Engineering E. coli for large-scale production – Strategies considering ATP expenses and transcriptional responses

Metabolic Engineering

Volumn 38, Issue , 2016, Pages 73-85

  Löffler, Michael ^a   Simen, Joana Danica ^a   Jäger, Günter ^b   Schäferhoff, Karin ^b   Freund, Andreas ^a   Takors, Ralf ^a  

^a UNIVERSITY OF STUTTGART   (Germany)

^b UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

ATP expense; Escherichia coli; Glucose limitation; Maintenance; Scale up scale down; Transcriptional response

Indexed keywords

BIOREACTORS; GENES; GLUCOSE; MAINTENANCE; SUBSTRATES;

GLUCOSE AVAILABILITY; LARGE SCALE CONDITIONS; LARGE SCALE PRODUCTIONS; SCALE-UP; SUBSTRATE AVAILABILITIES; THEORETICAL FRAMEWORK; TRANSCRIPTIONAL PROGRAM; TRANSCRIPTIONAL RESPONSE;

ESCHERICHIA COLI;

ADENOSINE TRIPHOSPHATE; GLUCOSE; GUANOSINE TRIPHOSPHATE; MESSENGER RNA; ESCHERICHIA COLI PROTEIN; TRANSCRIPTION FACTOR;

AMINO ACID COMPOSITION; AMINO ACID METABOLISM; AMINO ACID TRANSPORT; ARTICLE; BACTERIAL STRAIN; BIOENGINEERING; BIOMASS; CARBOHYDRATE METABOLISM; CARBOHYDRATE TRANSPORT; ENERGY CONVERSION; ENERGY YIELD; ESCHERICHIA COLI K 12; GENE DELETION; GENE EXPRESSION; LARGE SCALE PRODUCTION; METABOLISM; NONHUMAN; OXYGEN SATURATION; PLUG FLOW REACTOR; PRIORITY JOURNAL; STEADY STATE; STIRRED REACTOR; BATCH CELL CULTURE; BIOLOGICAL MODEL; BIOSYNTHESIS; COMPUTER SIMULATION; ESCHERICHIA COLI; METABOLIC ENGINEERING; METABOLIC FLUX ANALYSIS; PHYSIOLOGICAL STRESS; PHYSIOLOGY; PROCEDURES;

ADENOSINE TRIPHOSPHATE; BATCH CELL CULTURE TECHNIQUES; BIOSYNTHETIC PATHWAYS; COMPUTER SIMULATION; ESCHERICHIA COLI; ESCHERICHIA COLI PROTEINS; GLUCOSE; METABOLIC ENGINEERING; METABOLIC FLUX ANALYSIS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; STRESS, PHYSIOLOGICAL; TRANSCRIPTION FACTORS;

EID: 84978681142     PISSN: 10967176     EISSN: 10967184     Source Type: Journal    
DOI: 10.1016/j.ymben.2016.06.008     Document Type: Article

References (81)

