Chapter 24 : The Paradigm Shift in Microbial Prospecting

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This chapter explores the posited paradigm shift from traditional microbiology to bioinformatics in the search for exploitable biology. It also refers to the extraordinary rate of biological data acquisition and deposition in the world's databases. These databases are classified by type (e.g., genomes, gene expression, proteins, RNA sequences, pathology), but the distinction between categories is often arbitrary and individual databases may provide more than one type of information. Integration of the molecular biology databases, although by no means perfect, has attracted serious attention and may be able to deliver useful information on issues such as a protein's structure, function, phylogenetic occurrence, expression, and protein-protein interactions. Similarly, the various bioinformatics research groups and commercial organizations are developing multidatabase query systems that enable interoperability of heterogeneous, formerly incompatible resources. Within the medical sector, bioinformatics objectives have included (i) the detection and identification of pathogens, (ii) the identity of drug targets, and (iii) the search for new drugs and vaccines. The final stratagem to be considered for producing novel exploitable biology is directed evolution, which, as genome sequencing projects continue to grow, promises to become a principal route for search and discovery. Evolution via natural and artificial (sensu traditional animal and plant breeding) selection is dependent on genetic variation, inheritance, and differential reproduction.

Citation: Bull A. 2004. The Paradigm Shift in Microbial Prospecting, p 241-249. In Bull A (ed), Microbial Diversity and Bioprospecting. ASM Press, Washington, DC. doi: 10.1128/9781555817770.ch24
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Biotechnology—routes to discovery.

