ColinWikholm BIOL368 Week 5

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Contents

Electronic Lab Notebook: Database Work and Annotated Bibliography

The following link contains the week 5 in-class work: Completed Week 5 Assignment

HIV Evolution Project Progress

Purpose

The overall purpose of this project is to investigate the repeatability of the Markham et al. (1998) results regarding divergence and CD4 T cell levels (see the "Defining Your Research Project" section in my Individual Journal Page for Week 4. The purpose of this week's investigation is to strengthen and renew my understanding of HIV-1 evolution and the env gene in order to prepare me for project work in week 6.

Methods and Results

Although I did not perform statistical analysis on the Markham et al. (1998) subject data this week, I read through the articles by Evering et al. (2014), Gall et al. (2013), Merk et al. (2013), and Wang et al. (2013) to better understand more recent research on the HIV-1 envelope and env gene diversity and divergence. I also read through the Markham et al. (1998) paper again to ensure that I understand the plans for our project and the dynamics of the env gene with respect to HIV-1 evolution and pathogenicity. The scientific community has greatly expanded its knowledge of HIV-1 and the env gene since the Markham et al. (1998) paper. For example, it is currently widely believed that genetic diversity and divergence of HIV-1 env sequences are what assist in HIV-1 invasion and host immune system evasion. At the time of the Markham et al. (1998), such concepts were presented more tentatively.

Data and Files

No data or files were produced during this week's work

Scientific Conclusion

Genetic diversity and divergence of the env gene contributes majorly to HIV-1's invasive and evasive characteristics. Thus, our re-analysis of the Markham et al. (1998) paper should yield the same results: greater genetic divergence is associated with lower CD4 T cell counts. This is supported by recent literature, which has successfully strengthened my understanding of HIV-1 evolution and the env gene in preparation for week 6.

HIV Evolution Project Planned Methods/Procedure for Week 6

The following are the steps William P Fuchs and I plan to follow with reciprocated support from Anindita Varshneya and Mia Huddleston, who will work on the genetic diversity analysis:

  1. Use SDSC Biology Workbench and the ClustalW tool to create multiple sequence alignment for the env data of each of the visits of subjects 6, 8, 9, and 14.
  2. Use SDSC Biology Workbench and the ClustalW tool to create unrooted trees of the clones of each of the visits of subjects 6, 8, 9, and 14.
  3. Calculate env diversity (θ) for each of the visits of subjects 6, 8, 9, and 14.
  4. Use intransitive change in θ between visits to calculate genetic divergence ([θ2-θ1]/time)
  5. Perform correlation analysis between genetic divergence and CD4 T cell count for each of the corresponding visits of subjects 6, 8, 9, and 14.
  6. Test for significance, analyze results, and compare to results of Markham et al. (1998).
  7. If there is extra time, begin preparing PowerPoint presentation

Acknowledgements

I discussed project plans with Anindita Varshneya, Mia Huddleston, and William P Fuchs in class and in person on September 27, 2016. What is more, we all talked over Facebook Messenger on October 2, 2016 to reaffirm that we would be conducting diversity and divergence analysis separately (but assist each other if needed) during class on October 4, 2016. For the diversity component of the parallel projects, see Anindita Varshneya's procedure at AninditaVarshneya BIOL368 Week 5. Finally, I met with William P Fuchs in person to prepare for our project procedure on October 4, 2016 While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

Colin Wikholm 22:45, 3 October 2016 (EDT)

References

  1. Assignment Week 5
  2. Evering, T. H., Kamau, E., St. Bernard, L., Farmer, C. B., Kong, X.-P., & Markowitz, M. (2014). Single genome analysis reveals genetic characteristics of Neuroadaptation across HIV-1 envelope. Retrovirology, 11, 65. http://doi.org/10.1186/s12977-014-0065-0
  3. Gall, A., Kaye, S., Hué, S., Bonsall, D., Rance, R., Baillie, G. J., … Kellam, P. (2013). Restriction of V3 region sequence divergence in the HIV-1 envelope gene during antiretroviral treatment in a cohort of recent seroconverters. Retrovirology, 10, 8. http://doi.org/10.1186/1742-4690-10-8
  4. Markham, R. B., Wang, W.-C., Weisstein, A. E., Wang, Z., Munoz, A., Templeton, A., … Yu, X.-F. (1998). Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline. Proceedings of the National Academy of Sciences of the United States of America, 95(21), 12568–12573.
  5. Merk, A., & Subramaniam, S. (2013). HIV-1 envelope glycoprotein structure. Current Opinion in Structural Biology, 23(2), 268–276. http://doi.org/10.1016/j.sbi.2013.03.007
  6. Wang, W., Nie, J., Prochnow, C., Truong, C., Jia, Z., Wang, S., … Wang, Y. (2013). A systematic study of the N-glycosylation sites of HIV-1 envelope protein on infectivity and antibody-mediated neutralization. Retrovirology, 10, 14. http://doi.org/10.1186/1742-4690-10-14

Important links

Bioinfomatics Lab: Fall 2016

Class Page: BIOL 368-01: Bioinfomatics Laboratory, Fall 2016

Weekly Assignments Individual Journal Assignments Shared Journal Assignments

User:Colin Wikholm

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