1. Proteomic Analyses by Mass Spectrometry
Iris Finkemeier
MPI Plant Breeding Research
14 January 2014

2. This talk Concepts of MS-based proteomics The three main applications:
Description & identification
Quantitation
Interaction

3. What‘s a proteome?

4. Genes to proteins Gene Transcript Protein (mRNA) Translation
Transcription
Translation
TRANSCRIPTOME
PROTEOME
(mRNA)

5. “The proteome is the entire set of proteins expressed by a genome, cell, tissue or organism at a certain time.”

6. What‘s proteomics?

7. Proteomics
“The goal of proteomics is a comprehensive, quantitative description of protein expression and its changes under
the influence of biological perturbations such as disease
or drug treatment.”
From: N. Leigh Anderson and Norman G. Anderson: „Proteome and proteomics: New technologies,
new concepts, and new words“, ELECTROPHORESIS 19, 1853 – 1861 (1998)

8. Lack of correlation between transcript and protein
AGPase
Fd-GOGAT

9. Proteomics at the „sweet spot“
e.g. 20,000 genes
Spliceforms
(~ 5x increased complexity)
Post-translational modifications
(> 200 PTMs known, 10x increased complexity)
Hoog & Mann, Annu Rev Genom Human Genet (2004)

10. How complex is complex?
Human genome: predicted protein coding genes
230 cell types, body fluids
Spliceforms
Post-translational processing and modifications
Interactions and protein complexes
Human proteome project (launched 2011)!

11. Protein coverage & technological innovation
Bärenfaller et al., Nature (2008)
Arabidopsis proteome
> proteins identified
Mascot
LTQ-FT
Synapt
Shotgun proteomics
Orbitrap
Ahrens et al., Nat Rev Mol Cell Biol (2010)

12. Proteins -reminder of the basics-

13. α-Amino acids
The 20 amino acids specified by the genetic code have the general formula:
NH2
H C R
COOH
The size, polarity and hydrogen bonding properties of the side chain (R) attached to the α-carbon atom confer unique properties on each amino acid.
L-alanine

14. Aliphatic non-polar side chains
The amino acids in this group have side chains with no affinity for water.
These amino acids tend to be found in the hydrophobic core of water soluble proteins, or in contact with lipids in membrane proteins.

15. Uncharged polar side chains
The electronegative oxygen atom confers a degree of polarity on the side chains of asparagine, glutamine, serine and threonine, allowing the formation of hydrogen bonds.
The sulphur atom is only weakly electronegative and the cysteine side chain does not form hydrogen bonds.
These amino acids will often be found on the surface of a soluble protein, but their weak polarity means that they can also be easily stabilised in the interior of a folded protein.

16. Charged polar side chains
Some side chains ionise at normal physiological pH values. +
Amino acids with charged side chains are often found on the surfaces of soluble proteins. H
Charged side chains only occur in hydrophobic regions if they can form an ion pair with an oppositely charged side chain.

17. Aromatic side chains
The aromatic side chains are predominantly non-polar, but the –OH group in tyrosine and the NH group in tryptophan allow these side chains to form H-bonds.
Phenylalanine has the most non-polar side chain of all the amino acids and hence the strongest preference for a non-aqueous environment.
This preference can be quantified and it decreases in the order:
Phe > Met > Ile > Leu > Val > Cys > Trp > Ala > Thr > Gly >
Ser > Pro > Tyr > His > Gln > Asn > Glu > Lys > Asp > Arg.

18. The peptide bond
Condensation of two amino acids results in a peptide bond:
NH2 CH C OH R1 O R2
NH2 CH C
N CH C OH H + →
The condensation process is energy consuming (~160 kJ mol-1) and it can be repeated many times to produce polypeptides containing hundreds of amino acids. C N H O Cα Φ Ψ
The peptide bond has partial double bond character, preventing free rotation about the carbon-nitrogen axis:

