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  • Modeling cancer metabolism on a genome scale
    Modeling cancer metabolism on a genome scale
    1. Keren Yizhak*,1,
    2. Barbara Chaneton2,
    3. Eyal Gottlieb2 and
    4. Eytan Ruppin*,1,3,4
    1. 1The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
    2. 2Cancer Research UK, Beatson Institute, Glasgow, UK
    3. 3The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
    4. 4Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA
    1. * Corresponding author. Tel: +972 3 640 5378; E‐mail: kerenyiz{at}post.tau.ac.il

      Corresponding author. Tel: +972 3 640 6528; E‐mail: ruppin{at}post.tau.ac.il

    Cancer cells have fundamental metabolic alterations that are associated with tumorigenicity and malignancy. This review discusses our current knowledge of altered tumor metabolism and strategies to model these alterations, through the integration of omics data with genome‐scale metabolic models.

    • Cancer metabolism
    • Metabolic modeling
    • Genome‐scale simulations

    Mol Syst Biol. (2015) 11: 817

    • Received October 22, 2014.
    • Revision received April 4, 2015.
    • Accepted May 26, 2015.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Keren Yizhak, Barbara Chaneton, Eyal Gottlieb, Eytan Ruppin
  • Systems‐level quantification of division timing reveals a common genetic architecture controlling asynchrony and fate asymmetry
    Systems‐level quantification of division timing reveals a common genetic architecture controlling asynchrony and fate asymmetry
    1. Vincy Wing Sze Ho1,,
    2. Ming‐Kin Wong1,,
    3. Xiaomeng An1,,
    4. Daogang Guan1,,
    5. Jiaofang Shao1,
    6. Hon Chun Kaoru Ng1,
    7. Xiaoliang Ren1,
    8. Kan He1,2,
    9. Jinyue Liao3,
    10. Yingjin Ang3,
    11. Long Chen4,
    12. Xiaotai Huang4,
    13. Bin Yan1,
    14. Yiji Xia1,
    15. Leanne Lai Hang Chan4,
    16. King Lau Chow3,
    17. Hong Yan4 and
    18. Zhongying Zhao*,1,5
    1. 1Department of Biology, Hong Kong Baptist University, Hong Kong, China
    2. 2Center for Stem Cell and Translational Medicine, School of Life Sciences Anhui University, Hefei, China
    3. 3Division of Life Science and Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
    4. 4Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
    5. 5State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong, China
    1. *Corresponding author. Tel: +852 3411 7058; E‐mail: zyzhao{at}hkbu.edu.hk
    1. These authors contributed equally to this work

    An RNAi screen followed by quantitative analyses of cell division timing reveals dual roles of fate determinants in temporal regulation and cell fate specification and provides a resource for analyzing the genetic control of spatiotemporal coordination during metazoan development.

    Synopsis

    An RNAi screen followed by quantitative analyses of cell division timing reveals dual roles of fate determinants in temporal regulation and cell fate specification and provides a resource for analyzing the genetic control of spatiotemporal coordination during metazoan development.

    • A high‐content screen for C. elegans genes whose depletion affects asynchrony in cell division demonstrates that fate determinants are not only essential for establishing fate asymmetry, but also important in controlling division asynchrony regardless of cellular context.

    • Perturbation of cell fate determinants involved in the regulation of division pace frequently leads to a defective migration of the same cell.

    • The quantitative data with cellular resolution (available in the “Phenics” Database http://phenics.icts.hkbu.edu.hk/) constitute a resource for inferring cell‐specific gene pathways controlling spatiotemporal coordination during fate specification or tissue growth.

    • asynchrony of cell division
    • automated lineaging
    • C. elegans
    • cell cycle length
    • cell division timing

