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Degree

Master of Science (MS), Wright State University, Computer Science, 2005.

Abstract

Raiford III, Douglas . M.S., Department of Computer Science & Engineering, Wright State University, 2005. Multivariate analysis of prokaryotic amino acid usage bias: a computational method for understanding protein building block selection in primitive organisms. Organisms expend a significant fraction of their overall energy budget in the creation of proteins, particularly for those that are produced in large quantities. Recent research has demonstrated that genes encoding these proteins are shaped by natural selection to produce the proteins with low cost building blocks (amino acids) whenever possible. The negative correlation between protein production rate and their energetic costs has been established for two bacterial genomes: Escherichia coli and Bacillus subtilis. This thesis provides scientific validation of this theory by automating the analysis and extending the research to additional genomes. Investigations into building block selection are highly computational in nature. Diverse methodologies, including principal component analysis, calculation of Mahalanobis distance, and the execution of Mantel-Haenszel and Bonferroni tests, are required in order to automate the process. In order to verify that the cause of the observed trend is energetic cost minimization it is necessary to eliminate as many alternative explanations as possible. This is accomplished through demonstration that the trend is not localized to any particular region of the protein’s primary structure and that the trend is consistent across all genes regardless of functionality. This investigation of the energetic cost of polypeptide synthesis provides valuable insights into protein building block selection. As an example, parasitic organisms appear to exhibit no correlation between protein production rate and amino acid cost. When the costs associated with building blocks that the parasite obtains from its host are removed,however, a trend once again becomes evident.

Subject Headings

Computer Science

Keywords

metabolic efficiency; codon usage bias; amino acid; PCA; principal component analysis; protein synthesis; expressivity

Advisor

Michael L. Raymer

Pages

236p.

Document number: wright1133886196
Permalink: http://rave.ohiolink.edu/etdc/view?acc_num=wright1133886196

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