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Title: Vaccines for Infectious Diseases Successes and Challenges ADG 497


1
From Genome to Vaccine Faster, Better Design of
Vaccines through Immunoinformatics
The Immunopathogenesis of Human Immunodeficiency
Virus (HIV)
Annie De Groot
EpiVax, Providence RI Brown University - TB/HIV
Research Lab
2
2nd International Immunoinformatics
Symposium March 7, 8 and 9, 2005 Boston
University, Boston, Massachusetts (co-hosted by
Charles DeLisi, BU, and Annie De Groot, Brown
University) Workshop - March 7th Symposia March
8, 9 Vaccine Satellite - Brown University
March 10
3
Warning These Slides DO NOT contain Mathematical
Formulas
4
Outline
  • Why the Excitement
  • Our Vaccine Design and Construction Tools
  • Applications (TB/HIV)
  • Peering into the Future

5
What does a vaccine do?
. . . Trains the immune system to recognize and
fight infection . . . Without requiring exposure
to the pathogen How does this happen?
6
Generating a Cell-mediated Immune Response
antigen presenting cell
MHC/HLA
epitope
T cell Receptor
t cell
7
. . . Epitopes critical information for T cells
Pathogen Virus or Bacteria
8
If a pathogen is a language...
Determination of peptides that bind to major
histocompatability (MHC) molecules (MHC ligands)
is the first step in the process of identifying T
cell epitopes. Identification of MHC ligands from
primary HIV-1 sequences is particularly relevant
for HIV vaccine development and
immunopathogenesis research. Previous methods for
prospectively identifying MHC ligand and T cell
epitopes have been shown to be relatively
imprecise. MHC ligands that Une orange sur la
table, ta robe sur le tapis, et toi dans mon lit,
doux présent du présent, fraîcheur de la nuit,
chaleur de ma vie do not fit the typical pattern
or motif for a given MHC allele have been
described, as have peptides that contain the
motif but do not bind to the MHC. Matrix-based
motifs improve on the specificity of anchor-based
motifs the advantage of matrix motifs is that
peptides can be given a score that represents the
sum of the potential for each amino acid in the
sequence to promote or inhibit binding. We
constructed matrix motifs for 30 HLA Class I
alleles from lists of peptides known to bind to a
given MHC, and from information on peptides
eluted from MHC. The matrix motifs serve as
patterns to which potential binding regions from
primary protein sequences are compared. Each
putative MHC binding region within any given
protein sequence is scored according to its fit
to the matrix motif higher EpiMatrix scores are
expected to indicate greater MHC binding
potential. Over 69,485 potential ligands for
these 158 proteins were scored and ranked. For
the 158 proteins evaluated, 85 of known ligands
would have been identified if only the top 10
scored EpiMatrix predictions for these proteins
had been synthesized and tested. The number of
correctly identified published ligands would have
increased to 95 if the top 20 peptides had been
synthesized and tested.
. . . an epitope is a word
9
Epitopes are defined by 9 AA sequence
MHC Molecule
T cell Epitopes
  • Sequence-dependent
  • Protein processing
  • HLA - Binding
  • HLA-restriction
  • Clustering
  • T cell Response

