Analysis of HIV Evolution Bobak Seddighzadeh and Kristoffer Chin Department of Biology Loyola Marymount University Bio 398-01 February 23, 2010

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Transcript Analysis of HIV Evolution Bobak Seddighzadeh and Kristoffer Chin Department of Biology Loyola Marymount University Bio 398-01 February 23, 2010

Analysis of HIV
Evolution
Bobak Seddighzadeh
and
Kristoffer Chin
Department of Biology
Loyola Marymount University
Bio 398-01
February 23, 2010
Outline
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Background
Question
Methods
Results
Discussion
References
Function of the HIV Virus
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HIV is a retrovirus that affects immune cells, specifically T cells.
Retroviruses contain reverse transcriptase also known as RNA-dependent
DNA polymerase.
Reverse transcriptase synthesizes single stranded RNA into a c-DNA
molecule.
Since viruses cannot synthesize their own proteins, they require a host cell
to carry out its replication process.
HIV infects the host cell. It then injects its genome from its capsid and uses
reverse transcriptase to create a c-DNA template that it then incorperates
into the host cell’s DNA. The host cell transcribes and translates proteins
that assemble into more copies of the virus.
Virus can have either the lytic or lysogenic life cycle
Markham Study of HIV Virus
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Evolution is the change in the allele frequency in a population over a
period of time
More specific to HIV, the population refers to all the HIV viruses in an
affected individual, and the allele refers to each variant of the HIV env
gene.
Different individuals in the population vary in heritable traits that can be
passed onto offspring that may or may not give them a selective
advantage.
Markham et al. (1998) Study
Nucleotide sequences of the env region were used to study evolution
The viruses were classified into groups according to rate of CD4 T cell
decline: progressors and non-progressors
Progressors had increased rates of diversity and divergence in comparison
to non-progressors and ultimately higher rates of CD4 T cell decline.
We wanted to know why a disparity exists in the rate of evolution amongst
variants
Differences in Nucletide
Sequences?
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More specifically our question was: what is or are the nucleotide sequences in the
env region of the V3 domain that are responsible for the increased genetic
diversity, divergence, and rate of CD4 T cell decline amongst rapid progressors
and non-progressors
My partner and I predict that the increased rate of CD4 decline, genetic divergence
and diversity are directly related to two possible mechanism: A) HIV-1 variants
termed rapid progressors selected for a structural mechanism that does not protect
the genetic material against mutations as effectively B) or HIV-1 variants termed
rapid progressors selected for a mechanism that induces mutations on its own DNA.
We also predict that both these mechanism are related to nucleotide differences
found in the env region of the V3 domain.
Methods: Selection of Subjects, ClustalW,
ClustDist, Counting Nucleotide Differences
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Selection
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ClustalW
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Analysis and comparison of S
Analysis and comparison of Unrooted trees of subjects
ClustDist
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Subjects and visits – highest rate of CD4 T Cell decline
Clones – Largest Max distance, for more variation
Analysis of Max Distance of Nucleotide sequence
differences
Counting nucleotide differences
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Analysis of specific nucleotide differences from Non and
Rapid Progressors using Excel
Results:Non and Rapid Progressors Subjects,
Visits, and Clone Selection
Non Progressors Subject
Visit
Clones
Max Distance
2
1, 3, 4
(1,5) (4,5) (3,8)
(3) (11) (14)
12
3, 4, 5
(1,3) (1,2) (5,6)
(3) (6) (9)
13
2, 3, 5
(1,2) (3,6) (3,6)
(1) (3) (4)
Rapid Progressors Subject
Visit
Clones
Max Distance
4
2, 3, 4
(5, 13) (2,16) (1,4)
(16) (14) (15)
10
4, 5, 6
(5,8) (3,10) (4,7)
(13) (12) (20)
11
2, 3, 4
(1,6) (2,5) (6,8)
(3) (7) (7)
Results: Unrooted tree of selected Rapid Progressors
# of Clones
S
Theta
Min Distance
Max Distance
18
100
29
4
51
Results: Unrooted tree of selected Non Progressors
# of Clones
S
Theta
Min Distance
Max Distance
18
71
20
1
47
Results: Unrooted tree of selected Rapid and Non Progressors
# of Clones
S
Theta
Min Distance
Max Distance
36
142
34
1
52
Results: Samples of differences of Nucleotide
Sequence in Non and Rapid Progressors
S4V4-4
GAGGTAGTAATTA
GATCTGAAAATTT
CACGAACAATGCT
AAAATTATAATAGT
ACAGCTG
S4V4-4
AATAAATCTGTAGA
AATTAATTGTACAA
GACCCAACAACAAT
ACAATAAGAAGGAT
A---
