1. Global Internal Standard Technology (GIST) – A Tool for Protein Expression Analysis
Xiang Zhang
Bindley Bioscience Center
Purdue University
17 January 2019

2. Identification of changes in protein expression and its modification is essential for understanding biological processes
Cellular response to stimuli is reflected by changes, i.e. protein expression, post-translation modification or processing
Stimuli origin
Chemical (drug, toxin etc.)
Physical (cell interaction, changes in temperature, pressure etc.)
Combination of both (disease)
The search for differences in protein expression and modification is called Comparative Proteomics.
17 January 2019

3. There are several approaches for quantitation
The Key Element of Comparative Proteomics is Quantitation of Changes in Protein (Peptide) Levels
It is not easy to determine a change in a single protein level (such as Western Blot)
In comparative proteomics, the challenge is to identify changes for as many proteins (peptides) as possible
There are several approaches for quantitation
Pattern recognition approach
Isotopic labeling approach
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4. Pattern Recognition Works well but has some potential issues
Alignment,
normalization
and peak intensity
comparison
Individual analysis of
sample A and B by
LC-MS
Works well but has some potential issues
Strongly depends on LC-MS system reproducibility
Intensity of any peak is not only function of peptide concentration. It also depends on analyte composition
It is difficult to obtain direct fold changes between samples
Some of these potential issues could be overcome by using isotopic labeling strategies.
17 January 2019

5. Isotopic Labeling Biosynthetic labeling Post-biosynthetic labeling.
In vivo incorporation of isotopic labeled species (growing cells in media enriched in 14N vs. 15N)
Impossible to use it with human subjects
Post-biosynthetic labeling.
Labeling amino groups (GIST)
Labeling cysteine residues (ICAT)
18O incorporation during proteolysis
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6. Isotopic Labeling – Basic principles (ICAT)
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7. GIST – Isotopic Labeling Technique
Concept was first introduced by Fred Regnier lab at Purdue University in 2000
Labeling reagents
Succinimidyl propionate (12C vs 13C)
Succinimidyl acetate (1H vs 2H)
Target group
Primary amine (N-terminus, Lysine residue)
Sample is labeled following digestion
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8. GIST – Chemical structure of Labeling Reagents
Heavy forms CH 3 O N C 2
Acetate-based reagent
Propionate-based reagent
Light forms
H = 2H
C = 13C
H = 1H
C = 12C
17 January 2019

9. Generating primary amines
Trypsin cleaves polypeptides C-terminal to lysine and arginine
-NH-CH(R1)-CO-NH-CH(R2)-CO-
trypsin
-NH-CH(R1)-COOH
H2N-CH(R2)-CO-
It will be shown in subsequent slides that amino groups generated in proteolysis can be labeled. 18O labeling of carboxyl groups can also be used. There are however, some “tricks” associated with 18O labeling that we are still in the process of working out. It is not totally clear that the 18O process will be as quantitative as the acetate labeling described here.
Primary amine groups are present globally - every peptide generated will be labeled by GIST reagents
17 January 2019

10. Amino groups are easily alkylated
Note that Arg is
not acetylated.
All primary amino
groups are labeled.
This slide shows the use of N-acetoxysuccinimide labeling of peptides. N-hydroxysuccinimides have the great advantage that they can be used for acylation in aqueous solution and still provide quantitative derivatization. In the case of glycopeptides and ser/thre peptides, there is occasionally some acetylation of hydroxyl groups. Esters are easily cleaved by treating with hydroxylamine at pH Addition of hydroxyl amine is standard in the procedure to preclude ester formation.
17 January 2019

