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PROTEOMICS
Proteomics – in view of other fields
Proteome
Proteomics
Proteome
Proteomics
Genome
Genomics
Genome
Genomics
Structural
proteome
Structural
proteome
Database
Application
Database
Application
Molecular
evolution
Molecular
evolution
Data
Mining
Data
Mining
Chemistry
Cell Biology
Imaging
Biotechnology
Nanotechnology
Protein Science
Biochemistry
What is a Proteome?What is a Proteome?
All the proteins expressed by a
genome.
“Functional Proteome” = all the
proteins produced by a specific cell in a
single time frame.
Why is the ProteomeWhy is the Proteome
Important?Important?
 It is the proteins within the cell that:
 Provide structure
 Produce energy
 Allow communication
 Allow movement
 Allow reproduction
 Proteins provide the structural and functional
framework of cellular life
Hemoglobin
Antibody
Epidermal Growth Factor Receptor
Proteins are molecular machines of many shapes and sizes
Rubisco
What is Proteomics?What is Proteomics?
Proteomics refers to the systematic
analysis of protein profiles of entire
cells, tissues, organisms, or species.
It represents the protein counterpart
to the analysis of gene function.
Proteomics vs GenomicsProteomics vs Genomics
 DNA sequence does not predict if the protein is in an active form
 RNA quantitation does not always reflect corresponding protein levels
 Multiple proteins can be obtained from each gene (alternative splicing)
 Genomics cannot predict post-translational modifications and the
effects thereof
 DNA/RNA analysis cannot predict the amount of a gene product made
(if and when)
 DNA/RNA analysis cannot predict events involving multiple genes
Why is Proteomics Important?Why is Proteomics Important?
 Identification of proteins in normal and disease
conditions
 Investigating epidemiology and taxonomy of pathogens
 Analysis of drug resistance
 Identification of pathogenic mechanisms
 Reveals gene regulation events involved in disease
progression
 Promise in novel drug discovery via analysis of
clinically relevant molecular events
 Contributes to understanding of gene function
Proteomics: fundamentsProteomics: fundaments
and applicationsand applications
Susana Cristobal
Bioinformatik, 4p. KTH
0utline0utline
1.1. The virtue of proteomicsThe virtue of proteomics
2.2. Two dimensional gelTwo dimensional gel
electrophoresiselectrophoresis
3.3. Detection technologyDetection technology
4.4. Identification methodsIdentification methods
5.5. Application of proteomicsApplication of proteomics
Susana Cristobal
Bioinformatik, 4p. KTH
 Proteome, the end product of the genome.
 Proteome: dynamic entity.
 Protein world: study of less abundant proteins
 Transcriptomics: insufficient short-cut to study
most functional aspects of genomics
Susana Cristobal
Bioinformatik, 4p. KTH
Sampling biological materialSampling biological material
Factors:
 In cell cultures: growth phase,
culture conditions,strain employed
 Cell from multicellular organisms:
stage of differentiation
 Tissues from biopsy: isolation of
homogenous cell populations
Susana Cristobal
Bioinformatik, 4p. KTH
Phases of a large scale analytical processPhases of a large scale analytical process
1. Separation of biomolecules of
interest
• Extraction of protein sample
 Cell culture
 Organelle isolation
• Two dimensional electrophoresis
2. Molecular characterization
• Detection technology
• Identification of proteins
• Differential expression profilesSusana Cristobal
Bioinformatik, 4p. KTH
Different strategies for proteome purification andDifferent strategies for proteome purification and
protein separation for identification by MSprotein separation for identification by MS
 A. Separation of individual
proteins by 2-DE.
 B. Separation of protein
complexes by non-denaturing
2-DE (BN-PAGE)
 C. Purification of protein
complexes by immuno-affinity
chromatography and SDS-
PAGE.
 D. Multidimensional
chromatography.
 E. Organic solvent
fractionation for separation of
complex protein mixtures of
hydrobhobic membrane
proteins.
(van Wijk, 2001, Plant Physiology 126, 501-
508)
Susana Cristobal
Bioinformatik, 4p. KTH
Organelle can be separated by differential velocity
centrifugation
Rupture plasma
membrane to
prepare tissue/
cell homogenates:
• high speed
blender
• Sonication
• tissue
homogenize
• osmotic shock
( Molecular cell biology.
Lodish. Fig 5-23)
Susana Cristobal
Bioinformatik, 4p. KTH
Partially purified organelles can be better separated
by equilibrium density gradient centrifugation
(Lodish fig 5-24)
How can you assess purity?
Organelle-specific markers
• Cytchrome c,
mitochondria
• Catalase,
peroxisome
• Ribosome, rough ER
• Esterase,
microsomes
Susana Cristobal
Bioinformatik, 4p. KTH
Organelle-specific antibodies are useful in
preparing highly purified organelles
(Lodish fig 5-26)
Protein A o G is a
bacterial molecule
that selectively
binds Igs.
Protein A:Ab:Ag
complex collected
and dissociated to
release organelle.
Susana Cristobal
Bioinformatik, 4p. KTH
Two-dimensional gel electrophoresisTwo-dimensional gel electrophoresis
 Solubilization of proteins in
2D electrophoresis
 Two dimensional
electrophoresis with
immobilized pH gradients
 Detection of proteins on
2DE
Susana Cristobal
Bioinformatik, 4p. KTH
Solubilization of proteins in twoSolubilization of proteins in two
dimensional electrophoresisdimensional electrophoresis
 There is no universal solubilization
protocol.
 urea-reducer-detergent mixtures
usually achieve disruption of
disulfide bonds and non-covalent
interactions.
Goals:
 Breaking macromolecular
interaction (disulfide bonds).
 Preventing any artefactual
modification of polypeptides
in the solubilization medium.
 Removal of substances
that may interfere with 2DE.
 Keeping proteins in solution
during 2DE process. Susana Cristobal
Bioinformatik, 4p. KTH
Sample bufferSample buffer
 Chaotropes:
 8M Urea
 2M Thiourea/ 7M Urea
 Surfactants:
 4% CHAPS
 2 % CHAPS / 2 % SB-14
 Reducing agents:
 65 mM DTE (dithioerythritol)
 100 mM DTT ( dithiothreitol)
 2 mM tributyl phosphine
 Ampholytes 2%Susana Cristobal
Bioinformatik, 4p. KTH
How many quantities of samples can beHow many quantities of samples can be
loaded in one IPG strip?loaded in one IPG strip?
