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Determining the Future of A3 phages using Average

Determining the Future of A3 phages using Average N ucleotide I dentity (ANI) and Immunity Testing. Emily S., Emily N., Kris C., and Casey N. Abstract

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Determining the Future of A3 phages using Average

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  1. Determining the Future of A3 phages using Average Nucleotide Identity (ANI) and Immunity Testing Emily S., Emily N., Kris C., and Casey N. Abstract We are doing research in order to determine if the subcluster A3 should be divided further or if it should be a new subcluster all together. We used splitstree analysis for the protein repressor gene of the A3 phages. We also did Average Nucleotide Identity and Immunity Testing to figure out if A3 phages should be separated. From the splitstree and the ANI, evidence suggests that the A3 phages should be split into two different subclusters within itself. In order to get better results the immunity testing should be done again, due to possible contamination. Table 1. Average Nucleotide Identity forA3 phages. This table shows the two distinct A3 sub-subclusters. Key: The light pink color shows the A3-a phage, while the dark green shows the A3-b phage. The yellow color shows the absolute threshold of 1. The light blue shows how the A3-b phage is not similar to the A3-a phage. The orange depicts the threshold of similarity greater than 0.8, which represents similarity of A3-a among itself and A3-b among itself. Table 2. The results are hard to be determined because some plates became contaminated. If there was a spot the phage was not alike the lysogen. If there was not spot the known lysate was similar to the lysogen which assumes the same cluster. Introduction Based on the nucleotide sequence similarities that we observed in phamerator (1) we hypothesize the A3 phages should be split into sub-subclusters. We will call these new subclusters A3-a and A3-b. We rationalized that this would be better than separating the A3 subcluster into two separate subclusters, because they are similar to A3, but not as similar as a cluster should be. We chose to do ANI because ANI was used to create the original clusterization (2) of the phage. Figure 1. This is the tree we generated for the DNA repressor gene. We found that there are twoseparate groupings among the A3 phages. Summary of results For Splitstree and ANI we concluded similar results, that there are two specific groups in the A3 cluster that are different from each other. The immunity testing gave us conflicting results by showing us Phoxy is related to JHC117 . Our immunity testing results should be retested in order to determine more accurate results. References 1. Cresawn et al. (2011) Phamerator: a bioinformatic tool for comparative bacteriophage genomics. BioMed Central 1, 1-14. 2. Hatfull, G. (2010). 60-Phage Paper. Comparative Genomic Analysis of 60 Mycobacterium Phage Genomes,1, 119-143. Methods The first thing we did was make a tree for the DNA repressor gene for the A3 phages. We did this by using phagesdb where we used mega software, and splitstree. When we did ANI, we used phagesdb, DNA master’s genome comparison tool, and Excel. For immunity testing we tested the known lysogens(MarQuardt, Rockstar, JHC117, and Gomashi) against the known lysates (all the above + Phoxy and Spike509). We made two plates per lysogen and spotted the six lysates. We also did a plate of Msmeg. Conclusions/Discussion We found that the ANI and Splitstreehad the most accurate data. It also followed our hypothesis. The ANI showed two separate groups inside the A3 phages. The Splitstree also showed the two specific groups. This supports our hypothesis that the A3 phages should be divided further into sub-subclusters. The immunity testing gave us unexpected results, by having phoxy immune to JHC117, we would have expected the opposite since they should have been in separate groups in the A3 cluster. If we could do this differently we would have used better aseptic technique, to be more careful with contamination. Further plans would be to redo the immunity testing and get better results. Acknowledgements Karen Klyczek, Fred Bonilla, Kim Mogen, and Stephan Aiken

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