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  • Cell dynamics and gene expression control in tissue homeostasis and development
    1. Pau Rué1 and
    2. Alfonso Martinez Arias*,1
    1. 1Department of Genetics, University of Cambridge, Cambridge, UK
    1. *Corresponding author. Tel: +44 1223 766742; E‐mail: ama11{at}gen.cam.ac.uk

    Development and homeostasis require the regulation of cell fate assignment at the cell‐population level. Here we discuss how the control of stochastic events at the level of single cells is translated into coherent behavior in the population.

    • development
    • differentiation
    • homeostasis
    • stochastic cell fate
    • transition state

    Mol Syst Biol. (2015) 11: 792

    • Received July 4, 2014.
    • Revision received January 12, 2015.
    • Accepted January 21, 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.

    Pau Rué, Alfonso Martinez Arias
  • Targeting a cell state common to triple‐negative breast cancers
    1. Markus K Muellner1,
    2. Barbara Mair1,
    3. Yasir Ibrahim2,
    4. Claudia Kerzendorfer1,
    5. Hannelore Lechtermann1,
    6. Claudia Trefzer1,
    7. Freya Klepsch1,
    8. André C Müller1,
    9. Ernestine Leitner1,
    10. Sabine Macho‐Maschler3,
    11. Giulio Superti‐Furga1,
    12. Keiryn L Bennett1,
    13. José Baselga4,
    14. Uwe Rix5,
    15. Stefan Kubicek1,
    16. Jacques Colinge1,
    17. Violeta Serra2 and
    18. Sebastian MB Nijman*,1
    1. 1CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
    2. 2Experimental Therapeutics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    3. 3University of Veterinary Medicine, Vienna, Austria
    4. 4Memorial Sloan‐Kettering Cancer Center, New York, NY, USA
    5. 5H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
    1. *Corresponding author. Tel: +44 1865 612 885; E‐mail: snijman{at}cemm.oeaw.ac.at

    A chemical screen and systems approach reveal SYK‐STAT3 signaling as a druggable target in basal‐like breast cancers. The study supports the systems‐based notion that targeting a cell state, rather than a mutational state, can lead to therapeutic target discovery.

    Synopsis

    A chemical screen and systems approach reveal SYK‐STAT3 signaling as a druggable target in basal‐like breast cancers. The study supports the systems‐based notion that targeting a cell state, rather than a mutational state, can lead to therapeutic target discovery.

    • A chemical screen identifies a set of structurally related small molecules, including the drug midostaurin (PKC412), that target the mesenchymal cell state found in a subset of breast tumors.

    • A multi‐omics approach is combined with computational modeling for examining the drug mechanism of action and reveals the tyrosine kinase SYK as a novel breast cancer target.

    • Phospho‐proteomics analysis shows that SYK is required to maintain STAT3 phosphorylation in basal‐like breast cancer cells.

    • breast cancer
    • cell state
    • small‐molecule screen

    Mol Syst Biol. (2015) 11: 789

    • Received August 6, 2014.
    • Revision received January 16, 2015.
    • Accepted January 22, 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.

    Markus K Muellner, Barbara Mair, Yasir Ibrahim, Claudia Kerzendorfer, Hannelore Lechtermann, Claudia Trefzer, Freya Klepsch, André C Müller, Ernestine Leitner, Sabine Macho‐Maschler, Giulio Superti‐Furga, Keiryn L Bennett, José Baselga, Uwe Rix, Stefan Kubicek, Jacques Colinge, Violeta Serra, Sebastian MB Nijman
  • A multi‐scale approach reveals that NF‐κB cRel enforces a B‐cell decision to divide
    1. Maxim N Shokhirev1,2,3,
    2. Jonathan Almaden1,4,
    3. Jeremy Davis‐Turak1,2,3,
    4. Harry A Birnbaum1,2,5,6,
    5. Theresa M Russell7,
    6. Jesse A D Vargas1,2,5,6 and
    7. Alexander Hoffmann*,1,2,5,6
    1. 1Department of Chemistry and Biochemistry, Signaling Systems Laboratory, UCSD, La Jolla, CA, USA
    2. 2San Diego Center for Systems Biology, UCSD, La Jolla, CA, USA
    3. 3Bioinformatics and Systems Biology Graduate Program, UCSD, La Jolla, CA, USA
    4. 4Biological Sciences Graduate Program, UCSD, La Jolla, CA, USA
    5. 5Institute for Quantitative and Computational Biosciences, Los Angeles, CA, USA
    6. 6Department of Microbiology, Immunology and Molecular Genetics, UCLA, Los Angeles, CA, USA
    7. 7Fluidigm Corporation, South San Francisco, CA, USA
    1. *Corresponding author. Tel: +1 310 794 9925; E‐mail: ahoffmann{at}ucla.edu

    A new multi‐scale model predicts B‐cell population dynamics in terms intra‐cellular molecular networks. We predict and confirm that NF‐κB cRel enforces cellular fate decisions and characterize how molecular network noise determines robust cell population dynamics.

