1. Impact of Genetic Variation within the HIV-1 LTR and
Tat on Transcription
David Cunningham
MMS Presentation
Department of Microbiology and Immunology
Center for Molecular Virology and Translational Neuroscience
Drexel University College of Medicine
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2. HIV-1 virion structure and genomic organization
Adapted from http://www.stanford.edu/group/virus/retro/2005gongishmail/HIV.html
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3. Physical structure of the HIV-1 LTR
500 400 300 200 100 +1 100 200
U3 R U5
AP-1 NFAT-1 USF NF-B TATA CTF/NFI
NRRE AP-1 AP-1 SP-50 cETS-1 Sp HIP116 AP-1 AP-1
100kD 38kD C/EBP C/EBP E box YY-1 c-fos c-fos
GRE URS LEF-1 LBP-1
ATF/CREB C/EBP TDP-43
MODULATORY REGION ENHANCER REGION CORE REGION
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4. Regulation of HIV-1 LTR basal and stimulated transcription
- 405 - 245 + 20 + 165
U3 R U5
Cell activation
TNF-α, IL-1β, HDAC1
IL-6, IL-7, etc… p50
p50 CTD
TAR NELF TAT
DSIF
Ac Ac p65 Ac
Nuc-0 p50 Nuc-1
TFIID
TATA
C/EBP US2
AP3-L
C/EBP DS3
C/EBP US1
NF-B
ATF/CREB
AP-1
SP1
Ac Ac HAT
Ac Ac
Modulatory region Core region
Enhancer region
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5. Regulation of HIV-1 Tat-mediated LTR activation
- 405 - 245 + 20 + 165
U3 R U5
PCAF
cdk9
CTD
cycT1
TAR
TAT
Ac Ac p65 Ac
Nuc-0 p50 Nuc-1
TFIID
TATA
AP3-L
C/EBP DS3
C/EBP US2
C/EBP US1
NF-B
ATF/CREB
AP-1
SP1
Ac Ac Ac HAT Ac
Modulatory region Core region
Enhancer region
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6. Hypothesis
• Genetic variation within HIV-1 LTR and Tat co-
select due to selective pressures applied to the
HIV-1 genome during replication, resulting in
altered function of the LTR, Tat, or both.
7. DREXELMED HIV/AIDS Genetic Analysis Cohort in the HAART era
Ficoll-Pacque Qiagen DNEasy
Whole Blood Plus gradient Tissue Kit
Serum & PBMC
separation Isolation of PCR amplify
BSL-3 Facility genomic DNA proviral DNA
Serum and cell banking Separate on
Clinical and virus/host genomic data management agarose gel
HIV-1 Sequence
Database
Sequence PCR product
Analysis sequencing
Gel extraction
pGL3 Basic pCR4-TOPO
Incubate with
Functional PCR amplify/ Taq to add A
analysis clone proviral DNA overhang
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8. Summary of DREXELMED HIV/AIDS Genetic Analysis Cohort
ENROLLMENT UPDATE: March 20, 2012
Definitive LTR
Visit1 Number
sequences2
R003 486 400 1On average,
patients are seen
R01 271 195 every six months
R02 185 122
R03 120 72 2Definitive
LTR
sequences as called
R04 81 31
by Brian Moldover,
R05 51 15 Ph.D.
R06 32 4
3R00 has 1481
R07 14
definitive LTR clones
R08 5 from 110 patients
R09 1
TOTALS 1246 839
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9. Association analysis of SNPs with regard to CD4 count and log
viral load
Phenotype Position TF site Ref/Mut Mutant Frequency Effect p-value
CD4 244 Pet-1 A/G 56.0% 37.630 0.0233 Effect = change in CD4
293 USF G/ACT 11.5% -54.487 0.0366 count away from the
444 Oct 1 T/C 36.9% -65.098 0.0478 average
Viral Load 108 COUP/AP1 A/CGT 37.3% 153.8% 0.0263
115 unk A/GT 18.9% 61.8% 0.0418
131 unk A/CGT 12.2% 176.1% 0.0409 Effect = % change in VL
168 unk G/ACT 16.2% 56.4% 0.0156 away from the average
385 Sp III (9) G/AC 8.2% 229.6% 0.0242
605 unk C/AT 8.9% 756.8% 0.0308
adjusted for sex, age, race, days since baseline visit; unk = unknown
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10. Association analysis of HIV-1 LTR SNPs with regard to change in
CD4 count and change
Phenotype Position Location Ref/Mut Mutant Frequncy Effect p-value
CD4 273 unk C/A 8.3% -42.705 0.0486
304 unk T/A 13.2% -38.809 0.0336 Effect = change in
314 unk G/ACT 6.8% -60.034 0.0162
381 Sp III (5) C/T 27.9% 31.887 0.0301
CD4 count between
385 Sp III (9) G/A 8.3% -57.781 0.0215 visits
398 unk T/CGA 21.4% -42.769 0.0122
Log (Viral) 108 COUP/Ap 1 A/CGT 37.3% 0.161 0.0157
USF
Effect = % change
290 C/T 6.4% 0.319 0.0191
383 Sp III (7) T/C 6.0% 0.302 0.0425 in VL between visits
adjusted for sex, age, race, days since baseline visit; unk=unknown
