Oral Abstract Session 01 - Global HIV Vaccine Enterprise

POSTERS
Posters
Topic 12: Vaccine Concepts and Design
P12.63 LB
Pre-Clinical Development Of BCG.HIVA(CAT) Strain,
An Antibiotic-Free Selection Strain For HIV-TB
Pediatric Vaccine
N. Saubi 1 , E. Gea-Mallorquí 1 , A. Mbewe-Mvula 2 , C. Hurtado 1 ,
J. Gatell 1 , T. Hanke 2 , J. Joseph 1
1 AIDS Research Unit, Hospital Clinic/IDIBAPS-HIVACAT,
Barcelona, Spain; 2 The Jenner Institute, University of Oxford,
Oxford, United Kingdom (Great Britain)
Background: Our starting platform was based on a heterologous
BCG prime and MVA boost regimen delivering a common
immunogen called HIVA. In this study, we have i) developed a
BCG.HIVACAT strain containing an antibiotic free selection system
(Cobra); ii) evaluated the specific HIV-1 immune responses
induced after newborn BALB/c mice immunization with BCG.
HIVACAT prime and MVA.HIVA.85A boost; iii) evaluated the
specific-TB immune responses induced after newborn BALB/c
mice immunization with BCG.HIVACAT prime and MVA.HIVA.85A
boost and iv) evaluated the influence of age on specific HIV-1
immune responses using the same vaccination schedule.
Methods: 7-days-old newborn and 7-weeks-old adult mice
were either left unvaccinated or vaccinated subcutaneously
with 105 cfu of BCG.HIVACAT or BCGwt, and 16 weeks later were
boosted intramuscularly with 106 pfu MVA.HIVA.85A. The mice
were sacrificed 2 weeks later. The HIV-1 and TB-specific cellular
immune responses were analyzed in spleen cells by intracellular
cytokine staining and IFN-γ ELISPOT.
Results: The frequencies of TB-specific CD8 + T-cells producing
IFN-γ (P11 stimulation), and spleen cells producing IFN-γ (P11,
P15 and PPD stimulation), were higher in BCG.HIVACAT or BCGwt
primed and MVA.HIVA.85A boosted mice compared with mice
vaccinated with MVA.HIVA.85A alone (i.e. 231, 108 and 24
sfu/106 PPD stimulated splenocytes respectively). The specific
HIV-1 immune responses (P18I10 stimulation) were lower in
BCG.HIVACAT or BCGwt primed and MVA.HIVA.85A boosted mice
compared with mice vaccinated with MVA.HIVA.85A alone
(i.e. 270, 276 and 412 sfu/106 P18I10 stimulated splenocytes
respectively). When adult and newborn mice were immunized
using the same vaccination schedule, the HIV-1-specific immune
responses in adult mice were higher than in newborn mice
(0.45% vs 0.2% CD8 + T-cells producing IFN γ).
Conclusion: In conclusion we demonstrated the immunogenicity
of BCG.HIVACAT and MVA.HIVA.85A in newborn mice but
additional experiments should be performed in newborn mice
testing different routes and doses that might provide different
levels of immunogenicity.
272
AIDS Vaccine 2012
P12.64 LB
Novel Computational Methods for Predicting
Epitopes of Potent and Broadly Neutralizing HIV-1
Antibodies
M.C. Evans 1 , A. Paquet 1 , P. Phung 1 , A. Parikh 1 , C. Petropoulos 1 ,
T. Wrin 1 , M. Haddad 1
1 Monogram Biosciences, South San Francisco, CA, USA
Background: Recent efforts in HIV-1 vaccine design have focused
on immunogens that evoke potent neutralizing antibody
responses to a broad spectrum of viruses circulating worldwide.
However, the development of effective vaccines will depend
on the identification and characterization of the neutralizing
antibody epitopes. Consequently, we developed bioinformatics
methods to predict epitopes using corresponding genotypes and
phenotypes generated using a highly sensitive and reproducible
neutralization assay.
Methods: Using 264 clonal envelope (gp120) sequences from a
panel of multiclade HIV-1 viruses with matching neutralization
titers to an array of neutralizing monoclonal antibodies (b12,
PG9,16, PGT121 - 128, PGT130 - 131, PGT135 - 137, PGT141 - 145,
and PGV04), we correlated IC titers with envelope mutations,
50
and used this information to predict antibody epitopes. Structural
patches were generated as amino acid groupings based on
solvent-accessibility, diameter, atomic depth, and interaction
networks within 3D envelope models. These patches were then
evaluated as possible antibody targets by applying a boosted
algorithm comprised of machine learning and statistical models.
We identified residues with statistically significant correlation
with IC titers as sites that impact neutralization sensitivity.
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Residues frequently occurring within the significant patches
were mapped onto envelope structures as potential antibody
binding sites.
Results: Predicted epitopes were identified based on strong
correlations with neutralization response to each antibody.
Residues highly associated with the IC titers and patch clusters
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predicting neutralization response to these antibodies were
located within V1/V2, and V3. The predicted response by the
algorithm was highly concordant (>80%) with the neutralization
sensitivity of all antibodies.
Conclusion: We developed and applied computational methods
to rapidly survey protein structures and identify epitope regions
associated with neutralization response. This data mining
algorithm can help identify immunological hotspots, and provide
rapid and accurate insight into regions that are targeted by
potent and broad neutralization responses. Studies are ongoing
to confirm these novel epitopes.