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Efficient and Stereoselective Synthesis of α(2→9) Oligosialic Acids: From Monomers to Dodecamers†

Angewandte Chemie 2011年第40期123卷

作者： Kuo‐Ching Chu Chien‐Tai Ren Chun‐Ping Lu Che‐Hsiung Hsu Tsung‐Hsien Sun Jeng‐Liang Han Bikash Pal Tsung‐An Chao Yung‐Feng Lin Shih‐Hsiung Wu Chi‐Huey Wong Chung‐Yi Wu Genomics Research Center Academia Sinica 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Institute of Biological Chemistry Academia Sinica (Taiwan) Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Institute of Bioinformatics and Structural Biology National Tsing‐Hua University Hsin‐Chu (Taiwan)

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从磷酸酯化学刍议各类磷酸酶和三磷酸核苷酶的生物化学转化与机制

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化学教育（中英文） 2023年第8期44卷 19-29页

作者：王志鹏蒋振雄 Maggie Chen 张璇马新雨车子良 Division of Genetics Department of MedicineBrigham and Women's HospitalDepartment of Biological Chemistry and Molecular PharmacologyHarvard Medical SchoolBostonMA 02115USA Department of Chemistry Texas A&M UniversityCollege StationTX77840USA 清华大学化学系北京100084 Department of Biology Texas A&M UniversityCollege StationTX 77840USA Computational Biology and Bioinformatics Program Duke Center for Genomics and Computational BiologyDuke University School of MedicineDurhamNC 27705USA Department of Microbiology Miami UniversityOxfordOH 45056USA Department of Chemistry and Chemical Biology Harvard UniversityCambridgeMA02138US 清华大学生命学院北京100084 Department of Mathematics Harvard UniversityMA 02138 Citadel Securities LLC131 SouthDearborn St.Chicago Illinois 60603USA

磷作为一切生物体的必需元素,参与了包括生命体能量代谢、结构调控、遗传信息传递等在内的必要过程,其重要性不言而喻。然而,在国内基础学科教学过程中,基于酶促反应的调控机制和反应机理被拆分到众多生化专业相关的课程中,并未能得到... 详细信息

磷作为一切生物体的必需元素,参与了包括生命体能量代谢、结构调控、遗传信息传递等在内的必要过程,其重要性不言而喻。然而,在国内基础学科教学过程中,基于酶促反应的调控机制和反应机理被拆分到众多生化专业相关的课程中,并未能得到系统性的剖析与讲解。本文从基础磷酸酯和磷酸酐的化学结构及反应特性入手,分别讨论了生物体中磷酸酯相关的调控酶类,并对最重要的一类磷酸酐——三磷酸腺苷在生物体内的转化关系做了系统性的讲解及分析。作为对磷元素相关的生命化学过程的梳理归纳,希望对化学及生命科学的教学与科研实验设计有所助益。

关键词：磷化学磷酸酯酶促反应激酶三磷酸腺苷

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Auf dem Weg zur automatisierten Oligosaccharid‐ Synthese

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Angewandte Chemie 2011年第50期123卷

作者： Che‐Hsiung Hsu Shang‐Cheng Hung Chung‐Yi Wu Chi‐Huey Wong The Genomics Research Center Academia Sinica Taiwan 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica (Taiwan) Institute of Bioinformatics and Structural Biology National Tsing‐Hua University Hsin‐Chu (Taiwan) Department of Chemistry The Scripps Research Institute 10550 North Torrey Pines Road La Jolla CA 92037 (USA)

Kohlenhydrate spielen eine wichtige Rolle bei biologischen Vorgängen. Das Fortschrittstempo der Kohlenhydratforschung ist jedoch relativ langsam, was unter anderem mit der Komplexität der Kohlenhydratstrukturen und dem Fehlen allgemein anwendbarer Synthesemethoden und Verfahren zur Untersuchung dieser Klasse von Biomolekülen zusammenhängt. Jüngste Fortschritte in der Synthese haben ergeben, dass viele dieser Probleme umgangen werden können. In diesem Aufsatz beschreiben wir die Methoden, die entwickelt wurden, um mit den Herausforderungen kohlenhydratvermittelter biologischer Vorgänge umzugehen. Besonderes Augenmerk wird dabei auf die Entwicklung der automatisierten Synthese von Oligosacchariden gerichtet. Darüber hinaus werden auch Kohlenhydrat‐Mikroarrays und Impfstoffe auf Kohlenhydratbasis behandelt.

