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Immunological Bioinformatics Ole Lund Center for Biological Sequence Analysis BioCentrum-DTU Technical University of Denmark [email protected]

Transcript of Title goes here - CBS · Hantaan virus (Korean hemorrhagic fever virus) X Rift Valley Fever X...

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Immunological Bioinformatics

Ole LundCenter for Biological Sequence Analysis

BioCentrum-DTUTechnical University of Denmark

[email protected]

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Challenges and failures of the immune system

Outside

Infection with microbe A

Infection with microbe B

Allergen -> allergy

Peptide drugs

Time

Creation of self

Creation of an immune system/

Tolerance to self

Autoimmunity

(break of tolerance to self)

Cancer

Inside

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Basic concepts

•Immue: Free form disease (from greek)

Antigen: Something that can generate a response by the immune system

Immune system: Something that reacts to an antigen

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Clonal selection theory

Figure from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Search&db=books&doptcmdl=GenBookHL&term=clonal+selection+AND+imm%5Bbook%5D+AND+125019%5Buid%5D&rid=imm.figgrp.59

•Antigen: Something that can generate an immune response

Immune system: Something that reacts to an antigen

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Memory

Figure from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Search&db=books&doptcmdl=GenBookHL&term=typical+antibody+response+AND+imm%5Bbook%5D+AND+125025%5Buid%5D&rid=imm.figgrp.70

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Eradication of smallpox

Figure from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Search&db=books&doptcmdl=GenBookHL&term=eradication+of+smallpox+AND+imm%5Bbook%5D+AND+125001%5Buid%5D&rid=imm.figgrp.37

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How does the immune system “see” a virus?

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Immune system overview•Innate – fast, unspecific

•Addaptive – specific, remembers…

•Cellular

•Cytotoxic T lymphocytes (CTL)

•Helper T lymphocytes (HTL)

•Humoral

•B lymphocytes

Figures by Eric A.J. Reits

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MHC Class I pathway

1:5

1:200 1:2

Response to 1:(5x20x200) = 1:2000 9mers

Figure by Eric A.J. Reits

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Use of bioinformatics

Lauemøller et al., 2000

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Figure by Thomas Blicher

Peptide

T Cell receptor (TCR)

MHC

β2mCD8

Antigen Presenting cell

Cytotoxic T Lymphocyte

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Figure by Anne Mølgaard, peptide (KVDDTFYYV) used as vaccine by Snyder et al. J Virol 78, 7052-60 (2004).

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Influenza A virus (A/Goose/Guangdong/1/96(H5N1))

>polymerase

MERIKELRDLMSQSRTREILTKTTVDHMAIIKKYTSGRQEKNPALRMKWMMAMKYPITAD

KRIMEMIPERNEQGQTLWSKTNDAGSDRVMVSPLAVTWWNRNGPTTSTVHYPKVYKTYFE

KVERLKHGTFGPVHFRNQVKIRRRVDINPGHADLSAKEAQDVIMEVVFPNEVGARILTSE

SQLTITKEKKEELQDCKIAPLMVAYMLERELVRKTRFLPVAGGTSSVYIEVLHLTQGTCW

EQMYTPGGEVRNDDVDQSLIIAARNIVRRATVSADPLASLLEMCHSTQIGGIRMVDILRQ

NPTEEQAVDICKAAMGLRISSSFSFGGFTFKRTNGSSVKKEEEVLTGNLQTLKIKVHEGY

EEFTMVGRRATAILRKATRRLIQLIVSGRDEQSIAEAIIVAMVFSQEDCMIKAVRGDLNF

...

and 9 other proteins

MERIKELRD

ERIKELRDL

RIKELRDLM

IKELRDLMS

KELRDLMSQ

ELRDLMSQS

LRDLMSQSR

RDLMSQSRT

DLMSQSRTR

LMSQSRTRE

and 4376 other 9mers

Proteins 9mer peptides

>Segment 1

agcaaaagcaggtcaattatattcaatatggaaagaataaaagaactaagagatctaatg

tcgcagtcccgcactcgcgagatactaacaaaaaccactgtggatcatatggccataatc

aagaaatacacatcaggaagacaagagaagaaccctgctctcagaatgaaatggatgatg

gcaatgaaatatccaatcacagcagacaagagaataatggagatgattcctgaaaggaat

and 13350 other nucleotides on 8 segments

Genome

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Weight matrices (Hidden Markov models)

YMNGTMSQVGILGFVFTLALWGFFPVVILKEPVHGVILGFVFTLTLLFGYPVYVGLSPTVWLSWLSLLVPFVFLPSDFFPSCVGGLLTMVFIAGNSAYE

A2 Logo

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A

FC

G

Lauemøller et al., 2000

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Human Leukocyte antigen (HLA=MHC in humans) polymorphism - alleles

http://www.anthonynolan.com/HIG/index.html

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HLA polymorphism - supertypes