    Synopsis

    A new multi‐scale model predicts B‐cell population dynamics in terms of intra‐cellular molecular networks. We predict and confirm that NF‐κB cRel enforces cellular fate decisions and characterize how molecular network noise determines robust cell population dynamics.

    • We present a multi‐scale model that accounts for robust B‐cell population dynamics in terms of noisy molecular network dynamics in each cell.

    • Live cell microscopy confirms that cells entering a growth phase constitute a fate decision toward division rather than death.

    • Modeling and experimentation reveal that NF‐κB cRel is critical for enforcing the fate decision—its absence results in a ‘fate race’.

    • The multi‐scale model can predict how molecular perturbations and extrinsic noise effect cell population dynamics.

    • apoptosis
    • B‐lymphocyte
    • cell cycle
    • cell fate decision
    • NF‐κB cRel

    Mol Syst Biol. (2015) 11: 783

    • Received August 16, 2014.
    • Revision received December 21, 2014.
    • Accepted December 23, 2014.

    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.

    Maxim N Shokhirev, Jonathan Almaden, Jeremy Davis‐Turak, Harry A Birnbaum, Theresa M Russell, Jesse A D Vargas, Alexander Hoffmann
  • Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
    1. Sheng Hui1,
    2. Josh M Silverman2,3,
    3. Stephen S Chen2,3,
    4. David W Erickson1,
    5. Markus Basan1,
    6. Jilong Wang1,
    7. Terence Hwa*,1,4 and
    8. James R Williamson*,2,3
    1. 1Department of Physics, University of California at San Diego, La Jolla, CA, USA
    2. 2Department of Integrative Structural and Computational Biology, The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA, USA
    3. 3Department of Chemistry, The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA, USA
    4. 4Section of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, CA, USA
    1. * Corresponding author. Tel: +1 858 534 7263; E‐mail: hwa{at}ucsd.edu

      Corresponding author. Tel: +1 858 784 8740; E‐mail: jrwill{at}scripps.edu

    Quantitative relative and absolute protein abundance data allow the use of coarse‐graining analysis to reveal strategies of resource allocation by E. coli. A predictive, mathematical model of the proteome is constructed requiring only a few parameters.

    Synopsis

    Quantitative relative and absolute protein abundance data allow the use of coarse‐graining analysis to reveal strategies of resource allocation by E. coli. A predictive, mathematical model of the proteome is constructed requiring only a few parameters.

    • Coarse‐graining procedure makes proteomics data amenable to quantitative analysis.

    • Five functionally distinct proteome sectors each exhibit linear relations with the growth rate.

    • A simple flux model captures proteome‐wide responses accurately with few parameters.

    • Proteome economy is shown to be a principle governing global gene regulation.

    • growth physiology
    • metabolic network
    • microbiology
    • quantitative proteomics
    • systems biology

    Mol Syst Biol. (2015) 11: 784

    • Received August 18, 2014.
    • Revision received December 11, 2014.
    • Accepted December 23, 2014.

    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.

    Sheng Hui, Josh M Silverman, Stephen S Chen, David W Erickson, Markus Basan, Jilong Wang, Terence Hwa, James R Williamson
  • The functional interactome of PYHIN immune regulators reveals IFIX is a sensor of viral DNA
    1. Benjamin A Diner1,,
    2. Tuo Li1,,
    3. Todd M Greco1,
    4. Marni S Crow1,
    5. John A Fuesler1,
    6. Jennifer Wang1 and
    7. Ileana M Cristea*,1
    1. 1Department of Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, NJ, USA
    1. *Corresponding author. Tel: +1 6092589417; Fax: +1 6092584575; E‐mail: icristea{at}princeton.edu
    1. These authors contributed equally to this work

    This study presents the global protein interactome of the human PYHIN proteins (AIM2, IFI16, IFIX, and MNDA) and defines IFIX as an antiviral factor and sensor of viral DNA.

    Synopsis

    This study presents the global protein interactome of the human PYHIN proteins (AIM2, IFI16, IFIX, and MNDA) and defines IFIX as an antiviral factor and sensor of viral DNA.

    • The interaction network of the human PYHIN proteins highlights their roles in transcriptional regulation, chromatin remodeling, and DNA damage response.

    • IFIX interacts and co‐localizes with components of nuclear PML bodies.

    • IFIX acts as an antiviral factor, limiting the replication of herpes simplex virus 1 (HSV‐1).

    • IFIX binds to viral dsDNA and contributes to the onset of innate immunity.

    • DNA sensing
    • IFIX
    • innate immunity
    • interactome
    • PYHIN

    Mol Syst Biol. (2015) 11: 787

    • Received October 13, 2014.
    • Revision received December 10, 2014.
    • Accepted December 23, 2014.

