1. Quantitative Proteomics II: Targeted Quantitation

2. Traditional Affinity-based proteomics
Using antibodies to quantify proteins
RPPA
Western Blot
Immunohistochemistry
ELISA
Immunofluorescence

3. Using MS/MS for quantitative protein assays
Most clinical and biology studies in the literature rely on measurement of proteins which already have antibodies available
Goal of targeted proteomics is to create reliable, high quality assays to measure proteins that do not require antibodies and instead rely on MS/MS

4. Targeted Proteomics Focuses on a subset of proteins of interest
Disease related changes in proteins
Signaling processes
Highly multiplexed alternative method to western blots/antibodies
Can focus on unique and informative peptides for protein of interest
Hypothesis driven questions!
Nature Method of the Year 2012

5. Targeted Proteomics Overview

6. When to use targeted MS vs. global shotgun MS?
Identify maximum number of proteins in limited number of conditions
Identify limited number of proteins in maximum number of conditions
r2=0.4698
RNA
Protein
Kennedy JJ et al., (2014) Nature Methods 11(2)

7. Mass Spectrometry based proteomic quantitation
Shotgun proteomics
LC-MS
Targeted MS
1. Records M/Z
1. Select precursor ion MS MS
Digestion
2. Selects peptides based on abundance and fragments
Fractionation
2. Precursor fragmentation
MS/MS
MS/MS
Lysis
3. Protein database search for peptide identification
3. Use Precursor-Fragment pairs for identification
Data Dependent Acquisition (DDA)
Uses predefined set of peptides

8. Multiple Reaction Monitoring (MRM)
Triple Quadrupole acts as ion filters
Precursor selected in first mass analyzer (Q1)
Fragmented by collision activated dissociation (Q2)
One or several of the fragments are specifically measured in the second mass analyzer (Q3)

9. MRM Instrumentation: Triple Quadrupole (QqQ)

10. Fragment Ion Detection

11. Peptide Identification with MRM
Mass Select
Fragment Ion
Mass Select
Precursor
Fragment Q1 Q2 Q3
Transition
Transition: Precursor-Fragment ion pair are used for protein identification
Select both Q1 and Q3 prior to run
Pick Q3 fragment ions based on discovery experiments, spectral libraries
Q1 doubly or triply charged peptides
Use the 3 most intense transitions for quantitation

12. Peptide Identification with MRM
Used for to analyze small molecules since the late 1970s
More recently, used for proteins and peptide quantitation in complex biological matrices
Particularly for biomarker discovery
With small molecules, the matrix and analyte have different chemical natures so separation step is able to remove other components from analytes
Separation
MS analysis
With proteomics, both the analytes and the background matrix are made up of peptides, so this separation cannot occur
Separation
MS analysis

13. Strengths of MRM
Can detect multiple transitions on the order of 10msec per transition
Can analyze many peptides (100s) per assay and the monitoring of many transitions per peptide
High sensitivity
High reproducibility
Detects low level analytes even in complex matrix
Golden standard for quantitation!

14. Weaknesses of MRM Focuses on defined set of peptide candidates
Need to know charge state, retention time and relative product ion intensities before experimentation
Physical limit to the number of transitions that can be measured at once
Can get around this by using time-scheduled MRM, monitor transitions for a peptide in small window near retention time

15. Parallel Reaction Monitoring (PRM)
Q3 is substituted with a high resolution mass analyzer to detect all target product ions
Generates high resolution, full scan MS/MS data
All transitions can be used to confirm peptide ID
Don’t have to choose ions beforehand
Peterson et al., 2012

16. PRM Instrumentation: Quadrupole Time of Flight (Qqtof)
The third quadrupole is replaced with a time of flight (TOF) mass analyzer offering high sensitivity, mass resolution and mass accuracy for both precursor and product ion spectra

17. Applications of MRM/PRM
Metabolic pathway analysis
Protein complex
subunit stoichiometry
Phosphorylation
Modifications within protein
Biomarkers: protein indicator correlating to a disease state
Can enrich for proteins/peptides using antibody

18. Motivating example: AKT and breast cancer

19. MRM Workflow Clinical/Biological Question Proteotypic
Define protein set
Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Clinical/Biological Question
Proteotypic
LC and MS properties
Intensity of transitions MS
Interferences

20. MRM Workflow Clinical/Biological Question Proteotypic
Define protein set
Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Clinical/Biological Question
Proteotypic
LC and MS properties
Intensity of transitions MS
Interferences

