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Targeting protein-protein interaction interfaces with antiviral N protein inhibitor in SARS-CoV-2

Biophysical Journal 2024年第4期123卷 478-488页

作者： Hong, Jhen-Yi Lin, Shih-Chao Kehn-Hall, Kylene Zhang, Kai-Min Luo, Shun-Yuan Wu, Hung-Yi Chang, Sui-Yuan Hou, Ming-Hon Institute of Genomics and Bioinformatics and Department of Life Sciences National Chung Hsing University Taichung Taiwan Bachelor Degree Program in Marine Biotechnology College of Life Sciences National Taiwan Ocean University Keelung Taiwan Department of Biomedical Sciences and Pathobiology Virginia-Maryland College of Veterinary Medicine Virginia Polytechnic Institute and State University Blacksburg VA United States Center for Emerging Zoonotic and Arthropod-borne Pathogens Virginia Polytechnic Institute and State University Blacksburg VA United States Department of Chemistry National Chung Hsing University Taichung Taiwan Graduate Institute of Veterinary Pathobiology College of Veterinary Medicine National Chung Hsing University. Taichung Taiwan Department of Clinical Laboratory Sciences and Medical Biotechnology College of Medicine National Taiwan University Taipei Taiwan PhD Program in Medical Biotechnology National Chung Hsing University Taichung Taiwan Biotechnology Center National Chung Hsing University Taichung Taiwan

Coronaviruses not only pose significant global public health threats but also cause extensive damage to livestock-based industries. Previous studies have shown that 5-benzyloxygramine (P3) targets the Middle East respiratory syndrome coronavirus (MERS-CoV) nucleocapsid (N) protein N-terminal domain (N-NTD), inducing non-native protein-protein interactions (PPIs) that impair N protein function. Moreover, P3 exhibits broad-spectrum antiviral activity against CoVs. The sequence similarity of N proteins is relatively low among CoVs, further exhibiting notable variations in the hydrophobic residue responsible for non-native PPIs in the N-NTD. Therefore, to ascertain the mechanism by which P3 demonstrates broad-spectrum anti-CoV activity, we determined the crystal structure of the SARS-CoV-2 N-NTD:P3 complex. We found that P3 was positioned in the dimeric N-NTD via hydrophobic contacts. Compared with the interfaces in MERS-CoV N-NTD, P3 had a reversed orientation in SARS-CoV-2 N-NTD. The Phe residue in the MERS-CoV N-NTD:P3 complex stabilized both P3 moieties. However, in the SARS-CoV-2 N-NTD:P3 complex, the Ile residue formed only one interaction with the P3 benzene ring. Moreover, the pocket in the SARS-CoV-2 N-NTD:P3 complex was more hydrophobic, favoring the insertion of the P3 benzene ring into the complex. Nevertheless, hydrophobic interactions remained the primary stabilizing force in both complexes. These findings suggested that despite the differences in the sequence, P3 can accommodate a hydrophobic pocket in N-NTD to mediate a non-native PPI, enabling its effectiveness against various CoVs. © 2024 Biophysical Society

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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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A retinoic acid:YAP1 signaling axis controls atrial lineage commitment

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Cell Reports 2025年第5期44卷 115687页

作者： Abraham, Elizabeth Kostina, Aleksandra Volmert, Brett Roule, Thomas Huang, Ling Yu, Jingting Williams, April E. Megill, Emily Douglas, Aidan Pericak, Olivia M. Morris, Alex Stronati, Eleonora Larrinaga-Zamanillo, Arantza Fueyo, Raquel Zubillaga, Mikel Andrake, Mark D. Akizu, Naiara Aguirre, Aitor Estaras, Conchi Department of Cardiovascular Sciences Aging + Cardiovascular Discovery Center Lewis Katz School of Medicine Temple University Philadelphia 19140 PA United States Institute for Quantitative Health Science and Engineering Division of Developmental and Stem Cell Biology Michigan State University East Lansing 48824 MI United States Department of Biomedical Engineering College of Engineering Michigan State University East Lansing 48824 MI United States Raymond G. Perelman Center for Cellular and Molecular Therapeutics The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Integrative Genomics and Bioinformatics Core Salk Institute for Biological Studies La Jolla 92037 CA United States Cancer Epigenetics Institute Fox Chase Cancer Center Philadelphia 19111 PA United States Department of Child and Adolescence Psychiatry The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Department of Chemical and Systems Biology Stanford University School of Medicine Stanford 94305 CA United States Molecular Modeling Facility Program in Cancer Signaling and Microenvironment Fox Chase Cancer Center Philadelphia 19111 PA United States

