Exactive David A Peake PhD Thermo Fisher Scientific Metabolomics and Lipidomics Group San Jose CA USA Biologys Central Dogma Biological Potential Biological Reality Phenotype Lipidomics ID: 815773
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Slide1
Untargeted Lipidomics Using the Q Exactive
David A Peake, PhD
Thermo Fisher Scientific
Metabolomics and Lipidomics Group
San Jose, CA, USA
Slide2Biology’s Central Dogma
Biological
Potential
Biological
Reality:
Phenotype
Slide3Lipidomics
Impact
Slide4Lipid extraction or direct sampling
nESI
Lipid Identification and Statistical Analysis
Advion
Nanomate
nESI
infusion
Thermo TSQ Vantage
Lipidomics Platform
Detection/Quantitation of specific lipid species/classes using complementary precursor ion, neutral loss or SRM MS/MS scans
Structural analysis by
product
ion scan MS/MS
High Resolution Mass spectrum
pos &
neg
ion
Crude Lipid Extract
Thermo Q Exactive and Orbis
Cell/Tissue/Organ sample
Non-targeted
Discovery
Targeted
Quantitation
Shotgun
Infusion
LC-MS
Slide5Higher-efficiency lipid profiling system using a quadrupole
orbitrap
mass spectrometer and an automated search engine Lipid Search
ASMS 2012
Takayuki Yamada
1
,
Takato
Uchikata
1
, Shigeru Sakamoto
2
,
Yasuto
Yokoi
3
,
Eiichiro
Fukusaki
1, Takeshi Bamba1Dept. of Biotechnology,
Grad. School of Engineering, Osaka University, Suita, JPThermo Fisher Scientific, Yokohama,
JPMitsui Knowledge Industry, Tokyo,
JP
Slide6ObjectiveDevelopment of a higher-efficiency lipid profiling system using a
quadrupole
mass spectrometer and an automated lipid identification software
Experimental
Dionex
Ultimate 3000 RSLC system (Thermo Scientific)Separation of lipids by reverse phase liquid chromatographyQ
Exactive (Thermo Scientific)
High resolution full scan with successive polarity switching
Data-dependent MS
2
scan with the target parent mass list
Lipid Search (Mitsui Knowledge Industry)
Automated identification of lipid molecular species from MS raw data
Results
The combination of Q
Exactive
and Lipid Search enables us high-throughput and exhaustive lipid profiling
A small amount of lipid molecular species were effectively identified by the target parent mass list
Overview
Slide7Workflow for High-throughput Lipid P
rofiling
Sample preparation
Full scanning
high
mass accuracy and
resolution
Data-dependent MS
2
scanning
targeting the parent mass
from
the Lipid Search database
Identification of lipid molecular species based on
accurate
mass from
full scan MS and dd-MS
2
Fast, automated
peak
detection
LC/MS analysis
Data processing
Slide8Mass spectrometryFull scanning with high mass accuracy and high resolution
Lipid molecular species with similar molecular weight exist
High-speed product ion scanning for polar head groups and fatty acid chains
There are a lot of structural isomers by the difference of fatty acid chain composition
Polarity
switching in short cycle timePolar
lipid ionization efficiency and detection specificity depend on the acquisition polarity
Product ions from polar head groups show high sensitivity in positive-ion mode, and product ions from fatty acid chains show high sensitivity in negative-ion mode
Introduction
What is needed for
Lipidomics
?
Slide9In data analysisListing the lipid molecular species in a sample automatically for high-throughput lipid profiling
For identifying the lipid molecular species, it is necessary to confirm the spectra of MS
1
and MS
2
both in positive-ion mode and in negative-ion mode
Introduction
What is needed for data analysis?