11. Data dependent MS/MS and/or
GIST – Experimental Design
Normal (State 1)
sample digestion
Disease (State 2)
Combine
Light & Heavy
RP LC/MS Q-Tof
Light-1H or 12C
labeling
Heavy-2H or 13C
Ratio analysis using
GISTool V1.1™
Data dependent MS/MS and/or
targeted ion MS/MS
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12. Labeling samples from two different sources
After derivatization these
samples are mixed.
An internal standard is
created for each peptide
MW 500
MW 542
MW 545
Sample 1 – peptide A
Sample 2 – peptide A
This is a global labeling strategy in that all tryptic peptides are
derivatized except those that are amino terminally blocked. Control samples are acetylated with 1H3-acetate and experimental samples with 2H3-acetate. After differential labeling the samples are mixed, separated by multidimensional chromatography and analyzed by mass spectrometry. It is important that no resolution of the isotopic species occurs prior to mass spectrometry.
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13. Example of GIST labeled peptide analyzed by Mass Spectrometry
542
545
peptide from experimental
sample labeled with heavy form
peptide from
control sample
labeled with
light form
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m/z

14. How to Analyze GIST Data?
603.81
600.79
Peak picking
Identify peptide peak cluster
Doublet identification
Ratio calculation
627.25
630.28
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15. Process Flow Chart of GISTool
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16. Data Acquired on qTOF
Profile data
Centroid data
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17. Chemical Noise Filter I. Peak Density Filter spectrum is segmented
noise level of each segment is calculated based on local peak density
noise level is smoothed across spectrum
II. Spike Filter
One third of user defined peak width is used as minimum width of isotopic peak
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18. Charge Deconvolution – simple case
Peptide can carry different charges in ESI experiment
Peptide charge can be used for doublet recognition
Some overlapped peptides can be resolved
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19. Charge Deconvolution – complicated case
white and red peptides both have +1 charge, but they are shifted by 0.5 Da
Identify peak group
Find base peak
Try different charges
Assigned +2 to the group
Check isotopic peak profile
Flag white peaks
Check M/Z space of the white peaks
Assign white peaks as +1
Search other white peaks in the group
Try +1 on red peaks
Search other reds in peak group
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20. Deisotope Quantitatively resolve overlapped peptide peaks
Simplify peak list
Simple case
Overlapped peptides
M2+M0 M0 M0 M1
M3+M1 M1 M2 M3
M4+M2
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21. (12C+13C)m(1H+2H)n(16O+17O+18O)o(14N+15N)p(32S+33S+34S+36S)q
How Do We Deisotope ?
Peptide isotopic peak profile can be calculated if AA composition is known.
Peptide CmHnOoNpSq
(12C+13C)m(1H+2H)n(16O+17O+18O)o(14N+15N)p(32S+33S+34S+36S)q
peptide sequence is unknown during data processing
in-silico prediction of isotopic peak profile
comparing in-silico profile with experimental data
17 January 2019

22. Peptide Isotopic Distribution Can Be Predicted
Large peptide
Small peptide
Relative intensity
Peptide A
Peptide B
Molecular weight (amu)
Molecular weight (amu)
Peptide A and B have the same molecular weight but different AA composition
Peptide isotopic peak profile varies significantly with MW
To certain MW, the variation of isotopic peak profile is not significant
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23. Correlating in-silico Results with Experimental Results
Detect the significantly intense isotopic peaks by comparing experimentally measured isotopic peak profile with with in-silico predicted peak profile
- No, there is no other peptide
- Yes, a peak from other peptide contributes to the current peak
Relative Intensity
M/Z MW
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24. Charge Deconvolution and Deisotoping Process
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25. Doublet Recognition Mass difference Retention time
GIST Acetate +3, +6, …
ICAT +8, +16, …
Shifting according to labeling reagent.
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26. Calculation of Peak Ratio
I. Ratio is calculated in each scan – good for 12C/13C pairs
II. Ratio is calculated after smoothing peptide peaks at chromatographic level – good for H/D or 16O/18O pairs
SG smooth each peak
Peak detection
Doublet recognition
Peptide Regulation
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27. Ranking Doublets
RANK 1, 2, 3, ,
Good doublet Doublet complex Singlet
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28. Decharging to Rescue Mixed Doublets
PeptideA +2 light & heavy
PeptideB +2 light & heavy
500
505
6 possible combinations
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29. Overview of MS Proteomics Platform
Proteins
GIST label
Separation
Mass Spectrometer e.g. Ion Trap, Q-Tof
Ionization
Digest
RPLC/CapLC
+ESI
Purified &
Separated
MS/MS
(fragmentation pattern)
MS-only Ion Chromatogram
(stop here for quantitative profiling)
Survey Scan MS
select ion
Time
m/z
m/z
Protein Database
Theoretical MS/MS Spectrum
SEQUEST (Correlation Analysis)
Protein Identification
17 January 2019