Identification of membrane proteins
(Govorun, 2002)
Susana Cristobal
Bioinformatik, 4p. KTH
Two-dimensional gel electrophoresisTwo-dimensional gel electrophoresis
Internet-sites:
http://www.weihenstephan.de/blm/deg/manual/manualwork2html02testp6
htm and http://www.expasy.ch/ch2d/protocols.Susana Cristobal
Bioinformatik, 4p. KTH
First dimension: IEFFirst dimension: IEF
Immobilized pH gradients (IPGs)Immobilized pH gradients (IPGs)
IPG principle:
pH gradient is generated by a limited number
(6-8) of well defined chemicals
(immobilines) which are co-polymerized
with the acrylamide matrix.
IPG allows the generation of pH gradients
of any desired range ( broad, narrow,
ultra-narrow) between pH 3 and 12.
sample loading capacity is much higher.
This is the method of choice for micropreparative
separation or spot identification.Susana Cristobal
Bioinformatik, 4p. KTH
How many quantities of samples can beHow many quantities of samples can be
loaded in one IPG strip?loaded in one IPG strip?
(18 cm)(18 cm)
Analytical run: 50-100 µg
Micropreparative runs: 0.5-10 mg
Susana Cristobal
Bioinformatik, 4p. KTH
Two dimensional electrophoresisTwo dimensional electrophoresis
Running conditionsRunning conditions
SampleSample::Caenorhabditis elegansCaenorhabditis elegans
IEF: dry strips pH = 4-7IEF: dry strips pH = 4-7
Hydratation conditionsHydratation conditions:urea,:urea,
thiourea, CHAPS, DTT,thiourea, CHAPS, DTT,
ampholytes, iodoacetamine.ampholytes, iodoacetamine.
Passive 15h.Passive 15h.
 Isoelectrofocussing:Isoelectrofocussing:
200v 1h200v 1h
500v 1h500v 1h
1000v 1h1000v 1h
5000v 3h5000v 3h
SDS-PAGE: 12%SDS-PAGE: 12%
Silver stainingSilver staining
Susana Cristobal
Bioinformatik, 4p. KTH
Detection technologies in proteome analysisDetection technologies in proteome analysis
 General detection methods.
 Differential display proteomics.
 Specific detection methods for post-
translational modifications.
Susana Cristobal
Bioinformatik, 4p. KTH
General detection methods
 Organic dye- and silver-based
methods
 Coomassie blue (R and G)
 Silver
 Radiactive labeling methods
 Reverse stain methods
 Flourescence methods
Susana Cristobal
Bioinformatik, 4p. KTH
Differential display proteomicsDifferential display proteomics
 Detection techniques:
 Difference gel electrophoresisDifference gel electrophoresis
(DIGE).(DIGE).
 Multiplexed proteomics (MP)Multiplexed proteomics (MP)
 Isotope-coded affinity taggingIsotope-coded affinity tagging
(ICAT)(ICAT)
 Differential gel exposure.Differential gel exposure.
Susana Cristobal
Bioinformatik, 4p. KTH
Summary of protein expression profileSummary of protein expression profile
analysisanalysis
Susana Cristobal
Bioinformatik, 4p. KTH
Difference gel electrophoresis (DIGE)Difference gel electrophoresis (DIGE)
(Unlu, 1997, electrophoresis 18, 2071)
Susana Cristobal
Bioinformatik, 4p. KTH
Multiplexed proteomics (MP) technologyMultiplexed proteomics (MP) technology
platformplatform
(Steinberg, 2001, Proteomics 1,841, 2071)
Susana Cristobal
Bioinformatik, 4p. KTH
Isotope-codedIsotope-coded
affinity taggingaffinity tagging
(ICAT) technology(ICAT) technology
platformplatform
(Smolka, 2002, Mol Cell Proteomics 1, 19-29)
Very successful technique for
identification of integral
membrane proteins
Differential gel exposure
 Coelectrophoresis on 2DE of two protein samples.
 In vivo labelling, using 14
C and 3
H -isotopes.
 2DE separation.
 Transfer on a PVDF membrane.
 3
H /14
C ratio by exposure to two types of imaging plates.
 Investigate changes in the rate of synthesis of
individual proteins.
(Monribot-Espagne, 2002, Proteomics 2, 229-240)
Susana Cristobal
Bioinformatik, 4p. KTH
Image analysisImage analysis
Software commomly used to manipulate the gel images:Software commomly used to manipulate the gel images:
•Imagemaster TM
•Melanie III TM
•Other functions:Other functions:
• QuantificationQuantification
• AlignmentAlignment
• ComparisonComparison
• MatchingMatching
• Synthetic image from the image of the sampleSynthetic image from the image of the sample
Susana Cristobal
Bioinformatik, 4p. KTH
Example of data from differential displayExample of data from differential display
proteomicsproteomics
(Chevatier, 2000, Eur.J. Biochem. 267, 4624-4634)
Susana Cristobal
Bioinformatik, 4p. KTH
Protein profiling in response to various treatments atProtein profiling in response to various treatments at
two different time-pointstwo different time-points
(Chevatier, 2000, Eur.J. Biochem. 267, 4624-4634)
Susana Cristobal
Bioinformatik, 4p. KTH
General scheme of proteomic analysis
Pick the protein gel spot from the gel
Pick up the protein gel spot from gel
• Manual
• Automatic
In-gel digestion:
• Washing process
• Dehydratation and drying
• Trypsin digestion (50 ng trypsin,
37C 16h)
• Extraction
• Desalt and concentrate the
peptide
Identification methodsIdentification methods
Identification of proteins by mass
spectrometry:
 Identification of proteins by amino
acid composition after acid
hydrolysis
 Identification of proteins by amino
acid sequencing
FFlow chart for the analysis of proteomes by MSlow chart for the analysis of proteomes by MS
(van Wijk, 2001, Plant Physiology 126, 501-508)
Susana Cristobal
Bioinformatik, 4p. KTH
Identification of eluted protein spots by
different MS approaches
 Extraction of intact protein: (single peak)Extraction of intact protein: (single peak)
 MALDI-TOF LINEAR mode
 Passive elution of proteins.
