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Unlocking livestock development potential through science, influence and capacity
development ILRI APM, Addis Ababa, 15-17 May 2013
Immunoinformatics & MHC-Tetramers,
Revolutionary Technologies for
Vaccine Development
This document is licensed for use under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License May 2013
Nicholas Svitek, Andreas Martin Hansen, Lucilla Steinaa, Rosemary Saya, Elias Awino, Morten Nielsen, Søren Buus, Vishvanath Nene
Introduction
East Coast fever (ECF) is a tick-borne lethal disease of cattle in eastern, central and southern Africa that is caused by the apicomplexan parasite Theileria parva . An approved vaccine
currently exists based on the infection and treatment method (ITM) whereby cattle are given a lethal dose of the parasite concomitantly with a high dose of oxytetracycline. Even
though it induces a lifelong immunity based on a strong cytotoxic CD8+ T cell (CTL) response against homologous strains, it has several drawbacks as it can induce a carrier state, it is
expensive to produce, and necessitates a liquid nitrogen cold chain to be delivered to the field. The development of a recombinant vaccine can help solve these problems.
Goals
To generate a comprehensive map of T. parva antigens and discover new antigens from the parasite that can be included in a wide-spectrum recombinant vaccine.
Methodology
Using NetMHCpan for the identification of new antigens and CTL epitopes from T. parva and utilization of Bovine Leucocyte Antigen (MHC) class I tetramers to confirm the identity
of the new CTL epitopes and evaluate the CTL immune response towards these T. parva antigens in cattle.
Results
Bovine MHC-tetramers were successfully generated and were efficient in binding to T. parva specific CTL. Bovine MHC-tetramers are sufficiently sensitive to measure immune
response from Tp1+-CTL directly isolated from infected/vaccinated cattle. Moreover, the MHC-tetramer & NetMHCpan technologies allowed identification of the precise and correct
CTL epitope sequence from a known T. parva antigen (Tp2).
Conclusion
Immunoinformatics and MHC-tetramers are precise and sensitive technologies that can lead to identification of new antigens and CTL epitopes from T. parva or any other infectious
diseases of cattle where CTL play a role.
Partners Funding
University of Vermont, USDA-ARS, University of Copenhagen, Danish Technical University BREAD Program of the NSF (USA) and the Bill & Melinda Gates Foundation
Animal 1
day 8 p.i.
Animal 1
day 16 p.i.
Animal 2
day 8 p.i.
Animal 2
day 17 p.i.
CD8+
Antigen Known CTL epitope BoLA allele FP1 Alternative epitope FP2
Tp2 27SHEELKKLGML37 N*04101 0.133 29EELKKLGML37 0.009
CD8+
Tetramer +
Control Tp227-37
CTL
http://flow.csc.mrc.ac.uk/?page_id=852
CD8+
CD8+/Tp1+
Antigen-specific
CD8+ T Cell
TCR
biotin
Infected Lymphocyte
T. parva protein
T. parva peptide presented
by MHC class I molecule
T CD8+
= CTL
(killing)
Graham SP, et al., PNAS, 2006 & Graham SP, et al., Infect Immun., 2008
A) Mechanism of Immunity during
ITM Vaccination
B) List of Known T. parva Antigens
& CTL Peptide-Epitopes Identified by
Conventional Methods
A) MHC-Tetramers Mimic Natural
“MHC-CD8+ Killer Cell Interaction”
B) Identification of MHC-Tetramer Positive CD8+ Killer Cells
with the Flow Cytometer
C) Identification with Tetramer of Tp1+ CTL from ITM-Vaccinated Cattle
A) Prediction with NetMHCpan of an Alternative
CTL Epitope from the Tp2 Antigen
Tp1+
Tp1+
CD8+
Immunoinformatics
Computer algorithms
trained on biological data
(NetMHCpan)
Tp229-37
C) Immunoinformatics to Speed Up the Identification of
Antigens & CTL Peptide-Epitopes
Figure 1 Paradigm of Cellular Immunity to Theileria parva
Figure 2 MHC class I Tetramers to Identify T. parva CTL Peptide-Epitope Positive Cells
Figure 3 MHC Class I Tetramers & Immunoinformatics to Identify the Correct CTL Peptide-Epitope Sequence
anti-CD8
Tp1-tetramer
Killing
T. parva genome
C) Confirmation of the Alternative Epitope by the
Use of MHC-Tetramers.
