Methods & Resources
- Reply to “Do genome‐scale models need exact solvers or clearer standards?”
Chindelevitch et al address the issues raised by Ebrahim et al and advocate that both improved standards and exact arithmetic are needed to advance the field.
Mol Syst Biol. (2015) 11: 830
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Do genome‐scale models need exact solvers or clearer standards?
- Ali Ebrahim (aebrahim{at}ucsd.edu)1,
- Eivind Almaas2,
- Eugen Bauer3,
- Aarash Bordbar4,
- Anthony P Burgard5,
- Roger L Chang6,
- Andreas Dräger1,7,
- Iman Famili8,
- Adam M Feist1,
- Ronan MT Fleming3,
- Stephen S Fong9,
- Vassily Hatzimanikatis10,
- Markus J Herrgård11,
- Allen Holder12,
- Michael Hucka13,
- Daniel Hyduke14,
- Neema Jamshidi15,16,
- Sang Yup Lee11,17,
- Nicolas Le Novère18,
- Joshua A Lerman1,
- Nathan E Lewis19,
- Ding Ma20,
- Radhakrishnan Mahadevan21,
- Costas Maranas22,
- Harish Nagarajan5,
- Ali Navid23,
- Jens Nielsen11,24,
- Lars K Nielsen25,
- Juan Nogales26,
- Alberto Noronha3,
- Csaba Pal27,
- Bernhard O Palsson1,
- Jason A Papin28,
- Kiran R Patil29,
- Nathan D Price30,
- Jennifer L Reed31,
- Michael Saunders20,
- Ryan S Senger32,
- Nikolaus Sonnenschein11,
- Yuekai Sun33 and
- Ines Thiele3
- 1Department of Bioengineering, University of California, San Diego, CA, USA
- 2Department of Biotechnology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- 3Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg
- 4Sinopia Biosciences Inc., San Diego, CA, USA
- 5Genomatica, Inc., San Diego, CA, USA
- 6Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- 7Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany
- 8Intrexon, Inc., San Diego, CA, USA
- 9Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, USA
- 10Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- 11The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
- 12Department of Mathematics, Rose‐Hulman Institute of Technology, Terre Haute, IN, USA
- 13Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, CA, USA
- 14Department of Biological Engineering, Utah State University, Logan, UT, USA
- 15Department of Radiology, University of California, Los Angeles, CA, USA
- 16Institute of Engineering in Medicine, University of California, San Diego, CA, USA
- 17Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
- 18Babraham Institute, Cambridge, UK
- 19Department of Pediatrics, University of California, San Diego, CA, USA
- 20Department of Management Science and Engineering, Stanford University, Stanford, CA, USA
- 21Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada
- 22Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA
- 23Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, USA
- 24Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- 25Australian Institute for Bioengineering & Nanotechnology (AIBN), The University of Queensland, Brisbane, Queensland, Australia
- 26Department of Environmental Biology, Centro de Investigaciones Biológicas (CSIC), Madrid, Spain
- 27Synthetic and Systems Biology Unit, Biological Research Center, Szeged, Hungary
- 28Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- 29European Molecular Biology Laboratory, Heidelberg, Germany
- 30Institute for Systems Biology, Seattle, WA, USA
- 31Department of Chemical and Biological Engineering, University of Wisconsin‐Madison, Madison, WI, USA
- 32Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA, USA
- 33Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
Recent results obtained by Chindelevitch et al (2014) are challenged by Ebrahim et al, illustrating several issues in the reproducibility of computational biology methods.
Mol Syst Biol. (2015) 11: 831
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- A cell‐based model system links chromothripsis with hyperploidy
- Balca R Mardin1,
- Alexandros P Drainas1,
- Sebastian M Waszak1,
- Joachim Weischenfeldt1,
- Mayumi Isokane2,
- Adrian M Stütz1,
- Benjamin Raeder1,
- Theocharis Efthymiopoulos1,
- Christopher Buccitelli1,
- Maia Segura‐Wang1,
- Paul Northcott3,
- Stefan M Pfister3,
- Peter Lichter4,
- Jan Ellenberg2 and
- Jan O Korbel*,1
- 1European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- 2European Molecular Biology Laboratory, Cell Biology and Biophysics Unit, Heidelberg, Germany
- 3Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- 4Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- ↵*Corresponding author. Tel: +49 6221 3878822; E‐mail: korbel{at}embl.de
An experimental method based on the perturbation of isogenic cell lines followed by selection, transformation and deep sequencing is presented to study the onset and the consequences of chromothripsis, a massive DNA rearrangement process observed in cancer genomes.
Synopsis
An experimental method based on the perturbation of isogenic cell lines followed by selection, transformation and deep sequencing is presented to study the onset and the consequences of chromothripsis, a massive DNA rearrangement process observed in cancer genomes.
An in vitro cell‐based model system is developed to enable studies of catastrophic DNA rearrangements, including of chromothripsis events.
Hyperploidy is identified as a risk factor for chromothripsis in vitro and in vivo.
The system is applied to reveal a large impact of chromothripsis on gene expression.