 Analyze in a linear MALDI-TOF MS.
 Peptide mass FINGERPRINT:Peptide mass FINGERPRINT:
 MALDI-TOF REFLECTRON mode
 In situ tryptic digestion of spots.
 Analyze in reflectron MALDI-TOF MS.
 Fragments, SEQUENCE:Fragments, SEQUENCE:
 LC-ESI MS/MS
 Separation in a C18 column.
 MS/MS analysis in a Q-TOF.
Susana Cristobal
Bioinformatik, 4p. KTH
Comparison of MALDI-TOF and ESI-MS-MSComparison of MALDI-TOF and ESI-MS-MS
approaches to protein identificationapproaches to protein identification
MALDI-TOF MSMALDI-TOF MS
Sample on a a slide (crystalline
matrix).
Spectra indicate masses of the
peptide ions.
Protein identification by peptide
mass fingerprinting.
ESI-MS-MSESI-MS-MS
Sample in solution (high
performance liquid
chromatography).
MS-MS spectra reveal
fragmentation patterns.
Protein identification by cross-
correlation algorithms.
Susana Cristobal
Bioinformatik, 4p. KTH
Schematic of the MALDI quadrupole time ofSchematic of the MALDI quadrupole time of
flight instrumentflight instrument
Advantages:
 Mixture are analysed easily.
 It is highly tolerant to
contaminants.
 High sensitivity. (picomol range)
 Good accuracy in mass
determination.
 Quick and not expensive analysis.
Disadvantages:
 Low reproducibility and
repeatability of single shot spectra.
(Averaging )
 Low resolution.
 Matrix ions interfere in the low max
range.
Susana Cristobal
Bioinformatik, 4p. KTH
Comparison of MALDI-TOF and ESI-MS-MSComparison of MALDI-TOF and ESI-MS-MS
approaches to protein identificationapproaches to protein identification
MALDI-TOF spectrum
Susana Cristobal
Bioinformatik, 4p. KTH
Peptides that span exon splices will be missed whenPeptides that span exon splices will be missed when
matching uninterpreted MS-MS data to genomic DNAmatching uninterpreted MS-MS data to genomic DNA
(Jyoti, 2001, Trends 19, supp )
Susana Cristobal
Bioinformatik, 4p. KTH
ESI-MS-MSESI-MS-MS
Peptide sequencing by nano-electrosprayPeptide sequencing by nano-electrospray MSMS
Susana Cristobal
Bioinformatik, 4p. KTH
2DE gel
Intact protein
Experimental
proteolytic
peptides
Experimental MS
Theorectical
MSTheoretical
proteoly
tic
peptide
s
DNA
sequen
ce
databas
e
Protein
sequen
ce
databas
e
COMPUTER SEARCH
Peptide identification using mappingPeptide identification using mapping
fingerprint informationfingerprint information
Susana Cristobal
Bioinformatik, 4p. KTH
Applications ?Applications ?
• Cancer proteomics
• Peptidomics: for profiling small proteins in
the human fluids
• Neuroscience
• Toxicoproteomics: a new preclinical tool to
revolutionary drug target discovery
• Environmental pollution assessment
Susana Cristobal
Bioinformatik, 4p. KTH
Example Applications of Proteomics
• pecting the environment to identify proteins with desirable properties
• To better understand the role of proteins in human disease processes
• In anti-sports doping to catch drug cheats
• Cancer proteomics
• Peptidomics: for profiling small proteins in the human fluids
• Neuroscience
• Toxicoproteomics: a new preclinical tool to revolutionary drug target discovery
• Environmental pollution assessment
Colorectal cancer chemotherapy
 Can we a priori determine which patients will benefit
from chemotherapy?
Acquire proteomic data Identify candidate biomarkers Validate biomarkers
• All Stage C patients undergo chemo, yet only 50% need it
• Of those that need it, who will benefit?
Schedule of a proteomics experimentSchedule of a proteomics experiment
Day 1: Sample preparation and IEF
1. Load protein sample onto IPG strip (IEF)
2. Run the IEF (about 24 hours)
3. Polyacrylamide gel casting
Day 2: Equilibrium IPG strip and running SDS-PAGE
1. Remove IPG strip from IEF machine
2. Equilibrium IPG strip
3. Put IPG strip onto SDS-PAGE
4. Run the SDS-PAGE (overnight)Susana Cristobal
Bioinformatik, 4p. KTH
Day 3: Staining, image scanning and image analysis
1. Remove the gel from the cassette
2. Stain the gel by SYPRO Ruby or silver
3. Scan the gel image
4. Image analysis
Day 4: In-gel digestion, MALDI-TOF and database search
1. Pick the protein gel spot from gel
2. In-gel digestion
3. Spot the sample onto MALDI chip
4. MALDI-TOF analysis
5. Database search
Susana Cristobal
Bioinformatik, 4p. KTH
??? Questions ?????? Questions ???

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Vijay protiomics current

  • 2. Proteomics – in view of other fields Proteome Proteomics Proteome Proteomics Genome Genomics Genome Genomics Structural proteome Structural proteome Database Application Database Application Molecular evolution Molecular evolution Data Mining Data Mining Chemistry Cell Biology Imaging Biotechnology Nanotechnology Protein Science Biochemistry
  • 3. What is a Proteome?What is a Proteome? All the proteins expressed by a genome. “Functional Proteome” = all the proteins produced by a specific cell in a single time frame.
  • 4. Why is the ProteomeWhy is the Proteome Important?Important?  It is the proteins within the cell that:  Provide structure  Produce energy  Allow communication  Allow movement  Allow reproduction  Proteins provide the structural and functional framework of cellular life
  • 5. Hemoglobin Antibody Epidermal Growth Factor Receptor Proteins are molecular machines of many shapes and sizes Rubisco
  • 6. What is Proteomics?What is Proteomics? Proteomics refers to the systematic analysis of protein profiles of entire cells, tissues, organisms, or species. It represents the protein counterpart to the analysis of gene function.
  • 7.
