Modeling a Minimal Cell

  • Michael L. Shuler
  • Patricia Foley
  • Jordan Atlas
Part of the Methods in Molecular Biology book series (MIMB, volume 881)


One important aim of synthetic biology is to develop a self-replicating biological system capable of performing useful tasks. A mathematical model of a synthetic organism would greatly enhance its value by providing a platform in which proposed modifications to the system could be rapidly prototyped and tested. Such a platform would allow the explicit connection of genomic sequence information to physiological predictions. As an initial step toward this aim, a minimal cell model (MCM) has been formulated. The MCM is defined as a model of a hypothetical cell with the minimum number of genes necessary to grow and divide in an optimally supportive culture environment. It is chemically detailed in terms of genes and gene products, as well as physiologically complete in terms of bacterial cell processes (e.g., DNA replication and cell division). A mathematical framework originally developed for modeling Escherichia coli has been used to build the platform MCM. A MCM with 241 product-coding genes (those which produce protein or stable RNA products) is presented. This gene set is genomically complete in that it codes for all the functions that a minimal chemoheterotrophic bacterium would require for sustained growth and division. With this model, the hypotheses behind a minimal gene set can be tested using a chemically detailed, dynamic, whole-cell modeling approach. Furthermore, the MCM can simulate the behavior of a whole cell that depends on the cell’s (1) metabolic rates and chemical state, (2) genome in terms of expression of various genes, (3) environment both in terms of direct nutrient starvation and competitive inhibition leading to starvation, and (4) genomic sequence in terms of the chromosomal locations of genes.

Key words

Minimal cell Systems biology Synthetic biology Cell model Minimal gene set Dynamic cell model Bacterial cell model Differential algebraic equation cell model 



JA gratefully acknowledges funding from the DOE Computational Science Graduate Fellowship Program (CSGF) of the Office of Science and National Nuclear Security Administration in the DOE under contract DE-FG02-97ER25308.


  1. 1.
    Agapakis CM, Silver PA (2009) Synthetic biology: exploring and exploiting genetic modularity through the design of novel biological networks. Mol Biosyst 5(7):704–713. doi:  10.1039/b901484e,
  2. 2.
    Drubin DA, Way JC, Silver PA (2007) Designing biological systems. Genes Dev 21(3):242–254. doi:  10.1101/gad.1507207, Google Scholar
  3. 3.
    Purnick PEM, Weiss R (2009) The second wave of synthetic biology: from modules to systems. Nat Rev Mol Cell Biol 10(6):410–422. doi:  10.1038/nrm2698, Google Scholar
  4. 4.
    Leonard E et al (2008) Engineering microbes with synthetic biology frameworks. Trends Biotechnol 26(12):674–681. doi:  10.1016/j.tibtech.2008.08.003, Google Scholar
  5. 5.
    Loeb J (1906) The dynamics of living matter. Macmillan, New York, NYGoogle Scholar
  6. 6.
    Pohorille A, Deamer D (2002) Artificial cells: prospects for biotechnology. Trends Biotechnol 20(3):123–128PubMedCrossRefGoogle Scholar
  7. 7.
    Rasmussen S et al (2004) Evolution. Transitions from nonliving to living matter. Science 303(5660):963–965. doi:  10.1126/science.1093669, Google Scholar
  8. 8.
    Hanczyc MM, Szostak JW (2004) Replicating vesicles as models of primitive cell growth and division. Curr Opin Chem Biol 8(6):660–664. doi:  10.1016/j.cbpa.2004.10.002,
  9. 9.
    Luisi PL, Ferri F, Stano P (2006) Approaches to semi-synthetic minimal cells: a review. Naturwissenschaften 93(1):1–13. doi:  10.1007/s00114-005-0056-z, Google Scholar
  10. 10.
    Segré D et al (2001) The lipid world. Orig Life Evol Biosph 31(1–2):119–145PubMedCrossRefGoogle Scholar
  11. 11.
    Forster AC, Church GM (2006) Towards synthesis of a minimal cell. Mol Syst Biol 2:45PubMedCrossRefGoogle Scholar
  12. 12.
    Zimmer C (2003) Genomics—Tinker, tailor: can Venter stitch together a genome from scratch? Science 299(5609):1006–1007PubMedCrossRefGoogle Scholar
  13. 13.
    Morowitz HJ (1984) The completeness of molecular-biology. Isr J Med Sci 20(9):750–753PubMedGoogle Scholar
  14. 14.
