Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2014 (2014), Article ID 416289, 11 pages
http://dx.doi.org/10.1155/2014/416289
Research Article

Modeling the Differences in Biochemical Capabilities of Pseudomonas Species by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

Department of Biotechnology, College of Science, University of Tehran, Tehran 1417614411, Iran

Received 31 August 2013; Accepted 24 December 2013; Published 24 February 2014

Academic Editors: P. Giardina and E. Van Heerden

Copyright © 2014 Parizad Babaei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Ronaghi, “Pyrosequencing sheds light on DNA sequencing,” Genome Research, vol. 11, no. 1, pp. 3–11, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. J. Shendure and H. Ji, “Next-generation DNA sequencing,” Nature Biotechnology, vol. 26, no. 10, pp. 1135–1145, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. B. M. Venkatesan and R. Bashir, “Nanopore sensors for nucleic acid analysis,” Nature Nanotechnology, vol. 6, no. 10, pp. 615–624, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. N. Beckloff, S. Starkenburg, T. Freitas, and P. Chain, “Bacterial genome annotation,” Methods in Molecular Biology, vol. 881, pp. 471–503, 2012. View at Google Scholar
  5. X. Mao, T. Cai, J. G. Olyarchuk, and L. Wei, “Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary,” Bioinformatics, vol. 21, no. 19, pp. 3787–3793, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. A. M. Feist, M. J. Herrgård, I. Thiele, J. L. Reed, and B. Ø. Palsson, “Reconstruction of biochemical networks in microorganisms,” Nature Reviews Microbiology, vol. 7, no. 2, pp. 129–143, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. A. R. Zomorrodi, P. F. Suthers, S. Ranganathan, and C. D. Maranas, “Mathematical optimization applications in metabolic networks,” Metabolic Engineering, vol. 14, pp. 672–686, 2012. View at Google Scholar
  8. J. Schellenberger, R. Que, R. M. T. Fleming et al., “Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0,” Nature Protocols, vol. 6, no. 9, pp. 1290–1307, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. I. Thiele and B. Ø. Palsson, “A protocol for generating a high-quality genome-scale metabolic reconstruction,” Nature Protocols, vol. 5, no. 1, pp. 93–121, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. S. G. Thorleifsson and I. Thiele, “rBioNet: a COBRA toolbox extension for reconstructing high-quality biochemical networks,” Bioinformatics, vol. 27, no. 14, Article ID btr308, pp. 2009–2010, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. C. Liao, M. H. Tsai, F. C. Chen, and C. A. Hsiung, “GEMSiRV: a software platform for GEnome-scale metabolic model simulation, reconstruction and visualization,” Bioinformatics, vol. 28, pp. 1752–1758, 2012. View at Google Scholar
  12. R. Agren, L. Liu, S. Shoaie, W. Vongsangnak, I. Nookaew, and J. Nielsen, “The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum,” PLoS Computational Biology, vol. 9, Article ID e1002980, 2013. View at Google Scholar
  13. A. M. Feist, C. S. Henry, J. L. Reed et al., “A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information,” Molecular Systems Biology, vol. 3, article 121, 2007. View at Publisher · View at Google Scholar · View at Scopus
  14. M. Heinemann, A. Kümmel, R. Ruinatscha, and S. Panke, “In silico genome-scale reconstruction and validation of the Staphylococcus aureus metabolic network,” Biotechnology and Bioengineering, vol. 92, no. 7, pp. 850–864, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. C. H. Schilling, M. W. Covert, I. Famili, G. M. Church, J. S. Edwards, and B. O. Palsson, “Genome-scale metabolic model of Helicobacter pylori 26695,” Journal of Bacteriology, vol. 184, no. 16, pp. 4582–4593, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. A. M. Feist, J. C. M. Scholten, B. Ø. Palsson, F. J. Brockman, and T. Ideker, “Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri,” Molecular Systems Biology, vol. 2, Article ID 2006.0004, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. N. C. Duarte, S. A. Becker, N. Jamshidi et al., “Global reconstruction of the human metabolic network based on genomic and bibliomic data,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 6, pp. 1777–1782, 2007. View at Publisher · View at Google Scholar · View at Scopus