  • 8. Proteomics vs GenomicsProteomics vs Genomics  DNA sequence does not predict if the protein is in an active form  RNA quantitation does not always reflect corresponding protein levels  Multiple proteins can be obtained from each gene (alternative splicing)  Genomics cannot predict post-translational modifications and the effects thereof  DNA/RNA analysis cannot predict the amount of a gene product made (if and when)  DNA/RNA analysis cannot predict events involving multiple genes
  • 9. Why is Proteomics Important?Why is Proteomics Important?  Identification of proteins in normal and disease conditions  Investigating epidemiology and taxonomy of pathogens  Analysis of drug resistance  Identification of pathogenic mechanisms  Reveals gene regulation events involved in disease progression  Promise in novel drug discovery via analysis of clinically relevant molecular events  Contributes to understanding of gene function
  • 10. Proteomics: fundamentsProteomics: fundaments and applicationsand applications Susana Cristobal Bioinformatik, 4p. KTH
  • 11. 0utline0utline 1.1. The virtue of proteomicsThe virtue of proteomics 2.2. Two dimensional gelTwo dimensional gel electrophoresiselectrophoresis 3.3. Detection technologyDetection technology 4.4. Identification methodsIdentification methods 5.5. Application of proteomicsApplication of proteomics Susana Cristobal Bioinformatik, 4p. KTH
  • 12.  Proteome, the end product of the genome.  Proteome: dynamic entity.  Protein world: study of less abundant proteins  Transcriptomics: insufficient short-cut to study most functional aspects of genomics Susana Cristobal Bioinformatik, 4p. KTH
  • 13. Sampling biological materialSampling biological material Factors:  In cell cultures: growth phase, culture conditions,strain employed  Cell from multicellular organisms: stage of differentiation  Tissues from biopsy: isolation of homogenous cell populations Susana Cristobal Bioinformatik, 4p. KTH
  • 14. Phases of a large scale analytical processPhases of a large scale analytical process 1. Separation of biomolecules of interest • Extraction of protein sample  Cell culture  Organelle isolation • Two dimensional electrophoresis 2. Molecular characterization • Detection technology • Identification of proteins • Differential expression profilesSusana Cristobal Bioinformatik, 4p. KTH
  • 15. Different strategies for proteome purification andDifferent strategies for proteome purification and protein separation for identification by MSprotein separation for identification by MS  A. Separation of individual proteins by 2-DE.  B. Separation of protein complexes by non-denaturing 2-DE (BN-PAGE)  C. Purification of protein complexes by immuno-affinity chromatography and SDS- PAGE.  D. Multidimensional chromatography.  E. Organic solvent fractionation for separation of complex protein mixtures of hydrobhobic membrane proteins. (van Wijk, 2001, Plant Physiology 126, 501- 508) Susana Cristobal Bioinformatik, 4p. KTH
  • 16. Organelle can be separated by differential velocity centrifugation Rupture plasma membrane to prepare tissue/ cell homogenates: • high speed blender • Sonication • tissue homogenize • osmotic shock ( Molecular cell biology. Lodish. Fig 5-23) Susana Cristobal Bioinformatik, 4p. KTH
  • 17. Partially purified organelles can be better separated by equilibrium density gradient centrifugation (Lodish fig 5-24) How can you assess purity? Organelle-specific markers • Cytchrome c, mitochondria • Catalase, peroxisome • Ribosome, rough ER • Esterase, microsomes Susana Cristobal Bioinformatik, 4p. KTH
  • 18. Organelle-specific antibodies are useful in preparing highly purified organelles (Lodish fig 5-26) Protein A o G is a bacterial molecule that selectively binds Igs. Protein A:Ab:Ag complex collected and dissociated to release organelle. Susana Cristobal Bioinformatik, 4p. KTH
  • 19. Two-dimensional gel electrophoresisTwo-dimensional gel electrophoresis  Solubilization of proteins in 2D electrophoresis  Two dimensional electrophoresis with immobilized pH gradients  Detection of proteins on 2DE Susana Cristobal Bioinformatik, 4p. KTH
  • 20. Solubilization of proteins in twoSolubilization of proteins in two dimensional electrophoresisdimensional electrophoresis  There is no universal solubilization protocol.  urea-reducer-detergent mixtures usually achieve disruption of disulfide bonds and non-covalent interactions. Goals:  Breaking macromolecular interaction (disulfide bonds).  Preventing any artefactual modification of polypeptides in the solubilization medium.  Removal of substances that may interfere with 2DE.  Keeping proteins in solution during 2DE process. Susana Cristobal Bioinformatik, 4p. KTH
  • 21. Sample bufferSample buffer  Chaotropes:  8M Urea  2M Thiourea/ 7M Urea  Surfactants:  4% CHAPS  2 % CHAPS / 2 % SB-14  Reducing agents:  65 mM DTE (dithioerythritol)  100 mM DTT ( dithiothreitol)  2 mM tributyl phosphine  Ampholytes 2%Susana Cristobal Bioinformatik, 4p. KTH
  • 22. How many quantities of samples can beHow many quantities of samples can be loaded in one IPG strip?loaded in one IPG strip? Identification of membrane proteins (Govorun, 2002) Susana Cristobal Bioinformatik, 4p. KTH
  • 23. Two-dimensional gel electrophoresisTwo-dimensional gel electrophoresis Internet-sites: http://www.weihenstephan.de/blm/deg/manual/manualwork2html02testp6 htm and http://www.expasy.ch/ch2d/protocols.Susana Cristobal Bioinformatik, 4p. KTH
  • 24. First dimension: IEFFirst dimension: IEF Immobilized pH gradients (IPGs)Immobilized pH gradients (IPGs) IPG principle: pH gradient is generated by a limited number (6-8) of well defined chemicals (immobilines) which are co-polymerized with the acrylamide matrix. IPG allows the generation of pH gradients of any desired range ( broad, narrow, ultra-narrow) between pH 3 and 12. sample loading capacity is much higher. This is the method of choice for micropreparative separation or spot identification.Susana Cristobal Bioinformatik, 4p. KTH
  • 25. How many quantities of samples can beHow many quantities of samples can be loaded in one IPG strip?loaded in one IPG strip? (18 cm)(18 cm) Analytical run: 50-100 µg Micropreparative runs: 0.5-10 mg Susana Cristobal Bioinformatik, 4p. KTH