Slide10Introduction
High mass accuracy
3
ppm
in external standard method
High resolution
Up to 140,000 at
m/z
200
Successive polarity switching in practical cycle time
→
High-
sensitivivity
analysis of lipids with various polarity
Inclusion list
= Target parent mass list for data-dependent MS
2
scan
→
Efficient detection of target compounds information
Q
Exactive
Slide11Introduction
High-throughput identification system for the
Lipidome
Batch
identification
for lipids with raw spectra from mass spectrometer
More
than 200,000 actual and virtual structure of Lipids and product ions
High accuracy identification algorithm
Slide12Methods
Phosphatidylcholine
(PC)
Phosphatidylethanolamine
(PE)
Phosphatidylserine (PS)Phosphatidylinositol
(PI)Phosphatidylglycerol (PG)
Phosphatidic
acid (PA)
Lysophosphadylcholine
(LPC)
Lysophosphadylethanolamine
(LPE)
Lysophosphatidylserine
(LPS)
Lysophosphatidylinositol
(LPI)
Lysophosphatidylglycerol
(LPG)
Lysophosphatidic
acid (LPA)
Sphingomyelin (SM)Triacylglycerol (TG
)
Targeted Lipid Classes
Slide13Methods
Top 10 (positive)
Top 10 (negative)
Top 20 (positive)
Lyso
-phospholipids
Triacylglycerols
Phospholipids
Slide14Methods
LC:
Dionex
Ultimate 3000 RSLC system (Thermo Scientific)
Column
Hypersil
GOLD (150
×
4.6 mm, 3 µm; Thermo Scientific)
Column oven temperature
40 ˚C
Flow rate
0.5 ml/min
Mobile phase A
AcN
/
MeOH
/Water (19:19:2)
with 20
mM
ammonium
formate
and 5
mM
formic acid
Mobile phase B
2-propanol
with 20
mM
ammonium
formate
and 5
mM
formic acid
Injection volume
5 µl
Time (min)
A
B
0
95
5
5
95
5
30
70
30
60
10
90
70
10
90
71
95
5
75
95
5
Pump gradient program
A
B
Time (min
)
LC Conditions
Slide15Methods
Time (min)
0-30
30-70
Ionization conditions
Polarity
positive
negative
positive
Sheath gas flow rate
50
50
50
AUX gas flow rate
10
10
10
Spray voltage (kV)
0.85
0.8
1.6
Capillary temperature (
°
C)
350
350
350
Heater temperature (
°
C)
250
250
250
Full MS conditions
Resolution
70,000
70,000
70,000
Scan range (
m/z
)
230-1200
230-1200
600-1200
dd-MS
2
conditions
Resolution
13,500
13,500
13,500
Top N
10
10
20
NCE
25
25
25
Stepped NCE (%)
40
40
40
MS
2
was performed for 10 or 20 lipid ions, starting with the ion
of
the highest intensity
dd
(data-dependent) MS
2
Top 10 or 20 method
Slide16Methods
Target
m/z
values for dd-MS
2
Efficient qualitative analysis of lipids by using the database of Lipid Search
・・・
Inclusion list
Slide17Methods
Identification conditions of Lipid Search
Slide18Methods
10
µL
mouse plasma
Add 150
µL
MeOH
Vortex
Incubate on ice for 10 min
Centrifuge (
10,000×
g
, 5 min, 15
˚C
)
140
µL supernatant
and 140
µL
MeOH
→
LC/MS analysis
Lipid extraction
Slide19Results
full
MS
(
pos)
dd-MS2
(
pos)
full
MS
(
neg
)
dd-MS2
(
neg
)
cycle time: 4
sec
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Slide20Results
Positive ion
Negative ion
1
2
3
4
5
6
8
9
10
11
12
13
14
15
16
17
18
19
20
Slide21Results
0.1 ppb
1 ppb
10 ppb
100 ppb
1000 ppb
PC
✓
✓
✓
LPC
✓
✓
✓
✓
✓
SM
✓
✓
✓
PE
✓
✓
✓
✓
LPE
✓
✓
✓
✓
PS
✓
✓
LPS
✓
✓
PI
✓
✓
✓
LPI
✓
✓
✓
PG
✓
✓
LPG
✓
✓
PA
✓
LPA
✓
TG
✓
✓
✓
✓
The lower limit of dd-MS
2
(with inclusion list)
Slide22Results
