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New Developments in LC-IMS-MS Proteomic
Measurements and Informatic Analyses
Erin Shammel Baker Kristin E. Burnum-Johnson, Xing Zhang, Cameron P. Casey, Yehia M. Ibrahim, Matthew E. Monroe, Tao Liu, Brendan MacLean, Brian Pratt, Michael J. MacCoss and Richard D. Smith
Pacific Northwest National Laboratory
Why are we interested in using IMS-MS?
1. We would like to increase throughput of measurements and IMS-MS analyses are able
to detect high feature numbers with fast LC separations or no LC separations at all
2. IMS-TOF MS provides greater dynamic range of detection relative to trapping (e.g.
Orbitrap) instruments
3. IMS adds complementary information to MS measurements which helps lower false
discovery rates and separates isomers
4. Detection of structural changes in peptides/ proteins that can help characterize specific
disease states (structural biomarkers)
Introduction
p (Drift Gas)
Ffriction
Ion
Fel
Ion mobility concept
velocity is constant
v = K E
K = ion mobility
Drift Cell
E
E
in out
Drift Time
Pulse of 2 ions with
same m/z but different
shape
Different conformers are separated
in time with peak heights representing
the amount of each
Ion mobility concept
velocity is constant
v = K E
K = ion mobility
Drift Cell
Features:
• NanoESI ion source with 2 inlets for on-the-fly
calibration
• Off-axis hourglass ion funnel/accumulation trap
before IMS
• Rear ion funnel after IMS
• Segmented quadrupole for CID
• High dynamic range Agilent TOF or Q-TOF MS
IMS-MS concept ESI
Source Rear IF Trapping IF
MS
Q00
High Pressure Ion Funnel
Drift Cell
DRIFT CELL
Peptides
DNA Sugars
Drift Time Electric Field
Ion mobility concept LC (minutes) IMS (~60 ms) MS (~100 µs)
IMS MS
Elution Time Drift Time m/z
0 10 20 30 40 50 60
Elution Time (minutes)
Inte
nsi
ty
20 30 40 50 60
Drift Time (ms)
20 30 40 50 60
Drift Time (ms) 20 30 40 50 60
Drift Time (ms)
1100
100
m/z
1100
100
m/z
1100
100
m/z
Spiking
Level Non-Serum Peptide
60-min LC-
IMS-TOF MS
60-min LC-
TOF MS
100-min LC-
Velos-Orbitrap
100 pg/mL Melittin ND ND ND
100 pg/mL Dynorphin A Porcine Fragment 1-13 ND ND
1 ng/mL Des Pro Ala Bradykinin ND ND
1 ng/mL Leucine Enkephalin ND ND
10 ng/mL 3X FLAG Peptide ND
10 ng/mL Substance P
100 ng/mL [Ala92]-Peptide 6
100 ng/mL Methionine Enkephalin
8 peptides spiked in human serum
Sample analyzed using Velos-Orbitrap, TOF MS and IMS-TOF MS instruments
Spiking
Level Non-Serum Peptide
60-min LC-
IMS-TOF MS
60-min LC-
TOF MS
100-min LC-
Velos-Orbitrap
100 pg/mL Melittin ND ND ND
100 pg/mL Dynorphin A Porcine Fragment 1-13 1.7 (18) ND ND
1 ng/mL Des Pro Ala Bradykinin 21 (12) ND ND
1 ng/mL Leucine Enkephalin 23 (10) ND ND
10 ng/mL 3X FLAG Peptide 115 (8) 125 (20) ND
10 ng/mL Substance P 126 (7) 138 (18) 112 (19)
100 ng/mL [Ala92]-Peptide 6 868 (4) 848 (11) 841 (12)
100 ng/mL Methionine Enkephalin 1000 (3) 1000 (9) 1000 (10)
8 peptides spiked in human serum
Scaled abundance and (CV values)
Sample analyzed using Velos-Orbitrap, TOF MS and IMS-TOF MS instruments
Benefits of IMS drift time separation 1. Improved Sensitivity & Increase Feature Detection & Confidence
IMS-QTOF MS of Bradykinin (100 pM) QTOF MS of Bradykinin (100 pM)
Benefits of IMS drift time separation 1. Improved Sensitivity & Increase Feature Detection & Confidence
Only 3 features discerned without drift time dimension (*)
2. Utilizing IMS in databases reduces FDR due to extra dimension
Benefits of IMS drift time separation
Mass Error LC Error
Drift Time Error
Extra dimension adds confidence to LC-IMS-MS Features Matches to AMT Tag DB
