Matthew K. Oki Individual Journal 6

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Electronic Lab Notebook

Purpose

We went into this project looking to answer the question: Will the Markham et al. sequences group into the 10 different subtypes present in the Collinson-Streng et al. study? We hypothesized that the Markham study sequences would group to different subtypes in Collinson-Sterg et al.

Methods & Results

  1. Two Markham et al. sequences were selected at random from the first visit of all 15 subjects.
  2. Three Collinson-Streng et al. sequences were selected at random from each of the 10 subtypes.
  3. We followed the methods for ClustalW and ClustalDist from Exploring HIV Evolution
  4. ClustalW from Biology Workbench was used to find the unrooted tree, S, and theta values.
    • Download the sequences from PubMed as a FASTA file.
    • Run the ClustalW multiple sequence alignment.
    • Each nucleotide difference (S) was denoted by the absence of a star on the multiple sequence alignment
  5. Theta was then calculated:

mattokiScreen_Shot_2016-09-21_at_3.23.25_PM.png

  1. ClustalDist was used to find the minimum and maximum
    • Import the previously dowloaded sequences into the alignment tools section.
    • Run the ClustalDist
    • A matrix is produced.
    • The highest and lower numbers in this matrix were multiplied by the length of sequence
      • Rounding these numbers to the nearest integer gives us maximum and minimum respectively
  2. All of this data was compressed into the matrix and unrooted tree shown below:

DetamoreJordanHIVFinal.png MattokiScreen Shot 2016-10-10 at 5.32.55 PM.png

Data & Files

The PDF version of our powerpoint presentation can be found here.

Scientific Conclusion

The results of the unrooted tree and matrix proved there was no correlation between the Markham et al. sequences and the Collinson-Streng et al. sequences. This was mostly due to the large separation between the study groups. Markham's study group was taken from a study done in Maryland, U.S.A., while Collinson-Streng's study group was from a group in Uganda. Additionally, the Markham sequences were more diverse between each other than the Collinson-Streng sequences were. This is shown in the clustering of each group on the unrooted tree. However, another interesting result was that even the different subtypes didn't group together. We would like to pursue this in future research, given the opportunity. We would like to see if there is even any correlation between the subtypes sequentially from a much larger pool of sequences.

Acknowledgments

  • I would like to thank my partner, Jordan Detamore, for assistance on this project.
    • We collaborated in class on the searching for sources.
    • We also worked on our HIV project together in class and six hours out of class.
  • I would also like to thank Kam D. Dahlquist, Ph.D. for providing the instructions and information for this assignment both in class and on the BIOL368/F16:Week 6.
  • Even though I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

References

  • Collinson-Streng, A. N., Redd, A. D., Sewankambo, N. K., Serwadda, D., Rezapour, M., Lamers, S. L., … Laeyendecker, O. (2009). Geographic HIV Type 1 Subtype Distribution in Rakai District, Uganda. AIDS Research and Human Retroviruses, 25(10), 1045–1048. http://doi.org/10.1089/aid.2009.0127
  • Hemelaar, J., Gouws, E., Ghys, P. D., & Osmanov, S. (2006). Global and regional distribution of HIV-1 genetic subtypes and recombinants in 2004. Aids, 20(16), W13-W23. doi: 10.1089/aid.2009.0127
  • Markham, R.B., Wang, W.C., Weisstein, A.E., Wang, Z., Munoz, A., Templeton, A., Margolick, J., Vlahov, D., Quinn, T., Farzadegan, H., & Yu, X.F. (1998). Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline. Proc Natl Acad Sci U S A. 95, 12568-12573. doi: 10.1073/pnas.95.21.12568
  • Vlahov, D., Anthony, J.C., Munoz, A., Margolick, J., Nelson, K.E., Celentano, D.D., Solomon, L., Polk, B.F. (1991). The ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users: description of methods and characteristics of participants. NIDA Res Monogr 109, 75-100.
  • BIOL368/F16:Week 6
  • Exploring HIV Evolution
  • Biology Workbench

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