    Moya A et al (2009) Toward minimal bacterial cells: evolution vs. design. FEMS Microbiol Rev 33(1):225–235. doi:  10.1111/j.1574-6976.2008.00151.x,
  15. 15.
    Lartigue C et al (2007) Genome transplantation in bacteria: changing one species to another. Science 317(5838):632–638. doi:  10.1126/science.1144622, Google Scholar
  16. 16.
    Gibson DG et al (2008) Complete chemical synthesis, assembly, and cloning of a Mycoplasma genitalium genome. Science 319(5867):1215–1220. doi:  10.1126/science.1151721,
  17. 17.
    Lartigue C et al (2009) Creating bacterial strains from genomes that have been cloned and engineered in yeast. Science 325(5948):1693–1696. doi:  10.1126/science.1173759, Google Scholar
  18. 18.
    Gibson DG et al (2010) Creation of a bacterial cell controlled by a chemically synthesized genome. Science 329(5987):52–56. doi:  10.1126/science.1190719, Google Scholar
  19. 19.
    Waters E et al (2003) The genome of nanoarchaeum equitans: insights into early archaeal evolution and derived parasitism. Proc Natl Acad Sci USA 100(22):12984–12988PubMedCrossRefGoogle Scholar
  20. 20.
    Gil R et al (2002) Extreme genome reduction in Buchnera spp.: toward the minimal genome needed for symbiotic life. Proc Natl Acad Sci USA 99(7):4454–4458PubMedCrossRefGoogle Scholar
  21. 21.
    Nakabachi A et al (2006) The 160-kilobase genome of the bacterial endosymbiont carsonella. Science 314(5797):267. doi:  10.1126/science.1134196, Google Scholar
  22. 22.
    Fraser CM et al (1995) The minimal gene complement of Mycoplasma genitalium. Science 270(5235):397–403PubMedCrossRefGoogle Scholar
  23. 23.
    Blattner FR et al (1997) The complete genome sequence of Escherichia coli K-12. Science 277(5331):1453–1474PubMedCrossRefGoogle Scholar
  24. 24.
    Maniloff J (1996) The minimal cell genome: “on being the right size”. Proc Natl Acad Sci USA 93(19):10004–10006PubMedCrossRefGoogle Scholar
  25. 25.
    Mushegian AR, Koonin EV (1996) A minimal gene set for cellular life derived by comparison of complete bacterial genomes. Proc Natl Acad Sci USA 93(19):10268–10273PubMedCrossRefGoogle Scholar
  26. 26.
    Hutchison CA et al (1999) Global transposon mutagenesis and a minimal Mycoplasma genome. Science 286(5447):2165–2169PubMedCrossRefGoogle Scholar
  27. 27.
    Koonin EV (2000) How many genes can make a cell: the minimal-gene-set concept. Annu Rev Genomics Hum Genet 1:99–116PubMedCrossRefGoogle Scholar
  28. 28.
    Kobayashi K et al (2003) Essential Bacillus subtilis genes. Proc Natl Acad Sci USA 100(8):4678–4683PubMedCrossRefGoogle Scholar
  29. 29.
    Gil R et al (2004) Determination of the core of a minimal bacterial gene set. Microbiol Mol Biol Rev 68(3):518–537PubMedCrossRefGoogle Scholar
  30. 30.
    Glass JI et al (2006) Essential genes of a minimal bacterium. Proc Natl Acad Sci USA 103(2):425–430PubMedCrossRefGoogle Scholar
  31. 31.
    Tomita M et al (1999) E-CELL: software environment for whole-cell simulation. Bioinformatics 15(1):72–84PubMedCrossRefGoogle Scholar
  32. 32.
    Koonin EV (2003) Comparative genomics, minimal gene-sets and the last universal common ancestor. Nat Rev Microbiol 1(2):127–136PubMedCrossRefGoogle Scholar
  33. 33.
    Luisi PL (2002) Toward the engineering of minimal living cells. Anat Rec 268(3):208–214PubMedCrossRefGoogle Scholar
  34. 34.
    Lamichhane G et al (2003) A postgenomic method for predicting essential genes at subsaturation levels of mutagenesis: application to mycobacterium tuberculosis. Proc Natl Acad Sci USA 100(12):7213–7218PubMedCrossRefGoogle Scholar
  35. 35.