21. Define the set of proteins based on a biological question

22. MRM Workflow Clinical/Biological Question Proteotypic
Define protein set
Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Clinical/Biological Question
Proteotypic
LC and MS properties
Intensity of transitions MS
Interferences

23. Selecting Peptides
A few representative peptides will be used to quantify each protein
Need to fulfill certain characteristics
Have an unique sequence
Consistently observed by LC-MS methods
8-25 amino acids
Good ionization efficiency
m/z within the range of the instrument
No missed cleavages
Not too hydrophillic (poorly retained) or hydrophobic (may stick to column)

24. Identifying Proteotypic Peptides
Step 1: Full protein sequence in FASTA format
Set of Proteins
Trypsin
Peptides
Step 2: Tryptic Peptides
PTPIQLNPAPDGSAVNGTSSAETNLEALQK
LEAFLTQK
PSNIVLVNSR
LEELELDEQQR
DDDFEK…..
RefSeq
Ensembl
Uniprot
Step 3: Compare to human reference database
Proteotypic Peptides
-Contain all peptide sequences
-Find all peptides that only map back to one gene
PTPIQLNPAPDGSAVNGTSSAETNLEALQK
LEAFLTQK
PSNIVLVNSR
LEELELDEQQR
DDDFEK…..
Match peptide to proteins
Match proteins to genes
(Reference Protein DB)
(Using protein names and genomic DB)

25. LC/MS Properties: GPMDB
-Compares peptides to a collection of previously observed results -Determines how many times the peptide has been observed by others -Most proteins show very reproducible peptide patterns

26. LC/MS Properties: Skyline
-Compares peptides to MS/MS spectral library -Predicts most abundant transitions

27. Selection of transitions
MRM Workflow
Define protein set
Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Clinical/Biological Question
Proteotypic
LC and MS properties
Intensity of transitions MS
Interferences

28. Selecting Transitions
Limitation of MRM-MS: ~1-2 m/z unit window for precursor and fragment ion occasionally let in interfering peptides with similar characteristics
If we want to use these transitions for quantitation, we need to be confident there are no interferences
Largest always largest, smallest always smallest etc.
b-fragments of high m/z are less represented on QqQ
MRM

29. Selecting Transitions
Limitation of MRM-MS: ~1-2 m/z unit window for precursor and fragment ion occasionally let in interfering peptides with similar characteristics
If we want to use these transitions for quantitation, we need to be confident there are no interferences
Largest always largest, smallest always smallest etc.
b-fragments of high m/z are less represented on QqQ
MRM
Peptide of interest
Interfering peptide

30. Selecting Transitions: Skyline
Can use to find best transitions to pick
Intensity (rank)
Dot product (similarity to reference spectra)
Want high rank and dotp close to 1

31. Validation of transitions
MRM Workflow
Define protein set
Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Clinical/Biological Question
Proteotypic
LC and MS properties
Intensity of transitions MS
Interferences

32. Validating Transitions: “Branching ratio”
Branching Ratio (BR): ratio of the peak intensities
𝐵𝑅=𝑙𝑛 𝐼 𝐴𝑥 𝐼 𝐵𝑥 𝐼 𝐴𝑥𝑆 𝐼 𝐵𝑥𝑆 𝑛
Light (Analyte)
Heavy(SIS) I1 I3 I1 I2 I2 I3
IAx, IBx : Peak areas of Analyte
IAxS, IBxS : Peak areas of SIS
n=number of SIS transitions
Kushnir, 2005

33. Validating Transitions: AuDIT
AuDIT: Automated Detection of Inaccurate and imprecise Transitions
Uses “branching ratio”
1. Calculate relative ratios of each transition from the same precursor
2. Apply t-test to determine if relative ratios of analyte are different from relative ratios of SIS

34. Validating Transitions: AuDIT
Blue: Light
Red: Heavy
Relative product ions should have a constant relationship
Abbatiello, 2009

35. PRM Workflow MRM PRM MS Target Selection Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Target Selection
Selection of peptides
Selection of transitions
Selection/ Validation of transitions
Protein Quantitation MS

36. PRM Workflow MRM PRM MS Target Selection Selection of peptides
Selection of transitions
Validation of transitions
Protein Quantitation
Target Selection
Selection of peptides
Selection of transitions
Selection/ Validation of transitions
Protein Quantitation MS

37. Protein Quantitation

38. Label-free quantitation
Usually use 3 or more precursor-product ion pairs (transitions) for quantitation
Relies on direct evaluation of MS signal intensities of naturally occurring peptides in a sample.
Simple and straightforward
Low precision
Several peptides for each protein should be quantified to avoid false quantitation