ALQDSGSEV
AVLSIVNRV
ALQDSGSEV
GIKPVVSTQL
ALQDSGSEV
AVLSIVNRV
ALQDSGSEV
GRWPVKVl
Antigen Presenting Cell
10
T cells Drive Immune Responses
Epitope processing and Presentation by APC
AVLSIVNRV
ALQDSGSEV
APC (B)
GIKPVVSTQL
Stimulates T cell Response
AVLSIVNRV
GRWPVKVl
Need T cell response To get effective AB
11
Only a small part of the entire pathogen
interacts with the host
Genome / Proteome of Pathogen
Immune system filter
Immunogenic epitopes
12
Computer-driven filtering of Genome
Genome/Proteome
Computer tools that select peptides binding to MHC
immunome
13
Proof Vaccinia
Variola
Vaccinia
Smallpox
Its the Immunome
14
Mapping the Immunome
What are some Immediate Applications of Immunome
Discovery?
immunome
15
MAPPING EPITOPES A SHORT COURSE
Interaction between amino acids lining the
pockets (p2) and peptide side chains (L,V)
determine whether peptides bind
p7
p2
16
First Epitope Mapping Tools Anchor-based Motifs
Rötchke and Falk, 1989
17
Meister GE, Roberts CGP, Berzofsky JA, Anne S. De
Groot, Two novel T cell epitope prediction
algorithms based on MHC-binding motifs
comparison of predicted and published epitopes
from Mycobacterium tuberculosis and HIV protein
sequences, Vaccine 1995, Vol. 13, No. 6, pp.
581-591. Roberts CGP, Meister GE, Jesdale BM,
Lieberman J, Berzofsky JA, Anne S. De Groot,
Prediction of HIV peptide epitopes by a novel
algorithm, AIDS Research and Human Retroviruses,
1996, Vol. 12, No. 7, pp. 593-610.
18
New Method Matrix-based Motif
19
EpiMatrix
O
U
R
A
N
G
E
E
N
1 2 3 4 5 6 7 8 9 10
UNEORANGE EBP z score (now
standardized across alleles) indication of
binding likelihood
20
EpiMer. . . EpiMatrix Epitope mapping Tool
graphical representation of A0201 motif
(based on list of actual peptides from Chicz)
A C D E F G H I K L M N P Q R S T V W Y
Papers describing approach (1) Prediction of
well-conserved HIV-1 ligands using a Matrix-based
Algorithm, EpiMatrix, Schafer et al. Vaccine,
1998, Vol. 16, pp. 1880-1884. (2) From genome to
vaccine in silico predictions, ex vivo
verification De Groot et al. Vaccine 2001, Vol.
19 pp. 43854395. (3) A.S. De Groot, H. Sbai, C.
Saint-Aubin, W. Martin, A. Bosma, G. Skowron, K.
H. Mayer Designing HIV-1 vaccines to reflect
viral diversity and the global context of
HIV/AIDS. AIDScience 1(2) June 22,2001. (4) W.
Martin, A. Bosma, H. Sbai and A.S. De Groot. The
use of bioinformatics for identifying class I
restricted T cell epitopes. Methods (Epitope
Mapping Issue). Bill Kwok, editor, Methods 29
(2003) 289298.
amino acid residue
amino acid position in peptide
Bill Jesdale TB/HIV RL.
21
Distribution of Class II Scores by Allele
True epitopes
Random peptides
22
If we can do this for humans, why not cows and
pigs?
True
True
Random
Random
BOLA A-11 Matrix
23
True
Random
24
EpiMatrixStatus in 2004
  • 30 Class I matrices
  • 74 Class II matrices
  • BOLA (prediction capability for cattle)
  • SLA (prediction capability for swine)
  • . . . 99 coverage of human populations

25
FAQs
Yes Yes Yes Yes and Yes!
  • Does it work? (ELIspot our lab/other labs)
  • Does it predict published epitopes?
  • Does it predict new epitopes?
  • Does it predict epitopes in directly from genes?
  • Do the predictions work in vitro/ in vivo?

26
New Concept Genome-Derived Epitope-driven
Vaccines
Genome or proteome sequence
EpiMatrix
Conservatrix
Immuno-informatics
MHC ligands
T cell assays
T cell epitopes
Back translation, cloning
Vaccine construct
In vitro validation
Construct Design Delivery vehicle / production
Preclinical
HLA transgenic mice
Vaccine
Phase I
27
New Concept Understanding Useful Components of
existing Vaccines?
Mtb
BCG
Conserved Peptides (??)
Conserved Epitopes (??)
28
New Concept New Uses for Old Vaccines?
WEST NILE
JEV NN
1,433
3,426
HLA A3
Conserved Peptides (944)
Conserved Epitopes (300)
29
New ConceptWill Vaccines Work in the Field?
WILD TYPE JEV
JEV Vax
Conserved Peptides (??)
Conserved Epitopes (??)
30
Concepts Using Immunome Discovery Approach to
Vaccines
  • Rapid screen of antigens believed to be special
    (secreted, transmembrane) for vaccines
  • Select critical antigens by comparison of
    (virulent to avirulent) genomes and selection of
    unique proteins (e.g. Smallpox)
  • Direct genome-to-vaccine selection of critical
    antigens by screening of genome using
    immune-competent T cells and epitopes as bait