    Itaya M (1995) An estimation of minimal genome size required for life. FEBS Lett 362(3):257–260PubMedCrossRefGoogle Scholar
  36. 36.
    Forsyth RA et al (2002) A genome-wide strategy for the identification of essential genes in Staphylococcus aureus. Mol Microbiol 43(6):1387–1400PubMedCrossRefGoogle Scholar
  37. 37.
    Gerdes SY et al (2003) Experimental determination and system level analysis of essential genes in Escherichia coli MG1655. J Bacteriol 185(19):5673–5684PubMedCrossRefGoogle Scholar
  38. 38.
    Peterson SN, Fraser CM (2001) The complexity of simplicity. Genome Biol 2(2):1–8. Google Scholar
  39. 39.
    Nesbø CL, Boucher Y, Doolittle WF (2001) Defining the core of nontransferable prokaryotic genes: the euryarchaeal core. J Mol Evol 53(4–5):340–350. doi:  10.1007/s002390010224, Google Scholar
  40. 40.
    Harris JK et al (2003) The genetic core of the universal ancestor. Genome Res 13(3):407–412. doi:  10.1101/gr.652803, Google Scholar
  41. 41.
    Gil R et al (2003) The genome sequence of Blochmannia floridanus: comparative analysis of reduced genomes. Proc Natl Acad Sci USA 100(16):9388–9393PubMedCrossRefGoogle Scholar
  42. 42.
    Pál C et al (2006) Chance and necessity in the evolution of minimal metabolic networks. Nature 440(7084):667–670. doi:  10.1038/nature04568, Google Scholar
  43. 43.
    Gabaldón T et al (2007) Structural analyses of a hypothetical minimal metabolism. Philos Trans R Soc Lond B Biol Sci 362(1486):1751–1762. doi:  10.1098/rstb.2007.2067,
  44. 44.
    Carbone A (2006) Computational prediction of genomic functional cores specific to different microbes. J Mol Evol 63(6):733–746. doi:  10.1007/s00239-005-0250-9, Google Scholar
  45. 45.
    Forster AC, Church GM (2007) Synthetic biology projects in vitro. Genome Res 17(1):1–6. doi:  10.1101/gr.5776007, Google Scholar
  46. 46.
    Azuma Y, Ota M (2009) An evaluation of minimal cellular functions to sustain a bacterial cell. BMC Syst Biol 3:111. doi:  10.1186/1752-0509-3-111,
  47. 47.
    Foley PL, Shuler ML (2010) Considerations for the design and construction of a synthetic platform cell for biotechnological applications. Biotechnol Bioeng 105(1):26–36. doi:  10.1002/bit.22575,
  48. 48.
    Karp PD et al (2004) The E-coli ecocyc database: no longer just a metabolic pathway database. ASM News 70(1):25–30Google Scholar
  49. 49.
    Burgard AP, Maranas CD (2001) Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions. Biotechnol Bioeng 74(5):364–375PubMedCrossRefGoogle Scholar
  50. 50.
    Burgard AP, Vaidyaraman S, Maranas CD (2001) Minimal reaction sets for Escherichia coli metabolism under different growth requirements and uptake environments. Biotechnol Prog 17(5):791–797PubMedCrossRefGoogle Scholar
  51. 51.
    Edwards JS, Palsson BO (2000) The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc Natl Acad Sci USA 97(10):5528–5533PubMedCrossRefGoogle Scholar
  52. 52.
    Edwards JS, Covert M, Palsson B (2002) Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 4(3):133–140PubMedCrossRefGoogle Scholar
  53. 53.
    Durot M, Bourguignon PY, Schachter V (2009) Genome-scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiol Rev 33(1):164–190. doi:  10.1111/j.1574-6976.2008.00146.x,
  54. 54.
    Chassagnole C et al (2002) Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng 79(1):53–73PubMedCrossRefGoogle Scholar
  55. 55.
    Tomita M (2001) Whole-cell simulation: a grand challenge of the 21st century. Trends Biotechnol 19(6):205–210PubMedCrossRefGoogle Scholar
  56. 56.
    Schlosser PM, Bailey JE (1990) An integrated modeling-experimental strategy for the analysis of metabolic pathways. Math Biosci 100(1):87–114PubMedCrossRefGoogle Scholar
  57. 57.
    Shuler ML, Dick C (1979) A mathematical model for the growth of a single bacterial cell. Ann N Y Acad Sci 326:35–55CrossRefGoogle Scholar
  58. 58.