100-min LC-Velos Orbitrap 39806 Features with FDR <5%
60-min LC-IMS-MS 75129 Features with FDR <5% If you only use LC and MS 36057 Features with FDR <5%
Human Serum Peptide Analysis
P+
P2+
P3+
P4+
L+ L+
L2+
P+
P2+
P3+
P4+
L2+
L+
Peptide : red Lipid : blue
Benefits of IMS drift time separation
Peptides and lipids are easily distinguished
3. Distinguish different classes of compounds and sequence isomers
RPPGFSPFR+
GPFRPRFPS+
RRGPFPSPF+
NW Chem used to model 3-D conformations
Benefits of IMS drift time separation 3. Distinguish different classes of compounds and sequence isomers
Simultaneous Targeted and Discovery
Proteomic Measurements with LC-IMS-MS
Increasing sample throughput and identifications
1. To obtain the highest number of proteins, tissue samples are usually fractionated
2. However, fractionation increases analysis time, introduces errors and causes
quantitation difficulties (peptides split between fractions)
3. Our goal is to understand how many proteins can be detected in the unfractionated samples with the Velos Orbitrap, Q-Exactive and IMS-MS platforms using a single 100 minute LC gradient
Patient derived xenograft (PDX) tissue sample
Mice engrafted bilaterally with WHIM16 breast tumor (Luminal A)
6-9 weeks
WHIM16 PDX samples for MS analyses
Pooled and cryopulverized
• Genomically characterized breast-cancer-derived xenografts (Li et al, Cell Rep. 2013, 4: 1116-30)
• Has been used for evaluation of the ischemia effect on proteomic and phosphoproteomics analysis (Mertins et al, Mol Cell Proteomics. 2014, 13: 1690-704)
• Part of the Comparison Reference (CompRef) sample (has one basal, WHIM2, and one luminal A sample, WHIM16) that has been used as the QC for both identification and quantification throughout the CPTAC proteomic characterization of the TCGA tumors (Zhang et al, Nature. 2014, 513: 382-7)
Platform identifications
QExact 10489
VOrbi 2498 8607
QExact 19096
VOrbi 11105
• MS/MS undersampling (especially for Velos) led us to use an AMT tag database approach
MS/MS Identifications at 1% FDR For Qexact and VOrbi
Platform identifications
AMT Tag Matching at <1% FDR (MS/MS Database 0.01% FDR)
• MS/MS undersampling (especially for Velos) led us to use an AMT tag database approach
• AMT tag database was built from 48 fractions
• Each unfractionated run was aligned to the database for identifications
QExact 17289
VOrbi 16666
IMS 22401
QExact 10489
VOrbi 2498 8607
MS/MS Identifications at 1% FDR For Qexact and VOrbi
QExact 19096
VOrbi 11105
Identifications using AMT tag approach
Unique Peptides Non-redundant Human Proteins with at least 2 peptide identification
A representative protein was chosen for redundant peptides (peptides that are shared between multiple proteins)
8,055 peptides and 319 proteins were detected only by IMS-MS
QExact 17289
VOrbi 16666
IMS 22401
QExact 2164
VOrbi 2070
IMS 2618
Platform sequence coverage difference
Of the 1855 proteins detected by all platforms, IMS-MS has the least number of proteins with only 1 and 2 peptide identification and the highest number of proteins with more than 4 peptide identifications (best sequence coverage)
Of the 1855 proteins detected by all platforms
# of Peptides/Protein IMS QE VOrbi
1 161 245 308
2 230 317 299
3 252 259 240
>4 1212 1034 1008
Non-redundant Human Proteins
Platform sensitivity difference
The 8055 peptides detected only by IMS-MS had lower intensities than the peptides found in all platforms (IMS more sensitive)
9832 peptides detected by all platforms
8055 peptides detected only by IMS-MS Unique Peptides
Simultaneous targeted and discovery IMS-MS approach
Protein Peptides Detected/Protein