Mol Syst Biol. (2015) 11: 828
- Received August 13, 2015.
- Revision received August 24, 2015.
- Accepted August 28, 2015.
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Systems‐level quantification of division timing reveals a common genetic architecture controlling asynchrony and fate asymmetry
- Vincy Wing Sze Ho1,†,
- Ming‐Kin Wong1,†,
- Xiaomeng An1,†,
- Daogang Guan1,†,
- Jiaofang Shao1,
- Hon Chun Kaoru Ng1,
- Xiaoliang Ren1,
- Kan He1,2,
- Jinyue Liao3,
- Yingjin Ang3,
- Long Chen4,
- Xiaotai Huang4,
- Bin Yan1,
- Yiji Xia1,
- Leanne Lai Hang Chan4,
- King Lau Chow3,
- Hong Yan4 and
- Zhongying Zhao*,1,5
- 1Department of Biology, Hong Kong Baptist University, Hong Kong, China
- 2Center for Stem Cell and Translational Medicine, School of Life Sciences Anhui University, Hefei, China
- 3Division of Life Science and Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
- 4Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
- 5State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong, China
- ↵*Corresponding author. Tel: +852 3411 7058; E‐mail: zyzhao{at}hkbu.edu.hk
↵† 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.
Mol Syst Biol. (2015) 11: 814
- Received October 21, 2014.
- Revision received May 18, 2015.
- Accepted May 19, 2015.
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Single‐cell polyadenylation site mapping reveals 3′ isoform choice variability
- Lars Velten1,
- Simon Anders1,
- Aleksandra Pekowska1,
- Aino I Järvelin14,
- Wolfgang Huber1,
- Vicent Pelechano1 and
- Lars M Steinmetz*,1,2,3
- 1European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- 2Stanford Genome Technology Center, Palo Alto, CA, USA
- 3Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- 4Department of Biochemistry, University of Oxford, Oxford, UK
- ↵*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
Mol Syst Biol. (2015) 11: 812
- Received March 26, 2015.
- Revision received April 24, 2015.
- Accepted May 3, 2015.
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Using light to shape chemical gradients for parallel and automated analysis of chemotaxis
- Sean R Collins*,12,
- Hee Won Yang1,
- Kimberly M Bonger13,
- Emmanuel G Guignet14,
- Thomas J Wandless1 and
- Tobias Meyer*,1
- 1Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- 2Department of Microbiology and Molecular Genetics, University of California, Davis, Davis, CA, USA
- 3Department of Biomolecular Chemistry, Radboud University Nijmegen, Nijmegen, The Netherlands
- 4Bio‐Rad Laboratories, IHD, Cressier, Switzerland
- ↵*
Corresponding author. Tel: +1 530 752 7497; E‐mail: srcollins{at}ucdavis.edu
Corresponding author. Tel: +1 650 724 2971; E‐mail: tobias1{at}stanford.edu
A new strategy, involving optical shaping of gradients, allows systematically analyzing components regulating cell migration speed and directionality. The approach is applied to characterize migration and chemotaxis phenotypes for 285 siRNA perturbations in human neutrophils.
Synopsis
A new strategy, involving optical shaping of gradients, allows systematically analyzing components regulating cell migration speed and directionality. The approach is applied to characterize migration and chemotaxis phenotypes for 285 siRNA perturbations in human neutrophils.
Automated uncaging of attractants allows systematic live‐cell imaging of chemotaxis.
Leukocytes have distinct components specialized for regulating cell speed and cell direction in response to chemoattractant gradients.
Specialization in the chemoattractant signaling pathway occurs already at the level of the G‐proteins.
Mol Syst Biol. (2015) 11: 804
- Received January 8, 2015.
- Revision received March 25, 2015.
- Accepted March 27, 2015.
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- A high‐throughput ChIP‐Seq for large‐scale chromatin studies
- Christophe D Chabbert1,†,
- Sophie H Adjalley1,†,
- Bernd Klaus1,
- Emilie S Fritsch1,
- Ishaan Gupta1,
- Vicent Pelechano*,1 and
- Lars M Steinmetz*,1,2,3
- 1European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- 2Stanford Genome Technology Center, Palo Alto, CA, USA
- 3Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- ↵*
Corresponding author. Tel: +49 6221 3878542; Fax: +49 6221 387518; E‐mail: pelechan{at}embl.de
Corresponding author. Tel: +49 6221 3878389; Fax: +49 6221 387518; E‐mail: larsms{at}embl.de
-
↵† These authors contributed equally to this work
A new approach provides a rapid and accurate genome‐wide overview of the chromatin status of multiple yeast chromatin‐associated mutants at once. The simultaneous profiling of epigenetic marks in the mutants is achieved by multiplex immuno‐precipitation of barcoded chromatin samples.
Synopsis
A new approach provides a rapid and accurate genome‐wide overview of the chromatin status of multiple yeast chromatin‐associated mutants at once. The simultaneous profiling of epigenetic marks in the mutants is achieved by multiplex immuno‐precipitation of barcoded chromatin samples.
