Skip to main content
SpringerLink
Log in

Predicting Gene Essentiality Using Genome-Scale in Silico Models

  • Protocol
Microbial Gene Essentiality: Protocols and Bioinformatics

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 416))

Abstract

Genome-scale metabolic models of organisms can be reconstructed using annotated genome sequence information, well-curated databases, and primary research literature. The metabolic reaction stoichiometry and other physicochemical factors are incorporated into the model, thus imposing constraints that represent restrictions on phenotypic behavior. Based on this premise, the theoretical capabilities of the metabolic network can be assessed by using a mathematical technique known as flux balance analysis (FBA). This modeling framework, also known as the constraint-based reconstruction and analysis approach, differs from other modeling strategies because it does not attempt to predict exact network behavior. Instead, this approach uses known constraints to separate the states that a system can achieve from those that it cannot. In recent years, this strategy has been employed to probe the metabolic capabilities of a number of organisms, to generate and test experimental hypotheses, and to predict accurately metabolic phenotypes and evolutionary outcomes. This chapter introduces the constraint-based modeling approach and focuses on its application to computationally predicting gene essentiality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wheeler, D. L., Church, D. M., Edgar, R., Federhen, S., Helmberg, W., Madden, T. L., et al. (2004) Database resources of the National Center for Biotechnology Information: update. Nucleic Acids Res. 32 (Database issue), D35–40.

    Article  CAS  PubMed  Google Scholar 

  2. Wyrick, J. J., and Young, R. A. (2002) Deciphering gene expression regulatory networks. Curr. Opin. Genet. Dev. 12, 130–136.

    Article  CAS  PubMed  Google Scholar 

  3. Sanford, K., Soucaille, P., Whited, G., and Chotani, G. (2002) Genomics to fluxomics and physiomics—pathway engineering. Curr. Opin. Microbiol. 5, 318–322.

    Article  CAS  PubMed  Google Scholar 

  4. Joyce, A. R., and Palsson, B. O. (2006) The model organism as a system: integrating “omics” data sets. Nat. Rev. Mol. Cell. Biol. 7, 198–210.

    Article  CAS  PubMed  Google Scholar 

  5. Arkin, A. P. (2001) Synthetic cell biology. Curr. Opin. Biotechnol. 12, 638–644.

    Article  CAS  PubMed  Google Scholar 

  6. Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T. S., Matsuzaki, Y., Miyoshi, F., et al. (1999) E-CELL: software environment for whole-cell simulation. Bioinformatics 15, 72–84.

    Article  CAS  PubMed  Google Scholar 

  7. Hoffmann, A., Levchenko, A., Scott, M. L., and Baltimore, D. (2002) The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298, 1241–1245.

    Article  CAS  PubMed  Google Scholar 

  8. Elowitz, M. B., Levine, A. J., Siggia, E. D., and Swain, P. S. (2002) Stochastic gene expression in a single cell. Science 297, 1183–1186.

    Article  CAS  PubMed  Google Scholar 

  9. Arkin, A., Ross, J., and McAdams, H. H. (1998) Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. Genetics 149, 1633–1648.

    CAS  PubMed  Google Scholar 

  10. Sarkar, A., and Franza, B. R. (2004) A logical analysis of the process of T cell activation: different consequences depending on the state of CD28 engagement. J. Theor. Biol. 226, 455–466.

    Article  CAS  PubMed  Google Scholar 

  11. Reed, J. L., Famili, I., Thiele, I., and Palsson, B. O. (2006) Towards multidimensional genome annotation. Nat. Rev. Genet. 7, 130–141.

    Article  CAS  PubMed  Google Scholar 

  12. Price, N. D., Reed, J. L., and Palsson, B. O. (2004) Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat. Rev. Microbiol. 2, 886–897.

    Article  CAS  PubMed  Google Scholar 

  13. Edwards, J. S., Covert, M., and Palsson, B. (2002) Metabolic modelling of microbes: the flux-balance approach. Environ. Microbiol. 4, 133–140.