1. Akashi, H., Gojobori, T., Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis. Proc. Natl. Acad. Sci. USA 99 (2002), 3695–3700.
2. Amanullah, A., McFarlane, C.M., Emery, A.N., Nienow, A.W., Scale-down model to simulate spatial pH variations in large-scale bioreactors. Biotechnol. Bioeng. 73 (2001), 390–399.
3. Anders, S., Pyl, P.T., Huber, W., HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics, 2014 btu638.
4. Atkinson, D.E., Energy charge of the adenylate pool as a regulatory parameter. Interaction with feedback modifiers. Biochemistry 7 (1968), 4030–4034.
5. Atkinson, D.E., Walton, G.M., Adenosine triphosphate conservation in metabolic regulation. Rat liver citrate cleavage enzyme. J. Biol. Chem. 242 (1967), 3239–3241.
6. Battesti, A., Majdalani, N., Gottesman, S., The RpoS-mediated general stress response in Escherichia coli. Annu. Rev. Microbiol. 65 (2011), 189–213.
7. Benjamini, Y., Hochberg, Y., Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B, 1995, 289–300.
8. Bremer, H., Dennis, P., Modulation of chemical composition and other parameters of the cell by growth rate. Neidhardt, F.C., (eds.) Escherichia coli and Salmonella, 1996, American Society for Microbiology, Washington D.C, 1553–1569.
9. − perturbations of simulated large scale gradients in a scale-down device cause fast transcriptional responses in Corynebacterium glutamicum. Appl. Microbiol. Biotechnol. 98 (2014), 8563–8572.
10. Bylund, F., Collet, E., Enfors, S.O., Larsson, G., Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation. Bioprocess Eng. 18 (1998), 171–180.
11. Chapman, A.G., Fall, L., Atkinson, D.E., Adenylate energy charge in Escherichia coli during growth and starvation. J. Bacteriol. 108 (1971), 1072–1086.
12. Chen, H., Shiroguchi, K., Ge, H., Xie, X.S., Genome-wide study of mRNA degradation and transcript elongation in Escherichia coli. Mol. Syst. Biol., 11, 2015, 781.
13. Chubukov, V., Gerosa, L., Kochanowski, K., Sauer, U., Coordination of microbial metabolism. Nat. Rev. Microbiol. 12 (2014), 327–340.
14. Cserjan-Puschmann, M., Kramer, W., Duerrschmid, E., Striedner, G., Bayer, K., Metabolic approaches for the optimisation of recombinant fermentation processes. Appl. Microbiol. Biotechnol. 53 (1999), 43–50.
15. Delvigne, F., Boxus, M., Ingels, S., Thonart, P., Bioreactor mixing efficiency modulates the activity of a prpoS::GFP reporter gene in E. coli. Microb. Cell Factor., 8, 2009, 15.
16. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., Gingeras, T.R., STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29 (2013), 15–21.
17. Edwards, A.N., Patterson-Fortin, L.M., Vakulskas, C.A., Mercante, J.W., Potrykus, K., Vinella, D., Camacho, M.I., Fields, J.A., Thompson, S.A., Georgellis, D., Circuitry linking the Csr and stringent response global regulatory systems. Mol. Microbiol. 80 (2011), 1561–1580.
18. Elser, J., Acharya, K., Kyle, M., Cotner, J., Makino, W., Markow, T., Watts, T., Hobbie, S., Fagan, W., Schade, J., Growth rate-stoichiometry couplings in diverse biota. Ecol. Lett. 6 (2003), 936–943.
19. Ferenci, T., Hungry bacteria-definition and properties of a nutritional state. Environ. Microbiol. 3 (2001), 605–611.
20. Fox, J., Weisberg, S., An R Companion to Applied Regression. 2010, Sage, Thousand Oaks.
21. Gentry, D.R., Hernandez, V.J., Nguyen, L.H., Jensen, D.B., Cashel, M., Synthesis of the stationary-phase sigma-factor Sigma(S) is positively regulated by ppGpp. J. Bacteriol. 175 (1993), 7982–7989.
22. George, S., Larsson, G., Enfors, S.O., A scale-down two-compartment reactor with controlled substrate oscillations: metabolic response of Saccharomyces cerevisiae. Bioprocess Eng. 9 (1993), 249–257.