30. Typical GIST Doublet – Light:Heavy
shows 3 m/z unit separation
(6 Da difference) since 2+ ion
State 2 (disease)
2H or 13C 3
Intensity
State 1 (normal)
1H or 12C
m/z
17 January 2019

31. Are Singlets Ever Observed?
GIST-BSA
Doublets
Singlets
# peptides 46 2
PQVSTPTLVEVSR
doublet
singlet
Pro has no primary amine,
also no Lys present
doublet
There is usually a scientific explanation for singlets
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32. Effectiveness of GIST Technology
Peak ratio distribution is rather tight
Labeling efficiency is > 95%; no mixed populations of
labeled and unlabeled peptides are observed
13C labeled peptides show greater deviation from the
mean than 2H
Mean ratio values below 1.0 and 3.0 are most likely
due to experimental error
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33. GIST Results for 8 Protein Mixture
Experimental design – Create an unknown mixture of 8 standard proteins
in different concentrations and different ratios to test
the entire GIST process (labeling, MS, GISTool, etc.)
Jiri creating
secret mix
Protein Actual Ratio Exp. Ratio # peptides ID’d
BSA : :
Transferrin : :
Glucose oxidase : :
Lysozyme : :
Carbonic Anhydrase : :
Lactoglobulin : only Light detected
Myoglobin : :
Ovalbumin : N/A unidentified
Ratios determined by GISTool from MS only data
Proteins identified by MS/MS sequences
Ratios were successfully determined for most proteins in mix
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34. A Real Sample: Human Serum
Experimental design
Samples: 1 normal vs. 1 colon cancer
Protein Level
Fractionation
SAX RP
175, 225, 300, 1000 mM NaCl
40%, 100% organic
Sample
10 total fractions
No peptide level fractionation other than RP-LC/MS
A single protein fraction (175mM, 40% ACN) from 1 normal and 1 diseased
sample was digested separately with trypsin, GIST labeled, and mixed
17 January 2019

35. Serum Fold Changes Using Deuterium and 13C GIST Reagents
0.1 1 10
350
600
850
1100
1350
1600
0.1 1 10
350
600
850
1100
1350
1600
GIST Acetate Normal(1H) vs. Disease(2H)
GIST Propionate Normal(12C) vs. Disease(13C) 10 10
log (Ratio)
log (Ratio) 1 1
350
350
600
600
850
850
1100
1100
1350
1350
1600
1600
0.1
0.1
m/z
m/z
Only well-resolved doublets ranked 1-3 by GISTool are shown
Only fold changes ≥ 2:1 were considered significant
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36. Largest Fold Change Identified in Human Serum
Heavy
colon
cancer
LC/MS
10:1 Ratio
normal
Light
Up-regulation of deoxyhemoglobin indicates inadequate oxygen levels in blood
Diseases such as cancer usually result in deficient oxygen supplies to tissues
LC/MS/MS
deoxyhemoglobin
MS/MS data
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37. GIST Fold-Change Results from Normal vs. Diseased Serum
Identifications from a single data-dependent LC/MS/MS experiment
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38. Conclusions
GIST is an efficient global peptide isotopic labeling technique that can be used for protein expression analysis and can be used with many selections of chromatography
GISTool is a very successful software algorithm for analyzing any isotope-labeled data generated by high-resolution MS
(ICAT, etc.-not just GIST)
Since GIST is capable of easily obtaining direct fold changes,
PTM and/or post-translational processing experiments can be designed
Peptide fractionation will be necessary for complex samples since
isotopic-labeling strategies double the complexity of samples
17 January 2019