1. Proteomics & Mass Spectrometry
Nathan Edwards
Center for Bioinformatics and Computational Biology

2. Outline Proteomics Mass Spectrometry Protein Identification
Peptide Mass Fingerprint
Tandem Mass Spectrometry

3. Proteomics Proteins are the machines that drive much of biology
Genes are merely the recipe
The direct characterization of a sample’s proteins en masse.
What proteins are present?
How much of each protein is present?

4. Gene / Transcript / Protein
Systems Biology
Establish relationships by
Choosing related samples,
Global characterization, and
Comparison.
Gene / Transcript / Protein
Measurement
Predetermined
Unknown
Discrete (DNA)
Genotyping
Sequencing
Continuous
Gene Expression
Proteomics

5. Samples Healthy / Diseased Cancerous / Benign
Drug resistant / Drug susceptible
Bound / Unbound
Tissue specific
Cellular location specific
Mitochondria, Membrane

6. 2D Gel-Electrophoresis
Protein separation
Molecular weight (MW)
Isoelectric point (pI)
Staining
Birds-eye view of protein abundance

7. 2D Gel-Electrophoresis
Bécamel et al., Biol. Proced. Online 2002;4:

8. Paradigm Shift
Traditional protein chemistry assay methods struggle to establish identity.
Identity requires:
Specificity of measurement (Precision)
Mass spectrometry
A reference for comparison (Measurement → Identity)
Protein sequence databases

9. Mass Spectrometer Ionizer Sample Mass Analyzer Detector MALDI+ _
Mass Analyzer
Detector
MALDI
Electro-Spray Ionization (ESI)
Time-Of-Flight (TOF)
Quadrapole
Ion-Trap
Electron Multiplier (EM)

10. Mass Spectrometer (MALDI-TOF)
UV (337 nm)
Microchannel plate detector
Field-free drift zone
Source
Pulse voltage
Analyte/matrix
Ed = 0
Length = D
Length = s
Backing plate
(grounded)
Extraction grid
(source voltage -Vs)
Detector grid -Vs

11. Mass Spectrum

12. Mass is fundamental

13. Peptide Mass Fingerprint
Cut out
2D-Gel Spot

14. Peptide Mass Fingerprint
Trypsin Digest

15. Peptide Mass FingerprintMS

16. Peptide Mass Fingerprint

17. Peptide Mass Fingerprint
Trypsin: digestion enzyme
Highly specific
Cuts after K & R except if followed by P
Protein sequence from sequence database
In silico digest
Mass computation
For each protein sequence in turn:
Compare computer generated masses with observed spectrum

18. Protein Sequence
Myoglobin - Plains zebra GLSDGEWQQV LNVWGKVEAD IAGHGQEVLI RLFTGHPETL EKFDKFKHLK TEAEMKASED LKKHGTVVLT ALGGILKKKG HHEAELKPLA QSHATKHKIP IKYLEFISDA IIHVLHSKHP GDFGADAQGA MTKALELFRN DIAAKYKELG FQG

19. Protein Sequence
Myoglobin - Plains zebra GLSDGEWQQV LNVWGKVEAD IAGHGQEVLI RLFTGHPETL EKFDKFKHLK TEAEMKASED LKKHGTVVLT ALGGILKKKG HHEAELKPLA QSHATKHKIP IKYLEFISDA IIHVLHSKHP GDFGADAQGA MTKALELFRN DIAAKYKELG FQG

20. Peptide Masses 1811.90 GLSDGEWQQVLNVWGK 1606.85 VEADIAGHGQEVLIR
LFTGHPETLEK
HGTVVLTALGGILK
KGHHEAELKPLAQSHATK
GHHEAELKPLAQSHATK
YLEFISDAIIHVLHSK
HPGDFGADAQGAMTK
ALELFR

21. Peptide Mass Fingerprint
YLEFISDAIIHVLHSK
GLSDGEWQQVLNVWGK
GHHEAELKPLAQSHATK
HGTVVLTALGGILK
HPGDFGADAQGAMTK
VEADIAGHGQEVLIR
KGHHEAELKPLAQSHATK
ALELFR
LFTGHPETLEK

22. Mass Spectrometry Strengths Weaknesses Precise molecular weight
Fragmentation
Automated
Weaknesses
Best for a few molecules at a time
Best for small molecules
Mass-to-charge ratio, not mass
Intensity ≠ Abundance

23. Sample Preparation for MS/MS
Enzymatic Digest
and
Fractionation

24. Single Stage MS MS

25. Tandem Mass Spectrometry (MS/MS)
Precursor selection

26. Tandem Mass Spectrometry (MS/MS)
Precursor selection +
collision induced dissociation
(CID)
MS/MS

27. Peptide Fragmentation
Peptides consist of amino-acids arranged in a linear backbone.
N-terminus
H…-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH
Ri-1 Ri
Ri+1
C-terminus
AA residuei-1
AA residuei
AA residuei+1

28. Peptide Fragmentation

29. Peptide Fragmentationbi
yn-i
yn-i-1
-HN-CH-CO-NH-CH-CO-NH- Ri
CH-R’
i+1 R”
i+1
bi+1

30. Peptide Fragmentation
Peptide: S-G-F-L-E-E-D-E-L-K MW
ion 88 b1
S GFLEEDELK y9
1080
145 b2
SG FLEEDELK y8
1022
292 b3
SGF LEEDELK y7
875
405 b4
SGFL EEDELK y6
762
534 b5
SGFLE EDELK y5
633
663 b6
SGFLEE DELK y4
504
778 b7
SGFLEED ELK y3
389
907 b8
SGFLEEDE LK y2
260
1020 b9
SGFLEEDEL K y1
147