    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.

    Benjamin A Diner, Tuo Li, Todd M Greco, Marni S Crow, John A Fuesler, Jennifer Wang, Ileana M Cristea
  • Quantitative variability of 342 plasma proteins in a human twin population
    1. Yansheng Liu*,1,,
    2. Alfonso Buil2,,
    3. Ben C Collins1,
    4. Ludovic CJ Gillet1,
    5. Lorenz C Blum1,
    6. Lin‐Yang Cheng3,
    7. Olga Vitek3,
    8. Jeppe Mouritsen1,
    9. Genevieve Lachance4,
    10. Tim D Spector4,
    11. Emmanouil T Dermitzakis2 and
    12. Ruedi Aebersold*,1,5
    1. 1Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
    2. 2Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
    3. 3Department of Statistics and Department of Computer Science, Purdue University, West Lafayette, IN, USA
    4. 4Department of Twin Research and Genetic Epidemiology, King's College London St Tomas' Hospital Campus, London, UK
    5. 5Faculty of Science, University of Zurich, Zurich, Switzerland
    1. * Corresponding author. Tel: +41 44 633 2986; E‐mail: liu{at}imsb.biol.ethz.ch

      Corresponding author. Tel: +41 44 633 3170; Fax: +41 44 633 1051; E‐mail: aebersold{at}imsb.biol.ethz.ch

    1. These authors contribute equally to this study

    The degree and origins of the abundance variability of 342 human plasma proteins are analyzed by a longitudinal twin design and SWATH mass spectrometry. The results suggest genetic control and longitudinal variation affect protein levels and biological processes to different degrees.

    Synopsis

    The degree and origins of the abundance variability of 342 human plasma proteins are analyzed by a longitudinal twin design and SWATH mass spectrometry. The results suggest genetic control and longitudinal variation affect protein levels and biological processes to different degrees.

    • We used the highly accurate and reproducible SWATH mass spectrometry technique to quantify 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years.

    • The observed total quantitative variability of human plasma proteome is dissected to its root causes, genes, environment and longitudinal factors.

    • The roles of the heritable, environmental and longitudinal determinants in controlling plasma protein levels are different for different proteins and functional clusters, strongly suggesting that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors.

    • We further identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins as protein quantitative trait loci (pQTLs), and five of them are associated with gene expression QTLs (eQTLs) in human tissues.

    • heritability
    • longitudinal variability
    • plasma biomarkers
    • SWATH‐MS
    • twin study

    Mol Syst Biol. (2015) 11: 786

    • Received August 27, 2014.
    • Revision received January 7, 2015.
    • Accepted January 12, 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.

    Yansheng Liu, Alfonso Buil, Ben C Collins, Ludovic CJ Gillet, Lorenz C Blum, Lin‐Yang Cheng, Olga Vitek, Jeppe Mouritsen, Genevieve Lachance, Tim D Spector, Emmanouil T Dermitzakis, Ruedi Aebersold
  • Negative feedback buffers effects of regulatory variants
    1. Daniel M Bader1,
    2. Stefan Wilkening2,
    3. Gen Lin2,
    4. Manu M Tekkedil2,
    5. Kim Dietrich1,
    6. Lars M Steinmetz2,3,4 and
    7. Julien Gagneur*,1
    1. 1Computational Genomics, Gene Center, Ludwig Maximilians University, Munich, Germany
    2. 2European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
    3. 3Stanford Genome Technology Center, Palo Alto, CA, USA
    4. 4Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
    1. *Corresponding author. Tel: +49 89 218076742; E‐mail: gagneur{at}genzentrum.lmu.de

    Local trans regulation, mainly due to negative feedback, buffers effects of cis‐regulatory variants by about 15%. This buffering is stronger for essential genes and genes with low to middle expression levels, for which tight regulation matters most.

    Synopsis

    Local trans regulation, mainly due to negative feedback, buffers effects of cis‐regulatory variants by about 15%. This buffering is stronger for essential genes and genes with low to middle expression levels, for which tight regulation matters most.

    • Novel experimental design using expression of a diploid hybrid and its haploid spores allows systematic dissection of cis and local trans regulation.

    • Local trans effects buffer effects of cis‐regulatory variants in yeast by typically 15%.

    • Local trans buffering is primarily due to negative feedback.

    • Negative feedback as robustness strategy for genes with low to medium expression level.

    • buffering
    • canalization
    • cis regulation
    • feedback
    • trans regulation

    Mol Syst Biol. (2015) 11: 785

    • Received October 15, 2014.
    • Revision received December 19, 2014.
    • Accepted December 23, 2014.

    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.

    Daniel M Bader, Stefan Wilkening, Gen Lin, Manu M Tekkedil, Kim Dietrich, Lars M Steinmetz, Julien Gagneur