    Mol Syst Biol. (2015) 11: 814

    • Received October 21, 2014.
    • Revision received May 18, 2015.
    • Accepted May 19, 2015.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Vincy Wing Sze Ho, Ming‐Kin Wong, Xiaomeng An, Daogang Guan, Jiaofang Shao, Hon Chun Kaoru Ng, Xiaoliang Ren, Kan He, Jinyue Liao, Yingjin Ang, Long Chen, Xiaotai Huang, Bin Yan, Yiji Xia, Leanne Lai Hang Chan, King Lau Chow, Hong Yan, Zhongying Zhao
  • Single‐cell polyadenylation site mapping reveals 3′ isoform choice variability
    Single‐cell polyadenylation site mapping reveals 3′ isoform choice variability
    1. Lars Velten1,
    2. Simon Anders1,
    3. Aleksandra Pekowska1,
    4. Aino I Järvelin14,
    5. Wolfgang Huber1,
    6. Vicent Pelechano1 and
    7. Lars M Steinmetz*,1,2,3
    1. 1European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
    2. 2Stanford Genome Technology Center, Palo Alto, CA, USA
    3. 3Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
    4. 4Department of Biochemistry, University of Oxford, Oxford, UK
    1. *Corresponding author. Tel: +49 6221 387 389; Fax: +49 6221 387 8518; E‐mail: larsms{at}embl.de

    BATSeq, the first transcriptomic method to quantify polyadenylation site use in single cells, reveals that stem cells from homogeneous populations differ in their preference for 3′ mRNA isoforms.

    Synopsis

    BATSeq, the first transcriptomic method to quantify polyadenylation site use in single cells, reveals that stem cells from homogeneous populations differ in their preference for 3′ mRNA isoforms.

    • We introduce BATBayes, a Bayesian framework that accounts for technical and biological sources of noise to quantify underlying variability in isoform preference

    • 3′ isoform usage is sufficient to distinguish between cells from different stem cell populations

    • Within homogeneous cell populations, cells differ in their use of isoforms more than expected from random choice

    • An intrinsic mechanism acting at the level of individual genes is likely to contribute to isoform choice variability

    • single‐cell transcriptomics
    • alternative polyadenylation
    • transcript isoform
    • non‐genetic heterogeneity
    • Bayesian inference

    Mol Syst Biol. (2015) 11: 812

    • Received March 26, 2015.
    • Revision received April 24, 2015.
    • Accepted May 3, 2015.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Lars Velten, Simon Anders, Aleksandra Pekowska, Aino I Järvelin, Wolfgang Huber, Vicent Pelechano, Lars M Steinmetz
  • Phosphoproteome dynamics of Saccharomyces cerevisiae under heat shock and cold stress
    <div xmlns="http://www.w3.org/1999/xhtml">Phosphoproteome dynamics of <em>Saccharomyces cerevisiae</em> under heat shock and cold stress</div>
    1. Evgeny Kanshin1,,
    2. Peter Kubiniok1,2,,
    3. Yogitha Thattikota1,3,
    4. Damien D'Amours1,3 and
    5. Pierre Thibault*,1,2,4
    1. 1Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
    2. 2Department of Chemistry, Université de Montréal, Montréal, QC, Canada
    3. 3Department of Pathology and Cell Biology, Université de Montréal, Montréal, QC, Canada
    4. 4Department of Biochemistry, Université de Montréal, Montréal, QC, Canada
    1. *Corresponding author. Tel: +1 514 343 6910; E‐mail: pierre.thibault{at}umontreal.ca
    1. These authors contributed equally to this work

    High temporal resolution profiling of the yeast phosphoproteome upon heat shock and cold stress enabled the correlation of kinetic profiles between kinases and their substrates and identified cell signaling events associated with actin organization, septin assembly and cell cycle arrest.

    Synopsis

    High temporal resolution profiling of the yeast phosphoproteome upon heat shock and cold stress enabled the correlation of kinetic profiles between kinases and their substrates and identified cell signaling events associated with actin organization, septin assembly and cell cycle arrest.

    • Changes in phosphoproteome of Saccharomyces cerevisiae were profiled for the first 30 min upon heat and cold stresses with a resolution of 2 min.

    • Heat shock triggered more dramatic changes in phosphorylation compared to cold stress.

    • The shape of the kinetic profiles was used to infer kinase–substrate relationships.

    • Heat shock resulted in extensive changes in phosphorylation on proteins implicated in septin assembly, actin organization and cell cycle progression.

