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IDH1 fine-tunes cap-dependent translation initiation

Journal of Molecular Cell Biology 2019年第10期11卷 816-828页

作者： Lichao Liu JYuyang Lu Fajin Li Xudong Xing Tong Li Xuerui Yang Xiaohua Shen Tsinghua-Peking Center for Life Sciences School of Medicine and School of Life SciencesTsinghua UniversityBeijing 100084China MOE Key Laboratory of Bioinformatics Center for Synthetic Systems BiologySchool of Life SciencesTsinghua UniversityBeijing 100084China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua UniversityBeijing 100084China

The metabolic enzyme isocitrate dehydrogenase 1(IDH1)catalyzes the oxidative decarboxylation of isocitrate to a-ketoglutarate(a-KG).Its mutation often leads to aberrant gene expression in ***1 was reported to bind thousands of RNA transcripts in a sequence-dependent manner;yet,the functional significance of this RNA-binding activity remains ***,we report that IDH1 promotes mRNA translation via direct associations with polysome mRNA and translation *** proteomic analysis in embryonic stem cells(ESCs)revealed strikingenrichmentof ribosomal proteins and translation regulators in IDH1-bound protein *** performed ribosomal profiling and analyzed mRNA transcripts that are associated with actively translating ***,knockout of IDH1 in ESCs led to significant downregulation of polysome-bound mRNA in IDH1 targets and subtle upregulation of ribosome densities at the start codon,indicating inefficient translation initiation upon loss of *** IDH1 to a luciferase mRNA via the MS2-MBP system promotes luciferase translation,independently of the catalytic activity of ***,IDH1 fails to enhance luciferase translation driven by an internal ribosome entry ***,these results reveal an unforeseen role of IDH1 in fine-tuning cap-dependent translation via the initiation step.

关键词： IDH1 proteomic interactome translation regulation RNA-binding protein

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Ecological landscapes guide the assembly of optimal microbial communities

arXiv

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arXiv 2021年

作者： George, Ashish B. Korolev, Kirill S. Department of Physics Boston University BostonMA02215 United States Biological Design Center Boston University BostonMA02215 United States Carl R. Woese Institute for Genomic Biology Department of Plant Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Graduate Program in Bioinformatics Boston University BostonMA02215 United States

Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia. © 2021, CC BY-NC-ND.

关键词： Microorganisms

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Sleep Quality and Daily Activity Association Assessment From Wearable Device Data

Sleep Quality and Daily Activity Association Assessment From...

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International Conference on Information Management and Technology (ICIMTech)

作者： Bharuno Mahesworo Arif Budiarto Alam Ahmad Hidayat Haryono Soeparno Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Having good sleep is important to maintain physical and mental health. However, many young adults suffer poor sleep due to work or academic demands. Even more, sleep is associated with stress which is many young adults experienced it. To solve this problem, many epidemiologic studies suggest that exercise may improve sleep quality. On the other hand, several studies show that daily activity has no association with sleep quality. In this study, we tried to find more evidence of whether the daily activity has an association with sleep quality or not. We used a commercially available wearable device to capture the subject's heart rate, step count and deep sleep duration for 7 months. Then we used linear regression, XGBoost, and Long Short-Term Memory to find an association between these variables. The results show that there was no association between these variables.

关键词： Sleep Heart rate Biomedical monitoring Computer science Predictive models bioinformatics Data science

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A zinc finger-dependent, PRDM13-driven mechanism regulates retinal progenitor cell fate from mouse embryonic stem cells via WNT signaling

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Stem cell reports 2025年 102508页

作者： Brian W Basinski Yuanhao Huang Qiang Li Charukesi D Sivakumar Tyler J Carman Hana M Pan Jing Xu D Ford Hannum Jie Liu Rajesh C Rao Department of Ophthalmology and Visual Science W.K. Kellogg Eye Center University of Michigan Ann Arbor MI 48105 USA Molecular and Cellular Pathology Graduate Program Department of Pathology University of Michigan Ann Arbor MI 48105 USA. Department of Computational Medicine and Bioinformatics Ann Arbor MI 48105 USA. Department of Ophthalmology and Visual Science W.K. Kellogg Eye Center University of Michigan Ann Arbor MI 48105 USA. Molecular and Cellular Pathology Graduate Program Department of Pathology University of Michigan Ann Arbor MI 48105 USA Department of Computational Medicine and Bioinformatics Ann Arbor MI 48105 USA Department of Human Genetics University of Michigan Ann Arbor MI 48105 USA Rogel Cancer Center University of Michigan Ann Arbor MI 48105 USA Center of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI 48105 USA Center for RNA Biomedicine University of Michigan Ann Arbor MI 48105 USA A. Alfred Taubman Medical Research Institute University of Michigan Ann Arbor MI 48105 USA Section of Ophthalmology Surgical Service Veterans Administration Ann Arbor Healthcare System Ann Arbor MI 48105 USA. Electronic address: rajeshr@umich.edu.