  18. L. K. Nielsen, “On the reconstruction of the Mus musculus genome-scale metabolic network model,” in Genome Informatics, p. 253, World Scientific, 2008. View at Google Scholar
  19. S. Selvarasu, I. A. Karimi, G.-H. Ghim, and D.-Y. Lee, “Genome-scale modeling and in silico analysis of mouse cell metabolic network,” Molecular BioSystems, vol. 6, no. 1, pp. 152–161, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. M. I. Sigurdsson, N. Jamshidi, E. Steingrimsson, I. Thiele, and B. T. Palsson, “A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1,” BMC Systems Biology, vol. 4, article 140, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. P. Pharkya, A. P. Burgard, and C. D. Maranas, “OptStrain: a computational framework for redesign of microbial production systems,” Genome Research, vol. 14, no. 11, pp. 2367–2376, 2004. View at Publisher · View at Google Scholar · View at Scopus
  22. P. Pharkya, A. P. Burgard, and C. D. Maranas, “Exploring the overproduction of amino acids using the bilevel optimization framework optknock,” Biotechnology and Bioengineering, vol. 84, no. 7, pp. 887–899, 2003. View at Publisher · View at Google Scholar · View at Scopus
  23. O. Folger, L. Jerby, C. Frezza, E. Gottlieb, E. Ruppin, and T. Shlomi, “Predicting selective drug targets in cancer through metabolic networks,” Molecular Systems Biology, vol. 7, article 501, 2011. View at Publisher · View at Google Scholar · View at Scopus
  24. H. U. Kim, S. B. Sohn, and S. Y. Lee, “Metabolic network modeling and simulation for drug targeting and discovery,” Biotechnology Journal, vol. 7, no. 3, pp. 330–342, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. D. Perumal, A. Samal, K. R. Sakharkar, and M. K. Sakharkar, “Targeting multiple targets in Pseudomonas aeruginosa PAO1 using flux balance analysis of a reconstructed genome-scale metabolic network,” Journal of Drug Targeting, vol. 19, no. 1, pp. 1–13, 2011. View at Publisher · View at Google Scholar · View at Scopus
  26. A. M. Feist and B. Ø. Palsson, “The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli,” Nature Biotechnology, vol. 26, no. 6, pp. 659–667, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. C. Pál, B. Papp, and M. J. Lercher, “Adaptive evolution of bacterial metabolic networks by horizontal gene transfer,” Nature Genetics, vol. 37, no. 12, pp. 1372–1375, 2005. View at Publisher · View at Google Scholar · View at Scopus
  28. C. Pál, B. Papp, M. J. Lercher, P. Csermely, S. G. Oliver, and L. D. Hurst, “Chance and necessity in the evolution of minimal metabolic networks,” Nature, vol. 440, no. 7084, pp. 667–670, 2006. View at Publisher · View at Google Scholar · View at Scopus
  29. M. A. Oberhardt, J. Puchałka, K. E. Fryer, V. A. P. Martins Dos Santos, and J. A. Papin, “Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1,” Journal of Bacteriology, vol. 190, no. 8, pp. 2790–2803, 2008. View at Publisher · View at Google Scholar · View at Scopus
  30. M. A. Oberhardt, J. Puchałka, V. A. P. M. dos Santos, and J. A. Papin, “Reconciliation of genome-scale metabolic reconstructions for comparative systems analysis,” PLoS Computational Biology, vol. 7, no. 3, Article ID e1001116, 2011. View at Publisher · View at Google Scholar · View at Scopus
  31. J. Puchałka, M. A. Oberhardt, M. Godinho et al., “Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology,” PLoS Computational Biology, vol. 4, no. 10, Article ID e1000210, 2008. View at Publisher · View at Google Scholar · View at Scopus
