Literature DB >> 16986630

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

E O Voit1, J Almeida, S Marino, R Lall, G Goel, A R Neves, H Santos.   

Abstract

The unexpectedly long, and still unfinished, path towards a reliable mathematical model of glycolysis and its regulation in Lactococcus lactis is described. The model of this comparatively simple pathway was to be deduced from in vivo nuclear magnetic resonance time-series measurements of the key glycolytic metabolites. As to be expected from any nonlinear inverse problem, computational challenges were encountered in the numerical determination of parameter values of the model. Some of these were successfully solved, whereas others are still awaiting improved techniques of analysis. In addition, rethinking of the model formulation became necessary, because some generally accepted assumptions during model design are not necessarily valid for in vivo models. Examples include precursor-product relationships and the homogeneity of cells and their responses. Finally, it turned out to be useful to model only some of the metabolites, while using time courses of ubiquitous compounds such as adenosine triphosphate, inorganic phosphate, nicotinamide adenine dinucleotide (oxidised) and nicotinamide adenine dinucleotide (reduced) as unmodelled input functions. With respect to our specific application, the modelling process has come a long way, but it is not yet completed. Nonetheless, the model analysis has led to interesting insights into the design of the pathway and into the principles that govern its operation. Specifically, the widely observed feedforward activation of pyruvate kinase by fructose 1,6-bisphosphate is shown to provide a crucial mechanism for positioning the starving organism in a holding pattern that allows immediate uptake of glucose, as soon as it becomes available.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16986630     DOI: 10.1049/ip-syb:20050087

Source DB:  PubMed          Journal:  Syst Biol (Stevenage)        ISSN: 1741-2471


  24 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

2.  The intricate side of systems biology.

Authors:  Eberhard Voit; Ana Rute Neves; Helena Santos
Journal:  Proc Natl Acad Sci U S A       Date:  2006-06-09       Impact factor: 11.205

Review 3.  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

4.  System estimation from metabolic time-series data.

Authors:  Gautam Goel; I-Chun Chou; Eberhard O Voit
Journal:  Bioinformatics       Date:  2008-09-04       Impact factor: 6.937

5.  Calibration of dynamic models of biological systems with KInfer.

Authors:  Paola Lecca; Alida Palmisano; Adaoha Ihekwaba; Corrado Priami
Journal:  Eur Biophys J       Date:  2009-08-11       Impact factor: 1.733

6.  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

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

8.  Estimating parameters for generalized mass action models with connectivity information.

Authors:  Chih-Lung Ko; Eberhard O Voit; Feng-Sheng Wang
Journal:  BMC Bioinformatics       Date:  2009-05-11       Impact factor: 3.169

9.  Efficient, sparse biological network determination.

Authors:  Elias August; Antonis Papachristodoulou
Journal:  BMC Syst Biol       Date:  2009-02-23

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
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.