•Each HLA molecule within a supertypeessentially binds the same peptides•Nine major HLA class I supertypes have been defined

•HLA-A1, A2, A3, A24,B7, B27, B44, B58, B62

Sette et al, Immunogenetics (1999) 50:201-212

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HLA polymorphism - frequencies

Supertypes Phenotype frequenciesCaucasian Black Japanese Chinese Hispanic Average

A2,A3, B7 83 % 86 % 88 % 88 % 86 % 86%

+A1, A24, B44 100 % 98 % 100 % 100 % 99 % 99 %

+B27, B58, B62 100 % 100 % 100 % 100 % 100 % 100 %

A Sette et al, Immunogenetics (1999) 50:201-212

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O Lund et al., Immunogenetics. 2004 55:797-810

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O Lund et al., Immunogenetics. 2004 55:797-810

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O Lund et al., Immunogenetics. 2004 55:797-810

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O Lund et al., Immunogenetics. 2004 55:797-810

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O Lund et al., Immunogenetics. 2004 55:797-810

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Combined method

•Combining predicted MHC-I affinity with prediction of C-terminal proteasomal cleavage and TAP transport efficiency improves the ability to identify known CTL epitopes

MV Larsen et al., Accepted for publication in European Journal of Immunology

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Infectious Diseases

•More than 400 microbial agents are associated with disease in healthy adult humans

•There are only licensed vaccines in the United states for 22 microbial agents (vaccines for 34 pathogens have been developed)

•Immunological Bioinformatics may be used to

•Identify immunogenic regions in pathogen

•These regions may be used as in rational vaccine design

•Which pathogens to focus on? Infectious diseases may be ranked based on

•Impact on health

•Dangerousness

•Economic impact

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Infectious Diseases in the World

•11 million (19%) of the 57 million people who died in the world in 2002 were killed by infectious or parasitic infection [WHO, 2004]

•The three main single infectious diseases are HIV/AIDS, tuberculosis, and malaria, each of which causes more than 1 million deaths

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Deaths from infectious diseases in the world in 2002

www.who.int/entity/whr/2004/annex/topic/en/annex_2_en.pdf

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DodoPathogenic Viruses

Data derived from /www.cbs.dtu.dk/databases/Dodo.

1st column: log10 of the number of deaths caused by the pathogen per year

2nd column: DNA Advisory Committee (RAC) classificationDNA Advisory Committee guidelines [RAC, 2002] which includes those biological agents known to infect humans, as well as selected animal agents that may pose theoretical risks if inoculated into humans. RAC divides pathogens intofour classes.Risk group 1 (RG1). Agents that are not associated with disease in healthy adult humansRisk group 2 (RG2). Agents that are associated with human disease which is rarely serious and for which preventive or therapeutic interventions are often availableRisk group 3 (RG3). Agents that are associated with serious or lethal human disease for which preventive or therapeutic interventions may be available (high individual risk but low community risk)Risk group 4 (RG4). Agents that are likely to cause serious or lethal human disease for which preventive or therapeutic interventions are not usually available (high individual risk and high community risk)

3rd column: CDC/NIAID bioterror classificationclassification of the pathogens according to the Centers for Disease Control and Prevention (CDC) bioterror categories A–C, where category A pathogens are considered the worst bioterror threats

4th column: Vaccines availableA letter indicating the type of vaccine if one is available (A: acellular/adsorbet; C: conjugate; I: inactivated; L: live; P: polysaccharide; R: recombinant; S staphage lysate; T: toxoid). Lower case indicates that the vaccine is released as an investigational new drug (IND)).

5th column: G: Complete genome is sequenced

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BiodefenceTargets

www2.niaid.nih.gov/Biodefense/bandc_priority.htm

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NIH projectPathogen HLA binding ElispotInfluenza X XVariola major (smallpox) vaccine strain X XYersinia pestis XFrancisella tularensis (tularemia) X CBS/panumLCM XLassa Fever XHantaan virus (Korean hemorrhagic fever virus) XRift Valley Fever XDengue XEbola XMarburg XMulti-drug resistant TB (BCG vaccine) X XYellow fever XTyphus fever (Rickettsia prowazekii) XWest Nile Virus X

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Strategy for determination of peptide-HLA binding

DevelopmentDevelopment

ββ22mmHeavy chainHeavy chain

peptidepeptide IncubationIncubationPeptidePeptide--MHC MHC complexcomplex

Step I: Folding of MHC class I molecules in solution

Step II: Detection of Step II: Detection of de novode novo folded MHC class I molecules by ELISAfolded MHC class I molecules by ELISA

C Sylvester-Hvid et al., Tissue Antigens. 2002 59:251-8

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ELISPOT assay

•Measure number of white blood cells that in vitro produce interferon-γ in response to a peptide

