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Chapter 11 : The Impact of Genomics on Microbial Catalysis

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The Impact of Genomics on Microbial Catalysis, Page 1 of 2

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Abstract:

This chapter gives a brief introduction and then focuses on the projected major influence of genomics on the field of biocatalysis and biodegradation. The clustering of prokaryotic genomes within an order of magnitude contrasts with those of different multicellular eukaryotes, which vary by 4 orders of magnitude. While the lifestyles of prokaryotes differ widely, it is likely that they have an upper limit of genome size based on the need to replicate efficiently and thus have fairly compact genomes. While DNA sequence analysis is yielding important patterns, the greatest genomic richness results from assigning metabolic functions to individual genes and deriving a biological usefulness of the gene in the context of the organism and its environment. The process requires a comparison of new DNA sequences with sequences in databases, and as such is a very computationally intense exercise. The ultimate goal is to map a sequence back to one whose biological function has been well established by a variety of methods. Most assignments of new gene sequences match known sequence types with high confidence about 60% of the time. Genes can be assigned to a previously elucidated function based on sequence homology arguments. However, if a gene is discovered which encodes an enzyme catalyzing a fundamentally new reaction, that biological function will never be deduced from the sequence alone.

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11

Key Concept Ranking

Cytochrome P450
0.4878501
Bacillus subtilis
0.4535481
Burkholderia cepacia
0.4535481
0.4878501
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Figures

Image of Figure 11.1
Figure 11.1

Time line showing several highlights of discovery in molecular genetics and genomics.

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
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Image of Figure 11.2
Figure 11.2

Letter written by James Watson in 1952 indicating his thoughts on what has become known as the central dogma, or the flow of biological information from DNA to RNA to protein. (Reproduced from reference 8 with permission of James D. Watson.)

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
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Image of Figure 11.3
Figure 11.3

Flow of discovery in molecular biology pertaining to biocatalysis. (A) In current genomics studies, one often starts with DNA sequences and attempts to deduce the protein sequence and then the function of the protein, or the biological phenotype. (B) Reverse functional genomics, in which discovery flows from phenotype to protein to gene (DNA).

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
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Image of Figure 11.4
Figure 11.4

Gene sequences are annotated by assigning function when possible. A gene may be put into the known box, for example, by deducing that the gene encodes a cytochrome P450 monooxygenase. Genes that cannot be assigned a function go into the unknown box. Over time, the hope is to move as many proteins as possible from the unknown box to the known box.

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
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References

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1. Franklin, R. E.,, and R. G. Gosling. 1953. Molecular configurations in sodium thymonucleate. Nature 171:740741.
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*5. Romine, M. F.,, L. C. Stillwell,, K. K. Wong,, S. J. Thurston,, E. C. Sisk,, C. Sensen,, T. Gaasterland,, J. K. Fredrickson,, and J. D. Saffer. 1999. Complete sequence of a 184-kilobase catabolic plasmid from Sphingomonas aromaticivorans F199. J. Bacteriol. 181:15851602.
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*7. Shimkets, L. J . 1998. Structure and Sizes of the Genomes of Archaea and Bacteria. Chapman and Hall, New York, N.Y..
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*9. Watson, J. D.,, and F. H. C. Crick. 1953. A structure of deoxyribosenucleic acid. Nature 171:737738.
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Tables

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Table 11.1

Representative sizes of prokaryotic and eukaryotic genomes

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
Generic image for table
Table 11.2

Representative prokaryote plasmids which have been fully sequenced

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
Generic image for table
Table 11.3

Microbial complete-genome-sequencing projects, both completed and ongoing, as of 1 January 2000

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11
Generic image for table
Table 11.4

Organic functional groups represented in known microbial metabolism

Citation: Wackett L, Hershberger C. 2001. The Impact of Genomics on Microbial Catalysis, p 191-204. In Biocatalysis and Biodegration. ASM Press, Washington, DC. doi: 10.1128/9781555818036.ch11

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