19. Average length of proteins)

20. 1. Classical gel-based proteomics

21. 2-D gel electrophoresispI
Up to 1000 proteins can be reproducibly resolved on a single gel 94 66 43
kDa
The advent of precast IEF gels with IPG means that we can no run highly reproducible first dimensions
This is a typical 2D gel showing 800 ug of total protein from an Arabidopsis cell suspension culture stained with colloidal coomassie blue
You can see that up to 1000 proteins can be resolved on a single gel and many more can be seen if you first fractionate your protein sample and runt the fractions on separate gels. 30 20 14

22. 2D gel electrophoresis 1. Isoelectric focusing COOH COO- + H+
Alkaline pH
COOH COO- + H+
NH3+ NH2 + H+
Acidic pH
Generally 2D gels use isoelectric focusing in the first dimension and conventional SDS-PAGE in the second.
IEF takes advantage of the fact that the ionisation of side groups on proteins is dependent upon pH.
Thus for the carboxylic acid group shown here, at high pH it will tend to dissociate and will be negatively charged and at low pH the equilibrium will be shifted towards the protonated uncharged form.
Different groups have different dissociation constants and their ionisation state will vary accordingly at any given pH
A particular protein will have a unique isoelectric point, the pH at which it will have an equal number of +ve and –ve charged groups and will therefore carry no net charge
We can separate proteins according to their pI by electrophoresing them through a gel that contains a pH gradient.
Below its pI, a protein will be +ve chgd and will migrate to the cathode. Above its pI, -ve and to anode.
Proteins will therefore congregate at the pH that represents their pI where they carry no net charge.
pH gradient 3 10 + -
Anode (+)
Cathode (-)

23. 2D gel electrophoresis 2. SDS-polyacrylamide gel electrophoresis - - -
Cathode (-)
polyacrylamide gel
Anode (+)

24. Separation by charge
1st Dimension (IEF)
2nd Dimension
SDS-PAGE
Separation by size

25. analysis of 2D-gels
3 replicate gels for the control and each treatment were run
Gels were imaged using a CCD-based imaging system
Images were analysed using PDQuest software.
3. Data Analysis
1. Spot detection & quantitation
2. Spot matching
Statistical tests
t-test
Mann-Witney signed rank test
Wilcoxon paired sample test
Partial least squares test

26. Proteomics analysis of protein complexes?

27. Blue native PAGE of mitochondrial respiratory complexes
1-Dimension

28. Workflow Cell fractionation Membrane isolation
Solubilization of protein complexes
BN-PAGE
Denaturation of protein complexes
SDS-PAGE

29. Dodecyl-ß-D-maltoside
Detergents
Digitonin
Dodecyl-ß-D-maltoside
glu
gal
xyl

30. Effect of detergent concentration on membrane solubilization
Decreasing molecular mass of protein complexes
1.1 mM ß-DM or
4.5 mM Digitonin
4.5-9 mM ß-DM or 9-18 mM Digitonin
Increasing concentration of detergent micelles

31. Blue native PAGE of mitochondrial respiratory complexes
1-Dimension

32. Comparison of different staining methods after BN/SDS-PAGE : one gel, three stains
Coomassie
Silver
Fluorescence

33. CyDye labeling of membrane protein complexes
488 nm Ex Em
Cy5
Cy3
Cy2
532 nm
633 nm

34. 2D BN/SDS-DIGE of plastid membrane complexes
condition I
BN-PAGE
SDS-PAGE
condition II
BN-PAGE
SDS-PAGE +
condition I versus condition II
BN-PAGE
SDS-PAGE =

35. Protein identification by mass spectrometry!

36. Gel-based vs. gel-free proteomics
1D / 2D gel
digest 
Immunodetection
Spot excision
LC-MS/MS
αAOX
N-terminal sequencing,
mass spectrometry
Ponceau S
Database search (genome!!!)
Protein ID
Protein ID

37. Gel-based vs. gel-free proteomics
1D / 2D gel
digest
1 gel
1 sample 
> 1000 protein IDs
per sample
1 sample per spot/protein ID
Immunodetection
Spot excision
LC-MS/MS
1 blot
1 protein ID
αAOX
N-terminal sequencing,
mass spectrometry
Ponceau S
Database search
1000 hybrid.,
1000 antibodies!
1000 samples!
Protein ID
Protein ID