The transcriptional regulation underlying eye field (retinal primordium) development requires precise control, yet the mechanisms guiding lineage-specific differentiation within the central nervous system (CNS) remain incompletely understood. Using neuroectoderm (NE) organoids derived from mouse embryonic stem cells, we investigate the role of PRDM13 in eye field specification. We demonstrate that Prdm13 expression inhibits RX eye field fate but permits non-eye field NE differentiation, an effect that depends on its first and second zinc-finger domains. Prdm13 activates the WNT/β-catenin signaling pathway during differentiation, leading to downregulation of key transcription factors crucial for establishing the eye field. Pharmacological inhibition of WNT signaling abolishes PRDM13-mediated suppression, restoring RX eye field differentiation. Our work reveals a previously undescribed PRDM13-WNT signaling axis that regulates lineage-specific neural differentiation of embryonic stem cells.

关键词： PRDM13 WNT organoids retinal development stem cells

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High Resolution Imaging of Virus in Liquid Droplets: The Application of Cryo-TEM Methodology to Improve Liquid-phase TEM Imaging of Biological Materials

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Microscopy and Microanalysis 2021年第S2期27卷 19-20页

作者： Madeline J. Dukes GM Jonaid William J. Dearnaley Michael A. Casasanta Deborah F. Kelly Protochips Inc.Morrisville NC USA. Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA USA. Department of Biomedical Engineering Pennsylvania State University University Park PA USA. Materials Research Institute Pennsylvania State University University Park PA USA. Center for Structural Oncology Pennsylvania State University University Park PA16802 USA.

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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Buparlisib and ponatinib inhibit aggressiveness of cholangiocarcinoma cells via suppression of IRS1-related pathway by targeting oxidative stress resistance

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Biomedicine and Pharmacotherapy 2024年 180卷 117569-117569页

作者： Kaewlert, Waleeporn Sakonsinsiri, Chadamas Lert-itthiporn, Worachart Mahalapbutr, Panupong Ali, Saba Rungrotmongkol, Thanyada Jusakul, Apinya Armartmuntree, Napat Pairojkul, Chawalit Feng, Guofei Ma, Ning Pinlaor, Somchai Murata, Mariko Thanan, Raynoo Department of Biochemistry Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Cholangiocarcinoma Research Institute Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Program in Bioinformatics and Computational Biology Graduated School Chulalongkorn University Bangkok 10330 Thailand The Center for Research and Development of Medical Diagnostic Laboratories Faculty of Associated Medical Sciences Khon Kaen University Khon Kaen 40002 Thailand Department of Medical Science Amnatcharoen Campus Mahidol University Amnat Charoen 37000 Thailand Department of Pathology Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Department of Environmental and Molecular Medicine Mie University Graduate School of Medicine Mie 514-8507 Japan Graduate School of Health Science Suzuka University of Medical Science Suzuka Mie 510-0226 Japan Department of Parasitology Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand

Cholangiocarcinoma (CCA) is an oxidative stress-driven liver cancer with bile duct epithelial cell phenotypes and currently lacks effective treatments, making targeted drug therapy urgently needed. Oxidative stress plays a critical role in CCA carcinogenesis, involving cells with oxidative stress resistance via upregulation of the PI3K and MEKK3 signaling pathways. In this study, we investigated the antineoplastic efficacy of a PI3K inhibitor (buparlisib) and a multi-tyrosine kinase inhibitor (ponatinib) on CCA. The cytotoxicity of the drug combination was studied in vitro using CCA cell lines and in vivo using CCA xenograft models. It was found that the drug combination suppressed growth, colony formation, and migration abilities of CCA cells and induced oxidative damage, cell cycle arrest, and autophagy by suppressing MEKK3 and YAP1 through inhibition of insulin receptor substrate 1 (IRS1) signaling. Moreover, the drugs would potentially bind to the IRS1 protein, significanly decreasing IRS1 phosphorylation. Additionally, the drug combination significantly diminished the expression of YAP1, the cell proliferation marker and an antioxidant regulator, and increased oxidative stress-responsive markers in the xenograft model. In conclusion, targeting oxidative stress resistance with combined buparlisib and ponatinib suppressed tumor growth and migration by repressing IRS1-related pathways and ultimately inducing oxidative damage, suggesting the potential for targeted therapy and clinical trials in CCA patients over the use of a single drug. © 2024 The Authors

关键词： Anti-cancer Bile duct cancer Buparlisib Insulin receptor substrate 1 Ponatinib Targeted therapy

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Ten-Year Compilation of #SaveKPK Twitter Dataset

Ten-Year Compilation of #SaveKPK Twitter Dataset

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International Conference on Information Management and Technology (ICIMTech)

