Introduction of Research Center forAllergy and Immunology (RCAI)-What is “Immunogenomics” for?-Osamu Ohara
RIKEN Research Center for Allergy and Immuology
Kazusa DNA Research InstituteOrganization of RIKEN Research Center
for Allergy and Immunology

研究グループ

研究チーム

研究ユニットCentral Instruments for genomics

High-resolution fluorescent image scanner

Fluorescent gel image scanner

Plasmid preparation robot

Liquid dispensing robot

Thermal cyclers

DNA microarray system

Real-time PCR analyzer

Computer data mining system
Capillary DNA sequencers

Automated sample preparation
robot for MS analysis

Mass spec. instruments

SPR analysis instrumentFrom Genes to Immune systems

Analysis of DNA structure（Gene/Transcript analysis system）
Availability of comprehensive collections ofhuman/mouse cDNA clones

RCAI/Kazusa cDNA clones

RIKEN FANTOM clones

PC cluster computer
High-throughput DNA sequencers

DNA microarray system
Genome/protein databases

DNA microarray data

Expression profiling of tens of thousands of genes

Data integration and Data miningFrom Proteins to Immune Systems（Protein analysis system）
Separation of proteins

Isolation of proteins of interest

Detection of proteinsof interest

Differential detection offluorescently labeled proteinsHigh-throughput sample preparation robot

2D gel electrophoresis

Identification of proteins

Nano-LC-MS/MS system

MALDI-TOF Mass spectrometer時間軸と空間軸が捨象されている

GenomeTR(transcribed region)ome

ORFomeProtein (Ab) microarray
2D gel electrophoresisetc

DNA microarray
SAGE etc.

Snapshots of transcriptome/proteome
Real-world Transcriptome

高い空間・時間依存性をもつ

Real-world Proteome

Cell/Tissue

Real-world Biological System

Immunogenomics
Focused functional genomics
for Immunology
免疫系に関与する細胞のトランスクリプトーム・プロテオーム
スナップショットから免疫現象の理解に向かうーゲノム情報に依拠した免疫システムの理解ーOmics Approaches
Genome Information
Proteomic analysis2D gel electrophoretic analysis
followed by mass spectrometryProtein Interaction Network
Transcriptomic analysis

Comprehensive understandingof the immune system
Etiology of the immune disorders

Omicsアプローチとは従来の生命科学研究のアプローチと何が違うのか？
• データ量？ データの「量」は本質的な違いを与えるものではない。
しかし、しばしば実験手法で便宜的に区別されている場合が見かけられる。

• 仮説に誘導されているかどうか？
すべての生命現象がゲノムにコードされた遺伝子の振る舞いで記述されているというドグマの下の仮説形成型のアプローチであるかどうかが、Omicsと従来のアプローチを峻別するものである

情報科学への期待は、正にこうしたOmicsアプローチの実現へ向けてのものである

DNAマイクロアレイの原理
癌細胞由来のRNAを鋳型に逆転写させて調製したCy5
ラベルの１本鎖cDNA

正常細胞由来のRNAを鋳型に逆転写させて調製したCy3ラベルの１本鎖cDNA

競合的なハイブリダイゼーション

個別の遺伝子に相当するDNAをアレイ化したもの

２つの生理的に異なる状態で発現レベルの異なっている遺伝子を同定し、その中の遺伝子に今まで知られている機能では予想されない振る舞いがみられるかどうかを調べる。

包括的解析ではあるが、Omics的なアプローチとはちょっと違うのでは….

The Cycle of Knowledge
Synthesis
Induction
Abduction

IDEAS

DATA

Hypothesis
Analysis
Deduction

Hypothesis-driven vs. Hypothesis-free scienceCurrent needs of real-world
immunologists to “Omics” studies• Fill the gap between the physiologicalimmune responses and the molecular events
Detection of changes at the mRNA and/or protein levels
mRNA → DNA microarray
Protein → 2D Gel electrophoresis/MS
LC/MS/MS
Detection of changes in transcriptional and/or translational
states or in chromatin structure

mRNAと蛋白質レベルは独立なパラメータである
mRNAレベル蛋白質の合成速度を規定発現量を包括的に測定しうる

蛋白質レベル

合成速度と分解速度のバランスで決定されるたんぱく質レベルの包括的な測定は現在の技術ではまだ困難。
しかし、もし判ればそれは生体機能に直結している両者を追跡することが生命現象の理解には必須

mRNAレベルの包括的な測定

DNAマイクロアレイの原理

癌細胞由来のRNAを鋳型に逆転写させて調製したCy5ラベルの１本鎖cDNA

今後のバイオ分析機器は、コンピュータの世界で起こったことが再現されていくと言われている。
「ダウンサイジング」が一つのキーワードであり、DNAマイクロアレイはその先駆けである

正常細胞由来のRNAを鋳型に逆転写させて調製した
Cy3ラベルの１本鎖cDNA

競合的なハイブリダイゼーション

個別の遺伝子に相当するDNAをアレイ化したもの

Y

座標軸（Xi, Yi）のハイブリダイゼーションシグナルが遺伝子iのmRNA量に相関する。
xExamples of 2D protein map
X (pI)Y (Mw)X (pI)Y (Mw)

Protein spots identified by PMF or LC-MS/MS analysis
Quantities of gene products i, Qi, are expressed by the staining intensities
of protein spots at the positions (Xi, Yi) on 2D map.