  • 26. Two dimensional electrophoresisTwo dimensional electrophoresis Running conditionsRunning conditions SampleSample::Caenorhabditis elegansCaenorhabditis elegans IEF: dry strips pH = 4-7IEF: dry strips pH = 4-7 Hydratation conditionsHydratation conditions:urea,:urea, thiourea, CHAPS, DTT,thiourea, CHAPS, DTT, ampholytes, iodoacetamine.ampholytes, iodoacetamine. Passive 15h.Passive 15h.  Isoelectrofocussing:Isoelectrofocussing: 200v 1h200v 1h 500v 1h500v 1h 1000v 1h1000v 1h 5000v 3h5000v 3h SDS-PAGE: 12%SDS-PAGE: 12% Silver stainingSilver staining Susana Cristobal Bioinformatik, 4p. KTH
  • 27. Detection technologies in proteome analysisDetection technologies in proteome analysis  General detection methods.  Differential display proteomics.  Specific detection methods for post- translational modifications. Susana Cristobal Bioinformatik, 4p. KTH
  • 28. General detection methods  Organic dye- and silver-based methods  Coomassie blue (R and G)  Silver  Radiactive labeling methods  Reverse stain methods  Flourescence methods Susana Cristobal Bioinformatik, 4p. KTH
  • 29. Differential display proteomicsDifferential display proteomics  Detection techniques:  Difference gel electrophoresisDifference gel electrophoresis (DIGE).(DIGE).  Multiplexed proteomics (MP)Multiplexed proteomics (MP)  Isotope-coded affinity taggingIsotope-coded affinity tagging (ICAT)(ICAT)  Differential gel exposure.Differential gel exposure. Susana Cristobal Bioinformatik, 4p. KTH
  • 30. Summary of protein expression profileSummary of protein expression profile analysisanalysis Susana Cristobal Bioinformatik, 4p. KTH
  • 31. Difference gel electrophoresis (DIGE)Difference gel electrophoresis (DIGE) (Unlu, 1997, electrophoresis 18, 2071) Susana Cristobal Bioinformatik, 4p. KTH
  • 32. Multiplexed proteomics (MP) technologyMultiplexed proteomics (MP) technology platformplatform (Steinberg, 2001, Proteomics 1,841, 2071) Susana Cristobal Bioinformatik, 4p. KTH
  • 33. Isotope-codedIsotope-coded affinity taggingaffinity tagging (ICAT) technology(ICAT) technology platformplatform (Smolka, 2002, Mol Cell Proteomics 1, 19-29) Very successful technique for identification of integral membrane proteins
  • 34. Differential gel exposure  Coelectrophoresis on 2DE of two protein samples.  In vivo labelling, using 14 C and 3 H -isotopes.  2DE separation.  Transfer on a PVDF membrane.  3 H /14 C ratio by exposure to two types of imaging plates.  Investigate changes in the rate of synthesis of individual proteins. (Monribot-Espagne, 2002, Proteomics 2, 229-240) Susana Cristobal Bioinformatik, 4p. KTH
  • 35. Image analysisImage analysis Software commomly used to manipulate the gel images:Software commomly used to manipulate the gel images: •Imagemaster TM •Melanie III TM •Other functions:Other functions: • QuantificationQuantification • AlignmentAlignment • ComparisonComparison • MatchingMatching • Synthetic image from the image of the sampleSynthetic image from the image of the sample Susana Cristobal Bioinformatik, 4p. KTH
  • 36. Example of data from differential displayExample of data from differential display proteomicsproteomics (Chevatier, 2000, Eur.J. Biochem. 267, 4624-4634) Susana Cristobal Bioinformatik, 4p. KTH
  • 37. Protein profiling in response to various treatments atProtein profiling in response to various treatments at two different time-pointstwo different time-points (Chevatier, 2000, Eur.J. Biochem. 267, 4624-4634) Susana Cristobal Bioinformatik, 4p. KTH
  • 38. General scheme of proteomic analysis
  • 39. Pick the protein gel spot from the gel Pick up the protein gel spot from gel • Manual • Automatic In-gel digestion: • Washing process • Dehydratation and drying • Trypsin digestion (50 ng trypsin, 37C 16h) • Extraction • Desalt and concentrate the peptide
  • 40. Identification methodsIdentification methods Identification of proteins by mass spectrometry:  Identification of proteins by amino acid composition after acid hydrolysis  Identification of proteins by amino acid sequencing
  • 41. FFlow chart for the analysis of proteomes by MSlow chart for the analysis of proteomes by MS (van Wijk, 2001, Plant Physiology 126, 501-508) Susana Cristobal Bioinformatik, 4p. KTH
  • 42. Identification of eluted protein spots by different MS approaches  Extraction of intact protein: (single peak)Extraction of intact protein: (single peak)  MALDI-TOF LINEAR mode  Passive elution of proteins.  Analyze in a linear MALDI-TOF MS.  Peptide mass FINGERPRINT:Peptide mass FINGERPRINT:  MALDI-TOF REFLECTRON mode  In situ tryptic digestion of spots.  Analyze in reflectron MALDI-TOF MS.  Fragments, SEQUENCE:Fragments, SEQUENCE:  LC-ESI MS/MS  Separation in a C18 column.  MS/MS analysis in a Q-TOF. Susana Cristobal Bioinformatik, 4p. KTH
  • 43. Comparison of MALDI-TOF and ESI-MS-MSComparison of MALDI-TOF and ESI-MS-MS approaches to protein identificationapproaches to protein identification MALDI-TOF MSMALDI-TOF MS Sample on a a slide (crystalline matrix). Spectra indicate masses of the peptide ions. Protein identification by peptide mass fingerprinting. ESI-MS-MSESI-MS-MS Sample in solution (high performance liquid chromatography). MS-MS spectra reveal fragmentation patterns. Protein identification by cross- correlation algorithms. Susana Cristobal Bioinformatik, 4p. KTH
  • 44. Schematic of the MALDI quadrupole time ofSchematic of the MALDI quadrupole time of flight instrumentflight instrument Advantages:  Mixture are analysed easily.  It is highly tolerant to contaminants.  High sensitivity. (picomol range)  Good accuracy in mass determination.  Quick and not expensive analysis. Disadvantages:  Low reproducibility and repeatability of single shot spectra. (Averaging )  Low resolution.  Matrix ions interfere in the low max range. Susana Cristobal Bioinformatik, 4p. KTH
  • 45. Comparison of MALDI-TOF and ESI-MS-MSComparison of MALDI-TOF and ESI-MS-MS approaches to protein identificationapproaches to protein identification MALDI-TOF spectrum Susana Cristobal Bioinformatik, 4p. KTH
  • 46. Peptides that span exon splices will be missed whenPeptides that span exon splices will be missed when matching uninterpreted MS-MS data to genomic DNAmatching uninterpreted MS-MS data to genomic DNA (Jyoti, 2001, Trends 19, supp ) Susana Cristobal Bioinformatik, 4p. KTH