    Bailey JE (1998) Mathematical modeling and analysis in biochemical engineering: past accomplishments and future opportunities. Biotechnol Prog 14(1):8–20. doi:  10.1021/bp9701269,
  59. 59.
    Domach MM (1983) Refinement and use of a structured model of a single cell of Escherichia coli for the description of ammonia-limited growth and asynchonous population dynamics. Ph.D. thesis. Cornell UniversityGoogle Scholar
  60. 60.
    Shuler ML (1999) Single-cell models: promise and limitations. J Biotechnol 71(1–3):225–228PubMedCrossRefGoogle Scholar
  61. 61.
    Domach MM, Shuler ML (1984) Testing of a potential mechanism for Escherichia coli temporal cycle imprecision with a structural model. J Theor Biol 106(4):577–585PubMedCrossRefGoogle Scholar
  62. 62.
    Lee AL, Ataai MM, Shuler ML (1984) Double-substrate-limited growth of Escherichia coli. Biotechnol Bioeng 26(11):1398–1401PubMedCrossRefGoogle Scholar
  63. 63.
    Shuler ML, Domach MM (1983) Mathematical-models of the growth of individual cells—tools for testing biochemical-mechanisms. ACS Symp Ser 207:93–133CrossRefGoogle Scholar
  64. 64.
    Browning ST, Castellanos M, Shuler ML (2004) Robust control of initiation of prokaryotic chromosome replication: essential considerations for a minimal cell. Biotechnol Bioeng 88(5):575–584. doi:  10.1002/bit.20223, Google Scholar
  65. 65.
    Atlas JC et al (2008) Incorporating genome-wide DNA sequence information into a dynamic whole-cell model of Escherichia coli: application to DNA replication. IET Syst Biol 2(5):369–382. doi:  10.1049/iet-syb:20070079, Google Scholar
  66. 66.
    Nikolaev E, Atlas J, Shuler ML (2006) Computer models of bacterial cells: from generalized coarse-grained to genome-specific modular models. J Phys Conf Ser 46:322–326CrossRefGoogle Scholar
  67. 67.
    Shu J, Shuler ML (1991) Prediction of effects of amino-acid supplementation on growth of Escherichia coli B/r. Biotechnol Bioeng 37(8):708–715PubMedCrossRefGoogle Scholar
  68. 68.
    Laffend L, Shuler ML (1994) Ribosomal-protein limitations in Escherichia coli under conditions of high translational activity. Biotechnol Bioeng 43(5):388–398PubMedCrossRefGoogle Scholar
  69. 69.
    Laffend L, Shuler ML (1994) Structured model of genetic-control via the lac promoter in Escherichia coli. Biotechnol Bioeng 43(5):399–410PubMedCrossRefGoogle Scholar
  70. 70.
    Kim BG et al (1987) Growth-behavior and prediction of copy number and retention of cole1-type plasmids in Escherichia-coli under slow growth-conditions. Ann N Y Acad Sci 506:384–395PubMedCrossRefGoogle Scholar
  71. 71.
    Kim BG, Shuler ML (1990) A structured, segregated model for genetically modified Escherichia coli cells and its use for prediction of plasmid stability. Biotechnol Bioeng 36(6):581–592PubMedCrossRefGoogle Scholar
  72. 72.
    Kim BG, Shuler ML (1991) Kinetic-analysis of the effects of plasmid multimerization on segregational instability of cole1 type plasmids in Escherichia coli B/R. Biotechnol Bioeng 37(11):1076–1086PubMedCrossRefGoogle Scholar
  73. 73.
    Browning ST, Shuler ML (2001) Towards the development of a minimal cell model by generalization of a model of Escherichia coli: use of dimensionless rate parameters. Biotechnol Bioeng 76(3):187–192PubMedCrossRefGoogle Scholar
  74. 74.
    Castellanos M, Wilson DB, Shuler ML (2004) A modular minimal cell model: purine and pyrimidine transport and metabolism. Proc Natl Acad Sci USA 101(17):6681–6686. doi:  10.1073/pnas.0400962101,
  75. 75.
    Castellanos M et al (2007) A genomically/chemically complete module for synthesis of lipid membrane in a minimal cell. Biotechnol Bioeng 97(2):397–409. doi:  10.1002/bit.21251, Google Scholar
  76. 76.
    Gutenkunst RN et al (2007) Extracting falsifiable predictions from sloppy models. Ann N Y Acad Sci 1115:203–211. doi:  10.1196/annals.1407.003,
  77. 77.