    Article  PubMed  Google Scholar 

  14. Covert, M. W., Famili, I., and Palsson, B. O. (2003) Identifying constraints that govern cell behavior: a key to converting conceptual to computational models in biology? Biotechnol. Bioeng. 84, 763–772.

    Article  CAS  PubMed  Google Scholar 

  15. Price, N. D., Papin, J. A., Schilling, C. H., and Palsson, B. O. (2003) Genome-scale microbial in silico models: the constraints-based approach. Trends Biotechnol. 21, 162–169.

    Article  CAS  PubMed  Google Scholar 

  16. Varma, A., and Palsson, B. O. (1994) Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl. Environ. Microbiol. 60, 3724–3731.

    CAS  PubMed  Google Scholar 

  17. Kauffman, K. J., Prakash, P., and Edwards, J. S. (2003) Advances in flux balance analysis. Curr. Opin. Biotechnol. 14, 491–496.

    Article  CAS  PubMed  Google Scholar 

  18. Liolios, K., Tavernarakis, N., Hugenholtz, P., and Kyrpides, N. C. (2006) The Genomes On Line Database (GOLD) v.2: a monitor of genome projects worldwide. Nucleic Acids Res. 34, D332–334.

    Article  CAS  PubMed  Google Scholar 

  19. Overbeek, R., Begley, T., Butler, R. M., Choudhuri, J. V., Chuang, H. Y., Cohoon, M., et al. (2005) The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res. 33, 5691–5702.

    Article  CAS  PubMed  Google Scholar 

  20. Brent, M. R. (2005) Genome annotation past, present, and future: how to define an ORF at each locus. Genome Res. 15, 1777–1786.

    Article  CAS  PubMed  Google Scholar 

  21. Neidhardt, F. C., and Curtiss, R. (1996) Escherichia coli and Salmonella: cellular and molecular biology, 2nd ed. Washington, DC: ASM Press.

    Google Scholar 

  22. Scheffler, I. E. (1999) Mitochondria. New York: Wiley-Liss.

    Book  Google Scholar 

  23. Chen, Z. (2003) Assessing sequence comparison methods with the average precision criterion. Bioinformatics 19, 2456–2460.

    Article  CAS  PubMed  Google Scholar 

  24. Karp, P. D., Paley, S., and Romero, P. (2002) The Pathway Tools software. Bioinformatics 18(Suppl 1), S225–232.

    PubMed  Google Scholar 

  25. Cash, P. (2003) Proteomics of bacterial pathogens. Adv. Biochem. Eng. Biotechnol. 83, 93–115.

    CAS  PubMed  Google Scholar 

  26. Taylor, S. W., Fahy, E., and Ghosh, S. S. (2003) Global organellar proteomics. Trends Biotechnol. 21, 82–88.

    Article  CAS  PubMed  Google Scholar 

  27. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., and Hattori, M. (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res. 32 (Database issue), D277–280.

    Article  CAS  PubMed  Google Scholar 

  28. Karp, P. D., Riley, M., Saier, M., Paulsen, I. T., Collado-Vides, J., Paley, S. M., et al. (2002) The EcoCyc Database. Nucleic Acids Res. 30, 56–58.

    Article  CAS  PubMed  Google Scholar 

  29. Mewes, H. W., Amid, C., Arnold, R., Frishman, D., Guldener, U., Mannhaupt, G., et al. (2004) MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res 32 (Database issue), D41–44.

    Article  CAS  PubMed  Google Scholar 

  30. Christie, K. R., Weng, S., Balakrishnan, R., Costanzo, M. C., Dolinski, K., Dwight, S. S., et al. (2004) Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res 32 (Database issue), D311–314.

    Article  CAS  PubMed  Google Scholar 

  31. Caspi, R., Foerster, H., Fulcher, C. A., Hopkinson, R., Ingraham, J., Kaipa, P., et al. (2006) MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 34, D511–516.