  • 47. ESI-MS-MSESI-MS-MS Peptide sequencing by nano-electrosprayPeptide sequencing by nano-electrospray MSMS Susana Cristobal Bioinformatik, 4p. KTH
  • 48. 2DE gel Intact protein Experimental proteolytic peptides Experimental MS Theorectical MSTheoretical proteoly tic peptide s DNA sequen ce databas e Protein sequen ce databas e COMPUTER SEARCH Peptide identification using mappingPeptide identification using mapping fingerprint informationfingerprint information Susana Cristobal Bioinformatik, 4p. KTH
  • 49. Applications ?Applications ? • Cancer proteomics • Peptidomics: for profiling small proteins in the human fluids • Neuroscience • Toxicoproteomics: a new preclinical tool to revolutionary drug target discovery • Environmental pollution assessment Susana Cristobal Bioinformatik, 4p. KTH
  • 50. Example Applications of Proteomics • pecting the environment to identify proteins with desirable properties • To better understand the role of proteins in human disease processes • In anti-sports doping to catch drug cheats • Cancer proteomics • Peptidomics: for profiling small proteins in the human fluids • Neuroscience • Toxicoproteomics: a new preclinical tool to revolutionary drug target discovery • Environmental pollution assessment
  • 51. Colorectal cancer chemotherapy  Can we a priori determine which patients will benefit from chemotherapy? Acquire proteomic data Identify candidate biomarkers Validate biomarkers • All Stage C patients undergo chemo, yet only 50% need it • Of those that need it, who will benefit?
  • 52. Schedule of a proteomics experimentSchedule of a proteomics experiment Day 1: Sample preparation and IEF 1. Load protein sample onto IPG strip (IEF) 2. Run the IEF (about 24 hours) 3. Polyacrylamide gel casting Day 2: Equilibrium IPG strip and running SDS-PAGE 1. Remove IPG strip from IEF machine 2. Equilibrium IPG strip 3. Put IPG strip onto SDS-PAGE 4. Run the SDS-PAGE (overnight)Susana Cristobal Bioinformatik, 4p. KTH
  • 53. Day 3: Staining, image scanning and image analysis 1. Remove the gel from the cassette 2. Stain the gel by SYPRO Ruby or silver 3. Scan the gel image 4. Image analysis Day 4: In-gel digestion, MALDI-TOF and database search 1. Pick the protein gel spot from gel 2. In-gel digestion 3. Spot the sample onto MALDI chip 4. MALDI-TOF analysis 5. Database search Susana Cristobal Bioinformatik, 4p. KTH
  • 54. ??? Questions ?????? Questions ???

Editor's Notes

  1. ~30,000 genes = 300,000 to 1 million proteins when alternate splicing and post-translational modifications are considered. While a genome remains unchanged to a large extent, the proteins in any particular cell change dramatically as genes are turned on and off in response to environment. “ Functional Proteome” reflects the dynamic nature fo the proteome.
  2. Proteomics is high capacity global analysis of gene expression proteomics parallels and complements the related field of genomics Genomics, ie. DNA sequence information is static-a snapshot proteomic information is directed more to the dynamic life cycle and changes in protein populations associated with growth, disease, death , and the interactions between proteins and groups of proteins .
  3. Proteomics is high capacity global analysis of gene expression proteomics parallels and complements the related field of genomics Genetic information is static while the protein complement of a cell is dynamic Genomics, ie. DNA sequence information is static-a snapshot proteomic information is directed more to the dynamic life cycle and changes in protein populations associated with growth, disease, death , and the interactions between proteins and groups of proteins . Examples of post-translation modifications: Phophorylation glycosylation
  4. Can discriminate among disease subtypes that are not recognizable using traditional pathological criteria.
  5. - Term ”proteome” , was first introduce in 1995 (by Wasinger). Proteome can be seen as the end product of a genome . While genome is completely static, the proteome is a higly dynamic entity , as protein content of a given cell will vary with respect to changes in the surrounding environment, physical state of the cell, stress, etc. Different cell type within an organism will have different proteomes, while the genome is held relatively constant. Study of less abundant proteins become difficult becuase is the protein world there is not a comporable tool of PCR for amplification of proteins. The active product of a gene is a protein, what is important for the cell is the level of activity of this protein and its influence in the metabolic flux . Sometime mRNA level can be correleted with protein level but for many cases transcriptomics is an unsufficient short-cut to study functional aspects of the genomes. Importance of posttranslational modification in protein activity. - Proteomics may appear as the preferred tool for providing an understanding of how genemos function
  6. In any large scale analytical process like proteomics we should consider two phases: Separation of biomolecules of interest Molecular characterization Separation biomolecules : Problem of complexity in the sample preparation, how to resolve thousands of proteins. - Extraction of protein sample cell cultive ( possible in prokaryotes and low eukaryotes cells) organelle isolation ( high eukaryotes other alternatives, reduce the complesity by organelle isolation, that is the case in proteomics of peroxiosme) affinitty purified sample - Two dimensional electrophoresis Molecular characterization: - Detection technology: Identify proteins: MS Differential expression profile analysis
  7. A . Separation of individual proteins by fully denaturing 2-DE with immobilized pH gradient strips in the first dimension and SDS-PAGE in the second dimension. B . Separation of protein complexes by non-denaturing 2-DE (such as blue-native-PAGE), followed by SDS-PAGE in the second dimension. C . Purification of protein complexes by immuno-affinity chromatography , followed by SDS-PAGE. D . Multidimensional chromatography and chromatogram using the absorption at 215 nm for detection. E . Organic solvent fractionation for separation of complex protein mixtures of hydrobhobic membrane proteins. The numbers refer to different organic solvent mixtures; common solvents are aceton, isopropanol, chlorophorm, and methanol.