31
Outline
  • Why the Excitement
  • Our Vaccine Design and Construction Tools
  • Applications (TB/HIV)
  • Peering into the Future

32
List of Immunome to Vaccine Tools
  • EpiMatrix (CTL / T helper)
  • ClustiMer (Promiscuous / Supertype Epitopes)
  • Conservatrix (Conserved Epitopes)
  • EpiAssembler (Immunogenic Consensus)
  • BlastiMer - Avoiding self - autoimmunity
  • Vaccine-CAD - Processing and Assembly

33
Outline
  • Why the Excitement
  • Our Vaccine Design and Construction Tools
  • Applications (TB/HIV)
  • Peering into the Future

34
The GAIA HIV Vaccine
Globally relevant, globally accessible
35
RPGNTKTVVPCKRPGNKTVPGNKTVVPIGNKTKVVPITNKTVVPITLYIQ
YGVYIVLEQAQIQQEEQA IQQEKEAMQCTRPNNTRKAMYELQKLNSWGT
KNLQARYIQYGVYIVTVWGTKNLQRTVRFQTAIEK YLKISLNKYYNLRP
RQAWCWFHSFNCGGEFTLFCASDAKSLWDQSLKPSLYNVATYLVSEFPIP
IHA RLRPGGKKKLARNCRAPPKQIIEQLIKKAIFQSSMTKTACTRPNNT
RKIDRIRERKLTEDRWNKTACH NNCYCKTVPGNKTVVPIGNKTKVVPIT
NKTVVPITLYIQYGVYIVLEQALATLITPKQLDCTHLEGKAVF IHNFKR
KLVDFRELNKPGNTKTVVPCKRPGNKTVPGNKTVVPIGNKT
YLKISLNKYYNLRPRQAWC WFHSFNCGGEFTLFCASDAKSLWDQSLKPS
LYNVATYLVSEFPIPIHAPRQAWCWFKRQAWCWFK RLRPGGKKKLARNC
RAPPKQIIEQLIKKAIFQSSMTKTACNNCYCKRLIDRIRERKLTEDRWNK
TAC YLKISLNCTRPNNTRKAWCWFHSFNCGGEFTLFCASDAKSLWDQSL
KPSLYNVATYLVSEFPIPIHA RLRPGGKKKLARNCRAPPKQIIEQLCTR
PNNTRKTKTACNNCYCKRLIDRIRERKLTEDRWNKTAC ELIFQWVQRRP
NNYAKIKHTHTDIKQGPKEPSPRTLNAWVGGKKKYRLKQIIEQLIKKKIL
YQSNPYA AIFQSSMTKPRQAWCWFHSFNCGGEFTLFCASDAKSLWDQSL
CTRPNNTRKYLVSEFPIPHATVLD YLKISLNKYYNLRPRQAWCWFHSFN
CGGEFTLFCASDAKSLWDQSLKPSLYNVATYLVSEFPIPIHA RLRPCTR