关键词： Eintopfreaktionen Festphasensynthese Impfstoffe Kohlenhydrate Mikroarrays

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An integrative and multiscale approach to study dengue virus-like particle dynamics

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Biophysical Journal 2023年第3期122卷 44a-44a页

作者： Venkata Raghuvamsi Palur Gielenny Salem Fan-Chi Chen Shang-Rung Wu Peter J. Bond Day-Yu Chao Jan K. Marzinek Bioinformatics Institute (A∗STAR) Singapore Republic of Singapore Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung City Taiwan Microbial Genomics PhD Program National Chung Hsing University and Academia Sinica Taichung City Taiwan Department of Dentistry & Institute of Oral Medicine National Cheng Kung University Tainan Taiwan Department of Biological Sciences National University of Singapore Singapore Republic of Singapore

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Computation of Microbial Ecosystems in Time and Space (COMETS): An open source collaborative platform for modeling ecosystems metabolism

arXiv

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arXiv 2020年

作者： Dukovski, Ilija Bajić, Djordje Chacón, Jeremy M. Quintin, Michael Vila, Jean C.C. Sulheim, Snorre Pacheco, Alan R. Bernstein, David B. Riehl, William J. Korolev, Kirill S. Sanchez, Alvaro Harcombe, William R. Segrè, Daniel Bioinformatics Program Boston University BostonMA United States Biological Design Center Boston University BostonMA United States Department of Ecology and Evolutionary Biology Yale University New HavenCT United States Microbial Sciences Institute Yale University West HavenCT United States Department of Ecology Evolution and Behavior University of Minnesota St. PaulMN United States BioTechnology Institute University of Minnesota St. PaulMN United States Department of Biotechnology and Food Science Norwegian University of Science and Technology Trondheim Norway Department of Biotechnology and Nanomedicine SINTEF Industry Trondheim Norway Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory BerkeleyCA United States Department of Biomedical Engineering Boston University BostonMA United States Department of Physics Boston University BostonMA United States Department of Biology Boston University BostonMA United States

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are also emerging as a valuable avenue for predicting, understanding and designing microbial communities. COMETS (Computation Of Microbial Ecosystems in Time and Space) was initially developed as an extension of dynamic flux balance analysis, which incorporates cellular and molecular diffusion, enabling simulations of multiple microbial species in spatially structured environments. Here we describe how to best use and apply the most recent version of this platform, COMETS 2, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, as well as several new biological simulation modules, including evolutionary dynamics and extracellular enzyme activity. COMETS 2 provides user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, and comprehensive documentation and tutorials, facilitating the use of COMETS for researchers at all levels of expertise with metabolic simulations. This protocol provides a detailed guideline for installing, testing and applying COMETS 2 to different scenarios, with broad applicability to microbial communities across biomes and scales. Copyright © 2020, The Authors. All rights reserved.

关键词： Microorganisms

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401P Moderate-term dimethyl fumarate treatment reduces fibrosis of skeletal and cardiac muscle in in the mdx mouse model of Duchenne muscular dystrophy

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Neuromuscular Disorders 2024年 43卷 104441.272-104441.272页

作者： Timpani, C. Kourakis, S. Bagaric, R. Qi, B. Ali, B. Spiesberger, G. Boyer, R. Kandhari, N. Yan, X. Stupka, N. van Putten, M. Aartsma-Rus, A. Deveson-Lucas, D. Fischer, D. Rybalka, E. Victoria University Institute for Health & Sport Melbourne Australia Australian Institute for Musculoskeletal Science Inherited and Acquired Myopathy Program St Albans Australia The University of Melbourne Department of Medicine - Western Health Melbourne Medical School St Albans Australia Monash University Monash Genomics and Bioinformatics Platform Biomedical Discovery Institute Clayton Australia Australian Institute for Musculoskeletal Science Sarcopenia Research Program St Albans Australia Leiden University Medical Center Department of Human Genetics Leiden Netherlands University Children's Hospital of Basel Division of Neuropediatric and Developmental Medicine Basel Switzerland