23. Hardiman, T., Lemuth, K., Keller, M.A., Reuss, M., Siemann-Herzberg, M., Topology of the global regulatory network of carbon limitation in Escherichia coli. J. Biotechnol. 132 (2007), 359–374.
24. Hengge-Aronis, R., Fischer, D., Identification and molecular analysis of glgS, a novel growth-phase‐regulated and rpoS-dependent gene involved in glycogen synthesis in Escherichia coli. Mol. Microbiol. 6 (1992), 1877–1886.
25. Humphrey, A., Shake flask to fermentor: what have we learned?. Biotechnol. Prog. 14 (1998), 3–7.
26. Ihssen, J., Egli, T., Specific growth rate and not cell density controls the general stress response in Escherichia coli. Microbiology 150 (2004), 1637–1648.
27. Ntr in controlling fluxes in the central metabolism of E. coli K12. Biochim. Biophys. Acta 1833 (2013), 2879–2889.
28. Jishage, M., Ishihama, A., Transcriptional organization and in vivo role of the Escherichia coli rsd gene, encoding the regulator of RNA Polymerase Sigma D. J. Bacteriol. 181 (1999), 3768–3776.
29. Junker, B.H., Scale-up methodologies for Escherichia coli and yeast fermentation processes. J. Biosci. Bioeng. 97 (2004), 347–364.
30. Kaleta, C., Schaeuble, S., Rinas, U., Schuster, S., Metabolic costs of amino acid and protein production in Escherichia coli. Biotechnol. J. 8 (2013), 1105–1114.
31. Keseler, I.M., Mackie, A., Peralta-Gil, M., Santos-Zavaleta, A., Gama-Castro, S., Bonavides-Martínez, C., Fulcher, C., Huerta, A.M., Kothari, A., Krummenacker, M., EcoCyc: fusing model organism databases with systems biology. Nucleic acids Res. 41 (2013), D605–D612.
32. Lapin, A., Schmid, J., Reuss, M., Modeling the dynamics of E. coli populations in the three dimensional turbulent field of a stirred-tank bioreactor: a structured-segregated approach. Chem. Eng. Sci. 61 (2006), 4783–4797.
33. Lara, A.R., Leal, L., Flores, N., Gosset, G., Bolivar, F., Ramirez, O.T., Transcriptional and metabolic response of recombinant Escherichia coli to spatial dissolved oxygen tension gradients simulated in a scale-down system. Biotechnol. Bioeng. 93 (2006), 372–385.
34. Lara, A.R., Vazquez-Limon, C., Gosset, G., Bolivar, F., Lopez-Munguia, A., Ramirez, O.T., Engineering Escherichia coli to improve culture performance and reduce formation of by-products during recombinant protein production under transient intermittent anaerobic conditions. Biotechnol. Bioeng. 94 (2006), 1164–1175.
35. Larsson, G., Toernkvist, M., Wernersson, E.S., Traegardh, C., Noorman, H., Enfors, S.O., Substrate gradients in bioreactors: origin and consequences. Bioprocess Eng. 14 (1996), 281–289.
36. Levenspiel, O., Chemical Reaction Engineering, 3rd ed., 1999, John Wiley And Sons, New York.
37. Levenspiel, O., 2012. Tracer Technology: Modeling the Flow of Fluids (Fluid Mechanics and its Applications), Springer, New York, p. 96.
38. Li, B., Dewey, C.N., RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma., 2011, 12.
39. Li, B., Ruotti, V., Stewart, R.M., Thomson, J.A., Dewey, C.N., RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26 (2010), 493–500.
40. Lieder, S., Nikel, P.I., de Lorenzo, V., Takors, R., Genome reduction boosts heterologous gene expression in Pseudomonas putida. Microb. Cell Factor., 14, 2015, 23.
41. Limberg, M.H., Pooth, V., Wiechert, W., Oldiges, M., Plug flow versus stirred tank reactor flow characteristics in two-compartment scale-down bioreactor: setup-specific influence on the metabolic phenotype and bioprocess performance of Corynebacterium glutamicum. Eng. Life Sci., 2016 (in press), 10.1002/elsc.201500142.
