Structural synthetic biotechnology: From molecular structure to predictable design for industrial strain development

Trends in Biotechnology

Volumn 28, Issue 10, 2010, Pages 534-542

  Chen, Zhen ^a   Wilmanns, Matthias ^b   Zeng, An Ping ^a  

^a HAMBURG UNIVERSITY OF TECHNOLOGY   (Germany)

^b EUROPEAN MOLECULAR BIOLOGY LABORATORY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ATOMIC LEVELS; BIOREACTIONS; INDUSTRIAL BIOTECHNOLOGY; INDUSTRIAL STRAIN; MICROBIAL STRAIN; MOLECULAR LEVELS; PREDICTABLE DESIGN; RE-PROGRAMMING; STRAIN DEVELOPMENT; STRUCTURAL BIOLOGY; SYNTHETIC BIOLOGY;

BIOLOGY; BIOTECHNOLOGY; INDUSTRY;

STRAIN;

SCAFFOLD PROTEIN;

BIOTECHNOLOGY; CELL FUNCTION; CELL METABOLISM; CELL STRAIN; CHEMICAL STRUCTURE; ENZYME ENGINEERING; ENZYME REGULATION; GENOME ANALYSIS; METABOLIC REGULATION; NONHUMAN; PRIORITY JOURNAL; REVIEW; SYNTHESIS;

BIOTECHNOLOGY; GENETIC ENGINEERING; INDUSTRIAL MICROBIOLOGY; PROTEIN ENGINEERING; PROTEINS; RNA;

HARNESS;

EID: 77956870811     PISSN: 01677799     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tibtech.2010.07.004     Document Type: Review

References (88)

