Recent advances in DNA sequencing technology have enabled entire genomes to be sequenced quickly and accurately, resulting in an exponential increase in the number of organisms whose genome sequences have been elucidated. While the genome sequence of a given organism represents an important starting point in understanding its physiology, the functions of the protein products of many genes are still unknown; as such, computational methods for studying protein function are becoming increasingly important. In addition, this wealth of genomic information has created an unprecedented opportunity to compare the protein content of different organisms; among other applications, this can enable us to improve taxonomic classifications, to develop more accurate diagnostic tests for identifying particular bacteria, and to better understand protein content relationships in both closely-related and distantly-related organisms.<p> This thesis describes the design, evaluation, and use of a program called Proteome Subtraction and Intersection (PSI) that uses an idea called genome subtraction for discovering protein-phenotype relationships and for characterizing differences in protein content in groups of organisms. PSI takes as input a set of proteomes, as well as a partitioning of that set into a subset of "included" proteomes and a subset of "excluded" proteomes. Using reciprocal BLAST hits, PSI finds orthologous relationships among all the proteins in the proteomes from the original set, and then finds groups of orthologous proteins containing at least one orthologue from each of the proteomes in the "included" subset, and none from any of the proteomes in the "excluded" subset.<p> PSI is first applied to finding protein-phenotype relationships. By identifying proteins that are present in all sequenced isolates of the genus <i>Lactobacillus</i>, but not in the related bacterium <i>Pediococcus pentosaceus</i>, proteins are discovered that are likely to be responsible for the difference in cell shape between the lactobacilli and <i>P. pentosaceus</i>. In addition, proteins are identified that may be responsible for resistance to the antibiotic gatifloxacin in some lactic acid bacteria.<p> This thesis also explores the use of PSI for comparing protein content in groups of organisms. Based on the idea of genome subtraction, a novel metric is proposed for comparing the difference in protein content between two organisms. This metric is then used to create a phylogenetic tree for a large set of bacteria, which to the author's knowledge represents the largest phylogenetic tree created to date using protein content. In addition, PSI is used to find the proteomic cohesiveness of isolates of several bacterial species in order to support or refute their current taxonomic classifications.<p> Overall, PSI is a versatile tool with many interesting applications, and should become more and more valuable as additional genomic information becomes available.

Recent advances in DNA sequencing technology have enabled entire genomes to be sequenced quickly and accurately, resulting in an exponential increase in the number of organisms whose genome sequences have been elucidated. While the genome sequence of a given organism represents an important starting point in understanding its physiology, the functions of the protein products of many genes are still unknown; as such, computational methods for studying protein function are becoming increasingly important. In addition, this wealth of genomic information has created an unprecedented opportunity to compare the protein content of different organisms; among other applications, this can enable us to improve taxonomic classifications, to develop more accurate diagnostic tests for identifying particular bacteria, and to better understand protein content relationships in both closely-related and distantly-related organisms.<p> This thesis describes the design, evaluation, and use of a program called Proteome Subtraction and Intersection (PSI) that uses an idea called genome subtraction for discovering protein-phenotype relationships and for characterizing differences in protein content in groups of organisms. PSI takes as input a set of proteomes, as well as a partitioning of that set into a subset of "included" proteomes and a subset of "excluded" proteomes. Using reciprocal BLAST hits, PSI finds orthologous relationships among all the proteins in the proteomes from the original set, and then finds groups of orthologous proteins containing at least one orthologue from each of the proteomes in the "included" subset, and none from any of the proteomes in the "excluded" subset.<p> PSI is first applied to finding protein-phenotype relationships. By identifying proteins that are present in all sequenced isolates of the genus <i>Lactobacillus</i>, but not in the related bacterium <i>Pediococcus pentosaceus</i>, proteins are discovered that are likely to be responsible for the difference in cell shape between the lactobacilli and <i>P. pentosaceus</i>. In addition, proteins are identified that may be responsible for resistance to the antibiotic gatifloxacin in some lactic acid bacteria.<p> This thesis also explores the use of PSI for comparing protein content in groups of organisms. Based on the idea of genome subtraction, a novel metric is proposed for comparing the difference in protein content between two organisms. This metric is then used to create a phylogenetic tree for a large set of bacteria, which to the author's knowledge represents the largest phylogenetic tree created to date using protein content. In addition, PSI is used to find the proteomic cohesiveness of isolates of several bacterial species in order to support or refute their current taxonomic classifications.<p> Overall, PSI is a versatile tool with many interesting applications, and should become more and more valuable as additional genomic information becomes available.

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