Duchenne muscular dystrophy (DMD), a fatal inherited neuromuscular disease, is associated with hyper-immune responsivity secondary to the intense muscle degeneration caused by primary dystrophin deficiency. Corticosteroids (e.g., prednisone (PRED)) are potent immunomodulators that have been used in standard care for decades to control this aspect. However, for many patients, the side-effect profile is significant despite prolonging ambulation, which can limit clinical utility. Other immunomodulatory drugs could have a better benefit to side-effect profile. We recently demonstrated short-term treatment with repurposed dimethyl fumarate (DMF), an alternative pharmacological immunomodulator indicated for multiple sclerosis, more selectively modulates the DMD disease program compared to PRED. Here, we aimed to evaluate the therapeutic potential of moderate-term DMF treatment in dystrophic mdx mice. Male mdx mice were gavaged daily from 3 weeks of age with either vehicle (0.5% methylcellulose; VEH), DMF (100mg/kg), PRED (5mg/kg) or combinatorial DMF+PRED until 8 weeks of age. WT controls received daily VEH gavage. Bi-weekly treadmill running was used to aggravate the mdx phenotype from 4 weeks of age. At the experimental endpoint, grip strength and motor co-ordination (rotarod) were assessed. Then mice were sacrificed, and muscle damage, fibrosis and inflammation were quantified in the quadriceps and heart using H&E, Masson's Trichrome and pan macrophage CD68+ marker immuno-/histology staining, respectively. The quadriceps transcriptome was also assessed via bulk RNA sequencing. In mdx mice, DMF was the only treatment to improve a functional index (grip strength). DMF treatment alone improved muscle quality by reducing fibrosis of the quadriceps and heart. However, at 8 weeks age, a more stable phase of murine disease, it had no effect on the unhealthy:healthy tissue ratio. In combination, DMF+PRED treatment notably increased fibrosis of quadriceps muscle. This may be as

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Corrigendum to "Comparative genome analysis of Lactobacillus plantarum GB-LP3 provides candidates of survival-related genetic factors" [Infect. Genet. Evol. 9 (2017) 218-226]

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Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 2018年 59卷 186页

作者： Soomin Jeon Jaehoon Jung Kwondo Kim DongAhn Yoo Chanho Lee Jungsun Kang Kyungjin Cho Dae-Kyung Kang Woori Kwak Sook Hee Yoon Heebal Kim Seoae Cho Department of Agricultural Biotechnology and Research Institute of Population Genomics Seoul National University Seoul 151-742 Republic of Korea. CNK genomics Main Bldg. #514 SNU Research Park Seoul National University Mt.4-2 NakSeoungDae Seoul 151-919 Gwanakgu Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Seoul 151-742 Republic of Korea. Genebiotech Co. Ltd. Seocho-Gu Seoul 137-787 Republic of Korea. Department of Animal Resources Science Dankook University Cheonan Republic of Korea. Department of Agricultural Biotechnology and Research Institute of Population Genomics Seoul National University Seoul 151-742 Republic of Korea CNK genomics Main Bldg. #514 SNU Research Park Seoul National University Mt.4-2 NakSeoungDae Seoul 151-919 Gwanakgu Republic of Korea. Electronic address: seoae@***.

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Functional Analysis of an FHOD3 Founder Variant Causing Hypertrophic Cardiomyopathy in the Balkans Population

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Heart, Lung and Circulation 2024年 33卷 S97-S98页

作者： R. Bagnall S. Li G. Ranpura M. Holliday B. Hanna J. Ingles S. Kumar C. Semsarian S. Lim Bioinformatics and Molecular Genetics Centenary Institute Newtown NSW Australia The University of Sydney Sydney NSW Australia Agnes Ginges Centre for Molecular Cardiology Centenary Institute Newtown NSW Australia Department of Medical Genetics Westmead Hospital Sydney NSW Australia Genomics and Inherited Disease Program Garvan Institute of Medical Research Sydney NSW Australia Department of Cardiology Royal Prince Alfred Hospital Sydney NSW Australia Department of Cardiology Westmead Hospital Sydney NSW Australia

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Artificial intelligence-driven genotype–epigenotype–phenotype approaches to resolve challenges in syndrome diagnostics

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eBioMedicine 2025年 115卷 105677-105677页