42. Lin, H.Y., Hoffmann, F., Rozkov, A., Enfors, S.O., Rinas, U., Neubauer, P., Change of extracellular cAMP concentration is a sensitive reporter for bacterial fitness in high-cell-density cultures of Escherichia coli. Biotechnol. Bioeng. 87 (2004), 602–613.
43. Luo, W., Friedman, M.S., Shedden, K., Hankenson, K.D., Woolf, P.J., GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinform., 10, 2009, 1.
44. Martin, M., Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17 (2011), 10–12.
45. Murray, H.D., Schneider, D.A., Gourse, R.L., Control of rRNA expression by small molecules is dynamic and nonredundant. Mol. Cell. 12 (2003), 125–134.
46. Neidhardt, F.C., Physiology of the Bacterial Cell: A Molecular Approach, 1990, Sinauer Associates Inc, U.S., Sunderland, Massachusetts, 133–173.
47. Neubauer, P., Haggstrom, L., Enfors, S.O., Influence of substrate oscillations on acetate formation and growth yield in Escherichia coli glucose limited fed-batch cultivations. Biotechnol. Bioeng. 47 (1995), 139–146.
48. Neubauer, P., Ahman, M., Tornkvist, M., Larsson, G., Enfors, S.O., Response of guanosine tetraphosphate to glucose fluctuations in fed-batch cultivations of Escherichia coli. J. Biotechnol. 43 (1995), 195–204.
49. Noorman, H., An industrial perspective on bioreactor scale-down: What we can learn from combined large-scale bioprocess and model fluid studies. Biotechnol. J. 6 (2011), 934–943.
50. Novick, Szilard, Description of the chemostat. Science 112 (1950), 715–716.
51. Paul, B.J., Berkmen, M.B., Gourse, R.L., DksA potentiates direct activation of amino acid promoters by ppGpp. Proc. Natl. Acad. Sci. 102 (2005), 7823–7828.
52. Paul, B.J., Ross, W., Gaal, T., Gourse, R.L., rRNA transcription in Escherichia coli. Annu. Rev. Genet. 38 (2004), 749–770.
53. Rahimpour, M., Montero, M., Almagro, G., Viale, A.M., Sevilla, Á., Cánovas, M., Muñoz, F.J., Baroja-Fernández, E., Bahaji, A., Eydallin, G., GlgS, described previously as a glycogen synthesis control protein, negatively regulates motility and biofilm formation in Escherichia coli. Biochem. J. 452 (2013), 559–573.
54. Reeve, C.A., Bockman, A.T., Matin, A., Role of protein degradation in the survival of carbon-starved Escherichia coli and Salmonella typhimurium. J. Bacteriol. 157 (1984), 758–763.
55. Robinson, M.D., McCarthy, D.J., Smyth, G.K., edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26 (2010), 139–140.
56. Romeo, T., Preiss, J., Genetic regulation of glycogen biosynthesis in Escherichia coli: in vitro effects of cyclic AMP and guanosine 5′-diphosphate 3′-diphosphate and analysis of in vivo transcripts. J. Bacteriol. 171 (1989), 2773–2782.
57. Salgado, H., Peralta-Gil, M., Gama-Castro, S., Santos-Zavaleta, A., Muñiz-Rascado, L., García-Sotelo, J.S., Weiss, V., Solano-Lira, H., Martínez-Flores, I., Medina-Rivera, A., RegulonDB v8. 0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more. Nucleic acids Res. 41 (2013), D203–D213.
58. Sanamrad, A., Persson, F., Lundius, E.G., Fange, D., Gynnå, A.H., Elf, J., Single-particle tracking reveals that free ribosomal subunits are not excluded from the Escherichia coli nucleoid. Proc. Natl. Acad. Sci. USA 111 (2014), 11413–11418.
59. Schellenberger, J., Park, J.O., Conrad, T.M., Palsson, B.Ø., BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics, 11, 2010, 213.
60. Schneider, D.A., Gaal, T., Gourse, R.L., NTP-sensing by rRNA promoters in Escherichia coli is direct. Proc. Natl. Acad. Sci. USA 99 (2002), 8602–8607.
61. Schuhmacher, T., Loeffler, M., Hurler, T., Takors, R., Phosphate limited fed-batch processes: impact on carbon usage and energy metabolism in Escherichia coli. J. Biotechnol. 190 (2014), 96–104.