  32. S. E. Borgos, S. Bordel, H. Sletta et al., “Mapping global effects of the anti-sigma factor MucA in Pseudomonas fluorescens SBW25 through genome-scale metabolic modeling,” BMC Systems Biology, vol. 7, p. 19, 2013. View at Google Scholar
  33. E. E. Smith, D. G. Buckley, Z. Wu et al., “Genetic adaptation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 22, pp. 8487–8492, 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. J. Zhang, H. Li, J. Wang, Z. Dong, S. Mian, and F.-S. X. Yu, “Role of EGFR transactivation in preventing apoptosis in Pseudomonas aeruginosa-infected human corneal epithelial cells,” Investigative Ophthalmology and Visual Science, vol. 45, no. 8, pp. 2569–2576, 2004. View at Publisher · View at Google Scholar · View at Scopus
  35. J. I. Jiménez, B. Miñambres, J. L. García, and E. Díaz, “Genomic analysis of the aromatic catabolic pathways from Pseudomonas putida KT2440,” Environmental Microbiology, vol. 4, no. 12, pp. 824–841, 2002. View at Publisher · View at Google Scholar · View at Scopus
  36. M. J. Worsey and A. P. Williams, “Metablism of toluene and xylenes by Pseudomonas putida (arvilla) mt 2: evidence for a new function of the TOL plasmid,” Journal of Bacteriology, vol. 124, no. 1, pp. 7–13, 1975. View at Google Scholar · View at Scopus
  37. S. A. Becker, A. M. Feist, M. L. Mo, G. Hannum, B. Ø. Palsson, and M. J. Herrgard, “Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox,” Nature Protocols, vol. 2, no. 3, pp. 727–738, 2007. View at Publisher · View at Google Scholar · View at Scopus
  38. J. D. Orth, I. Thiele, and B. O. Palsson, “What is flux balance analysis?” Nature Biotechnology, vol. 28, no. 3, pp. 245–248, 2010. View at Publisher · View at Google Scholar · View at Scopus
  39. B. Mahendran, N.-C. Choi, J.-W. Choi, and D.-J. Kim, “Effect of dissolved oxygen regime on growth dynamics of Pseudomonas spp during benzene degradation,” Applied Microbiology and Biotechnology, vol. 71, no. 3, pp. 350–354, 2006. View at Publisher · View at Google Scholar · View at Scopus
  40. T. Nakazawa and T. Yokota, “Benzoate metabolism in Pseudomonas putida(arvilla) mt 2: demonstration of two benzoate pathways,” Journal of Bacteriology, vol. 115, no. 1, pp. 262–267, 1973. View at Google Scholar · View at Scopus
  41. C. Bagnéris, R. Cammack, and J. R. Mason, “Subtle difference between benzene and toluene dioxygenases of Pseudomonas putida,” Applied and Environmental Microbiology, vol. 71, no. 3, pp. 1570–1580, 2005. View at Publisher · View at Google Scholar · View at Scopus
  42. V. A. P. Martins Dos Santos, S. Heim, E. R. B. Moore, M. Strätz, and K. N. Timmis, “Insights into the genomic basis of niche specificity of Pseudomonas putida KT2440,” Environmental Microbiology, vol. 6, no. 12, pp. 1264–1286, 2004. View at Publisher · View at Google Scholar · View at Scopus
  43. D.-J. Kim, J.-W. Choi, N.-C. Choi, B. Mahendran, and C.-E. Lee, “Modeling of growth kinetics for Pseudomonas spp. during benzene degradation,” Applied Microbiology and Biotechnology, vol. 69, no. 4, pp. 456–462, 2005. View at Publisher · View at Google Scholar · View at Scopus
  44. R. Cunin, N. Glansdorff, A. Pierard, and V. Stalon, “Biosynthesis and metabolism of arginine in bacteria,” Microbiological Reviews, vol. 50, no. 3, pp. 314–352, 1986. View at Google Scholar · View at Scopus
  45. V. Stalon, C. Vander Wauven, P. Momin, and C. Legrain, “Catabolism of arginine, citrulline and ornithine by Pseudomonas and related bacteria,” Journal of General Microbiology, vol. 133, pp. 2487–2495, 1987. View at Google Scholar · View at Scopus
  46. M. H. Sawyer, P. Baumann, and L. Baumann, “Pathways of D fructose catabolism in species of Pseudomonas,” Archives of Microbiology, vol. 112, no. 1, pp. 49–55, 1977. View at Google Scholar · View at Scopus
  47. N. Palleroni and M. Doudoroff, “Some properties and taxonomic sub-divisions of the genus Pseudomonas,” Annual Review of Phytopathology, vol. 10, pp. 73–100, 1972. View at Google Scholar