作者： Mak, Christopher C.Y. Klinkhammer, Hannah Choufani, Sanaa Reko, Nikola Christman, Angela K. Pisan, Elise Chui, Martin M.C. Lee, Mianne Leduc, Fiona Dempsey, Jennifer C. Sanchez-Lara, Pedro A. Bombei, Hannah M. Bernat, John A. Faivre, Laurence Mau-Them, Frederic Tran Palafoll, Irene Valenzuela Canham, Natalie Sarkar, Ajoy Zarate, Yuri A. Callewaert, Bert Bukowska-Olech, Ewelina Jamsheer, Aleksander Zankl, Andreas Willems, Marjolaine Duncan, Laura Isidor, Bertrand Cogne, Benjamin Boute, Odile Vanlerberghe, Clémence Goldenberg, Alice Stolerman, Elliot Low, Karen J. Gilard, Vianney Amiel, Jeanne Lin, Angela E. Gordon, Christopher T. Doherty, Dan Krawitz, Peter M. Weksberg, Rosanna Hsieh, Tzung-Chien Chung, Brian H.Y. Department of Paediatrics and Adolescent Medicine School of Clinical Medicine The University of Hong Kong Hong Kong SAR China Institute for Genomic Statistics and Bioinformatics University Hospital Bonn Rheinische Friedrich-Wilhelms-Universität Bonn Bonn Germany Institute for Medical Biometry Informatics and Epidemiology University Hospital Bonn Rheinische Friedrich-Wilhelms-Universität Bonn Bonn Germany Genetics and Genome Biology Program Research Institute The Hospital for Sick Children Toronto M5G 1X8 ON Canada Department of Pediatrics University of Washington Seattle 98195 WA United States Laboratory of Embryology and Genetics of Human Malformations Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163 Institut Imagine Université Paris Cité Paris 75015 France CHU Lille Centre de Référence Anomalies du Développement et Syndromes Malformatifs Lille F-59000 France Department of Pediatrics Cedars-Sinai Medical Center Los Angeles CA United States Division of Medical Genetics and Genomics Stead Family Department of Pediatrics University of Iowa Hospitals Iowa City IA United States Centre de Génétique et Centre de Référence Anomalies du Développement et Syndromes Malformatifs FHU TRANSLAD Institut GIMI Hôpital d'Enfants CHU Dijon-Bourgogne Dijon France Equipe GAD INSERM UMR1231 Université de Bourgogne Franche Comté Dijon France UF 6254 Innovation en diagnostic Génomique des Maladies Rares Centre Hospitalier Universitaire de Dijon Dijon France Department of Clinical and Molecular Genetics University Hospital Vall d'Hebron and Medicine Genetics Group Valle Hebron Research Institute Barcelona Spain Liverpool Centre for Genomic Medicine Liverpool Women's Hospital Crown Street Liverpool United Kingdom Department of Clinical Genetics Nottingham University Hospitals National Health Service Trust Nottingham NG5 1PB United Kingdom Section of Genetics and Metabolism University of Arkansas for Medical Sciences Little Rock 72701 AR Uni

Background: Decisions to split two or more phenotypic manifestations related to genetic variations within the same gene can be challenging, especially during the early stages of syndrome discovery. Genotype-based diagnostics with artificial intelligence (AI)-driven approaches using next-generation phenotyping (NGP) and DNA methylation (DNAm) can be utilized to expedite syndrome delineation within a single gene. Methods: We utilized an expanded cohort of 56 patients (22 previously unpublished individuals) with truncating variants in the MN1 gene and attempted different methods to assess plausible strategies to objectively delineate phenotypic differences between the C-Terminal Truncation (CTT) and N-Terminal Truncation (NTT) groups. This involved transcriptomics analysis on available patient fibroblast samples and AI-assisted approaches, including a new statistical method of GestaltMatcher on facial photos and blood DNAm analysis using a support vector machine (SVM) model. Findings: RNA-seq analysis was unable to show a significant difference in transcript expression despite our previous hypothesis that NTT variants would induce nonsense mediated decay. DNAm analysis on nine blood DNA samples revealed an episignature for the CTT group. In parallel, the new statistical method of GestaltMatcher objectively distinguished the CTT and NTT groups with a low requirement for cohort number. Validation of this approach was performed on syndromes with known DNAm signatures of SRCAP, SMARCA2 and ADNP to demonstrate the effectiveness of this approach. Interpretation: We demonstrate the potential of using AI-based technologies to leverage genotype, phenotype and epigenetics data in facilitating splitting decisions in diagnosis of syndromes with minimal sample requirement. Funding: The specific funding of this article is provided in the acknowledgements section. © 2025 The Authors

关键词： GestaltMatcher MCTT Methylation MN1 Splitting Support vector machine

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Genome-wide analyses identify 30 loci associated with obsessive–compulsive disorder

