Counting and Correcting Thermodynamically Infeasible Flux Cycles in Genome-Scale Metabolic Networks

被引:30
作者
De Martino, Daniele [1 ,2 ]
Capuani, Fabrizio [1 ]
Mori, Matteo [1 ]
De Martino, Andrea [1 ,2 ,3 ]
Marinari, Enzo [1 ,2 ]
机构
[1] Sapienza Univ Roma, Dipartimento Fis, Ple A Moro 2, I-00185 Rome, Italy
[2] Ist Italiano Tecnol, Ctr Life Nano Sci Sapienza, I-00151 Rome, Italy
[3] Sapienza Univ Roma, Dipartimento Fis, UOS Roma, CNR,IPCF, I-00185 Rome, Italy
关键词
thermodynamics; infeasible cycles; genome-scale metabolic networks; flux-balance analysis;
D O I
10.3390/metabo3040946
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail) to eliminate them. As test cases, we tackle (a) the problem of identifying infeasible cycles in the E. coli metabolic network and (b) the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type-specific metabolic networks. Results for (a) are compared with previous analyses of the same issue, while results for (b) are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method, on the one hand, outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.
引用
收藏
页码:946 / 966
页数:21
相关论文
共 36 条
[1]  
ALBERTY RA, 2003, THERMODYNAMICS BIOCH
[2]  
[Anonymous], 2002, MONTE CARLO SIMULATI
[3]  
Beard DA, 2008, CAMB TEXT BIOMED ENG, P1, DOI 10.1017/CBO9780511803345
[4]   Thermodynamic constraints for biochemical networks [J].
Beard, DA ;
Babson, E ;
Curtis, E ;
Qian, H .
JOURNAL OF THEORETICAL BIOLOGY, 2004, 228 (03) :327-333
[5]   Energy balance for analysis of complex metabolic networks [J].
Beard, DA ;
Liang, SC ;
Qian, H .
BIOPHYSICAL JOURNAL, 2002, 83 (01) :79-86
[6]   Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity [J].
Beg, Q. K. ;
Vazquez, A. ;
Ernst, J. ;
de Menezes, M. A. ;
Bar-Joseph, Z. ;
Barabasi, A.-L. ;
Oltvai, Z. N. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2007, 104 (31) :12663-12668
[7]  
Bowden A.C., 2013, FUNDAMENTALS ENZYME
[8]   The solution space of metabolic networks: producibility, robustness and fluctuations [J].
De Martino, A. ;
Marinari, E. .
INTERNATIONAL WORKSHOP ON STATISTICAL-MECHANICAL INFORMATICS 2010 (IW-SMI 2010), 2010, 233
[9]   Reaction Networks as Systems for Resource Allocation: A Variational Principle for Their Non-Equilibrium Steady States [J].
De Martino, Andrea ;
De Martino, Daniele ;
Mulet, Roberto ;
Uguzzoni, Guido .
PLOS ONE, 2012, 7 (07)
[10]   Thermodynamics of biochemical networks and duality theorems [J].
De Martino, Daniele .
PHYSICAL REVIEW E, 2013, 87 (05)