Q-Exactive Orbitrap-Velos IMS-MS
Membrane-Associated Progesterone Receptor Component 2 (PR)
1 2 3
Kynureninase Isoform B
1 0 3
Epidermal Growth Factor Receptor (EGFR) Isoform A Precursor
0 0 3
Transmembrane & TPR Repeat-Containing Protein 3
0
0 2
MAP7 Domain-Containing Protein 1 0 0 1
Validated 5 low concentration proteins by spiking in heavy labeled peptides for each (2 peptides/protein except MAP7) Proteins were chosen due to their low abundance in previous studies and potential role in breast cancer
CPTAC_LabelFree_P6_4_17Sep14_Frodo_14... 9/17/2014 11:03:30 PM
RT: 0.00 - 99.00
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
NL: 2.38E9
TIC F: FTMS + p NSI
Full ms
[400.00-2000.00] MS
CPTAC_LabelFree_P6_
4_17Sep14_Frodo_14-
04-13
RT: 0.00 - 99.00
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
Targeted and discovery IMS-MS approach
Analysis of EGFR peptide (TIQEVAGYVLIALNTVER3+)
CPTAC_LabelFree_P6_4_17Sep14_Frodo_14... 9/17/2014 11:03:30 PM
RT: 0.00 - 99.00
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
NL: 2.38E9
TIC F: FTMS + p NSI
Full ms
[400.00-2000.00] MS
CPTAC_LabelFree_P6_
4_17Sep14_Frodo_14-
04-13
RT: 0.00 - 99.00
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
Target peptide from EGFR Protein 10 nM heavy added
CPTAC_LabelFree_P6_4_17Sep14_Frodo_14... 9/17/2014 11:03:30 PM
RT: 0.00 - 99.00
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
NL: 2.38E9
TIC F: FTMS + p NSI
Full ms
[400.00-2000.00] MS
CPTAC_LabelFree_P6_
4_17Sep14_Frodo_14-
04-13
RT: 0.00 - 99.00
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
2.5 nM heavy added Target peptide from EGFR Protein 10 nM heavy added
0 nM heavy added
Analysis of EGFR peptide (TIQEVAGYVLIALNTVER3+)
CPTAC_LabelFree_P6_4_17Sep14_Frodo_14... 9/17/2014 11:03:30 PM
RT: 0.00 - 99.00
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
NL: 2.38E9
TIC F: FTMS + p NSI
Full ms
[400.00-2000.00] MS
CPTAC_LabelFree_P6_
4_17Sep14_Frodo_14-
04-13
RT: 0.00 - 99.00
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rel
ative
Abu
ndan
ce
Target peptide from MAP7 Protein 10 nM heavy added
2.5 nM heavy added
Analysis of MAP7 peptide (TPETLLPFAEAEAFLKK3+)
0 nM heavy added
Biological importance
297 IMS-MS unique proteins found in Human Protein Atlas–Cancer database
319 proteins only detected by IMS-MS
Biological importance
60 of these unique IMS-MS proteins
ranked as ‘High’ in at least 25% of breast cancer stains
Of these 60 proteins: • All have functional roles in biological
process necessary for cancer progression
• > 26% have documented mechanistic roles in breast cancer progression in complementary literature
297 IMS-MS unique proteins found in Human Protein Atlas–Cancer database
319 proteins only detected by IMS-MS
The Hallmarks of Cancer
Hanahan D, Weinberg Robert A. Cell. 2011;144:646-74
Summary
LC-IMS-MS Measurements:
• Detected lower concentration proteins than the Velos
Orbitrap and Q-Exactive platforms
• Performed discovery and targeted studies simultaneously
• Identified hallmark of cancer proteins in unfractionated
samples, which are usually only observed in fractionated
studies
IMS-MS Informatic Analyses
Using Skyline
• Currently, all of our IMS-(CID)-MS all-ions fragmentation data is manually assigned which is very time consuming and limits our ability to analyze the benefit of IMS
• We need to understand the effect of the IMS separation on DIA identifications
• Skyline provides a rapid analysis tool to study MS and MS/MS quantitation with and without the IMS dimension
Why do we want to use Skyline to analyze our IMS-(CID)-MS all-ions fragmentation data?