Citation: Bull A. 2004. The Paradigm Shift in Microbial Prospecting, p 241-249. In Bull A (ed), Microbial Diversity and Bioprospecting. ASM Press, Washington, DC. doi: 10.1128/9781555817770.ch24
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1. Akerley, B. J.,, E. J. Rubin,, A. Camilli,, D. J. Lampe,, H. M. Robertson,, and J. J. Mekalanos. 1998. Systematic identification of essential genes by in vitro mariner mutagenesis. Proc. Natl. Acad. Sci. USA 95: 8927 8932.
2. Allen, J. F. 2001. Bioinformatics and discovery: induction beckons again. BioEssays 23: 104 107.
3. Almeida, R.,, A. Norrish,, M. Levick,, D. Vetrie,, T. Freeman, et al. 2002. From genomes to vaccines: Leishmania as a model. Phil. Trans. R. Soc. Lond. Ser. B 357: 5 11.
4. Altamirano, M. M.,, J. M. Blackburn,, C. Aguayo,, and A. R. Fersht. 2000. Directed evolution of new catalytic activity using the alpha/beta-barrel scaffold. Nature 403: 617 622.
5. Attwood, T. K.,, and C.J. Miller. 2001. Which craft is best in bioinformatics? Comp. Chem. 25: 329 339.
6. Baxevanis, A. D. 2002. The molecular biology database collection: 2002 update. Nucleic Acids Res. 30: 1 12.
7. Bentley, S. D.,, K. F. Chater,, A. M. Cerdeno-tarraga,, G. L. Chaiis,, N. R. Thomson, et al. 2002. Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2). Nature 417: 141 147.
8. Bisby, F. A. 2000. The quiet revolution: biodiversity informatics and the Internet. Science 289: 2309 2312.
9. Blohm, D. H.,, and A. Guiseppie-Elie. 2001. New developments in microarray technology. Curr. Opin. Biotechnol. 12: 41 47.
10. Boorman, G. A.,, S. P. Anderson,, W. M. Casey,, R. H. Brown,, L. M. Crosby, et al. 2002. Toxicogenomics, drug discovery, and the pathologist. Toxicol. Pathol. 30: 15 27.
11. Brenner, S.,, M. Johnson,, J. Bridgham,, G. Golda,, D. H. Lloyd, et al. 2000. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat. Biotechnol. 18: 630 634.
12. Brent, R. 1999. Functional genomics: learning to think about gene expression data. Curr. Biol. 9: R338 R341.
13. Brown, P. O.,, and D. Botstein. 1999. Exploring the new world of the genome with DNA microarrays. Nat. Genet. Suppl. 21: 33 37.
14. Bull, A. T.,, A. C. Ward,, and M. Goodfellow. 2000. Search and discovery strategies for biotechnology: the paradigm shift. Microbiol. Mol. Biol. Rev. 64: 573 606.
15. Bull, J. J.,, and H. A. Wichman. 2001. Applied evolution. Annu. Rev. Ecol. Syst. 32: 183 217.
16. Chang, C. C. J.,, T. T. Chen,, B. W. Cox,, G. N. Dawes,, W. P. C. Stemmer, et al. 1999. Evolution of a cytokine using DNA family shuffling. Nat. Biotechnol. 17: 793 797.
17. Cho, J.-C.,, and J. M. Tiedje. 2001. Biogeography and degree of endemicity of fluorescent Pseudomonas strains in soil. Appl. Environ. Microbiol. 66: 5448 5456.
18. Dean, P. M.,, E. D. Zanders,, and D. S. Bailey. 2001. Industrial-scale genomics-based drug design and discovery. Trends Biotechnol. 19: 288 292.
19. Earl, A. M.,, S. K. Rankin,, K. P. Kim,, O. N. Lamendola,, and J. R. Battista. 2002. Genetic evidence that the usvE gene product of Deinococcus radiodurans Rl is a UV damage endonuclease. J. Bacteriol. 184: 1003 1009.
20. Edwards, J. L.,, M. A. Lane,, and E. B. Nielsen. 2000. Interoperability of biodiversity databases: biodiversity information on every desktop. Science 289: 2312 2314.
21. Edwards, J. S.,, M. Covert,, and B. Palsson. 2002. Metabolic modelling of microbes: the flux-balance approach. Environ. Microbiol. 4: 133 140.
22. Fleischmann, R. D.,, M. D. Adams,, O. White,, R. A. Clayton,, E. F. Kirkness, et al. 1995. Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 269: 496 512.
23. Fuchs, R. 2002. From sequence to biology: the impact on bioinformatics . Bioinformatics 18: 505 506.
24. Gardner, M. J.,, N. Hall,, E. Fung,, O. White,, M. Berriman et al. 2002. Genome sequence of the human malaria parasite Plasmodium falciparum. Nature 419: 498 511.
25. Gerstein, M. 2000. Integrative database analysis in structural genomics. Nat Struct. Biol 7: 960 963.
26. Gingeras, T. R.,, and C. Rosenow. 2000. Studying microbial genomics with high-density oligonucleotide arrays. ASM News 66: 463 469.
27. Goodman, N. 2002. Biological data becomes computer literate: new advances in bioinformatics. Curr. Opin. Biotechnol. 13: 6871.
28. Hauser, N. C.,, K. Fellenberg,, and S. Rupp. 2002. How to discover pathogenic mechanisms. Screening 4: 28 31.
29. Huynen, M.,, T. Dandekar,, and P. Bork. 1998. Differential genome analysis applied to the species-specific features of Helicobacter pylori. FEBS Lett. 426: 1 5.
30. Joern, J. M.,, P. Meinhold,, and F. H. Arnold. 2002. Analysis of shuffled gene libraries. J. Mol. Biol. 316: 643 656.
31. Kell, D. B.,, and R. D. King. 2000. On the optimization of classes for the assignment of unidentified reading frames in functional genomics programmes: the need for machine learning. Trends Biotechnol. 18: 93 98.
32. Kuhn, T. S. 1970. The Structure of Scientific Revolutions, 2nd ed. University of Chicago Press, Chicago, Ill.
33. Lehmann, M.,, C. Loch,, A. Middendorf,, D. Studer,, S. F. Lassen, et al. 2002. The consensus concept for thermostability engineering of proteins: further proof of concept. Prot. Eng. 15: 403 411.
34. Lucchini, S.,, A. Thompson,, and J. C. D. Hinton. 2001. Microarrays for microbiologists. Microbiology (UK) 147: 1403 1414.
35. Luscombe, N. M.,, D. Greenbaum, and M. Gerstein. 2001. What is bioinformatics? a proposed definition and overview of the field. Methods Inform. Med. 40: 346 358.