In cardiac progenitor cells (CPCs), retinoic acid (RA) signaling induces atrial lineage gene expression and acquisition of an atrial cell fate. To achieve this, RA coordinates a complex regulatory network of downstream effectors that is not fully identified. To address this gap, we applied a functional genomics approach (i.e., scRNA-seq and snATAC-seq) to untreated and RA-treated human embryonic stem cell (hESC)-derived CPCs. Unbiased analysis revealed that the Hippo effectors YAP1 and TEAD4 are integrated with the atrial transcription factor enhancer network and that YAP1 activates RA enhancers in CPCs. Furthermore, Yap1 deletion in mouse embryos compromises the expression of RA-induced genes, such as Nr2f2, in the CPCs of the second heart field. Accordingly, in hESC-derived patterned heart organoids, YAP1 regulates the formation of an atrial chamber but is dispensable for the formation of a ventricle. Overall, our findings revealed that YAP1 cooperates with RA signaling to induce atrial lineages during cardiogenesis. © 2025 The Author(s)

关键词： atrial differentiation cardiac enhancers cardiac progenitors chamber development CP: Developmental biology heart organoids NR2F2 retinoic acid signaling SHF TEAD4 YAP1

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Artificial intelligence in gastrointestinal radiology: A review with special focus on recent development of magnetic resonance and computed tomography

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Artificial Intelligence in Gastroenterology 2021年第2期2卷 27-41页

作者： Kai-Po Chang Shih-Huan Lin Yen-Wei Chu PhD Program in Medical Biotechnology National Chung Hsing UniversityTaichung 40227Taiwan Department of Pathology China Medical University HospitalTaichung 40447Taiwan Institute of Genomics and Bioinformatics National Chung Hsing UniversityTaichung 40227Taiwan Institute of Molecular Biology National Chung Hsing UniversityTaichung 40227Taiwan Agricultural Biotechnology Center National Chung Hsing UniversityTaichung 40227Taiwan Biotechnology Center National Chung Hsing UniversityTaichung 40227Taiwan PhD Program in Translational Medicine National Chung Hsing UniversityTaichung 40227Taiwan Rong Hsing Research Center for Translational Medicine Taichung 40227Taiwan

Artificial intelligence(AI),particularly the deep learning technology,have been proven influential to radiology in the recent *** ability in image classification,segmentation,detection and reconstruction tasks have substantially assisted diagnostic radiology,and has even been viewed as having the potential to perform better than radiologists in some *** radiology,an important subspecialty dealing with complex anatomy and various modalities including endoscopy,have especially attracted the attention of AI researchers and engineers ***,recently many tools have been developed for lesion detection and image construction in gastrointestinal radiology,particularly in the fields for which public databases are available,such as diagnostic abdominal magnetic resonance imaging(MRI)and computed tomography(CT).This review will provide a framework for understanding recent advancements of AI in gastrointestinal radiology,with a special focus on hepatic and pancreatobiliary diagnostic radiology with MRI and *** fields where AI is less developed,this review will also explain the difficulty in AI model training and possible strategies to overcome the technical *** authors’insights of possible future development will be addressed in the last section.

关键词： Artificial intelligence Deep learning Image diagnosis Radiology Magnetic resonance imaging Computed tomography

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Array-Based High-Throughput Screening UNIT 5C.3 in Mouse Embryonic Stem Cells with shRNAs

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Current Protocols in Stem Cell Biology 2013年第SUPPL.26期1卷 5C.3.1-5C.3.19页

作者： Wang, Chia-Hui Ma, Nianhan Lin, Yu-Tsen Wu, Cheng-Chung Wu, Hong-Jin Yu, Ching-Chia Hsiao, Michael Lu, Frank Leigh Schuyler, Scott C. Lu, Jean Genomics Research Center Academia Sinica Taipei Taiwan Institute of Systems Biology and Bioinformatics National Central University Taoyuan Taiwan Graduate Institute of Life Sciences National Defense Medical Center Taipei Taiwan Department of Pediatrics National Taiwan University Hospital and National Taiwan University Medical College Taipei Taiwan Department of Biomedical Sciences College of Medicine Chang Gung University Taoyuan County Taiwan Genomics and System Biology Program College of Life Science National Taiwan University Taipei Taiwan National Core Facility Program for Biotechnology National RNAi Platform Taipei Taiwan

High-throughput short-hairpin RNA (shRNA) lentivirus screening is a powerful tool for identifying multiple functional regulators in embryonic stem cells (ESCs). shRNA libraries can efficiently down-regulate target genes persistently with high efficiency. The concurrent measurement of relative cell number by alamarBlue (AB) assay and undifferentiated ESC markers via an alkaline phosphatase (ALP) activity assay in the same cell culture well provides an efficient and economical way to pinpoint factors crucial for ESC pluripotency and/or expansion. Most of the renewal pathways affect ALP activity. Thus, multiple positive and negative regulators can be identified by this method. In addition, morphological changes and/or the expression levels of specific pluripotency or differentiation markers examined by immunofluorescence can be used as secondary screens for target-gene selection. In summary, we describe an efficient way to identify multiple regulators of ESC renewal using shRNAs. © 2013 by John Wiley & Sons, Inc.