    • cold stress
    • dynamics
    • heat shock
    • phosphoproteomics
    • signaling

    Mol Syst Biol. (2015) 11: 813

    • Received March 16, 2015.
    • Revision received May 1, 2015.
    • Accepted May 18, 2015.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Evgeny Kanshin, Peter Kubiniok, Yogitha Thattikota, Damien D'Amours, Pierre Thibault
  • Systems‐wide analysis of BCR signalosomes and downstream phosphorylation and ubiquitylation
    Systems‐wide analysis of BCR signalosomes and downstream phosphorylation and ubiquitylation
    1. Shankha Satpathy1,,
    2. Sebastian A Wagner16,
    3. Petra Beli17,
    4. Rajat Gupta1,
    5. Trine A Kristiansen18,
    6. Dessislava Malinova2,
    7. Chiara Francavilla1,
    8. Pavel Tolar2,
    9. Gail A Bishop3,4,
    10. Bruce S Hostager5 and
    11. Chunaram Choudhary*,1
    1. 1Department of Proteomics, The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
    2. 2Division of Immune Cell Biology, MRC National Institute for Medical Research, Mill Hill, London, UK
    3. 3Department of Microbiology, Graduate Program in Immunology and Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
    4. 4VAMC, Iowa City, IA, USA
    5. 5Department of Pediatrics, University of Iowa, Iowa City, IA, USA
    6. 6Department of Medicine, Hematology/Oncology, Goethe University School of Medicine, Frankfurt, Germany
    7. 7 Institute of Molecular Biology, Mainz, Germany
    8. 8 Stem Cell Center, Faculty of Medicine, Biomedical Center, Lund University, Lund, Sweden
    1. *Corresponding author. Tel: +4535325020; E‐mail: chuna.choudhary{at}cpr.ku.dk
    1. These authors contributed equally to this study

    Mass spectrometry‐based quantitative analysis of B‐cell receptor (BCR) signaling provides a global view of BCR signaling and identifies novel regulatory functions of phosphorylation and ubiquitylation in this system.

    Synopsis

    Mass spectrometry‐based quantitative analysis of B‐cell receptor (BCR) signaling provides a global view of BCR signaling and identifies novel regulatory functions of phosphorylation and ubiquitylation in this system.

    • Quantitative analysis of BCR signaling reveals the dynamics of BCR signalosome, ubiquitylome, and phosphoproteome.

    • BCR‐induced phosphorylation of RAB7A controls its binding to endosomes.

    • BCR stimulation increases linear ubiquitylation of BCL10 and activation of NF‐κB signaling.

    • HOIP and TRAF6 are involved in BCR‐induced ubiquitylation of BCL10.

    • BCL10
    • BCR
    • phosphorylation
    • RAB7A
    • ubiquitylation

    Mol Syst Biol. (2015) 11: 810

    • Received October 29, 2014.
    • Revision received April 30, 2015.
    • Accepted May 6, 2015.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Shankha Satpathy, Sebastian A Wagner, Petra Beli, Rajat Gupta, Trine A Kristiansen, Dessislava Malinova, Chiara Francavilla, Pavel Tolar, Gail A Bishop, Bruce S Hostager, Chunaram Choudhary
  • The making of Tara Oceans: funding blue skies research for our Blue Planet
    
      <div xmlns="http://www.w3.org/1999/xhtml">The making of <em>Tara</em> Oceans: funding blue skies research for our Blue Planet</div>
    1. Eric Karsenti (karsenti{at}embl-heidelberg.de) 1
    1. 1 Scientific Director Tara Oceans

    Transforming a romantic idea into the large‐scale Tara Oceans project was made possible by risk‐taking funders that provided seed support to a self‐organized community of highly committed researchers.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Eric Karsenti
  • Computational eco‐systems biology in Tara Oceans: translating data into knowledge
    
      <div xmlns="http://www.w3.org/1999/xhtml">Computational eco‐systems biology in <em>Tara </em>Oceans: translating data into knowledge</div>
    1. Shinichi Sunagawa 1 ,
    2. Eric Karsenti 1 , 2 ,
    3. Chris Bowler 2 and
    4. Peer Bork (bork{at}embl.de) 1 , 3
    1. 1 European Molecular Biology Laboratory, Heidelberg, Germany
    2. 2 Ecole Normale Supérieure Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, France
    3. 3 Max‐Delbrück‐Centre for Molecular Medicine, Berlin, Germany

    The computational analysis of the data collected by Tara Oceans represents a formidable challenge that will push the boundaries of our understanding of ecosystems at a planetary scale.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Shinichi Sunagawa, Eric Karsenti, Chris Bowler, Peer Bork

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