39. Stable Isotope Dilution (SID)
Use isotopically labeled reference protein
13C and/or 15N labeled peptide analogs
Chemically identical to the target peptide but with mass difference
Add known quantity of heavy standard
Compare signals for the light to the heavy reference to determine for precise quantification
Lysis
Fractionation
Digestion
Synthetic
Peptides
(Heavy)
Light
LC-MS MS H L

40. Quantitation Details MS H L
SIS: Stable Isotope Standard
PAR: Peak Area Ratio
Analyte
SIS
PAR = Light (Analyte) Peak Area Heavy (SIS) Peak Area
Analyte concentration= PAR*SIS peptide concentration
-Use at least 3 transitions
-Have to make sure these transitions do not have interferences

41. Limit of Blank, Limit of Detection and Limit of Quantitation
Limit of Blank (LoB)
Highest analyte concentration expected to be found when replicates of a blank sample containing no analyte are tested
Limit of Detection (LoD)
Minimal quantity of an analyte that can be confidently detected
Intrinsic to method or instrument
Limit of Quantitation (LoQ)
Minimal amount of an analyte that can be confidently quantified
Signal
LOQ
LOD
Noise

42. Calculating LOD, LOB and LOQ
Limit of Blank (LoB)
9thth percentile of blank measurements
Limit of Detection (LoD)
Mean of blanks + 3*SD of blanks
Limit of Quantitation (LoQ)
Mean of blank + 10*SD of blanks
3*LOD
Lowest concentration of peptide at which CV<20%
Armbruster DA and T Pry. Clin Biochem Rev. (2008)

43. Standard Curve
Standard concentration curve is generated using increasing concentrations of the “heavy peptide” in the presence of a constant amount of biological sample (aka matrix)
Matrix contains the “light” version of the peptide
Standard Curve typically created using:
5 heavy peptide serial dilutions
Blank (no heavy)
Once the curve is generated, biological samples can be processed measuring the amount of endogenous “light” peptide in each sample
Using the calibration curve, we can compute the endogenous concentration from the ratio of endogenous/heavy (PAR)

44. Label Free: Standard Curve
Lysis & Fractionation
Digestion
LC-MS MS

45. Lower Limit of Detection
The lowest amount of analyte that is statistically distinguishable from background or a negative control.
Two methods to determine lower limit of detection:
Lowest concentration of the analyte where CV is less than for example 20%.
Determine level of blank by taking 95th percentile of the blank measurements and add a constant times the standard deviation of the lowest concentration.
K. Linnet and M. Kondratovich, Partly Nonparametric Approach for Determining the Limit of Detection, Clinical Chemistry 50 (2004) 732–740.

46. Limit of Detection and Linearity
Measured Concentration
Measured Concentration
Theoretical Concentration
Theoretical Concentration

47. Precision and Accuracy
Measured Concentration
Measured Concentration
Theoretical Concentration
Theoretical Concentration

48. Open Source MRM analysis tools

49. Data Independent Acquisition

50. SWATH-MS
“Targeted” style method but allows for data collection on all precursor ions and not just a subset
Spectra are acquired over entire mass range in small windows of defined size
Data acquired on quadrupole-quadrupole TOF high resolution instrument cycling
S.I. Anjo et al., Proteomics (2017)

51. SWATH-MS: Data Analysis
MS co-fragments all peptide ions in a “swathe”
Records fragment ions in high resolution mass spectrum
Fragment ion intensities are extracted from the multiplexed spectra in a targeted way
Create extracted ion chromatogram peak groups
Rost et al, Proteomics (2017)

52. SWATH-MS: Data Analysis
Skyline: Windows application for DDA and DIA MS methods
Proteowizard: Converts vendor data into open formats
Assay Libraries: library of transitions and retention times
OpenMS: open source analysis package for large-sale datasets
pyProphet: calculates FDR using target decoy DB
TRIC Alignment: integrates information from multiple OpenSWATH runs and does cross-run and retention time correction
Rost et al, Proteomics (2017)

53. Summary
Targeted proteomics can be used as an alternative to antibody-based protein assays in hypothesis driven biological experiments.
Allows for multiplexed analysis of many proteins in different conditions.
PRM removes the step of transition validation and allows for all computational analysis post-acquisition.
SWATH removes the step of peptide selection and generates transitions for all precursor ions in the defined precursor retention time and m/z
Transition interference must be appropriately identified prior to protein quantitation.
Several computational tools to predict and identify interferences in MRM and PRM have been developed.

54. Questions?