0.1 ppb
1 ppb
10 ppb
100 ppb
1000 ppb
PC
✓
✓
LPC
✓
✓
✓
SM
✓
✓
✓
PE
✓
✓
LPE
✓
✓
✓
PS
✓
LPS
✓
PI
✓
LPI
✓
✓
PG
✓
✓
LPG
✓
✓
PA
LPA
TG
✓
✓
✓
The lower limit of dd-MS
2
(without inclusion list)
Slide23Results
0.1 ppb
1 ppb
10 ppb
100 ppb
1000 ppb
Negative
✓
✓
✓
Positive
✓
✓
✓
✓
✓
Comparison in positive-ion mode and negative-ion mode (PC)
The lower limit of dd-MS
2
(with inclusion list)
Slide24Results
Lipid class
Number of identified peaks
PC
165
LPC
57
PE
66
LPE
20
PS
14
PI
30
LPI
4
PG
1
LPG
2
SM
10
TG
78
Analysis of lipids in mouse plasma
Slide25We developed an analytical system for a high-throughput and exhaustive lipid profiling by switching the polarity of mass spectrometry
This method enables qualitative analysis of lipids including minor molecular species
Over 300 lipid molecular species were identified from a sample of mouse plasma
Conclusions
Slide26Quantitative yeast lipidomics via LC-MS profiling using the Q Exactive Orbitrap mass spectrometer
David A. Peake
1
, Jessica Wang
1, Pengxiang Huang1
, Adam Jochem2, Alan Higbee2, David J. Pagliarini 21Thermo Fisher Scientific, San Jose, CA2
University of Wisconsin, Madison, WI
Slide27Coenzyme
Q is central to mitochondrial energy metabolism.
A
, Q is a requisite gateway through which
electrons of the ETC must pass. B,
Biosynthetic pathway for CoQ production in yeast.
Coenzyme Q’s Role in Mitochondrial Energy Metabolism
Slide28Growth Phenotypes of WT and KO Yeast Strains
Growth
phenotypes of
WT and KO
yeast strains.
Wild-type yeast continue to grow after glucose is exhausted from the media (the Diauxic Shift point), whereas the KO yeast with a defect in Coenzyme Q production, fails
to thrive. Yeast of each strain were collected before, during / after
this shift point for mitochondrial metabolomic
analyses
.
WT
KO
Slide29Methods
Growth Conditions
.
1 Liter cultures (WT or KO strains) were grown in YPD media (1.0% glucose, 30˚C) with shaking. Glucose consumption and OD
600 were monitored and yeast were collected at 3 time points along their growth curves (
Figure 2). Harvested samples were pelleted, snap frozen and placed at -80°C. Mitochondrial Enrichment. Yeast were treated with zymolase and homogenized, and mitochondria were enriched by differential centrifugation. Mitochondria protein levels were determined by BCA assay.
Isopropanol Extraction. Equal amounts of mitochondria from each sample (~0.25 mg) were transferred into 1.7 mL microfuge tubes and 400 µL of IPA was added to each sample and vortexed for 10 min at 4˚C. Samples were spun at 5000 g for 2.5 min and the supernatant was transferred to a new tube. Pellets were extracted 2x more with 400 µL IPA and supernatants for each sample were combined and then vacuum spun until dry.
LC-MS Sample Preparation.
The dried samples were dissolved in 250 µL 65% Acetonitrile, 35% IPA, 5% Water containing 5 µg/mL17:0 PG internal standard. Solvent blanks were 65% Acetonitrile, 30% IPA and 5% Water.
Samples analyzed by LC MS and MS-MS (
Table 1
) were duplicates of two yeast strains (
WT and KO
) grown in separate flasks and sampled post the Diauxic shift (
green
triangle
Figure 2
).