  8. Rupture plasma membrane to prepare tissue/ cell homogenates: high speed blender sonication tissue homogenizer osmotic shock
  9. Figure 5-26. Immunological purification of clathrin-coated vesicles. (a) A suspension of membranes from rat liver is incubated with an antibody specific for clathrin, a protein that coats the outer surface of certain cytoplasmic vesicles. To this mixture is added a suspension of S. aureus bacteria whose surface membrane contains protein A. Specific binding of proteinA to the constant region of antibodies bound to the clathrin-coated vesicles links the vesicles to the bacterial cells. The vesicle-bacteria complexes then are recovered by low-speed centrifugation. (b) A thin-section electron micrograph of clathrin-coated vesicles bound to these bacteria. [See E. Merisko, M. Farquahr, and G. Palade, 1982, J. Cell Biol. 93: 846; part (b) courtsey ofG. Palade.]
  10. In the case of proteomics, the proteins have to be chemically resolved by a separation method and this is a major issue for proteomics. proteins show widely different structures and chemical properties. They also vary with respect to the intracellular abundance in different cell types or conditions. As a consequence, it is almost impossible to find an anlytical technique suitable for all proteins and able to resolve and separate the potentially hundreds of thousands of protein forms present in a particular cell. The only technique available with sufficient resolviong power is 2DE. CONCEPTS: Solubilization of proteins IEF/SDS-PAGE Detection of proteins
  11. Goals: Breaking macromolecular interaction (disulfide bonds). Preventing any artefactual modification of polypeptides in the solubilization medium (inactivate enzymes like proteases) Removal of substances that may interfere with 2DE ( salt, lipids, polysaccharides) Keeping proteins in solution during 2DE process. There is no universal solubilization protocol. Standard urea-reducer-detergent mixtures usually achieve disruption of disulfide bonds and non-covalent interactions Key issues for correct solubilization is the removal: Interfering components Blocking of protease actions Disruption of infrequent interactions (ionic bonds)
  12. Two dimesional polyacrylamide gel electrophoresis , in which proteins are separated according to charge (pI) by isoelectric focusing (IEF) in the first dimension and according to size in the second dimesion (M) by SDS-PAGE, has an unique capacity for the resolution of complex mixtures of proteins. Old technique with problems of irreproducibility of 2D gels In the first dimension IEF : generated by conventional method using carrier ampholytes CA-IEF due to pH gradient instability with prolonged focusing time. Batch to batch variability The problems were overcome by the introduction of immobilized pH gradients for IEF. (In 1982) In the second dimesion : batches of ready-made gradient gels are available in the market, avoid manual manipulation, manual gradients.
  13. IPG principle : pH gradient is generated by a limited number (6-8) of well defined chemicals (immobilines) which are co-polymerized with the acrylamide matrix. IPG allows the generation of pH gradients of any desired range ( broad, narrow, ultra-narrow) between pH 3 and 12. sample loading capacity is much higher. This is the method of choice for micropreparative separation or spot identification.
  14. Dye and silver staining methods: Coomassie: - low cost, simple. - Resolution:limit od detction: 8-10 ng/ 30-100 ng. Linear response - regressive staining - progressive staining Silver: based on saturation gels with silver ions, washing the less tighly bound ions out of the gel and reducing protein bound metal ions to form metalic silver. -Fixation with aldehides are incompatible with MS analyze. Radiolabelling: incorporation of H,C,S,p,P and I. Into proteins. - Detection by autoradiographyot phorography - use in in vivo metabolic experiments, rate of protein synthesis (s) Reverse stain : detection limit 10-20 ng, range 10-100 ng. Compatible with MS - potassium chloride - copper chloride - zinc chloride Flouresce-based staining methods : detection limit 4-8 ng. Sypro red, orange and tangerine . Excitation: 300 nm Documentation achieved in an UV atransiluminator. 470, 550, 490 nm. Emission: 570, 630, 640 nm Sypro ruby :: Excitation 300 nm. compatible with MS. compatible with MS. 1000 fold range liniarity reproducibility in quatification
  15. Proteomics are often based upon the comparison of different protein profiles. There are currently three different approaches:DiGE, MP, ICAT. Differential display proteomics will allow us to observe changes in the protein expression between both conditions.
  16. This image depicts the differents stages in this technique.
  17. Principle : Two different samples are derivatized with two different fluorophores , combined and then run on a single 2D gel. Proteins are detected using a dual laser scanning device or xenon arc-based instrument equipped with different excitation/emission filters in order to generate two separate images. The images are then matched by a computer-assisted overlay method, signals are normalized S pots are quantified. Differences in protein expression are identified by evaluation of a pseudo-colored image and data spreadsheet. DIGE technology can maximally evaluate three different samples using Cy2-, Cy3- and Cy5-based chemistries. Dyes: Succinimidyl esters of cyanine. DIGE allow three sample to separate in under identiacl electrophoretical conditions, simplify the process of register and matching. Requirement: 1-2% of lysine residues be flouresce modified, to mantain solubility in the electrophoresis. Problems: Detection limits : less sensity than silver. - Sypro Ruby detect 40% more - Post-stain for MS analysis.
  18. Principle : It is designed to allow parallel determination of protein expression levels as well as certain functional attributes of the protein ( glycosolation, drug.binding), post-translational modification. Two different samples are run on two different 2D gels. Gels are stained for a particular functional attribute, such as glycosylation, and then imaged. Gels are then stained for total protein expression using SYPRO Ruby protein gel stain and imaged again. The images resulting from glycoprotein staining and the images resulting from total protein staining are then matched by computer-assisted rubber sheeting and overlay methods . S ignals are normalized (if necessary) and spots are quantified. Differences in glycosylation and protein expression are identified by evaluation of pseudo-colored images and data spreadsheets. Registration of total protein profiles with glycosylation patterns is readily accomplished by direct superimposition of images from the same gel. MP technology can evaluate an almost limitless number of 2D gels with respect to two or three different attributes (protein expression, post-translational modification, drug-binding capability, drug-metabolizing capability).