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Nature Genetics 2025年 1-13页

作者： Strom, Nora I. Gerring, Zachary F. Galimberti, Marco Yu, Dongmei Halvorsen, Matthew W. Abdellaoui, Abdel Rodriguez-Fontenla, Cristina Sealock, Julia M. Bigdeli, Tim Coleman, Jonathan R. Mahjani, Behrang Thorp, Jackson G. Bey, Katharina Burton, Christie L. Luykx, Jurjen J. Zai, Gwyneth Alemany, Silvia Andre, Christine Askland, Kathleen D. Bäckman, Julia Banaj, Nerisa Barlassina, Cristina Nissen, Judith Becker Bienvenu, O. Joseph Black, Donald Bloch, Michael H. Børte, Sigrid Bosch, Rosa Breen, Michael Brennan, Brian P. Brentani, Helena Buxbaum, Joseph D. Bybjerg-Grauholm, Jonas Byrne, Enda M. Cabana-Dominguez, Judit Camarena, Beatriz Camarena, Adrian Cappi, Carolina Carracedo, Angel Casas, Miguel Cavallini, Maria Cristina Ciullo, Valentina Cook, Edwin H. Crosby, Jesse Cullen, Bernadette A. De Schipper, Elles J. Delorme, Richard Djurovic, Srdjan Elias, Jason A. Estivill, Xavier Falkenstein, Martha J. Fundin, Bengt T. Garner, Lauryn Gironda, Christina Goes, Fernando S. Grados, Marco A. Grove, Jakob Guo, Wei Haavik, Jan Hagen, Kristen Harrington, Kelly Havdahl, Alexandra Höffler, Kira D. Hounie, Ana G. Hucks, Donald Hultman, Christina Janecka, Magdalena Jenike, Eric Karlsson, Elinor K. Kelley, Kara Klawohn, Julia Krasnow, Janice E. Krebs, Kristi Lange, Christoph Lanzagorta, Nuria Levey, Daniel Lindblad-Toh, Kerstin Macciardi, Fabio Maher, Brion Mathes, Brittany McArthur, Evonne McGregor, Nathaniel McLaughlin, Nicole C. Meier, Sandra Miguel, Euripedes C. Mulhern, Maureen Nestadt, Paul S. Nurmi, Erika L. O’Connell, Kevin S. Osiecki, Lisa Ousdal, Olga Therese Palviainen, Teemu Pedersen, Nancy L. Piras, Federica Potluri, Sriramya Rabionet, Raquel Ramirez, Alfredo Rauch, Scott Reichenberg, Abraham Riddle, Mark A. Ripke, Stephan Rosário, Maria C. Sampaio, Aline S. Schiele, Miriam A. Skogholt, Anne Heidi Sloofman, Laura G. Smit, Jan Artigas, María Soler Thomas, Laurent F. Tifft, Eric Vallada, Homero van Kirk, Nathanial Veenstra-VanderWeele, Jeremy Vulink, Nienke N. Walker, Christopher P. Wang, Ying Wendland, Jens R. Winsvold Department of Psychology Humboldt-Universität zu Berlin Berlin Germany Department of Psychiatric Phenomics and Genomics (IPPG) Ludwig-Maximilians University Munich Munich Germany Centre for Psychiatry Research Department of Clinical Neuroscience Karolinska Institutet and Stockholm Health Services Region Stockholm Stockholm Sweden Department of Biomedicine Aarhus University Aarhus Denmark University Hospital of Psychiatry and Psychotherapy University of Bern Bern Switzerland Department of Mental Health and Neuroscience Translational Neurogenomics QIMR Berghofer Medical Research Institute Brisbane QLD Australia Department of Population Health and Immunity Healthy Development and Ageing Walter and Eliza Hall Institute of Medical Research Melbourne VIC Australia Department of Psychiatry Human Genetics Yale University New Haven CT United States VA Connecticut Healthcare System West Haven CT United States Department of Center for Genomic Medicine Psychiatric and Neurodevelopmental Genetics Unit Massachusetts General Hospital Boston MA United States Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA United States Department of Genetics University of North Carolina at Chapel Hill Chapel Hill NC United States Department of Psychiatry Amsterdam University Medical Centers University of Amsterdam Amsterdam Netherlands Center for Research in Molecular Medicine and Chronic Diseases (CiMUS) Genomics and Bioinformatics University of Santiago de Compostela Santiago de Compostela Spain Grupo de Medicina Xenómica Genetics Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS) Santiago de Compostela Spain Vanderbilt Genetics Institute Vanderbilt University Nashville TN United States Department of Psychiatry and Behavioral Sciences SUNY Downstate Health Sciences University Brooklyn NY United States VA NY Harbor Healthcare System Brooklyn NY United States Social Genetic and Developmental Psychiatry Centre Insti

Obsessive–compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D₁ and D₂ type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index. © The Author(s) 2025.

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