关键词： Embryonic stem cells High-throughput screening RNA interference Short-hairpin RNA

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Enhancement of cellulase activity from a new strain of bacillus subtilis by medium optimization and analysis with various cellulosic substrates

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Enzyme Research 2011年第1期2011卷 151656-151656页

作者： Deka, Deepmoni Bhargavi, P. Sharma, Ashish Goyal, Dinesh Jawed, M. Goyal, Arun Centre for the Environment Indian Institute of Technology Guwahati Assam Guwahati 781039 India Department of Biotechnology Indian Institute of Technology Guwahati Assam Guwahati 781039 India Bioinformatics and Genomics Program Pennsylvania State University University Park PA 16802-5301 United States Department of Biotechnology and Environmental Sciences Thapar University Punjab Patiala 140007 Bhadson Road India

The cellulase activity of Bacillus subtilis AS3 was enhanced by optimizing the medium composition by statistical methods. The enzyme activity with unoptimised medium with carboxymethylcellulose (CMC) was 0.07 U/mL and that was significantly enhanced by CMC, peptone, and yeast extract using Placket-Burman design. The combined effects of these nutrients on cellulase activity were studied using 2² full factorial central composite design. The optimal levels of medium components determined were CMC (1.8%), peptone (0.8%), and yeast extract (0.479%). The maximum enzyme activity predicted by the model was 0.49 U/mL which was in good agreement with the experimental value 0.43 U/mL showing 6-fold increase as compared to unoptimised medium. The enzyme showed multisubstrate specificity, showing significantly higher activity with lichenan and -glucan and lower activity with laminarin, hydroxyethylcellulose, and steam exploded bagasse. The optimised medium with lichenan or -glucan showed 2.5- or 2.8-fold higher activity, respectively, at same concentration as of CMC. © 2011 Deepmoni Deka et al.

关键词： CELLULASE BACILLUS subtilis ENZYME activation BIOTECHNOLOGY BIOCHEMISTRY

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Protein-protein binding affinity and conformation changes: a structure/affinity benchmark

Protein-protein binding affinity and conformation changes: a...

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the 3rd Asia Pacific Protein Association Conference in ConJunction with The 3rd Symposiun of the Chinese Protein Society(第三届亚太地区蛋白质科学大会暨第三届全国跨学科蛋白质研究学术讨论会)

作者： Jo(e)l Janin Panagiotis L.Kastritis Iain H.Moal Howook Hwang Zhiping Weng Paul A.Bates Alexandre M.J.J.Bonvin Yeast Structural Genomics IBBMC Bat.430 Université Paris-Sud 91405-Orsay France Bijvoet Center for Biomolecular Research Utrecht University 3584CH Utrecht NL Biomolecular Modelling Laboratory Cancer Research UK London Research Institute London WC2A 3LY UK program in Bioinformatics and Integrative Biology University of Massachusetts Medical School Worcester MA 01605

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Using ensemble learning and hierarchical strategy to predict the outcomes of ESWL for upper ureteral stone treatment

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Computers in Biology and Medicine 2024年 179卷 108904-108904页

作者： Chen, Chi-Wei Liu, Wayne-Young Huang, Lan-Ying Chu, Yen-Wei Graduate Degree Program of Smart Healthcare & Bioinformatics I-Shou University Kaohsiung City Taiwan Department of Biomedical Engineering I-Shou University Kaohsiung City Taiwan Doctoral Program in Medical Biotechnology National Chung Hsing University Taichung City Taiwan Department of Urology Jen-Ai Hospital Taichung City Taiwan Graduate Institute of Genomics and Bioinformatics National Chung Hsing University Taichung City Taiwan Institute of Molecular Biology National Chung Hsing University Taichung City Taiwan Agricultural Biotechnology Center National Chung Hsing University Taichung City Taiwan Rong Hsing Research Center for Translational Medicine Taichung City Taiwan Ph. D Program in Medical Biotechnology National Chung Hsing University Taichung City Taiwan Taichung402 Taiwan