  19. Distinguishing between two populations of proteins using isotope ratios. Reagents: protein reactive group (to thiol group in cysteine residues, an ethylene glycol linker region and a biotin tag. Two isotope tags are generated by using linker that contains: - dO 8H, light reagent - d8 8 Deuterium, heavy reagent Protocol: Two different samples are derivative with two different ICAT reagents; heavy (reiterated) and light (normal). The samples are combined and then run on a single 2D gel. – Proteins are detected using a sensitive mass spectrometry-compatible protein stain, such as modified silver stain or SYPRO Ruby protein gel stain. Proteins are excised from the gel, enzymatically digested in the gel matrix, extracted and analysed by mass spectrometry. Proteins are identified by peptide mass fingerprinting using a single stage mass spectrometer or by collision-induced dissociation of selected peptides and database sequence searching. Differences in protein expression between individual proteins in the two samples are determined by evaluation of the ratio of signal intensities for the isotopically normal and heavy forms of a specifically tagged peptide. As illustrated, every spot in the profile must be evaluated by mass spectrometry and cysteine-containing peptides identified. Alternatively, three gels can be run containing heavy isotope-labelled material, light isotope-labelled material and a mixture of the two. The first two gels are used to generate difference maps using a sensitive protein stain and computer-based matching software. The third gel is then used to excise differences identified from the first two gels.
  20. Insets from Fig. 2 S howing altered expression of two cleavage products of actin (spots 58 and 59), vimentin (spot 51) and ATP synthase subunit (spot 49) after treatment with nafenopin (Naf).
  21. Schematic of the 2D gel protein-expression patterns of rat primary hepatocyte cultures representing the maps of the proteins found to change after treatment nafenopin ( ), TNF (X) or EGF ( ) at (A) 6 h or ( B) 24 h. (C) Collated protein differences covering both time points. (D) Venn diagram showing the number of proteins with altered expression upon stimulation with one or more treatments.
  22. This is a summary of the features of the two principal approaches to MS analysis of peptide mixtures. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) MS employs laser energy to generate peptide ions from co-crystallized mixtures of peptides and ultraviolet-absorbing organic acids. MALDI-TOF analyses yield mass measurements of peptides, which can then be searched against databases with computer-assisted search algorithms to identify the proteins from which the peptides were derived. This technique, termed peptide mass fingerprinting , is a highly robust, useful means of rapidly identifying proteins, particularly in organisms for which completed genome sequences or extensive protein sequence databases are available ( 4 , 5 ). However, this approach becomes increasingly difficult in higher organisms for which reliably annotated genome and protein sequences are unavailable. Moreover, the increasing predominance of gene paralogs (highly homologous genes) in higher organisms ( 6 ) makes it more difficult to unambiguously identify proteins by this technique ( 7 ).
  23. Pick up the protein gel spot from gel MANUAL Automatic In-gel digestion: Why? Peptides are preferred for Ms analysis, since proteins cannot be eluted from gels without detergents like SDS, ( which is detrimental to mass spectrometry) large proteins are usually heterogenous and possess no single molecular weight that can be releted to the corresponding entry in a sequnece database. all tubes, etc eashed with metanol, rinse with milliQ water, metanol and dry) Washing process Dehydratation and drying Trypsin digestion (50 ng trypsin, 37C 16h) Extraction ( acetonitile/TFA. Disolve the petide in 20 microl of 0.1% TFA) Desalt and concentrate the peptide
  24. The protein spots or bands are excised, SDS, stain, and salts are removed, and the proteins are digested by a site-specific protease that is usually trypsin . Peptides subsequently are extracted and a small fraction is used to determine the mono-isotopic peptide ion masses by MALDI-time-of-flight (TOF) MS. The experimental peptide ion masses are then searched against proteins predicted from genomic sequence data. If no positive identification can be achieved, (partial) - sequences of the remaining peptides are determined by MALDI-TOF post-source decay (PSD)/MS or - ESI-MS/MS. The sequence tags (partial sequence, together with the parent- and fragment ion masses) are used to search against EST or annotated genomic sequence data. In the case of sequenced genomes it usually unumbiguous identification.
  25. Illustrate the identification of eluted protein spot by three different approaches Extraction of intact protein Sample load on a plate in a 3 layers method Peptide fingerprint In-gel digestion : The preferred method of proteolytic protein digestion today is in-gel digestion for its better overall sensitivity. O.5 pmol (blot) / 125 fmol (in-gel) Mix sample solution with matrix (a-ciano-4-hydroxycinnamic acid) Peptide masses were searchedd against Swiss-PROT and trEMBL databases - Peptident program http://www.expasy.ch/tools/peptident.html MS-Fit program http://prospector.ucsf.edu/ucsfhtml3.4/msfit.htm Peptide sequence Tryptic fragments were separated by LC and analyzed by MS/MS Q-TOF instrument.
  26. The analyte is mixed with a substance called matrix, which has a very high absorption in the UV region. About 2 ml of the sample is put in a metalic holder. After the evaporation of the solvent, the holder is put into the mass spectrometer and a high voltage is applied. A UV –laser shoot deposits its energy on the sample, which is mainly absorved by the matrix molecules the desorption process occurs. This process generates matrix and analyte ions that have inital position and velocity distributions. The high electric voltage accelerates these ions. All the ions get approximately the same kinetic energy. High mass molecules have lower velocities. After the ion source, the ions flight through a field-free region, pass an electrostatic ion mirror and drive to the detector. The total time of flight is measured and is related to mass/charge ratio of the molecules.
  27. Peptides that span exon splices will be missed when matching uninterpreted MS ¯ MS data to genomic DNA In most eukaryotes, genes are divided into : protein-coding exons (red) and non-coding introns (orange). After transcription to RNA, the coding sequences are spliced together before translation. Hence, when the mature protein is digested for analysis by mass spectrometry, a proportion of the peptides will correspond to coding sequences that span exon splice sites.
  28. Without applications, proteomics is just technology, To ilustrate some applications: - Cancer proteomics - Peptidomics: for profiling small proteins in the human fluids - In Neuroscience -Toxicoproteomics: a new preclinical tool to revolutionary drug target discovery