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11. Electrophoretic mobility shift assay (EMSA)
3. Run native PAGE
2. Incubate DNA probe with protein (N.E.) DNA
(probe)
antibody
TF
32P
TGACTCA
32P
1. Label double-stranded DNA
(oligonucleotide with binding element)
32P
TGACTCA
32P
12. Disease severity of patient 107 increases over the four visits
Li and Aiamkitsumrit et al 2011
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13. Patient acquires neurocognitive impairment over time
Patient Neurologic Neurologic Neurologic
Visit score test complications
A0107- depression, bipolar,
normal MSK
R00 schizophrenia
A0107- modified depression, bipolar,
12
R01 Hopkins schizophrenia
A0107- modified depression, bipolar,
8
R02 Hopkins schizophrenia
A0107- modified depression, bipolar,
9.5
R03 Hopkins schizophrenia
A0107-R01 A0107-R02 A0107-R03
Score: 2/2 Score: 0/2 Score: 0/2
Li and Aiamkitsumrit et al 2011
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14. Status of amplification and cloning of patient 107 tat genes
Isolation of
Patient Growth of Round 1 Round 2 pcDNA Sequence
4.4KB
Visit Culture Amplification Amplification Hygro3.1 Confirmed
Fragment
R00 ✔ ✔ ✔ ✔ ?
R01 ✔ ✔ ✔ ✔ ?
R02 ✔ ✔ ?
R03 ✔ ✔ ?
R04 ✔ ✔ ?
R05 ✔ ✔ ?
R06 ✔ ✔ ?
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16. Majority of 4.4 kb insert lost during sample preparation
GAG-POL ENV
tm
LTR pr rt in VPR su (gp 120)
(gp 41)
GAG VIF tat NEF LTR
rev
T-7 Primer M13R Primer
4.4kb
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17. Domains of Tat and important amino acid motifs
Basic
Cysteine-rich domain/TAR
Acidic domain domain Core binding EXON 1 EXON 2
domain/ARM
21 22 30 37 38 48 49 57 58 72 73 101
C C C CC C C LGISYG RKKRRQRRR RGD KKK E E E
I II III IV V VI
Basic region 86 87
Nuclear
Transactivation/ localization
CycT1 binding C/EBP
Co-factor binding binding
CBP/p300
Sp1
binding DNA-PK
binding
18. DREXELMED Cohort Tat sequences show conserved
cysteine residues and position 100 variation
Tat AA Position 100 analysis
Pt ID R00 R01 R02 R03 R04 R05 R06
Time (mnths) between
9 10 8 17 6
visits
37
Neuro NA NA 3.5 ND 10 11
Tat V to H
Time (mnths) between
9 10 9 5 18 5
visits
41
Neuro NA NA 4.5 8 5.5 ND ND
Tat V to F
Time (mnths) between
23
visits
51
Neuro norm 9
Tat conB
Time (mnths) between
19 8 12 18
visits
56
Neuro sub 6 9 9
Tat V to C
Time (mnths) between
14 2 11 6 3 5
visits
107
Neuro norm 12 8 9.5 10 11.5 10.5
Tat V to K V to K
Time (mnths) between
36
visits
119
Neuro norm 5
Tat conB
Time (mnths) between
visits
131
Neuro 4
Tat V to I
Time (mnths) between
visits
220
Neuro 11
Tat 3 conB
19. Brian Wigdahl, Ph.D., Professor & Chair
Department of Microbiology & Immunology
Drexel University College of Medicine
Edward Archaempong, Ph.D. Sonia Navas-Martin, Ph.D. Adriano Ferrucci Liudmila Mazaleuskaya
Jeffrey Jacobson, M.D. Michael Nonnemacher, Ph.D. Archana Gupta Saifur Rahman
Pooja Jain, Ph.D. Vanessa Pirrone, Ph.D. Bryan Irish Viraj Sanghvi
Steve Jennings, Ph.D. Laura Steel, Ph.D. Shawn Keogan Sonia Shah
Zafar Khan, Ph.D. Nirzari Parikh, M.S. Christina Kollias Luz Jeanette Sierra
Sandhya Kortagere, Ph.D. Shendra Passic, M.S. Jason Lamontage Melany Simmons
Fred Krebs, Ph.D. Benjamas Aiamkitsumrit Luna Li Marianne Strazza
Michele Kutzler, Ph.D. Brandon Blakely Karissa Lozenski Ken Thompson
Julio Martin-Garcia, Ph.D. Sharon Bandstra Raphael Lukov Kamiliah Williams
Brian Moldover, Ph.D. Betty Condran Sharron Manuel Adam Wojno
Olimpia Meucci, M.D., Ph.D. Satinder Dahiya Nyree Martin
NINDS NIMH NCI NIDA NIAID CONRAD
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Notes de l'éditeur
Proviral DNA is integrated in host chromosome is approximately 9.6 kb in length, which encodes for a number of HIV proteins. Important for today’s talk is that it encodes for the HIV regulatory protein Tat. The transcription, which is driven by RNA pol, occurs through the interaction of this enzyme with the viral promoter, or long terminal repeat. Contained in the 4.4 kb segment is the vpr region, tat, envelope, nef, and the LTR.
