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Structure and Dynamics of Oligonucleotides in the Gas Phase†

Angewandte Chemie 2014年第2期127卷

作者： Annalisa Arcella Jens Dreyer Emiliano Ippoliti Ivan Ivani Guillem Portella Valérie Gabelica Paolo Carloni Modesto Orozco Institute for Research in Biomedicine (IRB Barcelona) Joint BSC‐CRG‐IRB Program on Computational Biology Barcelona (Spain) Computational Biophysics German Research School for Simulation Sciences and Institute for Advanced Simulation IAS‐5 Computational Biomedicine Forschungszentrum Jülich (Germany) Mass Spectrometry Laboratory Department of Chemistry University of Liège (Belgium) Univ. Bordeaux IECB ARNA Laboratory 33600 Pessac (France) Inserm U869 ARNA Laboratory 33000 Bordeaux (France) Institute for Neuroscience and Medicine INM‐9 Computational Biomedicine Forschungszentrum Jülich (Germany) Department of Biochemistry and Molecular Biology University of Barcelona (Spain)

By combining ion‐mobility mass spectrometry experiments with sub‐millisecond classical and ab initio molecular dynamics we fully characterized, for the first time, the dynamic ensemble of a model nucleic acid in the gas phase under electrospray ionization conditions. The studied oligonucleotide unfolds upon vaporization, loses memory of the solution structure, and explores true gas‐phase conformational space. Contrary to our original expectations, the oligonucleotide shows very rich dynamics in three different timescales (multi‐picosecond, nanosecond, and sub‐millisecond). The shorter timescale dynamics has a quantum mechanical nature and leads to changes in the covalent structure, whereas the other two are of classical origin. Overall, this study suggests that a re‐evaluation on our view of the physics of nucleic acids upon vaporization is needed.

关键词： Ab‐initio‐Rechnungen DNA Gasphase Massenspektrometrie Moleküldynamik

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Distinct mechanisms of FAK mechanoactivation by different extracellular matrix proteins

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医用生物力学 2013年第S1期28卷 69-71页

作者： Jihye Seong Arash Tajik Jie Sun Jun-Lin Guan Martin J.Humphries Susan E.Craig Asha Shekaran Andrs J.García Ning Wang Yingxiao Wang Neuroscience Program University of Illinois Department of Mechanical Science and Engineering University of Illinois Department of Bioengineering & Beckman Institute for Advanced Science and Technology University of Illinois Division of Molecular Medicine and Genetics Departments of Internal Medicine and Cell & DevelopmentalBiologyUniversity of Michigan Medical School Wellcome Trust Centre for Cell-Matrix Research Faculty of Life SciencesUniversity of Manchester Woodruff School of Mechanical Engineering and Petit Institute for Bioengineering and Bioscience Georgia Institute of Technology Department of Biomedical Engineering School of Life Science and TechnologyHuazhong University of Science and Technology Department of Integrative and Molecular Physiology Center for Biophysics and Computational BiologyInstitute for Genomic BiologyUniversity of Illinois Department of Bioengineering University of California

Introduction Cells can sense and respond to the mechanical microenvironment by converting forces into biochemical signals inside the cells,***[1-3].Focal adhesions are the major sites of interaction between a cell and... 详细信息

Introduction Cells can sense and respond to the mechanical microenvironment by converting forces into biochemical signals inside the cells,***^[1-3].Focal adhesions are the major sites of interaction between a cell and its extracellular matrix（ECM）microenvironment,thus outside mechanical signals can be sensed at focal adhesions through transmembrane receptor *** particular,it has been shown that matrix elasticity can control the cell fate^[4]by modulating the interactions between ECM proteins and their receptor integrins^[5,6].For example,different rigidity of polyacrylamide（PA）gels can lead to different density of ECM ancho-

关键词： integrin converting transmembrane biochemical modulating elasticity rigidity polyacrylamide outside purchased

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Origin of Overstretching Transitions in Single-Stranded Nucleic Acids

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Physical Review Letters 2013年第18期111卷 188302-188302页

作者： Zackary N. Scholl Mahir Rabbi David Lee Laura Manson Hanna S-Gracz Piotr E. Marszalek Program in Computational Biology and Bioinformatics Duke University Durham North Carolina 27708 USA Department of Mechanical Engineering and Materials Science Center for Biologically Inspired Materials and Material Systems Duke University Durham North Carolina 27708 USA Department of Molecular and Structural Biochemistry North Carolina State University Raleigh North Carolina 27708 USA