36. Makarova, K. S.,, L. Ararvind,, Y. I. Wolf,, R. L. Tatusov,, K. W. Minton,, E. V. Koonin,, and M. J. Daly. 2001. Genome of the extremely radiation-resistant bacterium Deinococcus radiodurans viewed from the perspective of comparative genomics. Microbiol. Mol. Biol. Rev. 65: 44 79.
37. Moxon, E. R.,, D. W. Hood,, N. J. Saunders,, E. K. H. Schweda,, and J. C. Richards. 2002. Functional genomics of pathogenic bacteria. Phil. Trans. R. Soc. Lond. Ser. B 357: 109 116.
38. Norris, S. J.,, and G. M. Weinstock. 2001. The genome sequence of Treponema pallidum, the syphillis spirochaete: will clinicians benefit? Curr. Opin. Infect. Dis. 13: 29 36.
39. Omura, S.,, H. Ikeda,, J. Ishikawa,, A. Hanamoto,, C. Takahashi, et al. 2001. Genome sequence of an industrial microorganism Streptomyces avermitilis: deducing the ability of producing secondary metabolites. Proc. Natl. Acad. Sci. USA 98: 12215 12220.
40. Orencia, M. C.,, J. S. Yoon,, J. E. Ness,, W. P. C. Stemmer,, and R. C. Stevens. 2001. Predicting the emergence of antibiotic resistance by directed evolution and structural analysis. Nat. Struct. Biol. 8: 238 242.
41. Pikkemaat, M. G.,, and D. B. Janssen. 2002. Generating segmental mutations in haloalkane dehalogenase: a novel part in the directed evolution toolbox. Nucleic Acids. Res. 30: e35.
42. Posas, F.,, J. R. Chambers,, J. A. Heyman,, J. P. Hoeffler,, E. de Nadal,, and J. Arino. 2000. The transcriptional response of yeast to saline stress. J. Biol. Chem. 275: 17249 17255.
43. Powell, K. A.,, S. W. Ramer,, S. B. del Cardayre,, W. P. C. Stemmer,, M. B. Tobin, et al. 2001. Directed evolution and biocatalysis. Angew. Chem. Int. Ed. 40: 3948 3959.
44. Roos, D. S.,, M. J. Crawford,, R. G. K. Donald,, M. Fraunholz,, O. S. Harb, et al. 2002. Mining the Plasmodium genome database to define organellar function: what does the apicoplast do? Phil. Trans. R. Soc. Lond. Ser. B 357: e1 e12.
45. Rosamond, J.,, and A. Allsop. 2000. Harnessing the power of the genome in the search for new antibiotics. Science 287: 1973 1976.
46. Schilling, C. H.,, J. S. Edwards,, and B. O. Palsson. 1999. Towards metabolic phenomics: analysis of genomic data using flux balances. Biotechnol. Prog. 15: 288 295.
47. Schmidt-Dannert, C. 2001. Directed evolution of single proteins, metabolic pathways, and viruses. Biochemistry 40: 13125 13134.
48. Scott, R. K. 2002. Chemical space in in silico screening. Screening 4: 32 34.
49. Selifonova, O.,, F. Valle,, and V. Schellenberger. 2001. Rapid evolution of novel traits in microorganisms. Appl. Environ. Microbiol. 67: 3645 3649.
50. Siepel, A.,, A. Farmer,, A. Toopko,, M. Zhuang,, P. Mendes,, W. Beavis,, and B. Sobral. 2001. ISYS: a decentralized, component-based approach to the integration of heterogenous bioinformatics resources. Bioinformatics 17: 83 94.
51. Smalheiser, N. R. 2002. Informatics and hypothesis-driven research. EMBO Rep. 3: 702 703.
52. Takami, H.,, K. Nakasone,, Y. Takaki,, G. Maeno,, R. Sasaki, et al. 2000. Complete genome sequence of the alkaliphilic Bacillus halodurans and genomic sequence comparison with Bacillus subtilis. Nucleic Acids Res. 28: 4317 4331.
53. Tomita, M. 1999. E-CELL: software environment for whole cell simulation. Bioinformatics 15: 72 84.
54. Tomita, M. 2001. Towards computer aided design (CAD) of useful microorganisms. Bioinformatics 17: 1091 1092.
55. Valencia, A. 2002. Search and retrieve. Large-scale generation is becoming increasingly important. EMBO Rep. 3: 396 405.
56. Van Dien, S. J.,, and M. E. Lidstrom. 2002. Stoichiometric model for evaluating the metabolic capabilities of the facultative methy-lotroph Methylobacterium extorquens AMI, with application to reconstruction of C3 and C4 metabolism. Biotechnol. Bioeng. 78: 296 312.
57. Ward, D. C.,, and D. C. White. 2002. The new omics era. Curr. Opin. Biotechnol. 13: 11 13.
58. Watve, M. G.,, R. Tickoo,, M. M. Jog,, and B. D. Bhole. 2001. How many antibiotics are produced by the genus Streptomyces? Arch. Microbiol. 176: 386 390.
59. Wheeler, D. L.,, D. M. Church,, A. E. Lash,, D. D. Leipe,, T. L. Madden, et al. 2002. Databases resources of the National Center for Biotechnology Information: 2002 update. Nucleic Acids Res. 30: 13 16.
60. Wildpaner, M.,, G. Schneider,, A. Schleiffer,, and F. Eisenhaber. 2001. Taxonomy workbench. Bioinformatics 17: 1179 1182.
61. Wilson, D. S.,, and S. Nock. 2002. Functional protein microarrays. Curr. Opin. Chem. Biol. 6: 81 85.
62. Wilson, W. J.,, C. L. Strout,, T. Z. DeSantis,, J. L. Stilwell,, A. V. Carrano,, and G. L. Andersen. 2002. Sequence-specific identification of 18 pathogenic microorganisms using microarray technology. Mol. Cell. Probes 16: 119 127.
63. Zhao, H.,, K. Chockalingam,, and Z. Chen. 2002. Directed evolution of enzymes and pathways for industrial biocatalysts. Curr. Opin. Biotechnol. 13: 104 110.
64. Zhong, Y.,, Y. Luo,, S. Pramanik,, and J. H. Beaman. 1999. HI-CLAS: a taxonomic database system for displaying and comparing biological classification and phylogenetic trees. Bioinformatics 15: 149 156.


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Table 1

Impact of directed evolution on biotechnology

Citation: Bull A. 2004. The Paradigm Shift in Microbial Prospecting, p 241-249. In Bull A (ed), Microbial Diversity and Bioprospecting. ASM Press, Washington, DC. doi: 10.1128/9781555817770.ch24

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