    Article  CAS  PubMed  Google Scholar 

  32. Karp, P. D., Ouzounis, C. A., Moore-Kochlacs, C., Goldovsky, L., Kaipa, P., Ahren, D., et al. (2005) Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res. 33, 6083–6089.

    Article  CAS  PubMed  Google Scholar 

  33. Harris, M. A., Clark, J., Ireland, A., Lomax, J., Ashburner, M., Foulger, R., et al. (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res. 32 (Database issue), D258–261.

    Article  CAS  PubMed  Google Scholar 

  34. Gene Ontology Consortium (2006) The Gene Ontology (GO) project in 2006. Nucleic Acids Res. 34, D322–326.

    Article  Google Scholar 

  35. Serres, M. H., Goswami, S., and Riley, M. (2004) GenProtEC: an updated and improved analysis of functions of Escherichia coli K-12 proteins. Nucleic Acids Res. 32 (Database issue), D300–302.

    Article  CAS  PubMed  Google Scholar 

  36. Coulton, G. (2004) Are histochemistry and cytochemistry “Omics”? J. Mol. Histol. 35, 603–613.

    Article  PubMed  Google Scholar 

  37. Arita, M., Robert, M., and Tomita, M. (2005) All systems go: launching cell simulation fueled by integrated experimental biology data. Curr. Opin. Biotechnol. 16, 344–349.

    Article  CAS  PubMed  Google Scholar 

  38. Huh, W. K., Falvo, J. V., Gerke, L. C., Carroll, A. S., Howson, R. W., Weissman, J. S., and O’Shea, E. K. (2003) Global analysis of protein localization in budding yeast. Nature 425, 686–691.

    Article  CAS  PubMed  Google Scholar 

  39. Guda, C., and Subramaniam, S. (2005) pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes. Bioinformatics 21, 3963–3969.

    Article  CAS  PubMed  Google Scholar 

  40. Fields, S. (2005) High-throughput two-hybrid analysis. The promise and the peril. FEBS J. 272, 5391–5399.

    Article  CAS  PubMed  Google Scholar 

  41. Deeds, E. J., Ashenberg, O., and Shakhnovich, E. I. (2006) A simple physical model for scaling in protein-protein interaction networks. Proc. Natl. Acad. Sci. U.S.A. 103, 311–316.

    Article  CAS  PubMed  Google Scholar 

  42. Sprinzak, E., Sattath, S., and Margalit, H. (2003) How reliable are experimental protein-protein interaction data? J. Mol. Biol. 327, 919–923.

    Article  CAS  PubMed  Google Scholar 

  43. Palsson, B. (2004) Two-dimensional annotation of genomes. Nat. Biotechnol. 22, 1218–1219.

    Article  CAS  PubMed  Google Scholar 

  44. Beard, D. A., Liang, S. D., and Qian, H. (2002) Energy balance for analysis of complex metabolic networks. Biophys. J. 83, 79–86.

    Article  CAS  PubMed  Google Scholar 

  45. Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J., and Palsson, B. O. (2004) Integrating high-throughput and computational data elucidates bacterial networks. Nature 429, 92–96.

    Article  CAS  PubMed  Google Scholar 

  46. Covert, M. W., and Palsson, B. O. (2003) Constraints-based models: regulation of gene expression reduces the steady-state solution space. J. Theor. Biol. 221, 309–325.

    Article  CAS  PubMed  Google Scholar 

  47. Covert, M. W., Schilling, C. H., and Palsson, B. (2001) Regulation of gene expression in flux balance models of metabolism. J. Theor. Biol. 213, 73–88.

    Article  CAS  PubMed  Google Scholar 

  48. Covert, M. W., and Palsson, B. O. (2002) Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J. Biol. Chem. 277, 28058–28064.

    Article  CAS  PubMed  Google Scholar 

  49. Reed, J. L., and Palsson, B. O. (2004) Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states. Genome Res. 14, 1797–1805.