PNNTRKNRAPPKQIIEQLIKKAIFQSSMTKTACNNCYCKRLIDRIRERKL
TEDRWNKTACH NNCYCKTVPGNKTVVPIGNKTKVVPITNKTVVPITLYI
QYGVYIVLEQALATLITPKQLDCTHLEGKAVF PRQAWCWFHSFNCGGEF
TLFCASDAKSLWDQSLKPSLYNVATYLVSEFPIPIHAWTECTRPNNTRK
WFHSFNCGGEFTLFCASDACTRPNNTRKPSLYNVATYLVSEFPIPIHAPR
QAWCWFKRQAWCWFK RLRPGGKKKLARNCRAPPKQIIEQLIKKAIFQSS
MTKTACNNCYCKRLIDRIRERKLTEDRWNKTAC YLKISLNKYYNLRPRQ
AWCWFHSFNCGGEFTLFCASDAKSLWDQSLKPSLYNVATYLVSEFPIPIH
A RLRPGGKKKLARNCRAPPKQIIEQLIKKAIFQSSMTKTACNNCYCKRL
IDRIRERKLTEDRWNKTAC ELIFQWVCTRPNNTRKIKHTHTDIKQGPKE
PSPRTLNAWVGGKKKYRLKQIIEQLIKKKILYQSNPYA AIFQSSMTKPR
QAWCWFHSFNCGGEFTLFCASDAKSLWDCTRPNNTRKATYLVSEFPIPIH
ATVLD YLKISLNKYYNLRPRQAWCWFHSFNCGGEFTLFCASDAKSLWDQ
SLKPSLYNVATYLVSEFPIPIHA RLRPGGKKKLARNCRAPPKQIIEQLI
KKAIFQSSMTKTACNNCYCKRLIDRIRERKLTEDRWNKTAC NNCYCKTV
PGNKTVVPIGNKTKVVPITNKTVVPITLYIQYGVYIVLEQALATLITPKQ
LDCTHLEGKAVF IHNFKRKLVDFRELCTRPNNTRKPCKRPGNKTVPGNK
TVVPIGNKT YLKISLNKYYNLRPRQAWC WFHSFNCGGEFTLFCASDAK
SLWDQSLKPSLYNVATYLVSEFPIPIHAPRQAWCWFKRQAWCWFK RLRP
GGKKKLARNCRAPPKQIIEQLIKKAIFQSSMTKTACNNCYCKRLIDRIRE
RKLTEDRWNKTAC
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
Conservatrix Scans pathogen variants for
conserved epitopes
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
36
Step 1 Conserved or Cross-Clade Epitope
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
Conserved epitope
CTRPNNTRK
37
Step 2 EpiMatrix analysis - predicted to bind?
graphical representation of A0201 motif
(based on list of actual peptides from Chicz)
A C D E F G H I K L M N P Q R S T V W Y
amino acid residue
amino acid position in peptide
Bill Jesdale TB/HIV RL.
38

