intro

48
Intro Spring 2009 Bioinformatiatics Proteomics

Upload: bart

Post on 18-Mar-2016

51 views

Category:

Documents


0 download

DESCRIPTION

Intro. Bioinformatiatics. Spring 2009. Proteomics. workflow. Bioinformatiatics. Spring 2009. Proteomics Workflow. Sample Prep Sequencing Database Search Protein ID Protein Interactions. General workflow of proteomics analysis. Proteins/peptides. Digestion and/or separation. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Intro

IntroSpring 2009 Bioinformatiatics

Proteomics

Page 2: Intro

workflowSpring 2009 Bioinformatiatics

Proteomics Workflow• Sample Prep• Sequencing• Database Search• Protein ID• Protein Interactions

Page 3: Intro

IdentificationQuantification

General workflow of proteomics analysis

External data sourcestaxonomy, ontologies, bibliography…

Applications Systems biology (pathways, interactions..) biomarker-discovery, drug targets

Proteins/peptides

2D gel image aquisition and storage

MALDI, MS/MS

Store peak lists and all meta data

Digestion and/or separation

PMFMS/MSDIGELC-MS & Tags

Page 4: Intro

Sequence data bases:EMBL Nucleotide Sequence Database GenBank UniProtKB/Swiss-Prot & TrEMBL Ensemble EST database PIR

IdentificationQuantification

General workflow of proteomics analysis

Proteins/peptides

Digestion and/or separation

MALDI, MS/MS

2D Page data basesSwiss 2D PAGE, Gelbank, Cornelia, WordPAGE

Make 2D

Imaging tools:Melanie, PDQuest ProgenesisDelta 2D

Storing/ organising:ProteincsapeMSight

KEGG PDB DIPOMIMReactomePROSITPfamSPINBONDSTRINGAmiGODavidPubMedMEDLINE

MascotSequestAldentePopitamPhenyxFindModProfoundPepFragMS-FitOMSSASearch XLinksTagIdent

Page 5: Intro

General workflow of proteomics analysis

Proteins/peptides

Digestion and/or separation

2D Page data bases

Make 2D

Imaging Softwares:The ability to compare two gels (images) and then identify differently expressed spots

•Melanie•PDQuest•Progenesis•Delta 2DProteinscape –platform for storing, organizing

dataMSight -representation of mass spectra along with data from the separation

2D gel databases:Data integration on the webImage data and textual information

•Swiss 2D PAGE •Gelbank •Cornelia•WordPAGE

Page 6: Intro

Laser capture

Spring 2009 BioinformatiaticsLaser-Capture Micro dissection, LMC

Technique for selectively sampling certain cells within a tissue

Biopsy

Transfer film

Glass slide

Genomic/proteomic analysis

Tissue sample

Laser beam activates film

Selected cells are transferred

Tumor

Cells

Modified from “National Cancer Institute”, US National Institutes of Health:

http://www.cancer.gov/cancertopics/understandingcancer/moleculardiagnostics/Slide29

Page 7: Intro

TemplateSpring 2009 Bioinformatiatics

Page 8: Intro

FractionationSpring 2009 Bioinformatiatics

Affinity Purification

Page 9: Intro

2D gels at SwissprotSpring 2009 Bioinformatiatics

Swissprot ExPaSy Database

2D Electrophoresis

Page 10: Intro

TemplateSpring 2009 Bioinformatiatics

Protein Digestion•Primary sequence must be accessible•Denature – urea in solution or SDS in gel•Reduce & alkylate disulfide bonds between cysteines

•dithiothreitol (DTT) & Iodoacetamide (IAA)•Digest with enymes•Purify peptide fragments

Page 11: Intro

TemplateSpring 2009 Bioinformatiatics

Page 12: Intro

codon UsageSpring 2009 Bioinformatiatics

Standard Genetic Code (transl_table=1) AAs = FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGGStarts = ---M---------------M---------------M----------------------------Base1 = TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGGBase2 = TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGBase3 = TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG

AAs = FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGGStarts = ---M---------------M------------MMMM---------------M------------Base1 = TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGGBase2 = TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGBase3 = TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG

The Bacterial and Plant Plastid Code (transl_table=11)

AAs = FFLLSSSSYYQQCC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGGStarts = -----------------------------------M----------------------------Base1 = TTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCAAAAAAAAAAAAAAAAGGGGGGGGGGGGGGGGBase2 = TTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGTTTTCCCCAAAAGGGGBase3 = TCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAG

The CiliateHexamita Nuclear Code (transl_table=6)

Page 13: Intro

Unusual amino acidsSpring 2009 Bioinformatiatics

Unusual Amino Acids

Page 14: Intro

phosphorylationSpring 2009 Bioinformatiatics

Phosphorylation - signal transduction

mRNA

mRNA

Page 15: Intro

TemplateSpring 2009 Bioinformatiatics

Page 16: Intro

TemplateSpring 2009 Bioinformatiatics

Page 17: Intro

TemplateSpring 2009 Bioinformatiatics

Page 18: Intro

TemplateSpring 2009 Bioinformatiatics

Page 19: Intro

TemplateSpring 2009 Bioinformatiatics

Page 20: Intro

TemplateSpring 2009 Bioinformatiatics

Page 21: Intro

MS analysis

Page 22: Intro

Antibody arrays

Good for low-abundance proteinsProblem is antibody specificity

Page 23: Intro

Array-based protein interaction detection

Page 24: Intro

Protein microarrays

Page 25: Intro

Yeast Two-Hybrid System

Page 26: Intro

How to organize information?• Gene Ontology

– Biological process• Frequently from biochemical analyses• In silico analysis

– Molecular function• Biochemical analysis

– Cellular component• Biochemical analysis• GFP or other tagging

Page 27: Intro

Interaction maps - Grid

Page 28: Intro

challenges

• Complexity – some proteins have >1000 variants

• Need for a general technology for targeted manipulation of gene expression

• Limited throughput of todays proteomic platforms

• Lack of general technique for absolute quantitation of proteins

Page 29: Intro

Protein Profiling

• 2D gel electrophoresis

• Difference gel electrophoresis (DIGE)

• LC-MS/MS using coded affinity tagging(ICAT, iTrac, SILAC..)

• ProteinChip Array (SELDI analysis)

• Antibody arrays

Measure the expression of a set of proteins in two samples and compare them - Comparative proteomics

Page 30: Intro

IntroSpring 2007 Bioinformatiatics

RNA and Protein Structure Prediction

Page 31: Intro
Page 32: Intro

SSU Secondary StructureSSU Secondary Structure

Page 33: Intro

Ribosome

Page 34: Intro

Ribosome

Page 35: Intro

-Beaudry & Joyce, Science, 1992

Frq. Of mutation

(%; n=25) after

9 generations.

Page 36: Intro
Page 37: Intro

M13 vector sequence

TATAGGGCGAATTGAATTTAGCGGor

ATTAACCCTCACTAAAGGGACTAG

to

CCCTT

Page 38: Intro

Pseudoknots

Page 39: Intro

Hammerhead Ribozyme

Page 40: Intro

tRNA Secondary Structure

Page 41: Intro

RNA Tertiary Structure

Page 42: Intro
Page 43: Intro
Page 44: Intro
Page 45: Intro

Pyruvate Kinase

Page 46: Intro

Human DNA clamp PCNA

Page 47: Intro

Chou-Fasman Parameters

Page 48: Intro