Bar‐ChIP is based on the immuno‐precipitation of barcoded chromatin and permits sample multiplexing, thereby increasing the throughput of ChIP‐Seq experiments.
Application of the method to yeast chromatin‐associated mutants enabled the concurrent generation of 90 ChIP‐Seq datasets without the need for robotic instrumentation.
The rapid chromatin profiling of the mutants at single‐nucleosome resolution uncovered an association between intragenic H3K4 tri‐methylation and cryptic transcription in set2∆.
Mol Syst Biol. (2015) 11: 777
- Received September 18, 2014.
- Revision received December 4, 2014.
- Accepted December 5, 2014.
- © 2015 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Multi‐input CRISPR/Cas genetic circuits that interface host regulatory networks
- 1Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- ↵*Corresponding author. Tel: +1 617 324 4851; E‐mail: cavoigt{at}gmail.com
Genetic gates are assembled based on dCas9 and engineered small guide RNAs (sgRNAs) that drive Cas9 to target promoters. These transcriptional gates are linked to build larger genetic circuits that are connected to the natural regulatory network of the cell.
Synopsis
Genetic gates are assembled based on dCas9 and engineered small guide RNAs (sgRNAs) that drive Cas9 to target promoters. These transcriptional gates are linked to build larger genetic circuits that are connected to the natural regulatory network of the cell.
Synthetic promoters and cognate sgRNAs exhibit large dynamic range and negligible crosstalk.
sgRNA‐based NOT gate response functions are non‐cooperative and quantitatively different from those based on transcriptional repressors.
Multi‐input logic gates are constructed by layering orthogonal sgRNAs.
Host regulatory networks can be interfaced through the design of sgRNA circuit outputs targeted to native transcription factors.
Mol Syst Biol. (2014) 10: 763
- Received September 1, 2014.
- Revision received October 26, 2014.
- Accepted October 29, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Rapid neurogenesis through transcriptional activation in human stem cells
- Volker Busskamp1,215†,
- Nathan E Lewis1,2,3,4,†,
- Patrick Guye5,†,
- Alex HM Ng1,2,6,
- Seth L Shipman1,2,
- Susan M Byrne1,2,
- Neville E Sanjana7,8,
- Jernej Murn9,10,
- Yinqing Li5,
- Shangzhong Li11,
- Michael Stadler12,13,14,
- Ron Weiss5 and
- George M Church*,1,2
- 1Department of Genetics, Harvard Medical School, Boston, MA, USA
- 2Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
- 3Department of Biology, Brigham Young University, Provo, UT, USA
- 4Department of Pediatrics, University of California, San Diego, CA, USA
- 5Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- 6Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- 7Broad Institute of MIT and Harvard Cambridge Center, Cambridge, MA, USA
- 8McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- 9Department of Cell Biology, Harvard Medical School, Boston, MA, USA
- 10Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, USA
- 11Department of Bioengineering, University of California, San Diego, CA, USA
- 12Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- 13Swiss Institute of Bioinformatics, Basel, Switzerland
- 14University of Basel, Basel, Switzerland
- 15Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany
- ↵*Corresponding author. Tel: +1 617 432 1278; E‐mail: gchurch{at}genetics.med.harvard.edu
-
↵† These authors contributed equally to this work
Rapid and homogeneous neuronal differentiation is attained in human stem cells upon overexpression of two Neurogenin transcription factors. mRNA and miRNA expression profiling during differentiation reveals a regulatory network mediating neurogenesis from stem cells.
Synopsis
Rapid and homogeneous neuronal differentiation is attained in human stem cells upon overexpression of two Neurogenin transcription factors. mRNA and miRNA expression profiling during differentiation reveals a regulatory network mediating neurogenesis from stem cells.
Neurogenin‐1 and ‐2 drive homogeneous differentiation of human stem cells into bipolar neurons in 4 days in defined media.
The population homogeneity allowed mRNA and miRNA expression profiling over time during neurogenesis.
A network of key transcription factors and miRNAs that promote rapid neurogenesis and loss of pluripotency is identified.
Perturbations of key transcription factors affect the homogeneity and phenotypic properties of the resulting neurons.
Mol Syst Biol. (2014) 10: 760
- Received June 20, 2014.
- Revision received October 14, 2014.
- Accepted October 16, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
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.
- Efficient sample processing for proteomics applications—Are we there yet?
The ability to solubilize and digest protein extracts and recover peptides with high efficiency is of paramount importance in proteomics. A novel proteomic sample preparation protocol by Krijgsveld and colleagues (Hughes et al, 2014) provides significant advantages by enabling all sample processing steps to be carried out in a single tube to minimize sample losses, thereby enhancing sensitivity, throughput, and scalability of proteomics analyses.
See also: Hughes et al (October 2014)
A new proteomic sample preparation protocol by Krijgsveld and colleagues (Hughes et al, 2014) enables all sample processing steps to be carried out in a single tube to minimize sample losses, thereby enhancing sensitivity, throughput, and scalability of proteomics analyses.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
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.
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