    Labarère J (1992) DNA replication and repair. In: Maniloff J, McElhaney R, Finch L, Baseman J (eds) Mycoplasmas molecular biology and pathogenesis. American Society for Microbiology, Washington, DC, pp 23–40Google Scholar
  78. 78.
    Capaldo-Kimball F, Barbour SD (1971) Involvement of recombination genes in growth and viability of Escherichia coli k-12. J Bacteriol 106(1):204–212PubMedGoogle Scholar
  79. 79.
    Bramhill D (1997) Bacterial cell division. Annu Rev Cell Dev Biol 13:395–424. doi:  10.1146/annurev.cellbio.13.1.395,
  80. 80.
    Hutkins RW, Nannen NL (1993) pH homeostasis in lactic acid bacteria. J Dairy Sci 76:2354–2365CrossRefGoogle Scholar
  81. 81.
    Reynolds CM, Meyer J, Poole LB (2002) An NADH-dependent bacterial thioredoxin reductase-like protein in conjunction with a glutaredoxin homologue form a unique peroxiredoxin (AhpC) reducing system in Clostridium pasteurianum. Biochemistry 41(6):1990–2001PubMedCrossRefGoogle Scholar
  82. 82.
    Kuruma Y et al (2009) A synthetic biology approach to the construction of membrane proteins in semi-synthetic minimal cells. Biochimica et Biophysica Acta 1788(2):567–574. doi:  10.1016/j.bbamem.2008.10.017,
  83. 83.
    Sirand-Pugnet P et al (2007) Evolution of mollicutes: down a bumpy road with twists and turns. Res Microbiol 158(10):754–766. doi:  10.1016/j.resmic.2007.09.007,
  84. 84.
    Brown KS, Sethna JP (2003) Statistical mechanical approaches to models with many poorly known parameters. Phys Rev E 68(2)Google Scholar
  85. 85.
    Gutenkunst RN et al (2007) Universally sloppy parameter sensitivities in systems biology models. PLoS Comput Biol 3(10):1871–1878. doi:  10.1371/journal.pcbi.0030189,
  86. 86.
    Hucka M et al (2008) Systems biology markup language (SBML) level 2: structures and facilities for model definitions. Nat Proc. doi:,
  87. 87.
    Neidhardt FC, et al (1996) Chemical Composition of Escherichia coli, in Escherichia coli and Salmonella: cellular and molecular biology, 2nd edn., vol. 1 ASM Press, Washington, D.C., pp 13–16Google Scholar
  88. 88.
    Bremer H, Dennis P (1996) Modulation of chemical composition and other parameters of the cell by growth rate. In: Neidhart FC (ed) Escherichia coli and Salmonella: cellular and molecular biology. ASM Press, WashingtonGoogle Scholar
  89. 89.
    Kanehisa M, Goto S (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27–30PubMedCrossRefGoogle Scholar
  90. 90.
    Seto S, Miyata M (1998) Cell reproduction and morphological changes in Mycoplasma capricolum. J Bacteriol 180(2):256–264PubMedGoogle Scholar
  91. 91.
    Cheng Y, Prusoff WH (1973) Relationship between the inhibition constant (K1) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. Biochem Pharmacol 22(23):3099–3108PubMedCrossRefGoogle Scholar
  92. 92.
    Quintero MJ et al (2001) Identification of genes encoding amino acid permeases by inactivation of selected ORFs from the synechocystis genomic sequence. Genome Res 11(12):2034–2040PubMedCrossRefGoogle Scholar
  93. 93.
    Berkelaar M, Eikland K, Notebaert P (2010) lpsolve—open source (mixed-integer) linear programming system, version
  94. 94.
    Powell EO (1956) Growth rate and generation time of bacteria, with special reference to continuous culture. J Gen Microbiol 15(3):492–511PubMedCrossRefGoogle Scholar
  95. 95.
    Atlas JC (2010) Simulation of a whole-cell with the minimum number of genes necessary for sustained replication. Ph.D. thesis. Cornell UniversityGoogle Scholar
  96. 96.
    Hucka M et al (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4):524–531PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Michael L. Shuler
    • 1
  • Patricia Foley
    • 2
  • Jordan Atlas
    • 1
  1. 1.Department of Biomedical EngineeringCornell UniversityIthacaUSA
  2. 2.School of Chemical EngineeringCornell UniversityIthacaUSA

Personalised recommendations