Step 3 T cell response to the epitopes?
Chromagen added, reacts with enzyme. Entire
complex seen as spot
Capture Antibody, monoclonal anti-IFN-gamma
Antigen stimulated cell, producing IFN-gamma
Biotinylated Detection Antibody, anti-IFN-gamma
Avidin bound enzyme, Alkaline Phosphatase
SPOT!
YYY
YYY
YYY
YYYYYYYYY
YYYYYYYYY
YYYYYYYYY
YYYYYYYYY
YYYYYYYYY
ELISPOT Assay Natural Epitopes
39
The importance of Validation
ELIspot T Cell Assay
40
Current GAIA Epitope Summary
  • 301 epitopes mapped
  • 288 tested (ELIspot)
  • 169 confirmed (59)
  • HLA A2, A3, A24, B7, B44 and Class II (clustered)
  • Both Supertype and Promiscuous Epitopes

41
Highly Conserved // Clade and Country
Average 45 conserved, Max 98, 62 Countries.
42
Immunogenic Consensus Epitopes
43
Putting Epitopes into a DNA (or other) Vaccine
Intended Protein Product Many epitopes strung
together in a String-of-Beads
Reverse Translation Determines the DNA sequence
necessary to code for the intended protein. This
DNA is assembled for insertion into an expression
vector.
DNA insert
Protein product (folded)
DNA Vector
44
Epitope-driven Vaccine (Sting of Beads)
45
Vaccine-CAD How to align Epitopes
46
Original Sequence
47
Reordered Sequence
48
Optimized Sequence
49
DNA Vaccine Construct Evaluation in transgenic
mice
Vaccine construct
In vitro expression
Transgenic mouse model
50
Immunization Protocol Human MHC Class II
DRB10101Transgenic Mice
3 animals per group
DAY 0 7 14 21
28 35 42 48
Injection
N3
Immunizations DNA vaccination Intramuscular
injection 100 micrograms of Vector or HIV
Constructs
Sac Mice harvest spleen. immune analysis IFN-g
ELISPOT
51
Vaccine CADMolecular construct designminimizing
junctional immunogenicity
Default Re-Ordered
52
Proof of VaccineCAD principle (WC class II set
2) Ordered / / Re-ordered
53
Constructs with and without Spacers
Comparing two multi-epitope constructs cloned
into identical recombinant vectors with and
without spacers
1 2 3
4
VS.
1 2
3 4
54
DNA Vaccine Construct HLA A2 Transgenic Mice
(AAY spacers)
55
Improving Tolerance
BlastiMer
Maximizing Self Minimalizing Non-Self
56
ProgressEpitope MappingEpitope Confirmation
Immunogenic Consenus Sequence EpitopesDNA
constructsHLA A2 Transgenic Mice
57
Outline
  • Why the Excitement
  • Our Vaccine Design and Construction Tools
  • Applications (TB/HIV)
  • Peering into the Future

58
The TIGR TB Genome CDC1551
4,000 genes x 1000 overlapping 10-mer potential
epitopes 4 million vaccine candidates
59
Three Available Genomes
H37Rv
CDC 1551
BCG
M. tuberculosis (lab strain)
M. tuberculosis (clinical isolate)
M. bovis
www.sanger.ac.uk www.tigr.org
60
Three Available Genomes
CDC 1551
BCG
H37Rv
Align and compare
61
3 Approaches to Selecting Epitopes
eekikalveictemekegkiekigpenpyntpvfaikkkdstkwrklvdf
relnkrtqdfwevqlgiphpaglkkkksvtvldvgdayfsiplhedfrky
taftipsinnetpgiryqynvlpqgwkgspaifqssmtkilepfrkqnpe
vviyqymddlyvgsdleieqhrtkieelrehllrwgfttpdkkhqkerpd
kkhqkerp
UPREGULATED
SECRETED
UNIQUE TO MTB
62
For example Upregulated epitopes
H37Rv
BCG

CDC 1551
63
TB-Genome-to-Vaccine
Whole genome
Bioinformatics tools for vaccine design
Putative T cell Epitopes
95 Reduction
T-cell epitopes are mapped directly from the TB
genome
De Groot AS, et al. Vaccine, 2001
64

T-Cell Assay Results
Many of these proteins are hypothetical,
function is unknown . . . Subjects recognized
many distinct epitopes (Apparently, we have only
scratched the surface) Implication for
understanding the immunome? Implication for
selecting proteins for vaccines?
  • GS1 Secreted Mtb Proteins
  • 11 out of the 17 peptides tested were immunogenic
  • Peptide J induced IFN-? secretion in 14 / 17
    patients
  • 65 were immunogenic
  • GS2 Upregulated Mtb proteins
  • 17 out of 17 peptides induced IFN-? release
  • 100 were immunogenic

65

A New Concept
Fishing for proteins using Epitopes as Bait
66
DNA Vaccine Construct Evaluation in transgenic
mice
HIV and TB prototype vaccines
Vaccine construct
In vitro analysis
Transgenic mouse model
Immune response to vaccine confirmed!
67
Genome-Derived Smallpox Vaccine
Vaccinia
Smallpox (variola)
immunome
vaccine
68
Genome-derived Smallpox Vaccine Variola/Vaccinia
Variola (Bangladesh strain) polyprotein (L22579)
53,000 peptides
69
Donor Response (Vaccinia Peptides)
70

Tularemia vaccine
  • Clearly a T cell mediated immune response
  • Live Vaccine Strain is only available vaccine
  • Points to -- Secreted/upregulated proteins
  • Several genomes available (Shu 4, LVS)
  • Compare genomes/identify virulence antigens
  • Use epitopes rather than whole antigens
  • Fish for antigenic proteins using Epitopes as
    Bait