S4V4-4
CCTATAGGACCCG
GCAGAGCATTTTAT
ACAACAGG-------CAGAATAGGCAATA
TAAGGCAA
S10V4-5
GAGGTAGTAATTA
GATCTGAAAATTT
CACGGACAATGCT
AAAACCATAATAG
TACAGCTG
S10V4-5
AATGAATCTGTAGA
AATTAATTGCACAA
GACCCAACAACAAT
ACAAGAAGAAGGAT
A---
S10V4-5
CATATGGGACCAG
GCAGAGCATTTTAT
GCAACAGGAGAAA
TAATAGGAGATATA
AGGCAA
S10V4-5
GCACATTGTAACC
TTAGTAGAACAAAA
TGGAATGACACTTT
AAAACAGGTAGTT
GACAAA
S10V4-5
TTAAGAGAACA
ATTTAG----GAATAAAACAA
TAATCTTTAAG
CAATCCTCA
S2V1-1
GAGGTAGTAATTA
GATCCGAAAATTT
CACGAACAATGCT
AAAATCATAATAGT
ACAGCTG
S2V1-1
AATGAATCTGTAGA
AATTAATTGTACAA
GACCCAACAACAAT
ACAAGAAAAAGTAT
A---
S2V1-1
CATATAGGACCAG
GTAGAGCATTTTAT
ACAACAGGAGACAT
AATAGGAGATATAA
GACAA
S2V1-1
GCATATTGTAACAT
TAGTAGAGCAGAA
TGGAATAACACTTT
AAAACAGATAGTTA
TAAAA
S2V1-1
TTGAGAGAACA
CTTTGG----GAATAAAACAA
TAGTCTTTAATC
ACTCCTCA
S13V3-3
AAGGAATCTGTAGA
AATTAATTGTACAAG
ACCTGGCAACAATA
CAAGAAGAAGTATA--
S13V3-3
AATATAGGACCAGG
TAGAGCATTTTATG
CATCAAGAGGAATA
ATAGGAGATATAAG
ACAA
S13V3-3
GAGATAGTAATTAG
ATCCGAAAATTTCA
CAAACAATGCTAAA
ATCATAATAGTACA
GCTG
S4V4-4
GCTCATTGTAACA
TTATTGAAACAAAA
TGGAATAACACTTT
AAAACTGATAGTT
GACAAA
S13V3-3
GCATATTGTAACAT
CAGTAAAGCAAAAT
GGGATAACACTTTA
GGACAGGTAGCTA
CAAAA
S4V4-4
TTAAGAGAACA
GTTTGG----GAATAAAACAA
TAATCTTTAATC
AATCCTCA
S13V3-3
TTAAGAGAACA
ATTTAG---------GAATGCTACAA
TAGTCTTTAATC
ACTCATCA
Past Studies in the Nucleotide
Sequences in HIV
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Hill and Hernandez found a certain loop in the gene
sequence in Rapid progressors that in the beginning of
infection and showed up again in the end.
They also found that lack of immunity shows diverse
forms, but there is a significant domination once there
is a fit form of the disease
Found significant diversification in the beginning of the
infection and slowly lowered.
Specific Changes in the V3 region alter phenotype that
correlated to disease progression
Past Studies in the Nucleotide
Sequences in HIV
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Usage of CCR4 is related to high sequence
conservation in contrast theCXCR4 tropic viruses that
spread sequence space over larger regions.
The location of the sequences in the space can be
used to
improve the accuracy of the prediciton of the
coreceptror usage.
Bozek found that patients with high CD4 T cell
counts had highly conservessequences in comparison
to patients that had low CD4 T cell counts.
Interpretation of Differences
found in Nucleotide Sequences
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10 nucleotide sequence difference were found in the comparison of the non
and rapid progressor subjects that were chosen
These 10 differences shows that there were some common sequences that
may be necessary to the rapid decline of T Cells that is caused by the HIV
virus
The 10 differences may not seem a lot, but the unrooted tree of both Non
and Rpaid progressors shows a strong diversity in visits 13 and 11, 12 and
11.
The other branches of the trees shows close relation among the other
visitors which can be interpreted that there is no significant changes in the
nucelotide sequences in non and rapid progressors
Markham found a lot more diversity in the rapid progressors, it is possible
that the clones that we chose was not as effective
We were more concerned with nucleotide differences, and we did not even
consider the sequence space. This may provide insight as to why there
are not significant nucleotide differences amongst progressors and
non-progressors yet they functionalally different.
Translation of Sequences
and Nucleotide Spaces
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In future studies, we believe that a
translation of the nucleotide sequences will
show light to the results we found
There may be no specific change that is
found in the nucleotide sequence, but it is
quite possible with the amino acids
Hill an Hernandez found differences in the
amino acids as finding more Basic than
acidic
Analyzing the Nucleotide spacing found in
the V3 region as analyzed by Bozek
References
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Borrego P, Marcelino JM, Rocha C, Doroana M, Antunes F, Maltez
F, Gomes P, Novo C, Barroso H, and Taveira N. The role of the
humoral immune response in the molecular evolution of the
envelope C2, V3 and C3 regions in chronically HIV-2 infected
patients. Retrovirology 2008 Sep 8; 5 78.
Hill MD and Hernandez W. Nucleotide and amino acid mutations in
human immunodeficiency virus corresponding to CD4+ decline.
Arch Virol 2006 Jun; 151(6) 1149-58.
Templeton AR, Reichert RA, Weisstein AE, Yu XF, and Markham
RB. Selection in context: patterns of natural selection in the
glycoprotein 120 region of human immunodeficiency virus 1 within
infected individuals. Genetics 2004 Aug; 167(4) 1547-61.
Bozek K, Thielen A, Sierra S, Kaiser R, and Lengauer T. V3 loop
sequence space analysis suggests different evolutionary patterns
of CCR5- and CXCR4-tropic HIV. PLoS One 2009 Oct 9; 4(10)
e7387.