    Article  CAS  PubMed  Google Scholar 

  50. Vo, T. D., Greenberg, H. J., and Palsson, B. O. (2004) Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. J. Biol. Chem. 279, 39532–39540.

    Article  CAS  PubMed  Google Scholar 

  51. Palsson, B. O. (2006) Systems Biology: Properties of Reconstructed Networks. New York: Cambridge University Press.

    Book  Google Scholar 

  52. Schilling, C. H., Letscher, D., and Palsson, B. O. (2000) Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J. Theor. Biol. 203, 229–248.

    Article  CAS  PubMed  Google Scholar 

  53. Barrett, C. L., Herring, C. D., Reed, J. L., and Palsson, B. O. (2005) The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states. Proc. Natl. Acad. Sci. U.S.A. 102, 19103–19108.

    Article  CAS  PubMed  Google Scholar 

  54. Neidhardt, F. C., Ingraham, J. L., and Schaechter, M. (1990) Physiology of the Bacterial Cell. Sunderland, MA: Sinauer Associates, Inc.

    Google Scholar 

  55. Edwards, J. S., and Palsson, B. O. (2000) The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl. Acad. Sci. U.S.A. 97, 5528–5533.

    Article  CAS  PubMed  Google Scholar 

  56. Schilling, C. H., and Palsson, B. O. (2000) Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis. J. Theor. Biol. 203, 249–283.

    Article  CAS  PubMed  Google Scholar 

  57. Schilling, C. H., Covert, M. W., Famili, I., Church, G. M., Edwards, J. S., and Palsson, B. O. (2002) Genome-scale metabolic model of Helicobacter pylori 26695. J. Bacteriol. 184, 4582–4593.

    Article  CAS  PubMed  Google Scholar 

  58. Thiele, I., Vo, T. D., Price, N. D., and Palsson, B. (2005) An Expanded Metabolic Reconstruction of Helicobacter pylori (iIT341 GSM/GPR): An in silico genome-scale characterization of single and double deletion mutants. J. Bacteriol. 187, 5818–5830.

    Article  CAS  PubMed  Google Scholar 

  59. Feist, A. M., Scholten, J. C. M., Palsson, B. O., Brockman, F. J., and Ideker, T. (2006) Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri. Mol. Syst. Biol. 2, msb4100046-E4100041-msb4100046-E4100014.

    Google Scholar 

  60. Forster, J., Famili, I., Palsson, B. O., and Nielsen, J. (2003) Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae. Omics 7, 193–202.

    Article  PubMed  Google Scholar 

  61. Kuepfer, L., Sauer, U., and Blank, L. M. (2005) Metabolic functions of duplicate genes in Saccharomyces cerevisiae. Genome Res. 15, 1421–1430.

    Article  CAS  PubMed  Google Scholar 

  62. Duarte, N. C., Herrgard, M. J., and Palsson, B. O. (2004) Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res. 14, 1298–1309.

    Article  CAS  PubMed  Google Scholar 

  63. Allen, T. E., and Palsson, B. O. (2003) Sequence-based analysis of metabolic demands for protein synthesis in prokaryotes. J. Theor. Biol. 220, 1–18.

    Article  CAS  PubMed  Google Scholar 

  64. Papin, J. A., and Palsson, B. O. (2004) Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk. J. Theor. Biol. 227, 283–297.

    Article  PubMed  Google Scholar 

  65. Papin, J. A., Hunter, T., Palsson, B. O., and Subramaniam, S. (2005) Reconstruction of cellular signalling networks and analysis of their properties. Nat. Rev. Mol. Cell. Biol. 6, 99–111.

    Article  CAS  PubMed  Google Scholar 

  66. Papin, J. A., and Palsson, B. O. (2004) The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis. Biophys. J. 87, 37–46.