Table 1. Samples for LC-MS and MS-MS Analysis
Tube #
Strain
% Glucose
at
Collection
Description
3
Knockout
0
KO Post-shift
4
Knockout
0
KO Post-shift
11
wild-type
0
WT Post-shift
12
wild-type
0
WT Post-shift
Slide30HPLC MS-MS Method
Mobile phase A: 60:40
Acetonitrile
/ Water, 10mM ammonium
formate
, 0.1% formic acidMobile phase B: 90:10 IPA / Acetonitrile, 10mM ammonium
formate, 0.1% formic acidHPLC column:
Ascentis
Express C18 (Supelco, 2.1 x 150mm, 2.7µm) 55°C
Flow Rate: 260 µL / min
Injection volume: 10µL
LC MS-MS Conditions
ESI positive ion m/z 120 – 1800
Resolution = 70,000
Data-dependent Top 5 MS-MS
Resolution = 35,000
HCD @ 35.0 normalized collision energy
HPLC
Gradient Conditions
t
ime, min
%
A
% B
t
ime, min
%
A
% B
0.00
68
32
14.00
3070
1.506832
18.00
25754.00
554521.00
3975.00
4852
25.00 397
8.0042
58
25.0168
3211.00
3466
30.00
68
32
Hu
, C.; van
Dommelen
, J.; van
der
Heijden
, R.;
Spijksma
, G.;
Reijmers
, T.H.;
Wang, M.;
Slee
, E.; Lu, X.;
Xu
, G.; van
der
Greef
, J.;
Hankemeier
, T.
J. Proteome Res
.
2008
, 7, 4982–4991.
Slide31Data Analysis – SIEVE 2.0
LC-MS data was processed using Thermo Scientific SIEVE 2.0 software using the workflow:
1) Alignment
. Samples were aligned first using the full scan TIC (Total Ion Current) method.
2) Background Subtraction.
LC-MS data was corrected by the mean background obtained from the average of two blank solvent injections.3) Automated Mass Spectral Interpretation.
Spectra corresponding to the peak apex of each extracted ion chromatogram were examined for relationships between adducts, isotopes and dimers using accurate mass measurements. Related ions with similar retention times were grouped together into a component table represented by the largest adduct peak.
4) Statistical Analysis.
Principal Components Analysis was used to determine significant differences between samples. t-Tests were used to determine which components were significantly different between sample groups.
5) Identification.
ChemSpider searches of accurate m/z (or MW ) was used to identify potential metabolites and lipids. Phospholipids, DAG and TAG species were searched using a local database of lipids obtained from the LipidMaps.org online database. MS-MS spectra were manually inspected and species assigned based on known lipid fragmentation.
Slide32#3 KO post-shift
#12 WT post-shift
LC-MS of Lipids from WT and KO Yeast
TIC: 1.10 E+10
+ESI Full MS
TIC: 1.06 E+10
+ESI Full MS
LPC
PC
TAG
Slide33Alignment of TIC from WT and KO Samples
#
Strain
3
KO
4
KO
11
WT
12
WT
Improved TIC alignment – TAG region
Slide34Principal Component Analysis of WT vs. KO Samples
PCA Analysis shows that significant differences exist in lipids from WT and KO groups
#
Strain
3
KO
4
KO
11
WT
12
WT
Slide35Comp. #48, m/z 302.3053, KO/WT = 0.27, p = 0.021
#
Strain
3
KO
4
KO
11
WT
12
WT
Slide36ChemSpider
hits for Comp. #48, m/z 302.3053
#
Strain
3
KO
4
KO
11
WT
12
WT
Slide37ChemSpider hits for Comp. #48, m/z 302.3053
Sphinganine
Slide38Metabolite Differences: WT vs. KO Samples
Relative areas of metabolites that decrease or increase significantly
Ergosta-5,7,22,24(28)-tetraen-3
β-
ol
Co-Q6 (
oxid
.)
Co-Q9 (
oxid
.)
