A bioinformatic exploration of poxviruses




Da Silva, Melissa Elizabeth

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The overall theme of this dissertation is the genomic analysis of poxviruses using bioinformatics. The first analysis presented in this dissertation (Chapter 2) focuses on a new method for predicting which open reading frames (ORFs) in poxviruses are likely to be expressed. A measure that takes into account the amino acid and purine content of all predicted open reading frames (ORFs) in the genome was developed and when used on the vaccinia virus (VACV) strain Copenhagen genome (training case), the measure had a success rate of 94%. Using the measure on an extremely adenine and thymine rich entomopoxvirus (test case), 241 ORFs were found to be potentially expressed and 51 ORFs were likely not expressed although further biochemical experiments will be required to confirm this result. The second analysis of this dissertation (Chapter 3) focuses on determining the nature of an interesting background pattern similar to a set of stripes that was observed while analyzing a self-dotplot of the molluscum contagiosum virus genome. These stripe regions were further analyzed and were found to have a nucleotide composition and amino acid usage that was different to the remainder of the genome. Given this differing nucleotide and amino acid usage, the genes contained in these stripe regions are thought to have been recently acquired from the host or another virus, making these regions similar to bacterial pathogenicity islands. The third analysis of this dissertation (Chapter 4) focuses on predicting the function of “unknown” poxvirus proteins by using a hidden Markov model (HMM) comparison search tool to scan all “unknown” proteins in the VACV genome looking for any database matches that may have been missed by conventional approaches (BLASTp and PSI-BLAST). One protein, the VACV G5R protein, in this scan showed a promising hit (96% probability) to an archaeal flap endonuclease (FEN-1) protein. A structural model of the G5R protein was created and subsequently compared to the crystal structure of the human FEN-1 protein and was found to be highly conserved in both secondary and tertiary structure and with three of the five main features of the FEN-1 protein including the active site suggesting that the G5R protein should be classified as a flap endonuclease protein. Related to the analysis in Chapter 4, are the results presented in Chapter 5 of this dissertation that focus on locating a protein encoded by the VACV genome that is similar to proliferating cell nuclear antigen (PCNA). Knowing that the FEN-1 protein requires PCNA as an intermediary to contact DNA, the genome of VACV was scanned using InterProScan in order to identify any potential proteins that were similar to PCNA. One protein (VACV G8R) was identified and subsequently modeled and compared to the crystal structure of the human PCNA protein. The secondary and tertiary structure was highly conserved between the two proteins suggesting that the G8R protein should be classified as a sliding clamp similar to human PCNA.



Bioinformatics, Poxvirus, Computational biology, Genomics, Structural modeling