•A positive result means that the immune system have earlier reacted to the peptide (during a response ot a vaccine/natural infection)

SLFNTVATL

SLFNTVATL

SLFNTVATL

SLFNTVATL SLFNTVATLSLFNTVATL

Two spots

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Preliminary results

•167 peptides have so far been tested for binding to a HLA molecule

•113 of these (67%) have been shown to bind to the relevant HLA allele with a affinity better than 500nM

•180 predicted epitopes from influenza A virus were tested in an ELISPOT assay

•12 were so far found to be epitopes (recognized by donors previously exposed to Influenza)

•14% of peptides binding with an affinity better than 500nM were found to be epitopes

•1:2000 randomly chosen peptides are epitopes

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Vaccination

•Vaccination

•Administration of a substance to a person with the purpose of preventing a disease

•Traditionally composed of a killed or weakened microorganism

•Vaccination works by creating a type of immune response that enables the memory cells to later respond to a similar organism before it can cause disease

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Early History of Vaccination•Pioneered India and China in the 17th century

•The tradition of vaccination may have originated in India in AD 1000

•Powdered scabs from people infected with smallpox was used to protect against the disease

•Smallpox was responsible for 8 to 20% of all deaths in several European countries in the 18th century

•In 1721 Lady Mary Wortley Montagu brought the knowledge of these techniques from Constantinople (now Istanbul) to England

•Two to three percent of the smallpox vaccinees, however, died from the vaccination itself

•Benjamin Jesty and, later, Edward Jenner could show that vaccination with the less dangerous cowpox could protect against infection with smallpox

•The word vaccination, which is derived from vacca, the Latin word for cow.

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Successful vaccination campaigns

Figure from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Search&db=books&doptcmdl=GenBookHL&term=sucessfull+vaccines+AND+imm%5Bbook%5D+AND+125049%5Buid%5D&rid=imm.figgrp.93

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Vaccination Today•Vaccines have been made for only 34 of the more than 400 known pathogens that are harmful to man.

•Immunization saves the lives of 3 million children each year, but that 2 million more lives could be saved if existing vaccines were applied on a full-scale worldwide

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Human Vaccines against pathogens

Immunological Bioinformatics, The MIT press.

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Categories of Vaccines•Live vaccines

•Are able to replicate in the host

•Attenuated (weakened) so they do not cause disease

•Subunit vaccines

•Part of organism

•Genetic Vaccines

•Part of genes from organism

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Polytope construction

Linker

MNH2 COOH

Epitope C-terminal cleavage

Cleavage within epitopesNew epitopes

cleavage

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Helper responses

Figures by Eric A.J. Reits

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Figure by Anne Mølgaard

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MHC class II prediction

RFFGGDRGAPKRGYLDPLIRGLLARPAKLQVKPGQPPRLLIYDASNRATGIPAGSLFVYNITTNKYKAFLDKQSALLSSDITASVNCAKPKYVHQNTLKLATGFKGEQGPKGEPDVFKELKVHHANENISRYWAIRTRSGGITYSTNEIDLQLSQEDGQTIE

Complexity of problem– Peptides of different

length– Weak motif signal

Alignment crucialGibbs Monte Carlo

sampler

M Nielsen et al., Bioinformatics. 2004 20:1388-97

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Class II binding motif

RFFGGDRGAPKRGYLDPLIRGLLARPAKLQV

KPGQPPRLLIYDASNRATGIPAGSLFVYNITTNKYKAFLDKQ

SALLSSDITASVNCAKPKYVHQNTLKLAT

GFKGEQGPKGEPDVFKELKVHHANENISRYWAIRTRSGGI

TYSTNEIDLQLSQEDGQTI

RandomAlignment by Gibbs sampler ClustalW

Gibbs sampler

M Nielsen et al., Bioinformatics. 2004 20:1388-97

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Antibody responses

Figures by Eric A.J. Reits

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Prediction of Antibody epitopesLinear

– Hydrophilicity scales (average in ~7 window)• Hoop and Woods (1981)• Kyte and Doolittle (1982)• Parker et al. (1986)

– Other scales & combinations• Pellequer and van Regenmortel• Alix

– New improved method (Pontoppidan et al. in preparation)• http://www.cbs.dtu.dk/services/BepiPred/

Discontinuous– Protrusion (Novotny, Thornton, 1986)

• Pernille Haste Andersen, 2005, in preparation

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Immunological bioinformatics

Classical experimental research– Few data points– Data recorded by pencil and

paper/spreadsheetNew experimental methods

– Sequencing– DNA arrays– Proteomics

Need to develop new methods for handling these large data sets

• Immunological Bioinformatics/Immunoinformatics

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PernilleHasteAndersen

Morten Nielsen

Anne Mølgaard

SuneFrankild

ThomasBlicher

ClausLundegaard

Xiuxiu Ye

JensPontoppidan

Immunology group at CBS

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