Prediction of parasite peptides
that binds to
bovine MHC class I molecules
Antigen CTL epitope BoLA allele FP
Tp1 214VGYPKVKEEML224 N*01301 0.070
Tp2 27SHEELKKLGML37 N*04101 0.133
Tp2 49KSSHGMGKVGK59 N*01201 0.017
Tp2 96FAQSLVCVL104 BoLA-T2c 0.036
Tp2 98QSLVCVLMK106 N*01201 0.036
Tp4 328TGASIQTTL336 N*00101 0.086
Tp5 87SKADVIAKY95 BoLA-T5 0.017
Tp7 206EFISFPISL214 BoLA-T7 0.058
Tp8 379CGAELNHFL387 N*00101 0.168
Tp9 199AKFPGMKKSK208 N*02301 0.113
FP: the false-positive fraction score for NetMHCpan
trained with BoLA peptide binding data (the fraction of
peptides with a predicted binding affinity stronger than
the predicted affinity of the know CTL epitope). A FP
value closer to 0 shows stronger binding affinity.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
40,000 nM 8,000 nM 1,600 nM 320 nM 64 nM 12.8 nM 2.56 nM 0.512 nM 0.102 nM no peptide
Tp2.29-37 (Alt)
Tp2.27-37
O.D.(@450nm)
[Peptide]
B) Confirmation of the Higher Binding Affinity by the
Alternative Tp2 CTL Peptide-Epitope
Antigen CTL epitope BoLA (MHC) class I
Tp1 214VGYPKVKEEML224 N*01301
Tp2 27SHEELKKLGML37 N*04101 (T2b)
Tp2 49KSSHGMGKVGK59 N*01201 (T2a)
Tp2 96FAQSLVCVL104 BoLA-T2c
Tp2 98QSLVCVLMK106 N*01201 (T2a)
Tp4 328TGASIQTTL336 N*00101
Tp5 87SKADVIAKY95 BoLA-T5
Tp7 206EFISFPISL214 BoLA-T7
Tp8 379CGAELNHFL387 N*00101
Tp9 199AKFPGMKKSK208 N*02301
T. parva infects bovine lymphocytes. MHC class I molecules binds to
and presents specific T. parva CTL peptide-epitopes to cytotoxic T
lymphocytes (CTL). If the CTL is specific for that epitope, it will kill the
infected cell.
Initially, ELISpot and in vitro cytotoxicity assays lead to the discovery
of these T. parva CTL peptide-epitopes presented by these specific
MHC class I molecules.
Since using ELISpot and cytotoxicity assays are arduous, time consuming and expensive for initial screening of
novel antigens and CTL epitopes, the recourse to immunoinformatics like NetMHCpan predicting peptide
binding to MHC class I molecules can speed up the identification of CTL peptide-epitopes. This can lead to a
narrower list of T. parva peptides that can be potential CTL epitopes to test in ELISpot and cytotoxicity assays.
To evaluate the NetMHCpan technology, the known T. parva CTL peptide-epitopes were evaluated in the
system and for most of them, they were predicted as binders to their respective MHC class I molecules.
The MHC class I tetramer is a technology that can be used to identify CTL that are specific for a particular T. parva peptide-epitope. It is based on uniting together
4 recombinant MHC class I molecules that are bound to a specific T. parva CTL peptide-epitope and to a fluorochrome of which the fluorescence can be measured
by flow cytometry upon excitation with a laser.
The MHC class I tetramer was generated with the Tp1 T. parva CTL peptide-epitope and the BoLA-
N*01301 MHC class I molecule bound to PE (the fluorochrome). The Tp1+-specific CTL can be
identified in vaccinated animals at around day 16 post-inoculation with the parasite.
Analysing known T. parva antigens with NetMHCpan lead to the identification of an
alternative, shorter, CTL peptide-epitope from the Tp2 antigen with predicted stronger
binding affinity to the MHC class I molecule than the one previously identified by
conventional methods.
FP1: the false-positive fraction score using NetMHCpan for the known Tp2 CTL peptide-epitope.
FP2: the false-positive fraction score using NetMHCpan for the alternative Tp2 CTL peptide-
epitope. A FP value closer to 0 shows stronger binding affinity.
Evaluating peptide binding to the MHC class I molecule revealed that the predicted
alternative epitope from the Tp2 antigen is the correct epitope since the initially
discovered Tp2 peptide-epitope did not show any binding to the molecule.
Using the MHC class I tetramer technology with the known and the alternative CTL
peptide-epitopes from the Tp2 antigen, and a cell line specific for the Tp2 CTL peptide-
epitopes demonstrated that the sequence recognized by the bovine CTL is precisely the
alternative Tp2 CTL peptide-epitope; confirming again the correct prediction by
NetMHCpan.