作者： Reza Rahutomo Arif Budiarto Kartika Purwandari Anzaludin Samsinga Perbangsa Tjeng Wawan Cenggoro Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Politic is one of the most favorite topics to discuss in social media for people in Indonesia. It was proven when a people movement to support the Commission of Corruption Eradication (KPK) named #SaveKPK has been enlived for ten years and become a trending topic on Twitter for several times. In this research, all tweets contain `#SaveKPK' are crawled and compiled using an alternative algorithm to get twitter historical data instead of using Twitter API. The result described the characteristic of the dataset statistically, from the most frequently used words to the most active users. A clustering algorithm named Latent Dirichlet Allocation (LDA) was run over the gathered text dataset to discover most relevant keywords using unsupervised learning approach.

关键词： Twitter Computer science Resource management Natural language processing Information management Databases

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An Integrating Analysis Reveals Key Regulatory Networks in Breast Cancer

An Integrating Analysis Reveals Key Regulatory Networks in B...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Wenjuan Zhang Yifan Zhang William Yang Dan Li Jun S. Liu Mary Qu Yang MidSouth Bioinformatics Center and Bioinformatics Program University of Arkansas at Little Rock and Univ. of Arkansas Medical Sciences Little Rock USA Department of Computer Science Carnegie Mellon University School of Computer Science Pittsburgh USA Department of Statistics Harvard University Cambridge USA

ISBN: (数字)9781728155845

ISBN: (纸本)9781728155852

Breast cancer is the second most common cancer diagnosed with women in the United States. Treatment of the disease has been substantially improved in recent years. However, the 5-year survival rate of patients with distant metastatic breast cancer is still below 30%. The transcription factors (TFs) regulate the expression of many genes and are commonly mutated in cancer. It has been shown that targeting transcript factor activity is effective in cancer treatment. In this study, we performed a large-scale integrative analysis to reveal the TFs that play essential regulatory roles in disease development. We first constructed expression networks based on gene expression correlation patterns in normal and tumor tissues. Incorporating the Bayesian analysis, TF and target interactions and methylation analysis with the expression networks, we identified a total of 19 regulatory networks consisting of differentially expressed genes. Gene set enrichment analysis of TF targets further revealed four core regulatory networks that were mainly controlled by 10 transcription factors. The dysregulated gene networks and their major TF regulators inferred by our study provide new insights into the regulatory mechanisms of breast cancer and offer new therapeutic targets.

关键词： Breast cancer bioinformatics Bayes methods Rocks Tumors

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Uncovering chromatin accessibility and cancer diagnostic potential via cell-free DNA utilization

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Science Bulletin 2024年第19期69卷 2987-2992页

作者： Jie Li Jiahui Chen Xin Sun Heli Yang Keyong Sun Chang Liu Yongwang Wang Mengyue Xu Xin Ji Ji Zhang Xiaojiang Wu Anqiang Wang Biao Fan Xiaolu Zhang Yue Wu Peilin Cui Junya Peng Yupei Zhao Wenming Wu Honghao Yu Zhaode Bu Jiafu Ji Xun Lan Department of Basic Medical Sciences School of MedicineTsinghua UniversityBeijing 100084China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Center of Gastrointestinal CancerPeking University Cancer Hospital&InstituteBeijing 100142China Guangxi Key Laboratory of Drug Discovery and Optimization Guilin Medical UniversityGuilin 541001China Department of General Surgery Peking Union Medical College HospitalPeking Union Medical CollegeBeijing 100730China Department of Internal Medicine International Medical Services(IMS)Beijing Tiantan Hospital of Capital Medical UniversityBeijing 100070China Institute of Clinical Medicine Peking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100730China Academy of Biomedical Engineering Kunming Medical UniversityKunming 650500China MOE Key Laboratory of Bioinformatics Tsinghua UniversityBeijing 100084China Peking-Tsinghua-NIBS Joint Graduate Program Tsinghua UniversityBeijing 100084China Tsinghua-Peking Joint Center for Life Sciences Tsinghua UniversityBeijing 100084China Department of Anesthesiology Affiliated Hospital of Guilin Medical UniversityGuilin 541000China Key Laboratory of Medical Biotechnology and Translational Medicine Guilin Medical UniversityGuilin 541001China State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100730China Department of Gastric Surgery Zhejiang Cancer HospitalHangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhou 310022China The Islands Healthcare Complex-Macao Medical Center of Peking Union Medical College Hospital Macao 999078China

Gene expression patterns of tumor cells can be inferred from features of circulating cell-free DNA(cfDNA),such as histone modifications and fragmentation patterns at ***,the direct relationship between cfDNA patterns and tumor-specific chromatin accessibility has not yet been experimentally established,limiting its current application to cancer diagnosis alone.

关键词： diagnosis cancer alone

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