1. González-Pajuelo M., et al. Metabolic engineering of Clostridium acetobutylicum for the industrial production of 1,3-propanediol from glycerol. Metab. Eng. 2005, 7:329-336.
2. Nakamura C.E., Whited G.M. Metabolic engineering for the microbial production of 1,3-propanediol. Curr. Opin. Biotechnol. 2003, 14:454-459.
3. Park J.H., Lee S.Y. Towards systems metabolic engineering of microorganisms for amino acid production. Curr. Opin. Biotechnol. 2008, 19:454-460.
4. Wendisch V.F., et al. Metabolic engineering of Escherichia coli and Corynebacterium glutamicum for biotechnological production of organic acids and amino acids. Curr. Opin. Microbiol. 2006, 9:268-274.
5. Aloy P., Russell R.B. Structure-based systems biology: a zoom lens for the cell. FEBS Lett. 2005, 579:1854-1858.
6. Aloy P., Russell R.B. Structure systems biology: modeling protein interactions. Nat. Rev. Mol. Cell Biol. 2006, 7:188-197.
7. Beltrao P., et al. Structures in systems biology. Curr. Opin. Struct. Biol. 2007, 17:378-384.
8. Matthews, B.W. (2007) Protein structure initiative: getting into gear. Nat. Struct. Mol. Biol. 14, 459-460.
9. Zhang Y., et al. Three-dimensional structural view of the central metabolic network of Thermotoga maritima. Science 2009, 325:1544-1549.
10. Picataggio S. Potential impact of synthetic biology on the development of microbial systems for the production of renewable fuels and chemicals. Curr. Opin. Biotechnol. 2009, 20:325-329.
11. Carothers J.M., et al. Chemical synthesis using synthetic biology. Curr. Opin. Biotechnol. 2009, 20:498-503.
12. Prather K.J., Martin C.H. De novo biosynthetic pathways: rational design of microbial chemical factories. Curr. Opin. Biotechnol. 2008, 19:468-474.
13. McArthur, G.H. and Fong, S.S. (2010) Toward engineering synthetic microbial metabolism. J. Biomed. Biotechnol. 2010, 459760.
14. Tyo K.E., et al. Toward design-based engineering of industrial microbes. Curr. Opin. Microbiol. 2010, 13:259-262.
15. Na D., et al. Construction and optimization of synthetic pathways in metabolic engineering. Curr. Opin. Microbial. 2010, 13:363-370.
16. Koide T., et al. The role of predictive modelling in rationally re-engineering biological systems. Nat. Rev. Microbiol. 2009, 7:297-305.
17. Young E., Alper H. Synthetic biology: tools to design, build, and optimize cellular processes. J. Biomed. Biotechnol. 2010, 2010:130781.
18. Andrianantoandro, E. et al. (2006) Synthetic biology: new engineering rules for an emerging discipline. Mol. Syst. Biol. 2, 2006.0028.
19. Atsumi S., et al. Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels. Nature 2008, 451:86-90.
20. Zhang K., et al. Expanding metabolism for biosynthesis of nonnatural alcohols. Proc. Natl. Acad. Sci. U. S. A. 2008, 105:20653-20658.
21. Koffas M.A.G. Expanding the repertoire of biofuel alternatives through metabolic pathway evolution. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:965-966.
22. Gibson D.G., et al. Creation of a bacterial cell controlled by a chemically synthesized genome. Science 2010, 329:52-56.
23. Moult J., Melamud E. From fold to function. Curr. Opin. Struct. Biol. 2000, 10:384-389.
24. Eisenberg D., et al. Protein function in the post-genomic era. Nature 2000, 405:823-826.
25. Ioerger T.R., Sacchettini J.C. Structural genomics approach to drug discovery for Mycobacterium tuberculosis. Curr. Opin. Microbiol. 2009, 12:318-325.
26. Holton S.J., et al. Structure-based approaches to drug discovery against tuberculosis. Curr. Protein. Pept. Sci. 2007, 8:365-375.
27. Kiel C., et al. Analyzing protein interaction networks using structural information. Annu. Rev. Biochem. 2008, 77:415-441.
28. Lippow S.M., Tidor B. Progress in computational protein design. Curr. Opin. Biotechnol. 2007, 18:1-7.
29. Suarez M., Jaramillo A. Challenges in the computational design of proteins. J. R. Soc. Interface 2009, 6:S477-491.
30. Linda G.O., et al. Enzyme engineering for enantioselectivity: from trial-and error to rational design?. Trends Biotechnol. 2010, 28:46-54.
31. Reetz M.T., et al. Expanding the range of substrate acceptance of enzymes: combinatorial active-site saturation test. Angem. Chem. 2005, 44:4192-4196.