TCR = T Cell Receptor,
which will recognize
epitope by binding
to the peptide-MHC
class I complex
CD8+ CTL
specific for Tp1
CD8+ CTL

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Immunoinformatics and MHC-Tetramers, revolutionary technologies for vaccine development

  • 1. Unlocking livestock development potential through science, influence and capacity development ILRI APM, Addis Ababa, 15-17 May 2013 Immunoinformatics & MHC-Tetramers, Revolutionary Technologies for Vaccine Development This document is licensed for use under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License May 2013 Nicholas Svitek, Andreas Martin Hansen, Lucilla Steinaa, Rosemary Saya, Elias Awino, Morten Nielsen, Søren Buus, Vishvanath Nene Introduction East Coast fever (ECF) is a tick-borne lethal disease of cattle in eastern, central and southern Africa that is caused by the apicomplexan parasite Theileria parva . An approved vaccine currently exists based on the infection and treatment method (ITM) whereby cattle are given a lethal dose of the parasite concomitantly with a high dose of oxytetracycline. Even though it induces a lifelong immunity based on a strong cytotoxic CD8+ T cell (CTL) response against homologous strains, it has several drawbacks as it can induce a carrier state, it is expensive to produce, and necessitates a liquid nitrogen cold chain to be delivered to the field. The development of a recombinant vaccine can help solve these problems. Goals To generate a comprehensive map of T. parva antigens and discover new antigens from the parasite that can be included in a wide-spectrum recombinant vaccine. Methodology Using NetMHCpan for the identification of new antigens and CTL epitopes from T. parva and utilization of Bovine Leucocyte Antigen (MHC) class I tetramers to confirm the identity of the new CTL epitopes and evaluate the CTL immune response towards these T. parva antigens in cattle. Results Bovine MHC-tetramers were successfully generated and were efficient in binding to T. parva specific CTL. Bovine MHC-tetramers are sufficiently sensitive to measure immune response from Tp1+-CTL directly isolated from infected/vaccinated cattle. Moreover, the MHC-tetramer & NetMHCpan technologies allowed identification of the precise and correct CTL epitope sequence from a known T. parva antigen (Tp2). Conclusion Immunoinformatics and MHC-tetramers are precise and sensitive technologies that can lead to identification of new antigens and CTL epitopes from T. parva or any other infectious diseases of cattle where CTL play a role. Partners Funding University of Vermont, USDA-ARS, University of Copenhagen, Danish Technical University BREAD Program of the NSF (USA) and the Bill & Melinda Gates Foundation Animal 1 day 8 p.i. Animal 1 day 16 p.i. Animal 2 day 8 p.i. Animal 2 day 17 p.i. CD8+ Antigen Known CTL epitope BoLA allele FP1 Alternative epitope FP2 Tp2 27SHEELKKLGML37 N*04101 0.133 29EELKKLGML37 0.009 CD8+ Tetramer + Control Tp227-37 CTL http://flow.csc.mrc.ac.uk/?page_id=852 CD8+ CD8+/Tp1+ Antigen-specific CD8+ T Cell TCR biotin Infected Lymphocyte T. parva protein T. parva peptide presented by MHC class I molecule T CD8+ = CTL (killing) Graham SP, et al., PNAS, 2006 & Graham SP, et al., Infect Immun., 2008 A) Mechanism of Immunity during ITM Vaccination B) List of Known T. parva Antigens & CTL Peptide-Epitopes Identified by Conventional Methods A) MHC-Tetramers Mimic Natural “MHC-CD8+ Killer Cell Interaction” B) Identification of MHC-Tetramer Positive CD8+ Killer Cells with the Flow Cytometer C) Identification with Tetramer of Tp1+ CTL from ITM-Vaccinated Cattle A) Prediction with NetMHCpan of an Alternative CTL Epitope from the Tp2 Antigen Tp1+ Tp1+ CD8+ Immunoinformatics Computer algorithms trained on biological data (NetMHCpan) Tp229-37 C) Immunoinformatics to Speed Up the Identification of Antigens & CTL Peptide-Epitopes Figure 1 Paradigm of Cellular Immunity to Theileria parva Figure 2 MHC class I Tetramers to Identify T. parva CTL Peptide-Epitope Positive Cells Figure 3 MHC Class I Tetramers & Immunoinformatics to Identify the Correct CTL Peptide-Epitope Sequence anti-CD8 Tp1-tetramer Killing T. parva genome C) Confirmation of the Alternative Epitope by the Use of