4-12 Torr of Buffer Gas
Fragmentation takes place after the drift cell
IMS-(CID)-MS all-ions data acquisition
Parent Spectrum Fragmentation Spectrum
Fragments have the same drift time as precursors
Parent Spectrum (3 Peptides Observed in 1 sec LC acquisition) 2 hemepeptides identified
Fragmentation Spectrum
Heme Containing Peptides
(Heme)+
Heme Containing Peptides
No Heme
Zoomed into 617 region
Find multiple hemepeptides simultaneously by looking for heme+ ion at 617
Due to time consuming manual analyses, until now we have only studied specific fragments
Parent Spectrum (11 Peptides Observed in 1 sec LC acquisition) 3 Phosphopeptides Identified
Fragmentation Spectrum
Find multiple phosphopeptides by looking for PO3 or PO4 mass difference
Phospho-peptides
Due to time consuming manual analyses, until now we have only studied specific fragments
Concentration dependent IMS-(CID)-MS experiment
BSA Concentration in Yeast
100 pM 1 nM 5 nM 10 nM 50 nM 100 nM 500 nM 1 µM
All ions fragmentation IMS-(CID)-MS
All ions fragmentation (CID)-MS
• Spiked 8 different concentrations of tryptic BSA digest from 100 pM to 1
µM into 0.1 ug/uL yeast digest
• Analyzed the effect of IMS on the MS and MS/MS quantitation for the
DIA data
IMS-MS and IMS-(CID)-MS were alternated
CE of 29 V was chosen since it fragmented 2+ ions well
IMS-MS IMS-(CID)-MS (CE=29V)
Skyline provides the ability to perform fast DIA analyses
Good quantitation from 1 µM to 1 nM for all peptides when drift time filtering was used When drift time filtering wasn’t used, the lower concentration peptides quantitation wasn’t as linear
Drift time removes interference in MS quantitation
Another peak interferes when drift time filtering isn’t performed
5 nM 10 nM
Good quantitation from 1 µM to 1 nM for 7 of 10 peptides when drift time filtering and 10 for 10 from 1 µM to 10 nM When drift time filtering wasn’t used, many interferences caused bad quantitation
Drift time filtering removes interference in MS/MS quantitation
Baseline noise increases when drift time isn’t used
Interfering peaks cause quantitation problems when drift time isn’t used
Summary
Skyline:
• Quickly analyzed the IMS-(CID)-MS data
• Showed that IMS drift time allows better MS and MS/MS
quantitation by removing interfering peaks
• Enables further studies to better understand the effect of
IMS on other types of DIA data (such as SWATH)
Conclusions IMS-MS:
• Separates isomeric peptides
• Distinguished different classes of compounds
• Allows detection of low concentration components
• Is easily coupled with LC and other front end separations
• Data analysis is becoming automated with new programs such as
Skyline
Acknowledgements • Agilent Technologies
• National Institute of Environmental Health
Sciences of the NIH (R01ES022190)
• NIH: General Medical Sciences Proteomics
Center at PNNL (2 P41 GM103493-11) and
National Cancer Institute
• Leidos Biomedical Research, Inc.
• PNNL Laboratory Directed Research and
Development Program
• Environmental Molecular Sciences
Laboratory
Biological Separations & Mass Spectrometry Group