32. Reetz M.T., et al. Expanding the substrate scope of enzymes: combining mutations obtained by CASTing. Chem. Eur. J. 2006, 12:6031-6038.
33. Bartsch S., et al. Complete inversion of enantioselectivity towards acetylated tertiary alcohols by a double mutant of a Bacillus subtilis esterase. Angem. Chem. 2008, 47:1508-1511.
34. Horsman G.P., et al. Mutations in distant residues moderately increase the enantioselectivity of Pseudomonas fluorescens esterase toward methyl 3-bromo-2-methylpropanoate and ethyl 3-phenylbutyrate. Chem. Eur. J. 2003, 9:1933-1939.
35. Marshall S.A., et al. One- and two-body decomposable Poisson-Boltzmann methods for protein design calculations. Protein Sci. 2005, 14:1293-1304.
36. Jaramillo A., Wodak S.J. Computational protein design is a challenge for implicit solvation models. Biophys. J. 2005, 88:156-171.
37. Zollars E.S., et al. Simple electrostatic model improves designed protein sequences. Protein Sci. 2006, 15:2014-2018.
38. Pokala N., Handel T.M. Energy functions for protein design: adjustment with protein-protein complex affinities, models for the unfolded state, and negative design of solubility and specificity. J. Mol. Biol. 2005, 347:203-227.
39. Allen B.D., Mayo S.L. Dramatic performance enhancements for the FASTER optimization algorithm. J. Comput. Chem. 2006, 27:1071-1075.
40. Georgiev, I. et al. (2006) A novel minimized dead-end elimination criterion and its application to protein design. Lect. Notes Comput. Sc. 3909, 530-545.
41. Wang L., et al. Expanding the genetic code. Annu. Rev. Biophys. Biomol. Struct. 2006, 35:225-249.
42. Isaacs F.J., et al. RNA synthetic biology. Nat. Biotechnol. 2006, 24:545-553.
43. Bayer T.S., Smolke C.D. Programmable ligand-controlled riboregulators of eukaryotic gene expression. Nat. Biotechnol. 2005, 23:337-343.
44. Winkler W.C., et al. Control of gene expression by a natural metabolite-responsive ribozyme. Nature 2004, 428:281-286.
45. Beisel, C.L. et al. (2008) Model-guided design of ligand-regulated RNAi for programmable control of gene expression. Mol. Syst. Biol. 4, 224.
46. Rackham O., Chin J.W. A network of orthogonal ribosome-mRNA pairs. Nat. Chem. Biol. 2005, 1:159-166.
47. Rackham O., Chin J.W. Cellular logic with orthogonal ribosomes. J. Am. Chem. Soc. 2005, 127:17584-17585.
48. Rokem J.S., et al. Systems biology of antibiotic production by microorganisms. Nat. Prod. Rep. 2007, 24:1262-1287.
49. Ro D.K., et al. Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Nature 2006, 440:940-943.
50. Hanai T., et al. Engineered synthetic pathway for isopropanol production in Esherichia coli. Appl. Environ. Microbiol. 2007, 73:7814-7818.
51. Jiang L., et al. De novo computational design of retro-aldol enzymes. Science 2009, 319:1387-1391.
52. Röthlisberger D., et al. Kemp elimination catalysts by computational enzyme design. Nature 2009, 453:190-195.
53. Murphy P.D., et al. Alteration of enzyme specificity by computational loop remodeling and design. Proc. Natl. Acad. Sci. U. S. A. 2008, 106:9215-9220.
54. Todd A.E., et al. Evolution of function in protein superfamilies, from a structural prespective. J. Mol. Biol. 2001, 307:1113-1143.
55. Rausell A., et al. Protein interactions and ligand binding: from protein subfamilies to functional specificity. Proc. Natl. Acad. Sci. U. S, A. 2010, 107:1995-2000.
56. Wang Y.T., et al. Use of indirect site-directed mutagenesis to alter the substrate specificity of methylamine dehydrogenase specificity of methylamine dehydrogenase. J. Biol. Chem. 2002, 277:4119-4122.
57. Torres Pazmino D.E., et al. Altering the substrate specificity and enantioselectivity of phenylacetone monooxygenase by structure-inspired enzyme redesign. Adv. Synth. Catal. 2007, 349:1361-1368.
58. Cordente A.G., et al. Redesign of carnitine acetyltransferase specificity by protein engineering. J. Biol. Chem. 2004, 279:33899-33908.
59. Cera E.D. Engineering protease specificity made simple, but not simpler. Nat. Chem. Biol. 2008, 4:270-271.
