KP Ramirez Week 8

Week 8

Question: Are their differences in HIV-1 diversity or divergence between participants with high CD4 T cell variability within the study (between visits) as compared to participants with linear ‘progression’ (defined as CD4 T cell counts which fall rapidly, or linearly, over time (slope ~ -1)?

Prediction: We predict that participants with high variability in T cell count between visits will show a lower HIV-1 diversity and divergence than participants with linear progression. This is predicted under two assumptions

• (1) High diversity and divergence of HIV-1 variants indicates a more rapidly progressing virus (and thus a steadily falling CD4 T cell count)
• (2) high variability in T-Cell count will indicate a participant’s immune system was able to manage this virus better than a participant with a steadily falling CD4 counts. If we do see high diversity in participants with high variability in T cell count between visits, we predict that these will be predominantly synonymous mutations as opposed to non-synonymous mutations (which we would expect to see with linear progressors).

Subjects Chosen:

• Linear Progressors: (slope: -1) Subject: 4, 10
• High Variability between visits: Subject 12, 8
• (Low Variability between visits: 5

Article: Early viral load and CD4+ T cell count, but not percentage of CCR5+ or CXCR4+ CD4+ T cells, are associated with R5-to-X4 HIV type 1 virus evolution.*

1. van Rij RP, Hazenberg MD, van Benthem BH, Otto SA, Prins M, Miedema F, and Schuitemaker H. Early viral load and CD4+ T cell count, but not percentage of CCR5+ or CXCR4+ CD4+ T cells, are associated with R5-to-X4 HIV type 1 virus evolution. AIDS Res Hum Retroviruses. 2003 May;19(5):389-98. DOI:10.1089/088922203765551737 |

• Journal Club presentations in class.

Working with Protein Sequences In-class Activity

• This week we will begin to learn how to analyze protein structures. For today, we will be using the Bioinformatics for Dummies book extensively, so be sure to bring it to class. We will be using some bioinformatics tools to analyze the structure of the gp120 envelope protein.
  1. Completed
• Chapter 2: Retrieving Protein Sequences/Retrieving a list of Related protein sequences (pp. 42-51 in second edition). The example worked through in the book uses the sequence of an enzyme called dUTPase. Follow the book example yourself and then work through the example again, this time using the HIV gp120 envelope protein instead.
  1. Human immunodeficiency virus type 1 (isolate HXB2 group M subtype B) (HIV-1)
  2. P04578 Accession
  3. Presented 4 pages of results
  4. >sp|P04578|ENV_HV1H2 Envelope glycoprotein gp160 OS=Human immunodeficiency virus type 1 (isolate HXB2 group M subtype B) GN=env PE=1 SV=2

MRVKEKYQHLWRWGWRWGTMLLGMLMICSATEKLWVTVYYGVPVWKEATTTLFCASDAKA YDTEVHNVWATHACVPTDPNPQEVVLVNVTENFNMWKNDMVEQMHEDIISLWDQSLKPCV KLTPLCVSLKCTDLKNDTNTNSSSGRMIMEKGEIKNCSFNISTSIRGKVQKEYAFFYKLD IIPIDNDTTSYKLTSCNTSVITQACPKVSFEPIPIHYCAPAGFAILKCNNKTFNGTGPCT NVSTVQCTHGIRPVVSTQLLLNGSLAEEEVVIRSVNFTDNAKTIIVQLNTSVEINCTRPN NNTRKRIRIQRGPGRAFVTIGKIGNMRQAHCNISRAKWNNTLKQIASKLREQFGNNKTII FKQSSGGDPEIVTHSFNCGGEFFYCNSTQLFNSTWFNSTWSTEGSNNTEGSDTITLPCRI KQIINMWQKVGKAMYAPPISGQIRCSSNITGLLLTRDGGNSNNESEIFRPGGGDMRDNWR SELYKYKVVKIEPLGVAPTKAKRRVVQREKRAVGIGALFLGFLGAAGSTMGAASMTLTVQ ARQLLSGIVQQQNNLLRAIEAQQHLLQLTVWGIKQLQARILAVERYLKDQQLLGIWGCSG KLICTTAVPWNASWSNKSLEQIWNHTTWMEWDREINNYTSLIHSLIEESQNQQEKNEQEL LELDKWASLWNWFNITNWLWYIKLFIMIVGGLVGLRIVFAVLSIVNRVRQGYSPLSFQTH LPTPRGPDRPEGIEEEGGERDRDRSIRLVNGSLALIWDDLRSLCLFSYHRLRDLLLIVTR IVELLGRRGWEALKYWWNLLQYWSQELKNSAVSLLNATAIAVAEGTDRVIEVVQGACRAI RHIPRRIRQGLERILL

• Chapter 4: Reading a SWISS-PROT entry (pp. 110-123 in the second edition). The example worked through in the book is the epidermal growth factor receptor. Work through this example and then do it again with the HIV gp120 envelope protein instead.
• Chapter 5: ORFing your DNA sequence (pp. 146-147 in second edition). In the previous section of the course, we were working with DNA sequences from the HIV gp120 envelope protein. Take one of your DNA sequences and follow the instructions to find the open reading frames in the sequence. Since you were working with just a portion of the entire envelope protein, you may get some strange results. Compare your results with the SWISS-PROT entry you found for the protein above to decipher what the output means. Besides the NCBI Open Reading Frame Finder described in the book, ExPASy also has a translation tool you can use, found here.
• Chapter 6: Working with a single protein sequence (pp. 159-195 in second edition). Work through the following examples in this chapter using the entire HIV gp120 envelop protein sequence that you obtained from SWISS-PROT. We will then compare the results of these analyses with the actual structure of the gp120 protein obtained by X-ray crystallography.
  • ProtParam
  • Looking for transmembrane segments

Journal Assignments

KP Ramirez Week 2	KP Ramirez Week 6	KP Ramirez Week OFF
KP Ramirez Week 3	KP Ramirez Week 7	KP Ramirez Week 11
KP Ramirez Week 4	KP Ramirez Week 8	KP Ramirez Week 12
KP Ramirez Week 5	KP Ramirez Week 9	KP Ramirez Week 13

Shared Journals

1. Week 2
2. Week 3
3. Week 4
4. Week 5
5. Week 6
6. Week 7
7. Week 8
8. Week 9
9. Week 10
10. Week 11
11. Week 12
12. Week 13

Useful Links

• Introductory tutorial
• OpenWetWare help pages
• BIOL398-01/S10:People