Urinary tract stones are a common and frequently recurring medical issue. Accurately predicting the success rate after surgery can help avoid ineffective medical procedures and reduce unnecessary healthcare costs. This study collected data from patients with upper ureter stones who underwent extracorporeal shock wave lithotripsy, including cases of successful as well as unsuccessful stone removal after the first and second lithotripsy procedures, and constructed prediction systems for the outcomes of the first and second lithotripsy procedures. Features were extracted from three categories of information: patient characteristics, stone characteristics, and extracorporeal shock wave lithotripsy machine data, and additional features were created using Feature Creation. Finally, the impact of features on the models was analyzed using six methods to calculate feature importance. Our prediction model for the first lithotripsy, selected from among 43 methods and seven ensemble learning techniques, achieves an AUC of 0.91. For the second lithotripsy, the AUC reaches 0.76. The results indicate that the detailed and binary information provided by patients regarding their history of stone experiences contributes differently to the predictive accuracy of the first and second lithotripsy procedures. The prediction tool is available at https://***/ks. © 2024

关键词： Machine learning

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Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis (vol 56, pg 627, 2024)

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NATURE GENETICS 2024年第6期56卷 1319-1319页

作者： Mitra, Sneha Malik, Rohan Wong, Wilfred Rahman, Afsana Hartemink, Alexander J. Pritykin, Yuri Dey, Kushal K. Leslie, Christina S. Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York City NY USA Rye Country Day School Rye NY USA Tri-Institutional Training Program in Computational Biology and Medicine New York City NY USA Hunter College City University of New York New York City NY USA Department of Computer Science Duke University Durham NC USA Program in Computational Biology and Bioinformatics Duke University Durham NC USA Center for Genomic and Computational Biology Duke University Durham NC USA Department of Computer Science Princeton University Princeton NJ USA Lewis-Sigler Institute for Integrative Genomics Princeton University Princeton NJ USA

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC–seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene–peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

关键词： Epigenetics Population genetics Software

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Comprehensive evaluation of coding region point mutations in microsatellite-unstable colorectal cancer

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EMBO Molecular Medicine 2018年第9期10卷 e8552-e8552页

作者： Kondelin, Johanna Salokas, Kari Saarinen, Lilli Ovaska, Kristian Rauanheimo, Heli Plaketti, Roosa-Maria Hamberg, Jiri Liu, Xiaonan Yadav, Leena Gylfe, Alexandra E Cajuso, Tatiana Hänninen, Ulrika A Palin, Kimmo Ristolainen, Heikki Katainen, Riku Kaasinen, Eevi Tanskanen, Tomas Aavikko, Mervi Taipale, Minna Taipale, Jussi Renkonen-Sinisalo, Laura Lepistö, Anna Koskensalo, Selja Böhm, Jan Mecklin, Jukka-Pekka Ongen, Halit Dermitzakis, Emmanouil T Kilpivaara, Outi Vahteristo, Pia Turunen, Mikko Hautaniemi, Sampsa Tuupanen, Sari Karhu, Auli Välimäki, Niko Varjosalo, Markku Pitkänen, Esa Aaltonen, Lauri A Medicum/Department of Medical and Clinical Genetics University of Helsinki Helsinki Finland Genome-Scale Biology Research Program Research Programs Unit University of Helsinki Helsinki Finland Institute of Biotechnology University of Helsinki Helsinki Finland Helsinki Institute of Life Science University of Helsinki Helsinki Finland Division of Functional Genomics Department of Medical Biochemistry and Biophysics (MBB) Karolinska Institutet Stockholm Sweden Department of Biosciences and Nutrition Karolinska Institutet Huddinge Sweden Science for Life Center Huddinge Sweden Department of Surgery Helsinki University Central Hospital Hospital District of Helsinki and Uusimaa Helsinki Finland The HUCH Gastrointestinal Clinic Helsinki University Central Hospital Helsinki Finland Department of Pathology Jyväskylä Central Hospital Jyväskylä Finland Department of Surgery Jyväskylä Central Hospital University of Eastern Finland Jyväskylä Finland Department Sport and Health Sciences University of Jyväskylä Jyväskylä Finland Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Institute for Genetics and Genomics in Geneva (iGE3) University of Geneva Geneva Switzerland Swiss Institute of Bioinformatics Geneva Switzerland

Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI colorectal cancers (CRCs), however, also contain more point mutations than microsatellite-stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit-targeted area from 24 exome-sequenced sporadic MSI CRCs and respective normals, and 12 whole-genome-sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs. The MutSigCV ranking identified several well-established MSI CRC driver genes and provided additional evidence for previously proposed CRC candidate genes as well as shortlisted genes that have to our knowledge not been linked to CRC before. Two genes, SMARCB1 and STK38L, were also functionally scrutinized, providing evidence of a tumorigenic role, for SMARCB1 mutations in particular. © 2018 The Authors. Published under the terms of the CC BY 4.0 license

关键词： cancer genetics colorectal cancer microsatellite instability

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