60. Andreadeli A., et al. Structure-guided alteration of coenzyme specificity of formate dehydrogenase by saturation mutagenesis to enable efficient utilization of NADP+. FEBS J. 2008, 275:3859-3869.
61. Woodyer R., et al. Relaxing the nicotinamide cofactor specificity of phosphate dehydrogenase by rational design. Biochemistry 2003, 42:11604-11614.
62. Bubner P., et al. Structure-guided engineering of the coenzyme specificity of Pseudomonas fluorescens mannitol 2-dehydrogenase to enable efficient utilization of NAD(H) and NADP(H). FEBS Lett. 2008, 582:233-237.
63. Chen C.Y., et al. Computational structure-based redesign of enzyme activity. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:3764-3769.
64. Korkegian A., et al. Computational thermostabilization of an enzyme. Science 2010, 308:857-860.
65. Heinzelman P., et al. A family of thermostable fungal cellulases created by structure-guided recombination. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:5610-5615.
66. Goodey N.M., Benkovic S.J. Allosteric regulation and catalysis emerge via a common route. Nat. Chem. Biol. 2008, 4:474-482.
67. Vincent J.H. An ensemble view of allostery. Science 2010, 327:653-654.
68. Pawlyk A., Pettigrew D.W. Transplanting allosteric control of enzyme activity by protein-protein interactions: coupling a regulatory site to the conserved catalytic core. Proc. Natl. Acad. Sci. U. S. A. 2002, 99:11115-11120.
69. Lockless S.W., Ranganathan R. Evolutionarily conserved pathways of energetic connectivity in protein families. Science 1999, 286:295-299.
70. Suel G.M., et al. Evolutionarily conserved networks of residues mediate allosteric communication in proteins. Nat. Struct. Biol. 2003, 10:59-69.
71. Hatley M.E., et al. Allosteric determinants in guanine nucleotide-binding proteins. Proc. Natl. Acad. Sci. U. S. A. 2003, 100:14445-14450.
72. Halabi N., et al. Protein sectors: evolutionary units of three-dimensional structure. Cell 2009, 138:774-786.
73. Estabrook R.A., et al. Statistical coevolution analysis and molecular dynamics: Identification of amino acid pairs essential for catalysis. Proc. Natl. Acad. Sci. U. S. A. 2005, 102:994-999.
74. Zeng, A.P and Chen, Z. Hamburg University of Technology. Enzymes having a reduced L-lysine feedback inhibition, EP 10155377.
75. Zeng, A.P. et al. Hamburg University of Technology. Modified aspartate kinase from Corynebacterium glutamicum and its application for amino acid production. EP 10003770.
76. Fastrez J. Engineering allosteric regulation into biological catalysts. Chembiochem. 2009, 10:2824-2835.
77. Lee J., et al. Surface sites for engineering allosteric control in proteins. Science 2008, 322:438-442.
78. Dueber J.E., et al. Synthetic protein scaffolds provide modular control over metabolic flux. Nat. Biotechnol. 2009, 27:753-759.
79. Kuriyan J., Eisenberg D. The origin of protein interactions and allostery in colocalization. Nature 2007, 450:983-990.
80. Moon T.S., et al. Use of modular, synthetic scaffolds for improved production of glucaric acid in engineered E. coli. Metab. Eng. 2010, 12:298-305.
81. Perham R.N. Swinging arms and swinging domains in multifunctional enzymes: catalytic machines for multistep reactions. Annu. Rev. Biochem. 2000, 69:961-1004.
82. Kämpf M.M., Weber W. Synthetic biology in the analysis and engineering of signaling processes. Integr. Biol. 2009, 2:12-24.
83. Grünberg R., et al. Building blocks for protein interaction devices. Nucleic. Acids Res. 2010, 38:2645-2662.
84. Bhattacharyya R.P. Domains, motifs, and scaffolds: the role of modular interactions in the evolution and wiring of cell signaling circuits. Annu. Rev. Biochem. 2006, 75:655-680.
85. Dueber J.E., et al. Reprogramming control of an allosteric signaling switch through modular recombination. Science 2003, 301:1904-1908.
86. Yeh B.J., et al. Rewiring cellular morphology pathways with synthetic guanine nucleotide exchange factors. Nature 2007, 447:596-600.
87. Bashor C.J., et al. Using engineered scaffold interactions to reshape MAP kinase pathway signaling dynamics. Science 2008, 319:1539-1543.
88. Levskaya A., et al. Spatiotemporal control of cell signalling using a light-switchable protein interaction. Nature 2009, 461:997-1001.