62. Schweder, T., Kruger, E., Xu, B., Jurgen, B., Blomsten, G., Enfors, S.O., Hecker, M., Monitoring of genes that respond to process-related stress in large-scale bioprocesses. Biotechnol. Bioeng. 65 (1999), 151–159.
63. Shimada, T., Fujita, N., Yamamoto, K., Ishihama, A., Novel roles of cAMP receptor protein (CRP) in regulation of transport and metabolism of carbon sources. PLoS One, 6, 2011, e20081.
64. Srivatsan, A., Wang, J.D., Control of bacterial transcription, translation and replication by (p)ppGpp. Curr. Opin. Microbiol. 11 (2008), 100–105.
65. Stouthamer, A.H., A theoretical study on the amount of ATP required for synthesis of microbial cell material. Antonie Leeuwenhoek 39 (1973), 545–565.
66. Takors, R., Scale-up of microbial processes: impacts, tools and open questions. J. Biotechnol. 160 (2012), 3–9.
67. Tatusov, R., Koonin, E., Lipman, D., A genomic perspective on protein families. Science 278 (1997), 631–637.
68. Taymaz-Nikerel, H., Borujeni, A.E., Verheijen, P.J., Heijnen, J.J., van Gulik, W.M., Genome-derived minimal metabolic models for Escherichia coli MG1655 with estimated in vivo respiratory ATP stoichiometry. Biotechnol. Bioeng. 107 (2010), 369–381.
69. Teich, A., Meyer, S., Lin, H.Y., Andersson, L., Enfors, S., Neubauer, P., Growth rate related concentration changes of the starvation response regulators sigmaS and ppGpp in glucose-limited fed-batch and continuous cultures of Escherichia coli. Biotechnol. Prog. 15 (1999), 123–129.
70. Theobald, U., Mailinger, W., Baltes, M., Rizzi, M., Reuss, M., In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: I. Experimental observations. Biotechnol. Bioeng. 55 (1997), 305–316.
71. Tian, Z., Fauré, A., Mori, H., Matsuno, H., Identification of key regulators in glycogen utilization in E. coli based on the simulations from a hybrid functional Petri net model. BMC Syst. Biol., 7, 2013, S1.
72. Traxler, M.F., Summers, S.M., Nguyen, H.T., Zacharia, V.M., Hightower, G.A., Smith, J.T., Conway, T., The global, ppGpp-mediated stringent response to amino acid starvation in Escherichia coli. Mol. Microbiol. 68 (2008), 1128–1148.
73. Traxler, M.F., Zacharia, V.M., Marquardt, S., Summers, S.M., Nguyen, H.T., Stark, S.E., Conway, T., Discretely calibrated regulatory loops controlled by ppGpp partition gene induction across the'feast to famine’ gradient in Escherichia coli. Mol. Microbiol. 79 (2011), 830–845.
74. Wagner, G.P., Kin, K., Lynch, V.J., Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci. 131 (2012), 281–285.
75. Wallenius, K.T., Biased Sampling; The Non-central Hypergeometric Probability Distribution. 1963, Department of Statistics Stanford University, Stanford University.
76. Wassarman, K.M., Storz, G., 6S RNA regulates E. coli RNA polymerase activity. Cell 101 (2000), 613–623.
77. Wu, G., Yan, Q., Jones, J.A., Tang, Y.J., Fong, S.S., Koffas, M.A., Metabolic burden: cornerstones in synthetic biology and metabolic engineering applications. Trends Biotechnol., 2016 (article in press).
78. Yamaguchi, Y., Inouye, M., Regulation of growth and death in Escherichia coli by toxin–antitoxin systems. Nat. Rev. Microbiol. 9 (2011), 779–790.
79. Young, M.D., Wakefield, M.J., Smyth, G.K., Oshlack, A., Method Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol., 11, 2010, R14.
80. Glc and induction behavior of the ptsG gene. J. Bacteriol. 182 (2000), 4443–4452.
81. Zhao, J., Li, Q., Sun, T., Zhu, X., Xu, H., Tang, J., Zhang, X., Ma, Y., Engineering central metabolic modules of Escherichia coli for improving beta-carotene production. Metab. Eng. 17 (2013), 42–50.