We combined single-molecule force spectroscopy with nuclear magnetic resonance measurements and molecular mechanics simulations to examine overstretching transitions in single-stranded nucleic acids. In single-stranded DNA and single-stranded RNA there is a low-force transition that involves unwinding of the helical structure, along with base unstacking. We determined that the high-force transition that occurs in polydeoxyadenylic acid single-stranded DNA is caused by the cooperative forced flipping of the dihedral angle formed between four atoms, O5’-C5’-C4’-C3’ (γ torsion), in the nucleic acid backbone within the canonical B-type helix. The γ torsion also flips under force in A-type helices, where the helix is shorter and wider as compared to the B-type helix, but this transition is less cooperative than in the B type and does not generate a high-force plateau in the force spectrums of A-type helices. We find that a similar high-force transition can be induced in polyadenylic acid single-stranded RNA by urea, presumably due to disrupting the intramolecular hydrogen bonding in the backbone. We hypothesize that a pronounced high-force transition observed for B-type helices of double stranded DNA also involves a cooperative flip of the γ torsion. These observations suggest new fundamental relationships between the canonical structures of single-and double-stranded DNA and the mechanism of their molecular elasticity.

关键词： NUCLEAR magnetic resonance spectroscopy SINGLE-stranded DNA NUCLEOTIDE sequence DEOXYRIBOSE ATOMIC force microscopy

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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A "non-fratricidal" αβ- T Cell Receptor That Targets Survivin Expressed By Hematological Malignancies

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BLOOD 2013年第21期122卷 141-141页

作者： Arber, Caroline Feng, Xiang Abhyankar, Harshal Heslop, Helen E. Brenner, Malcolm K. Barth, Patrick Dotti, Gianpietro Savoldo, Barbara Center for Cell and Gene Therapy Baylor College of Medicine Houston TX USA Department of Pharmacology Baylor College of Medicine Houston TX USA Structural and Computational Biology and Molecular Biophysics Graduate Program Baylor College of Medicine Houston TX USA Center for Cell and Gene Therapy Baylor College of Medicine The Methodist Hospital Texas Children's Hospital Houston TX USA

141

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Phytohormone signaling pathway analysis method for comparing hormone responses in plant-pest interactions

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BMC Research Notes 2012年第1期5卷 1-7页

作者： Studham, Matthew E. MacIntosh, Gustavo C. Bioinformatics and Computational Biology Program Iowa State University Ames IA 50011 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011 United States

Background: Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean. Findings: We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses. Conclusions: This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization. © 2012 Studham and MacIntosh;licensee BioMed Central Ltd.

关键词： Salicylic Acid Jasmonic Acid Soybean Cyst Nematode Soybean Aphid Salicylic Acid Pathway

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Stable Small Quantum Dots for Synaptic Receptor Tracking on Live Neurons†

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Angewandte Chemie 2014年第46期126卷

作者： En Cai Pinghua Ge Sang Hak Lee Okunola Jeyifous Yong Wang Yanxin Liu Katie M. Wilson Sung Jun Lim Michelle A. Baird John E. Stone Kwan Young Lee Michael W. Davidson Hee Jung Chung Klaus Schulten Andrew M. Smith William N. Green Paul R. Selvin Department of Physics and Center for the Physics of Living Cells University of Illinois at Urbana‐Champaign 1110 W Green St. Urbana IL 61801 (USA) Department of Neurobiology University of Chicago Chicago IL (USA) Beckman Institute University of Illinois at Urbana‐Champaign Urbana IL (USA) Department of Structural and Chemical Biology and Institute of Integrative Biology University of Liverpool Liverpool (UK) Department of Bioengineering University of Illinois at Urbana‐Champaign Urbana IL (USA) The National High Magnetic Field Laboratory and Department of Biological Science The Florida State University Tallahassee FL (USA) Department of Molecular and Integrative Physiology University of Illinois at Urbana‐Champaign Urbana IL (USA) Center for Biophysics and Computational Biology University of Illinois at Urbana‐Champaign Urbana IL (USA) Marine Biological Laboratory Woods Hole MA (USA)

We developed a coating method to produce functionalized small quantum dots (sQDs), about 9 nm in diameter, that were stable for over a month. We made sQDs in four emission wavelengths, from 527 to 655 nm and with different functional groups. AMPA receptors on live neurons were labeled with sQDs and postsynaptic density proteins were visualized with super‐resolution microscopy. Their diffusion behavior indicates that sQDs access the synaptic clefts significantly more often than commercial QDs.