38. Identification of proteins by mass spectrometry analysis
Bottom-up proteomics
(Top-down proteomics)

40. A very short LC-MS/MS introduction
Liquid chromatography (LC)
Tandem mass spectrometry (MS/MS)
digest

41. (separation/UV detection)
Coupling of HPLC and MS
Sample
HPLC
(separation/UV detection) MS
TIC = total ion count

42. Basic Components of a Mass Spectrometer
ion source mass analyzer detector
generate ions ion separation ion analysis
ESI
MALDI
Quadrupol
Iontraps
TOF (Time of Flight)
Used for Peptides and Proteins

43. What LC-MS/MS does ECCHGDIIECADDR ECCHGDIIECADDR ECCH GDIIECADDR CADDR
fragmentation
measure
masses

44. Identifying Proteins by peptide mass fingerprinting (PMF)
2. Translate
3. Predict trypsin cleavage sites
Genomic DNA
1. Identify genes
Predicting tryptic-fragment masses
4. Calculate theoretical masses of tryptic fragments
OBSERVED
THEORETICAL

45. Example: BSA

46. Trypsin cleavage site prediction
(web.expasy.org/peptide cutter)

49. How can Peptides and Proteins Be Ionized?
Elektrospray-Ionisation
(ESI)
John B. Fenn
Matrix-Assisted Laser
Desorption/Ionization
(MALDI)
Koichi Tanaka
Franz Hillenkamp
Michael Karas

52. MS/MS Provides Information About Peptide Sequences
Q Q Q Q Detector
Support
Quadrupole
1st Mass
Quadrupole
collision
chamber
2nd Mass
Quadrupole
m/z = constant fragmentation m/z scanning

53. Important features of a mass spectrometer
Resolution
Accurate detection
Scan speed
Sensitivity
Dynamic range

54. Important features of a mass spectrometer
Resolution
Accurate detection
Scan speed
Sensitivity
Dynamic range

56. Peptide Fragmentation (MS2, tandem mass spectrum)

57. MS/MS spectrum interpretation & database search

58. A simple chromatogram
separate

59. What a real, complex sample looks like…

60. What a real, complex sample looks like…
retention time

61. What a real, complex sample looks like…
~ 100 putative peptides within 1 min

62. Coverage? How many proteins can you detect?
In a 4 h run on the newest generation instrument:
peptides
4.000 proteins
Sample requirement: 4 µg peptide sample
Sample preparation time: 6h plus digest time

63. Acquired peptide masses can be analysed by MASCOT peptide Mass Fingerprint analysis

68. This talk Concepts of MS-based proteomics The three main applications:
Description & identification
Quantitation
Interaction

69. Protein atlas: mapping complete proteomes

70. The Arabidopsis proteome atlas 1.0
~ 50% coverage

71. Finding new genes or gene models
Bärenfaller et al., Nature (2008)

72. Finding new genes or gene models
Bärenfaller et al., Nature (2008)

73. Finding new genes or gene models
Bärenfaller et al., Nature (2008)

74. Finding new genes or gene models
Bärenfaller et al., Nature (2008)

75. Exploring sub-proteomes at fine scale
mapping of 2000 root proteins
700 specific for single cell type

76. Most data are fully accessible

77. Mapping post-translational modifications
affinity-based enrichment
digest P P P P
LC-MS/MS
Database search
Phospho-protein ID

78. Mapping post-translational modifications
Number of phosphoproteins:
5.460
Total no. of phosphopeptides
34.700
No. of unique phosphopeptides:
13.205
Other MS-accessible PTMs:
Acetylation
Oxidation
Nitrosylation
Ubiquitination
Glycosylation …

79. This talk Concepts of MS-based proteomics
The three challenges and potentials:
Description & identification
Quantitation
Interaction

80. - + Western-blots are quantitative. For 100 proteins:
treatment
αProteinX
For 100 proteins:
100 antibodies Many gels, blots, workhours, €
Sometimes there is no antibody!

