Immunology In Genomics And Proteomics Era

Immunology in genomics and proteomics era Chatchai Tayapiwatana Div of Clinical Immunology Fac of Associated Medical Sciences Chiang Mai University

Copyright 2008

After 3x,xxx human genes  



Genome sequences (DNA only) by themselves are not as useful as genomes that are fully annotated. Need to know where the protein coding sequences are, and what they do: this is a very big challenge in bioinformatics. Functions of many processes reside 3D proteins, and the structure of proteins is known for only few sequences.

Definitions:  Computational

biology: an interdisciplinary field that applies the techniques of computer science and applied mathematics to biology  Bioinformatics: applies algorithms and statistical techniques to biological datasets, typically large numbers of DNA, RNA, or protein sequences  Immunoinformatics: bioinformatics applied to the study of immune system and its function

Immunology is essentially a combinatorial science  multi-step

processing pathways  network-type interactions  complex signalling  mechanisms for modulation of immune responses

Immunoinformatics  Database

technology for storage, analysis, and modelling of immunological data  Sequence analysis and various statistical tools  Computational models to facilitate research in immunology  molecular

level models  system level models

Basic immunology

Clinical immunology

Networks, pathways, and systems

-omics

IMMUNOINFORMATICS Artificial intelligence

Cell biology

Physics/ Chemistry

Databases Algorithms

Maths/Stats

Why Immunoinformatics?  Using

Bioinformatics to address problems in Immunology  Application

of bioinformatics to accelerate immune system research has the potential to deliver vaccines and address immunotherapeutics.  Computational systems biology of immune response

Disease alleviation 1. 2. 3. 4. 5. 6. 7.

Genome screening - marker detection Transcriptomics/Proteomics of diseased state Sequence analysis of antigens/markers Structure analysis of antigens T cell epitope analysis Antibody epitope analysis Vaccine design

OMICS Genomics Transcriptomics Proteomics Immunomics Others

ie. Metabolomics, Interactomics, …..

What is Proteomics? Proteomics – An emerging field of life science research that uses High Throughput (HT) technologies to display, identify and/or characterize all the proteins in a given cell, tissue or organism (i.e. the proteome). molecular biology chromatography 2D electrophoresis mass spectrometry X-ray crystallography NMR spectroscopy robotics computational biology

Genomics vs. Immunomics  Genomics: 

solving the genome puzzle

104 genes coding for 106 products

 Immunomics:

understanding immune

response 

102-103 genes leading to >1012 products

 Enormous

diversity in immunomics has implications for immune function and modulation

An enormous diversity in human immune system >1013 MHC class I haplotypes (IMGT-HLA) 107-1015 different T-cell receptors (Arstila et

al., 1999)

1012 B-cell clonotypes in an individual (Jerne,

1993)

acids

1011 linear epitopes composed of nine amino >>1011 conformational epitopes

Dana-Farber prediction

RIKEN Structural Genomics/Proteomics Initiative (RSGI)

Liquid handlers  

Picking up cDNA clones and PCR primers from stock library plates for PCR reactions. Picking up and re-arranging PCR products for subsequent experiments.

Genesis 150 (TECAN)

Genesis 200 (TECAN)

Riken GSC Protein Purification Facility ÄKTA 10S ÄKTA 100 ÄKTA prime

27 sets 3 sets 28 sets

Automated Crystallization and Visualization Robot (RIKEN/Takeda RIKA/STECK/AdvanSoft]

Major histocompatibility complex

Gene structure of the human MHC

3D structure of the human MHC

MHC Class II

MHC Class I

Modelling MHC-binding peptides

Antigen processing pathway: peptides, MHC, T-cells 1. 2. 3.