    Article  CAS  PubMed  Google Scholar 

  67. Gianchandani, E. P., Papin, J. A., Price, N. D., Joyce, A. R., and Palsson, B. O. (2006) Matrix formalism to describe functional States of transcriptional regulatory systems. PLoS Comput. Biol. 2, e101.

    Article  PubMed  Google Scholar 

  68. Reed, J. L., Vo, T. D., Schilling, C. H., and Palsson, B. O. (2003) An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol. 4, R54.

    Article  PubMed  Google Scholar 

  69. Reed, J. L., and Palsson, B. O. (2003) Thirteen years of building constraint-based in silico models of Escherichia coli. J. Bacteriol. 185, 2692–2699.

    Article  CAS  PubMed  Google Scholar 

  70. Becker, S. A., and Palsson, B. O. (2005) Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: an initial draft to the two-dimensional annotation. BMC Microbiol. 5, 8.

    Article  PubMed  Google Scholar 

  71. Mahadevan, R., Bond, D. R., Butler, J. E., Esteve-Nunez, A., Coppi, M. V., Palsson, B. O., Schilling, C. H., and Lovley, D. R. (2006) Characterization of metabolism in the Fe(III)-reducing organism Geobacter sulfurreducens by constraint-based modeling. Appl. Environ. Microbiol. 72, 1558–1568.

    Article  CAS  PubMed  Google Scholar 

  72. Borodina, I., Krabben, P., and Nielsen, J. (2005) Genome-scale analysis of Streptomyces coelicolor A3 (2) metabolism. Genome Res. 15, 820–829.

    Article  CAS  PubMed  Google Scholar 

  73. Forster, J., Famili, I., Fu, P., Palsson, B. O., and Nielsen, J. (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13, 244–253.

    Article  CAS  PubMed  Google Scholar 

  74. Almaas, E., Oltvai, Z. N., and Barabasi, A. L. (2005) The Activity Reaction Core and Plasticity of Metabolic Networks. PLoS Comput. Biol. 1, e68.

    Article  PubMed  Google Scholar 

  75. Segre, D., DeLuna, A., Church, G. M., and Kishnoy, R. (2005) Modular epistasis in yeast metabolism. Nat. Genet. 37, 77–83.

    CAS  PubMed  Google Scholar 

  76. Sheikh, K., Forster, J., and Nielsen, L. K. (2005) Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus. Biotechnol. Prog. 21, 112–121.

    Article  CAS  PubMed  Google Scholar 

  77. Wiback, S. J., and Palsson, B. O. (2002) Extreme pathway analysis of human red blood cell metabolism. Biophys. J. 83, 808–818.

    Article  CAS  PubMed  Google Scholar 

  78. Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., et al. (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531.

    Article  CAS  PubMed  Google Scholar 

  79. Novere, N. L., Finney, A., Hucka, M., Bhalla, U. S., Campagne, F., Collado-Vides, J., et al. (2005) Minimum information requested in the annotation of biochemical models (MIRIAM). Nat. Biotechnol. 23, 1509–1515.

    Article  PubMed  Google Scholar 

  80. Hartwell, L. (2004) Genetics. Robust interactions. Science 303, 774–775.

    Article  CAS  PubMed  Google Scholar 

  81. Tong, A. H., Lesage, G., Bader, G. D., Ding, H., Xu, H., Xin, X., et al. (2004) Global mapping of the yeast genetic interaction network. Science 303, 808–813.

    Article  CAS  PubMed  Google Scholar 

  82. Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., et al. (2006) Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, msb4100050-E4100051-msb4100050-E4100011.

    Google Scholar 

  83. Glasner, J. D., Liss, P., Plunkett, G. 3rd, Darling, A., Prasad, T., Rusch, M., et al. (2003) ASAP, a systematic annotation package for community analysis of genomes. Nucleic Acids Res. 31, 147–151.

    Article  CAS  PubMed  Google Scholar 

  84. Herrgard, M. J., Lee, B. S., Portnoy, V., and Palsson, B. O. (2006) Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res. 16, 627–635.