关键词： AMPA‐Rezeptoren Einzelmoleküluntersuchungen Fluoreszenzsonden Quantenpunkte

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GOAT

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Applied Bioinformatics 2012年第4期4卷 281-283页

作者： Xu, Qikai Shaulsky, Gad Graduate Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston USA Department of Molecular and Human Genetics Baylor College of Medicine Houston USA

Understanding the composition of gene lists that result from high-throughput experiments requires elaborate processing of gene annotation lists. In this article we present GOAT (Gene Ontology Analysis Tool), a tool based on the statistical software ‘R’ for analysing Gene Ontology™ (GO) term enrichment in gene lists. Given a gene list, GOAT calculates the enrichment and statistical significance of every GO term and generates graphical presentations of significantly enriched terms. GOAT works for any organism with a genome-scale GO annotation and allows easy updates of ontologies and annotations.

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Gorgon and pathwalking: Macromolecular modeling tools for subnanometer resolution density maps

Gorgon and pathwalking: Macromolecular modeling tools for su...

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作者： Baker, Matthew L. Baker, Mariah R. Hryc, Corey F. Ju, Tao Chiu, Wah Verna and Marrs McLean Department of Biochemistry and Molecular Biology National Center for Macromolecular Imaging Baylor College of Medicine Houston TX 77030 United States Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX 77030 United States Department of Computer Science and Engineering Washington University in St. Louis St. Louis MO 63130 United States

The complex interplay of proteins and other molecules, often in the form of large transitory assemblies, are critical to cellular function. Today, X-ray crystallography and electron cryo-microscopy (cryo-EM) are routinely used to image these macromolecular complexes, though often at limited resolutions. Despite the rapidly growing number of macromolecular structures, few tools exist for modeling and annotating structures in the range of 3-10 Å resolution. To address this need, we have developed a number of utilities specifically targeting subnanometer resolution density maps. As part of the 2010 Cryo-EM Modeling Challenge, we demonstrated two of our latest de novo modeling tools, Pathwalking and Gorgon, as well as a tool for secondary structure identification (SSEHunter) and a new rigid-body/flexible fitting tool in Gorgon. In total, we submitted 30 structural models from ten different subnanometer resolution data sets in four of the six challenge categories. Each of our utlities produced accurate structural models and annotations across the various density maps. In the end, the utilities that we present here offer users a robust toolkit for analyzing and modeling protein structure in macromolecular assemblies at non-atomic resolutions. © 2012 Wiley Periodicals, Inc.

关键词： X ray crystallography

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computational analysis of spatiotemporal molecular hierarchy in single live cells

Computational analysis of spatiotemporal molecular hierarchy...

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第五届中美生物医学工程暨海内外生物力学学术研讨会

作者： Shaoying Lu Jihye Seong Yi Wang Shiou-chi Chang John Paul Eichorst Mingxing Ouyang Yingxiao Wang Department of Bioengineering Beckman Institute for Advanced Science and TechnologyDepartment of Molecular and Integrative PhysiologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Bioengineering University of California San DiegoLa JollaCA 92093USA. Neuroscience Program Beckman Institute for Advanced Science and TechnologyDepartment of Molecular and Integrative PhysiologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Chemical Engineering Beckman Institute for Advanced Science and TechnologyDepartment of Molecular and Integrative PhysiologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Center of Biophysics and Computational Biology Beckman Institute for Advanced Science and TechnologyDepartment of Molecular and Integrative PhysiologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA

Genetically encoded biosensors based on fluorescence resonance energy transfer(FRET) have been widely applied to visualize the molecular activity in live cells with high spatiotemporal *** enormous amount of video images and the complex dynamics of signaling events present tremendous challenges for data analysis and demand the development of intelligent and automated imaging analysis methods specifically envisioned for the studies of live cell *** have developed a general correlative FRET imaging method(CFIM) to quan-

关键词： computational analysis of spatiotemporal molecular hierarchy in single live cells

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