blank cell images. AI models trained using images of 1-day culture could predict CSC in images of 2-day culture; however, the quality of the CSC prediction was reduced. Convolutional neural network (CNN) classification indicated that miPS-LLCcm cell image classification was done based on cultivation day. By using a dataset that included images of each cell culture day, the prediction of CSC remains to be improved. This is useful because cells do not change the characteristics of stem cells owing to stem cell marker expression, even if the cell morphology changes during culture.

    DOI: 10.3390/biomedicines10050941

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  • Role of polyphenol in sugarcane molasses as a nutrient for hexavalent chromium bioremediation using bacteria International journal

    Kento Ikegami, Yuki Hirose, Hiroaki Sakashita, Ryuto Maruyama, Tomoyasu Sugiyama

    Chemosphere250   126267 - 126267   7 2020

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    Biological methods for the removal of hexavalent chromium (Cr(VI)) from contaminated sites are safe and efficient. This is especially true because they employ microorganisms and nutrients. The use of appropriate nutrients is important for the methods to be economically feasible. This paper aims to investigate the role of polyphenol from sugarcane molasses, an inexpensive material derived from the waste of the sugar industry, as a nutrient that efficiently provides carbon for Cr(VI)-removing bacteria. The colored constituents of sugarcane molasses were characterized based on the activity of Cr(VI)-reduction and the support of bacterial growth. Molasses promoted Cr(VI)-reducing activity in a pH dependent manner. The activity was related to the colored constituents, excluding sugar, by using absorbent-column chromatography. Moreover, the activity was closely related to the polyphenol fractions, which were slightly different from those of the colored constituents. Unlike the colored constituents, the isolated sugar was sufficient to support the growth of bacteria. Polyphenols from sugarcane molasses could reduce Cr(VI) with no effect on bacterial growth. The removal of Cr(VI) combining molasses and Cr(VI)-reducing bacteria may present an additive and/or synergistic effect.

    DOI: 10.1016/j.chemosphere.2020.126267

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