71
Tularemia Vaccine Approach
Compare genomes // TM/OMP/Secr // Upregulated
EpiMatrix
Conservatrix
Immuno-informatics
MHC ligands
T cell assays (MVH)
T cell epitopes
Back translation, cloning
Vaccine construct
In vitro validation
Construct Design Delivery vehicle / production
Preclinical
HLA transgenic mice Live challenge model (Brown U)
Vaccine
Phase I
72
Proposed Animal Pathogen Genome to Vaccine
Genome or proteome sequence
EpiMatrix
Conservatrix
MHC ligands
Immuno-informatics
T cell assays (ELISPOT)
T cell epitopes
Chose Genes/ Epitopes Back translation, cloning
Vaccine construct
Construct Design Delivery vehicle / production
Preclinical
Animal model
Vaccine
Phase I
73
Outline
  • Why the Excitement
  • Our Vaccine Design and Construction Tools
  • Applications (TB/HIV)
  • Peering into the Future

74
Generating an Activated T cell
APC - T cell Epitope Danger signal
AVLSIVNRV
APC (B)
Activated T cell secretes g IF, IL-2, IL-4
Measure in ELISpot assay
75
Proteins have Different Inherent Immunogenicities
Proteins ranked by T- Epitope content per Amino
Acid
Tet Tox
Random Peptide Standard
Ig Constant Domain
76
De-immunization of Functional Therapeutics (DeFT)
  • Find hot spots
  • Identify critical amino acids
  • Suggest substitutions
  • Evaluate functional regions?

Epimatrix
  • Epitope Clusters
  • High affinity
  • binders

77
EXAMPLE BETA INTERFERON DE-IMMUNIZATION
78
Rapid Vaccine Design via Immunoinformatics
  • Products currently in development
  • Tularemia (multiepitope whole genome scan)
  • Genome Derived Smallpox Vaccine
  • HIV (cross-clade multi epitope DNA vaccine)
  • TB (genome-derived multi epitope DNA vaccine)
  • EBV (therapeutic)
  • HPV (cross-type therapeutic vaccine)

79
A new Era - Genome to Vaccine
  • Hundreds of genome sequences are available
  • (e.g. F. tularensis, Smallpox, H pylori)
  • Bioinformatics can be used to discern proteome
  • Immunome can also be uncovered . . .
  • Epitopes can be used to make vaccines
  • Epitopes can be used to determine whether
  • the genes from which theyre derived
  • Interface with the immune system . . .
  • (using epitopes to fish out antigens)

80
TB/HIV Research Lab and EpiVax 1992-2004
EpiVax Bill Martin Lee Schekter James
Rayner Ronita Fisher Deb Good Mentor Jay
Berzofsky funded by NIH / NIAID / DMID and
DAIDS
TB/HIV Research Lab Luisa Marcon Betty
Bishop Shawn Foti Judith Franco Dan Rivera Toni
Vale gone but not forgotten Gabriel E.
Meister Bill Jesdale Julie Frost Natasha
Chinai Jessica Stevens Rebecca Nerenberg Betsy
Stubblefield Hakima Sbai Julie McMurry
Students Rebecca Doctors Shirley Chan gone but
not forgotten Brian Edelson Caroline G.P.
Roberts Jessica Stevens Lieschen Quiroz Neal Muni
James Robert Schafer Natasha Chinai Tony
Breu Igor Brichkov Jean David Barnea Sarah
Johnson Kara Chew Andrew Girvin Brian Tuch
Akanksha Mehta Basim Khan Nicole Pattamanuch
THANK YOU VERY MUCH
81
Some members of the TB/HRL Team and Providence
Mayor David Cicilline
Funded by NIH/NIAID/DAIDS and GAIA Vaccine
Foundn D. Weiner, M. Klutzner (U Penn) O. Koita,
A.Tounkara, S. Dao, N. Keita (U. Bamako) J.
Beckerman, S. Tripathi (Brown U) R.
Criscitiello, M. Kone, S. Alzouma (GAIA/Mali)
82
From the mind, to the computer, to reality
. . . NASA Houston
83
The TB/HRL Team and Providence Mayor David
Cicilline
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