31. Peptide Fragmentation88
145
292
405
534
663
778
907
1020
1166
b ions S G F L E E D E L K
1166
1080
1022
875
762
633
504
389
260
147
y ions
100
% Intensity
m/z
250
500
750
1000

32. Peptide Fragmentation88
145
292
405
534
663
778
907
1020
1166
b ions S G F L E E D E L K
1166
1080
1022
875
762
633
504
389
260
147
y ions y6
100 y7
% Intensity y5 b3 b4 y2 y3 y4 b5 y8 b6 b8 b7 b9 y9
m/z
250
500
750
1000

33. Peptide Identification
Given:
The mass of the precursor ion, and
The MS/MS spectrum
Output:
The amino-acid sequence of the peptide

34. Peptide Identification
Two paradigms:
De novo interpretation
Sequence database search

35. De Novo Interpretation
100
250
500
750
1000
m/z
% Intensity

36. De Novo Interpretation
100
250
500
750
1000
m/z
% Intensity E L

37. De Novo Interpretation
100
250
500
750
1000
m/z
% Intensity E L F KL
SGF G D

38. De Novo Interpretation
Amino-Acid
Residual MW A
Alanine M
Methionine C
Cysteine N
Asparagine D
Aspartic acid P
Proline E
Glutamic acid Q
Glutamine F
Phenylalanine R
Arginine G
Glycine S
Serine H
Histidine T
Threonine I
Isoleucine V
Valine K
Lysine W
Tryptophan L
Leucine Y
Tyrosine

39. De Novo Interpretation
…from Lu and Chen (2003), JCB 10:1

40. De Novo Interpretation

41. De Novo Interpretation
…from Lu and Chen (2003), JCB 10:1

42. De Novo Interpretation
Find good paths in spectrum graph
Can’t use same peak twice
Simple peptide fragmentation model
Usually many apparently good solutions
Amino-acids have duplicate masses!
“Best” de novo interpretation may have no biological relevance
Identifies relatively few peptides in high-throughput workflows

43. Sequence Database Search
Compares peptides from a protein sequence database with spectra
Filter peptide candidates by
Precursor mass
Digest motif
Score each peptide against spectrum
Generate all possible peptide fragments
Match putative fragments with peaks
Score and rank

44. Peptide FragmentationS G F L E E D E L K
100
% Intensity
m/z
250
500
750
1000

45. Peptide Fragmentation88
145
292
405
534
663
778
907
1020
1166
b ions S G F L E E D E L K
1166
1080
1022
875
762
633
504
389
260
147
y ions
100
% Intensity
m/z
250
500
750
1000

46. Peptide Fragmentation88
145
292
405
534
663
778
907
1020
1166
b ions S G F L E E D E L K
1166
1080
1022
875
762
633
504
389
260
147
y ions y6
100 y7
% Intensity y5 b3 b4 y2 y3 y4 b5 y8 b6 b8 b7 b9 y9
m/z
250
500
750
1000

47. Sequence Database Search
Sequence fills in gaps in the spectrum
All candidates have biological relevance
Practical for high-throughput peptide identification
Correct peptide might be missing from database!

48. Peptide Candidate Filtering
Digestion Enzyme: Trypsin
Cuts just after K or R unless followed by a P.
Must allow for “missed” cleavage sites
“Average” peptide length about amino-acids

49. Peptide Candidate Filtering
>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…
No missed cleavage sites MK
WVTFISLLFLFSSAYSR
GVFR R
DAHK
SEVAHR FK
DLGEENFK
ALVLIAFAQYLQQCPFEDHVK
LVNEVTEFAK …

50. Peptide Candidate Filtering
>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…
One missed cleavage site
MKWVTFISLLFLFSSAYSR
WVTFISLLFLFSSAYSRGVFR
GVFRR
RDAHK
DAHKSEVAHR
SEVAHRFK
FKDLGEENFK
DLGEENFKALVLIAFAQYLQQCPFEDHVK
ALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK …

51. Peptide Scoring Peptide fragments vary based on
The instrument
The peptide’s amino-acid sequence
The peptide’s charge state
Etc…
Search engines model peptide fragmentation to various degrees.
Speed vs. sensitivity tradeoff
y-ions & b-ions occur most frequently

52. Mascot Search Engine

53. Mascot MS/MS Ions Search

54. Mascot MS/MS Search Results

55. Mascot MS/MS Search Results

56. Mascot MS/MS Search Results

57. Mascot MS/MS Search Results

58. Mascot MS/MS Search Results

59. Mascot MS/MS Search Results

60. Mascot MS/MS Search Results

61. Mascot MS/MS Search Results

62. Mascot MS/MS Search Results

63. Mascot MS/MS Search Results

64. Summary
Protein identification by mass spectrometry is a key element of proteomics and systems biology.
Mass spectrometry + sequence databases represent a huge leap for protein (bio-)chemistry.
Sample prep, instruments and algorithms still maturing, much work to be done.

65. Further Reading Matrix Science (Mascot) Web Site
Seattle Proteome Center (ISB)
Proteomic Mass Spectrometry Lab at The Scripps Research Institute
fields.scripps.edu
UCSF ProteinProspector
prospector.ucsf.edu