  48. A. Steen, F. Ö. Utkür, J. M. Borrero-de Acuña et al., “Construction and characterization of nitrate and nitrite respiring Pseudomonas putida KT2440 strains for anoxic biotechnical applications,” ,Journal of Biotechnology, vol. 163, pp. 155–165, 2013. View at Google Scholar
  49. K. Förster-Fromme, B. Höschle, C. Mack, M. Bott, W. Armbruster, and D. Jendrossek, “Identification of genes and proteins necessary for catabolism of acyclic terpenes and leucine/isovalerate in Pseudomonas aeruginosa,” Applied and Environmental Microbiology, vol. 72, no. 7, pp. 4819–4828, 2006. View at Publisher · View at Google Scholar · View at Scopus
  50. P. M. Bapat, D. Das, S. V. Sohoni, and P. P. Wangikar, “Hierarchical amino acid utilization and its influence on fermentation dynamics: rifamycin B fermentation using Amycolatopsis mediterranei S699, a case study,” Microbial Cell Factories, vol. 5, article 32, 2006. View at Publisher · View at Google Scholar · View at Scopus
  51. S. A. Macko, M. L. Fogel, P. E. Hare, and T. C. Hoering, “Isotopic fractionation of nitrogen and carbon in the synthesis of amino acids by microorganisms,” Chemical Geology, vol. 65, no. 1, pp. 79–92, 1987. View at Google Scholar · View at Scopus
  52. L. M. Li, H. Diao, X. L. Ding, K. Qian, and Z. J. Yin, “Effects of methionine or Lysine served as sole Nitrogen and Carbon sources on level of free amino acids and activity of transaminases at in vitro incubation of rumen microorganisms,” Journal of Animal and Veterinary Advances, vol. 10, no. 12, pp. 1588–1591, 2011. View at Publisher · View at Google Scholar · View at Scopus
  53. H. Halvorson, “Utilization of single L-amino acids as sole source of carbon and nitrogen by bacteria,” Canadian Journal of Microbiology, vol. 18, no. 11, pp. 1647–1650, 1972. View at Google Scholar · View at Scopus
  54. A. G. Lochhead and F. E. Chase, “Qualitative studies of soil microorganisms: V. Nutritional requirements of the predominant bacterial flora,” Soil Science, vol. 55, pp. 185–196, 1943. View at Google Scholar
  55. J. G. Coote and H. Hassall, “The degradation of L-histidine, imidazolyl-L-lactate and imidazolylpropionate by Pseudomonas testosteroni,” Biochemical Journal, vol. 132, no. 3, pp. 409–422, 1973. View at Google Scholar · View at Scopus
  56. X.-X. Zhang and P. B. Rainey, “Genetic analysis of the histidine utilization (hut) genes in Pseudomonas fluorescens SBW25,” Genetics, vol. 176, no. 4, pp. 2165–2176, 2007. View at Publisher · View at Google Scholar · View at Scopus
  57. M. L. Gerth, M. P. Ferla, and P. B. Rainey, “The origin and ecological significance of multiple branches for histidine utilization in Pseudomonas aeruginosa PAO1,” Environmental Microbiology, vol. 14, no. 8, pp. 1929–1940, 2012. View at Publisher · View at Google Scholar · View at Scopus
  58. A. Sonawane, U. Klöppner, C. Derst, and K.-H. Röhm, “Utilization of acidic amino acids and their amides by pseudomonads: role of periplasmic glutaminase-asparaginase,” Archives of Microbiology, vol. 179, no. 3, pp. 151–159, 2003. View at Google Scholar · View at Scopus
  59. K. R. Kjeldsen and J. Nielsen, “In silico genome-scale reconstruction and validation of the Corynebacterium glutamicum metabolic network,” Biotechnology and Bioengineering, vol. 102, no. 2, pp. 583–597, 2009. View at Publisher · View at Google Scholar · View at Scopus
  60. W. Zou, M. Zhou, L. Liu, and J. Chen, “Reconstruction and analysis of the industrial strain Bacillus megaterium WSH002 genome-scale in silico metabolic model,” Journal of Biotechnology, vol. 164, pp. 503–509, 2013. View at Google Scholar
  61. Y.-K. Oh, B. O. Palsson, S. M. Park, C. H. Schilling, and R. Mahadevan, “Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data,” Journal of Biological Chemistry, vol. 282, no. 39, pp. 28791–28799, 2007. View at Publisher · View at Google Scholar · View at Scopus