Basal HIV transcription occurs through the interaction of RNA pol II enzyme with various cellular transcription, principal being NF kappa-B factors. This basal transcription results in short and long transcipts of the HIV genome. Important for the talk today is the fact that these transcripts encode for Tat and it is the build up of this protein that leads to superactivation of HIV transcription.
Thatsuperactivation is depicted here, where you can see Tat interacting with the TAR element, allowing for increased processivity and elongation of the RNA pol II. This leads to between a 30 and 70X increase in transcription.
So, my PI and I have developed a hypothesis that states that genetic variation within HIV-1 LTR and Tat co-select due to selective pressures applied to HIV genome during replication, resulting in altered function of the LTR, Tat, or both. If anyone asks: reverse transcriptase is driving the SNP changes that we see in the genome.
SNPs associate with CD4 T cell count and viral load. Scatter plot of p-valuesUsing the preliminary data from 350 subjects with a total of 602 visits, the results of the best fit models demonstrated both gender (5x10-5)and time (days since first visit, p=0.0021) are significantly associated with CD4 counts. Age, cocaine use, and time are all significant (0.0024, 0.0041, 1x10-7, respectively) in affecting viral load while gender is not. Cocaine users have 2.74 times more viral load than non-users. In a preliminary SNP association study, SNPs identified above were associated with CD4 T cell count and viral load. We have found 7 SNPs significantly associated with CD4 and 3 with viral load at p=0.05, after adjusting for age, gender, cocaine use, and time (Fig. 6).
As an initial investigation of CD4 and viral load progression, the association between the SNPs and relative changes of CD4 and viral load at following visits compared to their baseline levels using the same models were tested (Fig. 6). 8 SNPs were found significant and 6 of them are associated with greater changes of CD4 and viral load. The possible associations between these SNPs and the relative change confirm our hypothesis that SNPs may affect disease progression and prompt examination of the next hypothesis regarding progression rate and SNPs.
What was interesting about this patient is that the 3T/5T variation existed as a predominant quasispecies within the patient when she had a good CD4 count and low viral load.
Even more interesting was that these variants existed prior to this patient declining in their ability to perform well on a mini-neurologic exam. This mini-neurologic exam tests a patient for psychomotor speed, memory recall, and constructional abilities. A perfect score on this test is a 12; any score below 10 is considered neurologically impaired. As you can see on the right table, as this patient came back for subsequent visits, her neurologic score declined. In addition to the neurologic score decline, the important point to notice in that in the previous slide, her CD4 count declined. While this patient can be viewed as a proof of concept for the original 3T/5T observation, the lab was interested in understanding the functionality of the LTR and Tat from this patient and if it potentially contributed to the increase in pathogenesis.
Current progress to date includes growing up cultures of bacteria into which the HIV genome has already been cloned from patient 107 blood samples. I have been able to grow up clones from all patient 107 visits, and isolate the 4.4KB fragment from the genome. However, this process has not been without its problems.
One such portion of the genome which is amplified is called the 4.4 kb fragment. This fragment spans from the VPR to the 3 prime LTR. As you can see, within this fragment, the Tat gene is contained. Important to note is that Tat is a protein that is made through two exons which are spliced together (keep this in mind, as it will be important in describing some of the techniques that I am employing to assist this project).
Tat has been divided into six different functional domains. The two domains that are of importance to this presentation are 2 and 6. While I am bringing these two domains to your attention, I performed sequence analysis on all domains to look for amino acid changes that were common to patients that demonstrated neurocognitive impairment. In regards to domain 2, we found that the cysteine rich region was conserved in all patients through all samples obtained. Domain 6, however, did show some changes that correlated with neurocognitive impairment. The two important changes that were seen in patients that did demonstrate neurocognitive impairment were residue changes in both positions 74 and 100, both located in exon II domain 6 of the protein, the domain that plays a role in viral infectivity, cell surface integrin binding and NF-kappa-B transactivation of replication. Interestingly enough, both of these changes correlated with brain derived Tat.
When you look at position 100 specifically, you will notice that during the second visit, labeled R01, this change was detected. During subsequent visits in patients 37, 41, and 107, neurocognitive assessments scores were suboptimal, indicating neurocognitive impairment. For patient 56, the change was detected during the first visit, with neurocognitive impairment detected in all subsequent visits.