Literature DB >> 22760628

In silico method for modelling metabolism and gene product expression at genome scale.

Joshua A Lerman1, Daniel R Hyduke, Haythem Latif, Vasiliy A Portnoy, Nathan E Lewis, Jeffrey D Orth, Alexandra C Schrimpe-Rutledge, Richard D Smith, Joshua N Adkins, Karsten Zengler, Bernhard O Palsson.   

Abstract

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

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Year:  2012        PMID: 22760628      PMCID: PMC3827721          DOI: 10.1038/ncomms1928

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  55 in total

1.  KEGG: kyoto encyclopedia of genes and genomes.

Authors:  M Kanehisa; S Goto
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Filling gaps in a metabolic network using expression information.

Authors:  Peter Kharchenko; Dennis Vitkup; George M Church
Journal:  Bioinformatics       Date:  2004-08-04       Impact factor: 6.937

3.  The challenges of integrating multi-omic data sets.

Authors:  Bernhard Palsson; Karsten Zengler
Journal:  Nat Chem Biol       Date:  2010-11       Impact factor: 15.040

4.  Interdependence of cell growth and gene expression: origins and consequences.

Authors:  Matthew Scott; Carl W Gunderson; Eduard M Mateescu; Zhongge Zhang; Terence Hwa
Journal:  Science       Date:  2010-11-19       Impact factor: 47.728

Review 5.  In situ to in silico and back: elucidating the physiology and ecology of Geobacter spp. using genome-scale modelling.

Authors:  Radhakrishnan Mahadevan; Bernhard Ø Palsson; Derek R Lovley
Journal:  Nat Rev Microbiol       Date:  2010-12-06       Impact factor: 60.633

Review 6.  Industrial systems biology.

Authors:  José Manuel Otero; Jens Nielsen
Journal:  Biotechnol Bioeng       Date:  2010-02-15       Impact factor: 4.530

7.  Role of the three consecutive G:C base pairs conserved in the anticodon stem of initiator tRNAs in initiation of protein synthesis in Escherichia coli.

Authors:  N Mandal; D Mangroo; J J Dalluge; J A McCloskey; U L Rajbhandary
Journal:  RNA       Date:  1996-05       Impact factor: 4.942

8.  Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models.

Authors:  Nathan E Lewis; Kim K Hixson; Tom M Conrad; Joshua A Lerman; Pep Charusanti; Ashoka D Polpitiya; Joshua N Adkins; Gunnar Schramm; Samuel O Purvine; Daniel Lopez-Ferrer; Karl K Weitz; Roland Eils; Rainer König; Richard D Smith; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2010-07       Impact factor: 11.429

Review 9.  Applications of genome-scale metabolic reconstructions.

Authors:  Matthew A Oberhardt; Bernhard Ø Palsson; Jason A Papin
Journal:  Mol Syst Biol       Date:  2009-11-03       Impact factor: 11.429

10.  Sequences and consequences.

Authors:  Sydney Brenner
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-01-12       Impact factor: 6.237

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  97 in total

1.  Elementary Growth Modes provide a molecular description of cellular self-fabrication.

Authors:  Daan H de Groot; Josephus Hulshof; Bas Teusink; Frank J Bruggeman; Robert Planqué
Journal:  PLoS Comput Biol       Date:  2020-01-27       Impact factor: 4.475

2.  Reconciling a Salmonella enterica metabolic model with experimental data confirms that overexpression of the glyoxylate shunt can rescue a lethal ppc deletion mutant.

Authors:  Nicole L Fong; Joshua A Lerman; Irene Lam; Bernhard O Palsson; Pep Charusanti
Journal:  FEMS Microbiol Lett       Date:  2013-03-15       Impact factor: 2.742

Review 3.  Using Genome-scale Models to Predict Biological Capabilities.

Authors:  Edward J O'Brien; Jonathan M Monk; Bernhard O Palsson
Journal:  Cell       Date:  2015-05-21       Impact factor: 41.582

4.  Laboratory Evolution to Alternating Substrate Environments Yields Distinct Phenotypic and Genetic Adaptive Strategies.

Authors:  Troy E Sandberg; Colton J Lloyd; Bernhard O Palsson; Adam M Feist
Journal:  Appl Environ Microbiol       Date:  2017-06-16       Impact factor: 4.792

Review 5.  Transparency in metabolic network reconstruction enables scalable biological discovery.

Authors:  Benjamin D Heavner; Nathan D Price
Journal:  Curr Opin Biotechnol       Date:  2015-01-03       Impact factor: 9.740

Review 6.  Constraint-based models predict metabolic and associated cellular functions.

Authors:  Aarash Bordbar; Jonathan M Monk; Zachary A King; Bernhard O Palsson
Journal:  Nat Rev Genet       Date:  2014-01-16       Impact factor: 53.242

7.  Optimizing genome-scale network reconstructions.

Authors:  Jonathan Monk; Juan Nogales; Bernhard O Palsson
Journal:  Nat Biotechnol       Date:  2014-05       Impact factor: 54.908

8.  Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation.

Authors:  Ke Chen; Ye Gao; Nathan Mih; Edward J O'Brien; Laurence Yang; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-10       Impact factor: 11.205

Review 9.  Analysis of omics data with genome-scale models of metabolism.

Authors:  Daniel R Hyduke; Nathan E Lewis; Bernhard Ø Palsson
Journal:  Mol Biosyst       Date:  2012-12-18

10.  Global Rebalancing of Cellular Resources by Pleiotropic Point Mutations Illustrates a Multi-scale Mechanism of Adaptive Evolution.

Authors:  Jose Utrilla; Edward J O'Brien; Ke Chen; Douglas McCloskey; Jacky Cheung; Harris Wang; Dagoberto Armenta-Medina; Adam M Feist; Bernhard O Palsson
Journal:  Cell Syst       Date:  2016-04-27       Impact factor: 10.304

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