Degradation of antigen Peptide binding to MHC Recognition of peptide-MHC complex by T-cells Yewdell et al. Ann. Rev Immunol (1999)

0.05% chance of immunogenicity

20% processed

0.5% bind MHC

50% CTL response

Virtual Screening Protein 3D Structure

Active Site Docking Search

ca.300,000 compounds

Compound Database

Computational models can help identify T cell epitopes  Suggest candidate epitopes by in silico screening of entire proteins and even proteomes  Minimize the number of wet-lab experiments  Cut down the lead time involved in epitope discovery and vaccine design

IMMUNOINFORMATICS COMPUTER COMPUTER SCIENCE SCIENCE

Learning Algorithms, Pattern Recognition, Adaptive Memories, Intelligent Agents

IMMUNOLOGY IMMUNOLOGY

COMPUTATIONAL IMMUNOLOGY DATABASES DATABASES

COMPUTATIONAL COMPUTATIONAL MODELS MODELS

COMPUTATIONAL COMPUTATIONAL EXPERIMENTS EXPERIMENTS

Design of Experiments, Data Interpretation

Specialist databases

ABAT MGT WAM MULTIPRED MHCPEP YFPEITHI

HIV molecular

immunolog

ALLERDB

2D-gel

CONTROL (Normal) DNA Labelled target from RNA

Cy5

TEST (Altered) DNA Cy3

Cy5

Cy5 Cy5

Cy3

Cy3

Cy5

Cy3

Cy3

Hybridise

Probe printed onto slide Gene 1 Gene 2 Gene 3 Gene 4

Gene 5

Slide Scanned Spot intensities analysed Gene 1 Gene 2 Gene 3 Gene 4 No Difference

Higher expression in test

No Difference

Higher expression in control

Gene 5 No Difference

Antibody Array  cDNA

level may not correlate with protein level  Antibody microarray is of need  Specific binding ligand with vast diversity (McAb libraries)  Hybridoma 1975  Recombinant DNA & cloning technique  Bacterial expression, E. coli (Phage display)  Cell-free system (ribosome display)

BD (CLONTECH)

SUBSTRATE ADDING

ENZ

ENZ

CLONDIAG

Principles of the Luminex Technology

The flow cell – where it all happens..

Red laser reads the bead, i.e. the target

Green laser detects the amount of the target

The Luminex machine

Beadlyte Immunoassay format for the Luminex Machine.

The After In Free assays phycoerythrin excess another with streptavidinwash highisstep The immune-complex/ The A primary biotinylated, Microsphere primary antibody antibody analyte is a Streptavidin analyte PE excited binds by numbers to the the PE reporter nonis excess added microsphere isanalyte then 5.6mM binds specific to polystyrene for reporter the the specific antibody bead is toexcited biotinylated specifically laser theand assay. emits bound reporter The a by the ****** with conjugated analyte is added two–to fluorescent no the to the assay bead dyes antibodies biotinylated fluorescence bind reporter which to the is laser. Thean bead specific incorporated surface crossreactivity after another by into wash amine with it step. in other Strep-PE antibody quantified in binds leading by a non-specific the to to one a of emmission is quantified different coupling analytes reaction occurs. ratios. the manner. signal Luminex amplification. available reader. and sites. byfour the luminex the bead identified.

Phage display technique         

1976 Tonegawa ----> Ig genes rearrangement 1991 McCafferty (Winter group) and Lerner + Burton (Scripps) ---> Phage Display Phage display Ab libraries Bacterial expression, E. coli mRNA purification, cDNA amplification kits PCR for Ig H and L chain genes Phagemid vector; pComb3H M13 filamentus helper phage XL-1 BLUE E. coli host

Phagemid vector, pComb3HSS

Concenus Design of an Ankyrin

Ankyrin with 3 internal repeats and capping repeats N et C External side chains can be randomized

Ank Off7/MBP KD=4.4 nM Revue: Current Opinion in Biotechnology 2005, 16:459–469

Towards protein chips?

Domaine Fn 3

Intrabody Therapy

R.E. Kontermann / Methods 34 (2004) 163–170

Collaborators  Prof.

Watchara Kasinrerk, CMU  Dr. Vannajan Sanghiran Lee, CMU  Prof. Carlos F Barbas, TSRI  Prof. Sabine Mai, U. Manitoba  Prof. Philippe Minards, U. Paris Sud XI  Prof. Pierre Boulanger, U. Lyon

Data in Bioinformatics and their management and analysis

Sequences

Structures

Databases, Data & text ontologies mining

Genomes Transcriptomes

Algorithms Maths/Stats

Networks, Genetics and pathways populations and systems

Physics/ Chemistry

Evolution and phylogenetics