Abstract
The activity and essentiality of metabolic reactions of two model organisms, Escherichia coli and Mycoplasma pneumoniae, are studied using flux balance analysis in different environments. In particular, synthetic lethal pairs correspond to combinations of active and active or inactive non-essential reactions whose simultaneous deletion causes cell death. Lethal knockouts of pairs of reactions separate in two different groups depending on whether the pair of reactions works as a backup or as a parallel use mechanism, the first corresponding to essential plasticity and the second to essential redundancy. Within this perspective, functional plasticity and redundancy are essential mechanisms underlying the ability to survive of metabolic networks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Almaas E, Kovacs B, Vicsek T, Oltvai ZN, Barabási AL (2004) Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427(6977):839–843
Almaas E, Oltvai ZN, Barabási AL (2005) The activity reaction core and plasticity of metabolic networks. PLoS Comput Biol 1:0557–0563
Baba T et al (2006) Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol 2(1)
Joyce AR et al (2006) Experimental and computational assessment of conditionally essential genes in Escherichia coli. J Bacteriol 188(23):8259–8271
Barve A, Rodrigues JFM, Wagner A (2012) Superessential reactions in metabolic networks. Proc Natl Acad Sci USA 1091:E1121–E1130
Suthers PF, Zomorrodi A, Maranas CD (2009) Genome-scale gene/reaction essentiality and synthetic lethality analysis. Mol Syst Biol 5:301
Wang Z, Zhang J (2009) Abundant indispensable redundancies in cellular metabolic networks. Genome Biol Evol 1:23–33
Nygaard P, Smith JM (1993a) Evidence for a novel glycinamide ribonucleotide transformylase in Escherichia coli. J Bacteriol 175:3591–3597
Hartman JL, Garvik B, Hartwell L (2001) Principles for the buffering of genetic variation. Science 291:1001–1004
Tucker CL, Fields S (2003) Lethal combinations. Nat Genet 35:204–205
Masel J, Siegal ML (2009) Robustness: mechanisms and consequences. Trends Genet 25:395–403
Nijman SMB (2011) Synthetic lethality: general principles, utility and detection using genetic screens in human cells. FEBS Lett 585:1–6
Kaelin WG (2005) The concept of synthetic lethality in the context of anticancer therapy. Nat Rev Cancer 5:689–698
Harrison R, Papp B, Pál C, Oliver SG, Delneri D (2007) Plasticity of genetic interactions in metabolic networks of yeast. Proc Natl Acad Sci USA 104:2307–2312
Wagner A (2005) Distributed robustness versus redundancy as causes of mutational robustness. BioEssays 27:176–188
Kelley R, Ideker T (2005) Systematic interpretation of genetic interactions using protein networks. Nat Biotechnol 23:561–566
Güell O, Serrano MÁ, Sagués F (2014) Environmental dependence of the activity and essentiality of reactions in the metabolism of Escherichia coli. In Engineering of Chemical Complexity II. World Scientific Publishing, Singapore ISBN 978-981-4616-12-6
Güell O, Sagués F, Serrano MÁ (2014) Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis. PLoS Comput Biol 10(5):e1003637
Novick P, Osmond BC, Botstein D (1989) Suppressors of yeast actin mutations. Genetics 121:659–674
Zhao G, Winkler ME (1995) An Escherichia coli K-12 tktA tktB mutant deficient in transketolase activity requires pyridoxine (vitamin B\(_6\)) as well as the aromatic amino acids and vitamins for growth. J Bacteriol 176:883–891
Deutscher D, Meilijson I, Kupiec M, Ruppin E (2006) Multiple knockout analysis of genetic robustness in the yeast metabolic network. Nat Genet 38:993–998
Mahadevan R, Schilling CH (2003) The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng 5:264–276
Gudmundsson S, Thiele I (2010) Computationally efficient flux variability analysis. BMC Bioinform 11:489
Orth JD et al (2011) A comprehensive genome-scale reconstruction of Escherichia coli metabolism - 2011. Mol Syst Biol 7:535
Glass JI et al (2006) Essential genes of a minimal bacterium. Proc Natl Acad Sci USA 103:425–430
Wodke JAH et al (2013) Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling. Mol Syst Biol 9:653
Yus E et al (2009) Impact of genome reduction on bacterial metabolism and its regulation. Science 326:1263–1268
Whalen WA, Berg CM (1982) Analysis of avtA: Mu d1(ap lac) mutant: metabolic role of transaminase C. J Bacteriol 150:739–746
Nygaard P, Smith JM (1993b) Evidence for a novel glycinamide ribonucleotide transformylase in Escherichia coli. J Bacteriol 175:3591–3597
Troup B, Hungerer C, Jahn D (1995) Cloning and characterization of the Escherichia coli hemN gene encoding the oxygen-independent coproporphyrinogen III oxidase. J Bacteriol 177:3326–3331
Rompf A et al (1998) Regulation of Pseudomonas aeruginosa hemF and hemN by the dual action of the redox response regulators Anr and Dnr. Mol Microbiol 29:985–997
Jiao Z, Baba T, Mori H, Shimizu K (2003) Analysis of metabolic and physiological responses to gnd knockout in Escherichia coli by using C-13 tracer experiment and enzyme activity measurement. FEMS Microbiol Lett 220:295–301
Rude MA, Schirmer A (2009) New microbial fuels: a biotech perspective. Curr Opin Microbiol 12:274–281
Serrano MÁ, Boguñá M, Sagués F (2012) Uncovering the hidden geometry behind metabolic networks. Mol BioSyst 8:843–850
Giaever G et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418:387–391
Steinmetz LM et al (2002) Systematic screen for human disease genes in yeast. Nat Genet 31:400–404
Nakahigashi K et al (2009) Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism. Mol Syst Biol 5:306
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Güell, O. (2017). Effects of Reaction Knockouts on Steady States of Metabolism. In: A Network-Based Approach to Cell Metabolism. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-64000-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-64000-6_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63999-4
Online ISBN: 978-3-319-64000-6
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)