Literature DB >> 16766654

The intricate side of systems biology.

Eberhard Voit1, Ana Rute Neves, Helena Santos.   

Abstract

The combination of high-throughput methods of molecular biology with advanced mathematical and computational techniques has propelled the emergent field of systems biology into a position of prominence. Unthinkable a decade ago, it has become possible to screen and analyze the expression of entire genomes, simultaneously assess large numbers of proteins and their prevalence, and characterize in detail the metabolic state of a cell population. Although very important, the focus on comprehensive networks of biological components is only one side of systems biology. Complementing large-scale assessments, and sometimes at the risk of being forgotten, are more subtle analyses that rationalize the design and functioning of biological modules in exquisite detail. This intricate side of systems biology aims at identifying the specific roles of processes and signals in smaller, fully regulated systems by computing what would happen if these signals were lacking or organized in a different fashion. We exemplify this type of approach with a detailed analysis of the regulation of glucose utilization in Lactococcus lactis. This organism is exposed to alternating periods of glucose availability and starvation. During starvation, it accumulates an intermediate of glycolysis, which allows it to take up glucose immediately upon availability. This notable accumulation poses a nontrivial control task that is solved with an unusual, yet ingeniously designed and timed feedforward activation system. The elucidation of this control system required high-precision, dynamic in vivo metabolite data, combined with methods of nonlinear systems analysis, and may serve as a paradigm for multidisciplinary approaches to fine-scaled systems biology.

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Year:  2006        PMID: 16766654      PMCID: PMC1480428          DOI: 10.1073/pnas.0603337103

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  13 in total

Review 1.  Overview on sugar metabolism and its control in Lactococcus lactis - the input from in vivo NMR.

Authors:  Ana Rute Neves; Wietske A Pool; Jan Kok; Oscar P Kuipers; Helena Santos
Journal:  FEMS Microbiol Rev       Date:  2005-08       Impact factor: 16.408

2.  Regulation of glycolysis in Lactococcus lactis: an unfinished systems biological case study.

Authors:  E O Voit; J Almeida; S Marino; R Lall; G Goel; A R Neves; H Santos
Journal:  Syst Biol (Stevenage)       Date:  2006-07

3.  Biochemical systems analysis. I. Some mathematical properties of the rate law for the component enzymatic reactions.

Authors:  M A Savageau
Journal:  J Theor Biol       Date:  1969-12       Impact factor: 2.691

4.  Feedfoward inhibition in biosynthetic pathways: inhibition of the aminoacyl-tRNA synthetase by intermediates of the pathway.

Authors:  M A Savageau; G Jacknow
Journal:  J Theor Biol       Date:  1979-04-21       Impact factor: 2.691

5.  Feedforward inhibition in biosynthetic pathways: inhibition of the aminoacyl-tRNA synthetase by the penultimate product.

Authors:  M A Savageau
Journal:  J Theor Biol       Date:  1979-04-21       Impact factor: 2.691

6.  A modelling study of feedforward activation in human erythrocyte glycolysis.

Authors:  M Bali; S R Thomas
Journal:  C R Acad Sci III       Date:  2001-03

7.  Metabolic control through reflexive enzyme action.

Authors:  A L Koch
Journal:  J Theor Biol       Date:  1967-04       Impact factor: 2.691

8.  Effect of different NADH oxidase levels on glucose metabolism by Lactococcus lactis: kinetics of intracellular metabolite pools determined by in vivo nuclear magnetic resonance.

Authors:  Ana Rute Neves; Ana Ramos; Helena Costa; Iris I van Swam; Jeroen Hugenholtz; Michiel Kleerebezem; Willem de Vos; Helena Santos
Journal:  Appl Environ Microbiol       Date:  2002-12       Impact factor: 4.792

9.  Effect of pyruvate kinase overproduction on glucose metabolism of Lactococcus lactis.

Authors:  Ana Ramos; Ana Rute Neves; Rita Ventura; Christopher Maycock; Paloma López; Helena Santos
Journal:  Microbiology       Date:  2004-04       Impact factor: 2.777

10.  The importance of inorganic phosphate in regulation of energy metabolism of Streptococcus lactis.

Authors:  P W Mason; D P Carbone; R A Cushman; A S Waggoner
Journal:  J Biol Chem       Date:  1981-02-25       Impact factor: 5.157

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  28 in total

Review 1.  Subcellular metabolic organization in the context of dynamic energy budget and biochemical systems theories.

Authors:  S Vinga; A R Neves; H Santos; B W Brandt; S A L M Kooijman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-11-12       Impact factor: 6.237

Review 2.  Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

Authors:  Gautam Goel; I-Chun Chou; Eberhard O Voit
Journal:  J Biomol Tech       Date:  2006-09

3.  Systems chemical biology.

Authors:  Tudor I Oprea; Alexander Tropsha; Jean-Loup Faulon; Mark D Rintoul
Journal:  Nat Chem Biol       Date:  2007-08       Impact factor: 15.040

4.  On the identifiability of metabolic network models.

Authors:  Sara Berthoumieux; Matteo Brilli; Daniel Kahn; Hidde de Jong; Eugenio Cinquemani
Journal:  J Math Biol       Date:  2012-11-15       Impact factor: 2.259

5.  Functioning of a metabolic flux sensor in Escherichia coli.

Authors:  Karl Kochanowski; Benjamin Volkmer; Luca Gerosa; Bart R Haverkorn van Rijsewijk; Alexander Schmidt; Matthias Heinemann
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-31       Impact factor: 11.205

Review 6.  Coordination of microbial metabolism.

Authors:  Victor Chubukov; Luca Gerosa; Karl Kochanowski; Uwe Sauer
Journal:  Nat Rev Microbiol       Date:  2014-03-24       Impact factor: 60.633

7.  Analysis of operating principles with S-system models.

Authors:  Yun Lee; Po-Wei Chen; Eberhard O Voit
Journal:  Math Biosci       Date:  2011-03-04       Impact factor: 2.144

Review 8.  Computational systems chemical biology.

Authors:  Tudor I Oprea; Elebeoba E May; Andrei Leitão; Alexander Tropsha
Journal:  Methods Mol Biol       Date:  2011

Review 9.  Network dynamics.

Authors:  Herbert M Sauro
Journal:  Methods Mol Biol       Date:  2009

10.  Identification of neutral biochemical network models from time series data.

Authors:  Marco Vilela; Susana Vinga; Marco A Grivet Mattoso Maia; Eberhard O Voit; Jonas S Almeida
Journal:  BMC Syst Biol       Date:  2009-05-05
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