hiv-1 evolution in response to immune selection pressures bisc 441 guest lecture
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HIV-1 evolution in response to immune selection pressures BISC 441 guest lecture Zabrina Brumme, Ph.D. Assistant Professor, Faculty of Health Sciences Simon Fraser University. http://www3.niaid.nih.gov/topics/HIVAIDS/Understanding/Biology/structure.htm. On an individual level…. - PowerPoint PPT PresentationTRANSCRIPT
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HIV-1 evolution in response to immune selection pressures
BISC 441 guest lecture
Zabrina Brumme, Ph.D.
Assistant Professor, Faculty of Health Sciences
Simon Fraser University
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http://www3.niaid.nih.gov/topics/HIVAIDS/Understanding/Biology/structure.htm
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On an individual level….
Time since infection
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HIV evolution in a single individual: 12 year period
eg:: Shankarappa et al, J Virol 1999
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BD Walker, BT Korber, Nat Immunol 2001
On a global level…
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HIV subtypes are differentially distributed throughout the world
http://www.hiv.lanl.gov
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1. High mutation rate
HIV reverse transcriptase makes 1 error per replication cycle
Recombination
Host factors: APOBEC 3G
2. High replication rate
~up to 1010 virions/day in untreated infection
3. Lifelong infection
4. High numbers of infected individuals worldwide
5. Multitude of selection pressures:
- antiretroviral drugs
- immune selection pressures
Why does HIV evolution and diversification occur so rapidly?
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My research program combines molecular biology and computational approaches to:
Study HIV-1 evolution in response to selection pressures imposed by cellular immune responses* (“immune escape”)
Use this information to identify characteristics of effective anti-HIV immune responses and other information that may be
useful to vaccine design
*humoral (antibody) responses are important too!
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HLA class I alleles present HIV-derived peptide epitopes on the infected cell surface, thus alerting CTL to the presence of infection
CTL
HLA
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HLA class I alleles act as a selective force shaping HIV evolution through the selection of immune escape mutations
“CTL Escape Mutant”
CTL
CTL
HLA
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HLA genetic diversity protects us against diverse infectious diseases
CBA
Population:
HLA-A = 1757 alleles*
HLA-B = 2338 alleles*
HLA-C = 1304 alleles*
*as of January 2012. http://hla.alleles.org/nomenclature/stats.html
Individual:
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HIV adapts to the HLA class I alleles of each host it passes through
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Moore et al Science 2002; Bhattacharya et al Science 2007, Brumme et al PLoS Pathogens 2007; Rousseau et al J Virol 2008; Kawashima et al Nature 2009
Immune escape pathways are broadly predictable based on host HLA
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Mapping sites of immune escape across the HIV-1 genome:
…first, a brief primer on techniques and challenges…
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Identifying patterns of host-
mediated evolution in HIV
Brumme laboratory
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Identifying patterns of host-
mediated evolution in HIV
Assemble large cohort of HIV-infected individuals
Brumme laboratory
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Identifying patterns of host-
mediated evolution in HIV
Assemble large cohort of HIV-infected individuals
Undertake host (HLA class I) and HIV genotyping
Brumme laboratory
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Identifying patterns of host-
mediated evolution in HIV
Assemble large cohort of HIV-infected individuals
Undertake host (HLA class I) and HIV genotyping
Apply statistical methods to identify patterns of HIV adaptation
Brumme laboratory
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Identifying patterns of host-
mediated evolution in HIV
Assemble large cohort of HIV-infected individuals
Undertake host (HLA class I) and HIV genotyping
Apply statistical methods to identify patterns of HIV adaptation
*
*
*Note: these steps are
harder and more complicated than they
appear
*Brumme laboratory
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00 44
44 00not B*57not B*57
B*57B*57
NNTT
p = 0.03 p = 0.03
Pt1: ..TSNLQEQIGW.. B*57+Pt2: ..TSTLQEQIGW.. B*57-Pt3: ..TSNLQEQIGW.. B*57+Pt4: ..TSTLQEQIGW.. B*57-Pt5: ..TSTLQEQIGW.. B*57-Pt6: ..TSNLQEQIAW.. B*57+Pt7: ..TSTLQEQITW.. B*57-Pt8: ..TSNLQEQIGW.. B*57+
B*57
TW10 epitope
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HIV-1 Gag:
Immune escape map
Susceptible
Adapted
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Are escape mutations in HIV-1 accumulating at the population level?
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Transmission and reversion of escape mutations
non-B*57 B*57
selection
non-B*57
reversion
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Failure to revert leads to accumulation of escape variant at the population level
non-B*51 B*51
non-B*51
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Example: escape in B*51-TI8 epitope
B*51-associated I135X mutation
HIV Reverse Transcriptase
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% HLA-B*51 Prevalence
75
50
25
0 10 20
R=0.91p=0.0006
% I
135X
in B
*51-
Kumamoto
London
Vancouver
Perth
Oxford
Barbados
LusakaDurban
Gaberone
Increased prevalence of I135X in populations with high B*51 prevalence
Kawashima et al, Nature 2009
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Is it possible that HIV-1 is acting as a selective pressure on humans??
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Vertical transmission of HIV (and genetic inheritance of HLA)
non-B*57B*57
50% chance B*57
Mothers with protective HLA alleles less likely to
transmit HIV to childnon-B*57B*57
If B*57 improved survival
HIV-infected children who inherit protective alleles have improved chances of survival
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Summary and Conclusions
- Strong evidence of HLA-associated immune selection on HIV
- HIV Immune escape pathways are broadly predictable based on host HLA
- Characterization of sites, pathways, kinetics of immune escape mutations will help identify regions for inclusion in vaccine design
- Information on common escape pathways can be incorporated into immunogen design to block “preferred” mutational escape pathways
- Evidence for accumulation of escape mutations in contemporary HIV-1 sequences
- Potential for HIV-1 selection on humans??