d18:0/16:0
Ceramide
Sphinganine
p = 0.003
p = 0.028
p = 0.020
p = 0.021
p = 0.006
p = 0.024
#
Strain
3
KO
4
KO
11
WT
12
WT
Histidine
Slide39PC (26:0)
Lipid Differences: WT vs. KO Samples
Relative areas of lipids that decrease or increase significantly
DG (18:1/18:1/0:0)
p = 0.010
TG(16:0/12:0/16:0)
p = 0.002
TG(18:1/18:1/18:1)
p = 0.008
PC (36:5)
PE (17:1/16:1)
p = 0.004
p = 0.012
p = 0.001
#
Strain
3
KO
4
KO
11
WT
12
WT
Slide40Co-Enzyme Q6 – LC-MS of Wild-type Yeast
[M+H]
+
NL: 2.94 E+8
RT: 15.28-15.33
Avg. 4 scans
+ESI Full MS
NL: 7.75 E+8
m/z 591.4408
+608.4673
TIC: 9.06 E+9
+ESI Full MS
[M+NH
4
]
+
CoQ6
34:1 PC
Slide41LC MS-MS of 52:1 TAG (M+NH4)
+
from WT Yeast
NL: 5.58 E+8
RT = 24.91
m/z 878.8171+ESI Full MSTIC: 1.12 E+10+ESI Full MS
NL: 3.83 E+5
RT: 24.9 Scan 8271
878.81
@ HCD 35.0
+ESI Full MS2
HCD
C16:0
C18:1
C18:0
16:0/18:0/18:1 TAG
MS-MS of TAG NH
4
+ adducts reveals fatty acid composition
Slide42LC MS-MS of 36:5 PC from WT Yeast
1ppm mass tolerance
NL: 1.17 E+7
RT = 12.22
m/z 780.5538
+ESI Full MS
TIC: 9.69 E+9
+ESI Full MS
NL: 5.58 E+5
RT: 12.2 #4001
780.53
HCD@35.0
+ESI Full MS2
NL: 1.30 E+7
RT: 12.2 #4028
+ESI Full MS
HCD
MS-MS of PC gives m/z 184
phosphocholine
fragment
Slide43LC MS-MS of 34:3 PE from WT YeastNL: 6.35 E+4
RT: 12.90 #4260
714.51
HCD@35.0
+ESI Full MS2
NL: 1.17 E+7RT = 12.94
m/z 714.5068+ESI Full MS
TIC: 8.28 E+9
+ESI Full MS
HCD
263.271
C
18
H
31
O
0.4498 ppm
311.2577
C
19
H
35
O
-1.3222 ppm
PE (16:1/18:2)
18:2
16:1
(M+H) –141.0191
MS-MS of PE gives loss of
headgroup
and fatty
acyl
ions
Slide44325.2740
C
20
H
37
O0.7218 ppm
251.2375C 17
H
31
O
2.0504 ppm
LC MS-MS of 37:2 PG (M+NH
4
)
+
from WT Yeast
C17:1
NL: 8.51 E+5
RT: 13.49 #4457
778.52
HCD@35.0
+ESI Full MS2
NL: 7.11 E+7
RT = 13.51
m/z 778.5593
+ESI Full MSTIC: 8.28 E+9
+ESI Full MS
C20:1
HCD
(M+NH
4
) – 189.0402
MS-MS of PG gives loss of
headgroup
and fatty acyl ions
Slide45Summary of Differences Between WT vs. KO Yeast
Analytes with p-Values < 0.05 for t-Test between WT and KO groups
Average fold-change (KO vs. WT) indicated by
Red
(increase) or
Green (decrease)
Slide46Summary of Differences between WT vs. KO Yeast
Analytes with p-Values < 0.05 for t-Test between WT and KO groups
Average fold-change (KO vs. WT) indicated by
Red
(increase) or
Green
(decrease)
Slide47Conclusions
This work demonstrates this new Hybrid quadrupole-Orbitrap mass spectrometer capable of up to 140,000 mass resolving power obtains very high quality accurate mass LC-MS and MS-MS data.
This preliminary analysis of yeast lipid extracts demonstrates the ability to obtain statistically significant results with a single injection of each biological replicate. The expected change in CoQ6 levels was accompanied by changes in 60 different lipid species.
Identification of 78 phospholipids, 16 DAG, 57 TAG and 16 other metabolites was possible using a single collision energy setting and without any prior optimization of conditions.
Acquiring untargeted lipidomics data provides full coverage of major lipid species as well as any other unexpected metabolites without any compromise in the data quality.
Slide48Acknowledgments
Dave
Pagliarini
– Univ. of Wisconsin, Madison, WI, USA
Takayuki YamadaTakeshi Bamba– Dept. of Biotechnology, Osaka Univ., Suita, JPYasuto
Yokoi – Mitsui Knowledge Industry, Tokyo, JP
Michael Athanas –
Thermo
Alain
Guiller
Pengxiang
Huang
Yingying Huang
Markus
Kellmann
Andre
Makarov
Madalina
OppermannShigeru SakamotoMark SandersJennifer SuttonJessica WangMartin Zeller