Quantitative protein 2D map of the immune system

2490

3478
2582

3479

020918S1KMSS-IEFLS1_20①020918s1kmss-iefls1_20a020918S1WMSS-IEFLS1_20②020918s1wmss-iefls1_20a

Ref. SpotVolumePeak Height

Area

Height / Area

Volume / Area

VolumePeak Height

Area

Height / Area

Volume / Area

2490

11111

1.423

-1.0551.654-1.745-1.163

2582

11

1

1

1

1.215

-1.1491.518-1.745-1.249

3478

1

11

1

1-3.85-2.498-2.489-1.004-1.547

3479

11

1

1

1

3.746

1.734

2.3-1.326

1.629

VolumeOnce amounts of proteins are expressed quantitatively, the data can beanalyzed in exactly the same way as the DNA microarray data

Differential Fluorescent 2D Protein Map
Co-electrophoresed two differentially fluoresecent labeled protein samples
Cell B

Cell AMerge

More sensitive than fluorescent protein detection!

Conventional “Omics” Routine
1. DNA microarray analysis
2. 2D gel analysis or LC/MS/MS analysis
1. Confirmation of modulated genes by real-time PCR or RNA blotting analysis
2. Confirmation of modulated proteins by protein blotting analysis

When changes are observed only at the protein level, they are frequently considered
to be biologically significant. However, when the changes at the mRNA level are notaccompanied by those at the protein level, their biological significance are ambiguous.

Current concerns in proteomic analysis• Low comprehensivenessDNA microarray ~Tens of thousands of genes
less than 1 copy mRNA/cellProtein 2D analysis <1000 protein spots/gel
more than 50 fmole/spot

How to obtain protein profiles more comprehensively
and more sensitively

Beyond the identification ofhuman transcribed sequences
Identification and characterization ofproteins encoded by the transcripts
Protein primary structure in vivo
(post-translational modifications)
Cellular and subcellular localization
Protein-Protein interaction network
Quantitative protein level profilingWhat is required to move beyond theidentification of transcribed sequences?
High-throughput platforms to analyze proteins
and their functions+A non-redundant collection of cDNAs
which can produce authentic proteins

How to fill the gap between thegenome and the proteome• Preparation of affinity capture reagents
which can specifically detect the geneproducts of interest with high affinity
Identification and characterization of the gene products in vivo
Tag

Gene product of interest

High-affinity capture reagent

Molecular mass and pI
Post-translational modifications
Interacting protein partners
Cellular and subcellular localization

Complementation of the in vitro results!

Mouse KIAA projects (2002~)
Moving toward “Real-World Proteome” using
mouse KIAA cDNAs and antibodies against
KIAA proteins
Evaluation of RNA editing, alternative forms,
and the authenticity of human KIAA cDNAs bycomparison of KIAA cDNA sequences fromhuman and mouse and analysis at the protein
level.
Preparation of affinity reagents specific toKIAA gene products*This project is supported by JSTMammalian Genomic data

Mammalian cDNA data

Mammalian protein sequence database
Gel electrophoresis

Protein sequence tags
HPLCAnalysis of primary structure of proteins

Conventional proteome analysis through protein analysis
Kazusa DNA Research InstituteMammalian Genomic data

Mammalian cDNA data

Mammalian protein sequence database

Expression-ready cDNAclones

Gel electrophoresis
Recombinant proteins

Immunodetection

Antibodies against therecombinant proteins

Pull-down the protein complex

Antibody array

Proteome analysis through cDNA analysis
Kazusa DNA Research InstituteFour members of mammalian protein 4.1 family

Kazusa DNA Research InstituteDifferential localization of four members ofprotein 4.1 family in rat cerebellum
Neurofilament H(neuronal axon staining)
Member of protein 4.1 family

g: Granule cell layer
W: white matter

Kazusa DNA Research InstituteAnalysis of mKIAA protein using antibodies

Protein size
Alternative form
Tissue abundanceWestern blot
CLSM analysis
Subcellular localizaton

Tissue array
Cellular localization

TEM analysis
Subcellular localization

Specific Antibodies

IP coupled with LC-MSanalysis
Interacting proteins
Post-translational modifications

Omicsアプローチの実現のために求められているもの
1. 共通基盤に立った、相互比較可能な包括的解析
データリソースの確立
データフォーマットの標準化、コントロールされた用語の使用など
解析手法の革新：まだまだ包括的解析の技術レベルは改良されなければならない！

2. データマイニングのための情報科学的なプラット
フォーム
Focused genomicsで求められているのは、目的指向型の「仮説形成推理」を成立させるためのプラットフォーム

Theory of Enlightened Self-Interest“A genome enthusiast is a genome critic who justgot a hit in the EST database”

From“Lessons Learned, Promises Kept: A Biologist’s Eye View of the Genome Project”
S.M.Tilghman

Genome Res. 1996 6, 773-80

A modified version for Immunoinformatics

Theory of Enlightened Self-Interest“An informatics enthusiast is an informatics
critic who just got an immunological insightfrom hypothesis-free science”

Thanks to my colleagues!
• Immunogenomics Team (RCAI)
Kitamura, H., Kimura, Y., Nishigaki, T., Murahashi, Y.,Nakagawa, T., Yokoyama, R., Ishizu, Y., Takayama, M.,Nomura, Y.

• Kazusa DNA Research InstituteNagase, T., Kikuno, R., Nakayama, M., Yamakawa, H.
and many excellent technicians• JST CREATE Program
Koga, H., Okazaki, N., Ohara, R., Yuasa, S., and manycollaborators and excellent technicians