MHC-Tetramers. Prediction of parasite peptides that binds to bovine MHC class I molecules Antigen CTL epitope BoLA allele FP Tp1 214VGYPKVKEEML224 N*01301 0.070 Tp2 27SHEELKKLGML37 N*04101 0.133 Tp2 49KSSHGMGKVGK59 N*01201 0.017 Tp2 96FAQSLVCVL104 BoLA-T2c 0.036 Tp2 98QSLVCVLMK106 N*01201 0.036 Tp4 328TGASIQTTL336 N*00101 0.086 Tp5 87SKADVIAKY95 BoLA-T5 0.017 Tp7 206EFISFPISL214 BoLA-T7 0.058 Tp8 379CGAELNHFL387 N*00101 0.168 Tp9 199AKFPGMKKSK208 N*02301 0.113 FP: the false-positive fraction score for NetMHCpan trained with BoLA peptide binding data (the fraction of peptides with a predicted binding affinity stronger than the predicted affinity of the know CTL epitope). A FP value closer to 0 shows stronger binding affinity. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 40,000 nM 8,000 nM 1,600 nM 320 nM 64 nM 12.8 nM 2.56 nM 0.512 nM 0.102 nM no peptide Tp2.29-37 (Alt) Tp2.27-37 O.D.(@450nm) [Peptide] B) Confirmation of the Higher Binding Affinity by the Alternative Tp2 CTL Peptide-Epitope Antigen CTL epitope BoLA (MHC) class I Tp1 214VGYPKVKEEML224 N*01301 Tp2 27SHEELKKLGML37 N*04101 (T2b) Tp2 49KSSHGMGKVGK59 N*01201 (T2a) Tp2 96FAQSLVCVL104 BoLA-T2c Tp2 98QSLVCVLMK106 N*01201 (T2a) Tp4 328TGASIQTTL336 N*00101 Tp5 87SKADVIAKY95 BoLA-T5 Tp7 206EFISFPISL214 BoLA-T7 Tp8 379CGAELNHFL387 N*00101 Tp9 199AKFPGMKKSK208 N*02301 T. parva infects bovine lymphocytes. MHC class I molecules binds to and presents specific T. parva CTL peptide-epitopes to cytotoxic T lymphocytes (CTL). If the CTL is specific for that epitope, it will kill the infected cell. Initially, ELISpot and in vitro cytotoxicity assays lead to the discovery of these T. parva CTL peptide-epitopes presented by these specific MHC class I molecules. Since using ELISpot and cytotoxicity assays are arduous, time consuming and expensive for initial screening of novel antigens and CTL epitopes, the recourse to immunoinformatics like NetMHCpan predicting peptide binding to MHC class I molecules can speed up the identification of CTL peptide-epitopes. This can lead to a narrower list of T. parva peptides that can be potential CTL epitopes to test in ELISpot and cytotoxicity assays. To evaluate the NetMHCpan technology, the known T. parva CTL peptide-epitopes were evaluated in the system and for most of them, they were predicted as binders to their respective MHC class I molecules. The MHC class I tetramer is a technology that can be used to identify CTL that are specific for a particular T. parva peptide-epitope. It is based on uniting together 4 recombinant MHC class I molecules that are bound to a specific T. parva CTL peptide-epitope and to a fluorochrome of which the fluorescence can be measured by flow cytometry upon excitation with a laser. The MHC class I tetramer was generated with the Tp1 T. parva CTL peptide-epitope and the BoLA- N*01301 MHC class I molecule bound to PE (the fluorochrome). The Tp1+-specific CTL can be identified in vaccinated animals at around day 16 post-inoculation with the parasite. Analysing known T. parva antigens with NetMHCpan lead to the identification of an alternative, shorter, CTL peptide-epitope from the Tp2 antigen with predicted stronger binding affinity to the MHC class I molecule than the one previously identified by conventional methods. FP1: the false-positive fraction score using NetMHCpan for the known Tp2 CTL peptide-epitope. FP2: the false-positive fraction score using NetMHCpan for the alternative Tp2 CTL peptide- epitope. A FP value closer to 0 shows stronger binding affinity. Evaluating peptide binding to the MHC class I molecule revealed that the predicted alternative epitope from the Tp2 antigen is the correct epitope since the initially discovered Tp2 peptide-epitope did not show any binding to the molecule. Using the MHC class I tetramer technology with the known and the alternative CTL peptide-epitopes from the Tp2 antigen, and a cell line specific for the Tp2 CTL peptide- epitopes demonstrated that the sequence recognized by the bovine CTL is precisely the alternative Tp2 CTL peptide-epitope; confirming again the correct prediction by NetMHCpan. TCR = T Cell Receptor, which will recognize epitope by binding to the peptide-MHC class I complex CD8+ CTL specific for Tp1 CD8+ CTL