81. MS is not inherently quantitative
1 : 1
2 : 1
intensity
mass

82. MS is not inherently quantitative
digest
LC-MS/MS
mass
intensity
Peptides have…
different physicochemical properties
different „flyability“ in MS
Intensity of different peptides is not a direct measure of their abundance!
Electrospray ionization

83. Solutions of quantitative proteomics
Computational solutions (on protein level)
Label-free analysis, iBAQ
Intermediate accuracy, stable conditions required
Isotopic labeling

84. Stable isotopic labeling
two samples
with isotopically labeled proteins (e.g. 13C, 15N)
1:3
„light“
„heavy“
1:3
intensity
ratio calculation
and quantification
m/z

85. Quantifying peptide abundance by comparison of the intensity of MS1 spectrum
Protein
peptide
ratio H/L
Protein 1 1
1.04 2
50.6
Protein 1, peptide 1
Protein 1, peptide 2
light
heavy
heavy
light

86. Isotopic labeling Absolute, add known amount of:
Synthetic AQUA peptides
Purified isotopically labelled proteins
Relative, compare between samples:
Metabolic labeling
Chemical labeling

87. SILAC-Based Proteomics Analysis
SILAC: Stabile Isotope Labeling with Amino Acids in Cell Culture
Biological Question:
How does the expression level of cellular proteins change during differentiation?
Addressing this Question with SILAC:
Differential Isotopic labeling of the cells in differentiated and non-differentiated stage.
Separate and analyze the proteins by MS and MS/MS.

88. Isotope Labeled Amino Acids Commonly used
in SILAC Experiments
Lysine Lysine Lysine Lysine-8
Arginine Arginine Arginine Arginine-10

89. Metabolic labeling: SILAC
Arg, Lys light
Arg, Lys heavy
SILAC: Stable Isotope Labeling with Amino Acids in Cell Culture
Mix lysate or cells 1:1
digest
LC-MS/MS
m/z
intensity
ratio calculation
and quantification

90. Metabolic labeling in plants
m/z
intensity
ratio calculation
and quantification

91. Chemical labeling: dimethylation as example
addition of two methyl groups to all α- and ε-amino groups
Boersema et al., Nature Protocols, 2009.

92. Stable isotope dimethyl labeling
Boersema et al., Nature Protocols, 2009.

93. Stable isotope dimethyl labeling
Boersema et al., Nature Protocols, 2009.

94. Labeling strategies: an overview
Bantscheff M. et al., Anal Bioanal Chem (2007)

95. Yeast as an example pheromone response
3824 proteins identified and quantified
67% ORF „coverage“
80% expressed, 800 dubious ORFs
~82% real coverage
Around 75 samples and 300h measuring time!

96. Rapid technological progress…
2011: Thermo: Q-Exactive Orbitrap
Waters: Synapt G2

97. … leads to new depths in coverage.
Nagaraj et al., MCP, 2012
85-90% coverage per 4h run!

98. Proteome coverage in yeast
all proteins in sample
Number of protenis
proteins identified
& quantified
Protein concentration

99. Larger proteome, less coverage
Bantscheff M et al., Anal Bioanal Chem (2007) 389:1017–1031
HeLa proteome (10000 proteins) is largely covered but with lots of samples and measuring time.

100. Faster and reliable alternatives for selected proteins?
Problem like in the early days of microarrays
Incomplete coverage
low abundant transcripts/proteins are hard to quantify reliably
What would the molecular biologists do?
quantitative real-time PCR!

101. The qPCR in proteomics: SRM and MRM
SRM - selected reaction monitoring
MRM - multiple reaction monitoring
„Targeted proteomics“ Nature method of the year 2012!

102. Why SRM is appealing
LC-MS/MS
Database search
 Selectivity!

103. SRM: the basic idea
Gilette & Carr, Nature Methods, 2013

104. SRM: the basic idea
Gilette & Carr, Nature Methods, 2013

105. Targeted proteomics advantages: fast cheaper & more robust instruments
highly sensitive
promising for clinical applications!
disadvantages:
optimisation & standards needed
limited to a max. of 100 proteins per run

106. This talk Concepts of MS-based proteomics
The three challenges and potentials:
Description & identification
Quantitation
Interaction