    Article  CAS  PubMed  Google Scholar 

  85. Salgado, H., Gama-Castro, S., Martinez-Antonio, A., Diaz-Peredo, E., Sanchez-Solano, F., Peralta-Gil, M., et al. (2004) RegulonDB (version 4.0): transcriptional regulation, operon organization and growth conditions in Escherichia coli K-12. Nucleic Acids Res. 32 (Database issue), D303–306.

    Article  CAS  PubMed  Google Scholar 

  86. Segre, D., Vitkup, D., and Church, G. M. (2002) Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad. Sci. U.S.A. 99, 15112–15117.

    Article  CAS  PubMed  Google Scholar 

  87. Segre, D., Zucker, J., Katz, J., Lin, X., D’Haeseleer, P., Rindone, W. P., et al. (2003) From annotated genomes to metabolic flux models and kinetic parameter fitting. Omics 7, 301–316.

    Article  CAS  PubMed  Google Scholar 

  88. Shlomi, T., Berkman, O., and Ruppin, E. (2005) Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc. Natl. Acad. Sci. U.S.A. 102, 7695–7700.

    Article  CAS  PubMed  Google Scholar 

  89. Burgard, A. P., Pharkya, P., and Maranas, C. D. (2003) Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 84, 647–657.

    Article  CAS  PubMed  Google Scholar 

  90. Fong, S. S., Burgard, A. P., Herring, C. D., Knight, E. M., Blattner, F. R., Maranas, C. D., and Palsson, B. O. (2005) In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol. Bioeng. 91, 643–648.

    Article  CAS  PubMed  Google Scholar 

  91. Oh, Y.K., Palsson, B.O., Park, S.M., Schilling, C.M., and Mahadevon, R. (2007) Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data. J. Biol. Chem., in press.

    Google Scholar 

  92. Edwards, J. S., and Palsson, B. O. (1999) Systems properties of the Haemophilus influenzae Rd metabolic genotype. J. Biol. Chem. 274, 17410–17416.

    Article  CAS  PubMed  Google Scholar 

  93. Oliveira, A. P., Nielsen, J., and Forster, J. (2005) Modeling Lactococcus lactis using a genome-scale flux model. BMC Microbiol. 5, 39.

    Article  PubMed  Google Scholar 

  94. Hong, S. H., Kim, J. S., Lee, S. Y., In, Y. H., Choi, S. S., Rih, J. K., et al. (2004) The genome sequence of the capnophilic rumen bacterium Mannheimia succiniciproducens. Nat. Biotechnol. 22, 1275–1281.

    Article  CAS  PubMed  Google Scholar 

  95. Taylor, S. W., Fahy, E., Zhang, B., Glenn, G. M., Warnock, D. E., Wiley, S., et al. (2003) Characterization of the human heart mitochondrial proteome. Nat. Biotechnol. 21, 281–286.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bioinformatics Program, University of California, San Diego, La Jolla, CA

    Andrew R. Joyce

  2. Department of Bioengineering, University of California, San Diego, La Jolla, CA

    Bernhard Ø. Palsson

Authors
  1. Andrew R. Joyce
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bernhard Ø. Palsson
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Burnham Institute for Medical Research, La Jolla, California

    Andrei L. Osterman

  2. Fellowship for Interpretation of Genomes (FIG), Burr Ridge, Illinois

    Svetlana Y. Gerdes

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Humana Press Inc., a part of Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Joyce, A.R., Palsson, B.Ø. (2008). Predicting Gene Essentiality Using Genome-Scale in Silico Models. In: Osterman, A.L., Gerdes, S.Y. (eds) Microbial Gene Essentiality: Protocols and Bioinformatics. Methods in Molecular Biology™, vol 416. Humana Press. https://doi.org/10.1007/978-1-59745-321-9_30

Download citation

  • DOI: https://doi.org/10.1007/978-1-59745-321-9_30

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-378-7

  • Online ISBN: 978-1-59745-321-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation