quantitative ms of peptides and proteins · wherein different endogenous peptides are quantified...
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Quantitative MS of Peptides and Proteins
Relative Quantitation
Isotope Labels
SILAC
Label-Free
Absolute Quantitation
Isotopically Labeled Authentic Standards
Label-Free
Quantitative Mass Spectrometry of Peptides and Proteins
– Quantitative MS is easy to try, hard to do right
– Quantitative MS often relies on use of isotopically labeled authentic standards
– Sets of “Light and Heavy” reagents can be used for relative quantitation
– Label-free quantitation is often very useful
• Used for relative quantitation and “Top-3” Molar Quantitation
– Recommended reading:
• “The Principles of Quantitative Mass Spectrometry”
Mark Duncan, P. Jane Gale, and Alfred L. Yergey
www.RockpoolProductions.com , ISBN 0-9786058-0-2
Differential Expression Proteomics
Isotopic Labeling for MS-based Quantitation in Proteomics
(ICAT) developed by Reudi Aebersold (Nature Biotechnology, 17, 994, 1999)
Goshe and Smith, Curr Op in Biotech (2003) 14:101
Stable Isotope Labeling for Quantitative Proteomics:
- Lots of Options
Goshe and Smith, Curr Op in Biotech (2003) 14:101
Chemical Labeling with Stable Isotope Tags: ICAT, iTRAQ, etc
ICAT Reagent and Strategy
Analytical Challenges Associated with Performing Quantitative
Proteomics Using Chemical Isotopic Labeling
• Bypassing gels avoids problems with membrane proteins, other special cases
• Sample loading issues contributing to poor dynamic range are reduced
• Not all proteins contain cysteine (tag dependent)
• Post-translational modifications will be missed (tag dependent)
• Isotope effects in chromatography of some tagged peptides, depending on label chemistry
• Quantitation from LC/MS: relative intensities of isotope clusters
• Protein Identification from LC/MS/MS: peptide sequencing (MS/MS)
• Analytical challenge - very complex mixtures (30,000+ peptides/sample) – pre-fractionate tissue sample
– Multidimensional analytical HPLC (capillary LC/LC/MS/MS)
http://docs.appliedbiosystems.com/pebiodocs/00113379.pdf
Applied Biosystems iTRAQ reagents use isobaric tags
Multiple tags present with the
same nominal mass in survey
spectra
Quantitation is done during the
MS/MS step, simultaneously
with peptide identification
Only quantify peptides
sequenced by MS/MS
- A subset of all peptides
present
Goshe and Smith, Curr Op in Biotech (2003) 14:101
Metabolic Stable Isotope Coding
SILAC generates a lot of
data regarding 2 samples
- Be aware of statistical
considerations
Even when quantitative methods are used, most of the time, the focus
is on function. There is little attention to the details of quantitation. Such
an approach is fundamentally flawed. Forget not the basic principals of
quantitative analyses.
– Replication; QCs; Validation
Rigorously use Quantitatively Reproducible Analytical Methods
Forget not the basics of analytical chemistry
• Highly reproducible chromatography is required
• A high sampling rate across the chromatographic peak is required for
accurate quantitation
•Ideally want 15-20 sampling points across chromatographic profile
•Highly reproducible chromatography is required for sample-to-sample
comparisons
• High resolution, accurate mass (precursor & products) tandem mass
spectrometry technology needed
• For quantitative selectivity (near isobaric cross-talk)
• For accurate qualitative identifications
1% FPR at peptide level (Decoy DB; Peptide Prophet)
• No QCs = No Quantifiably Reliable Data
• No Replication = No Quantifiably Reliable Data
• No Common Standard = No Meaningful Comparison
across Projects
Column Condition
QC1 Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 QC 2 Sample 11 Sample 12 Sample 13
Rigorously use Quantitatively Reproducible Analytical Methods Daily QC Checks of Data Acquisition Precision and Reproducibility
Instrument Performance Checks
Day 1(+) QCs Column Conditioning
Preliminary database searches
Day 2: Data Collection Day 3: Data Collection
QC X-1
Sample X-5
Sample X-4
Sample X-3
Sample X-2
Sample X-1
Sample X
QC X ………
Day X: Data Collection
• Want to maximize biological powering - analyzing as many samples as possible
• Must use robust LC-MS platform and singlicate analysis of each sample
• Data QC is performed by daily injections of a “standard” of the same biological sample
(pool)
• Aliquots of same pool used in all projects – QC tracking across projects
Quantitatively Reproducible Analytical Methods Forget not the basics of analytical chemistry
Assessing Quantitative Reproducibility with Daily QCs
• Analytical Variability ~ 35,000
peptides
• Daily QC Sample (pool of QC plasma sample)
• Analytical + Biological Variability
• Patient Samples
25% CV Plasma Peptides
Note X- Axis Scale Differences
QC Samples 0 to 170% CV
Biological Samples 0 to 500% CV 125% CV Plasma Peptides
~ 40% peptides
CV < 10%
~ 70% peptides
CV < 20%
~ 90% peptides
CV < 25%
~ 2 % peptides
CV < 25%
QC Metric #1 = %CV (Anal. + Biol. Variability) - %CV (Anal. Variability)
- Alternating cycles (1 sec. each) of precursor / product scans provides high
reproducibility via a high sampling rate across chromatographic peak
- Major attribute of MSE
VVGLSTLPEYIEK, 12.8% CV across all samples
Rigorously use Quantitatively Reproducible Analytical Methods Assessing Quantitative Reproducibility at the Peptide Level with QCs
Reproducibility of Internal Standard Spiked into Each Sample
ADH1_YEAST (50fmol/ug)
Peptide Abundance across 60 patient clinical cohort
DDA Data
Qual only
Accurate Mass & Time Tags
Gel-Free, Label Free Qualitative and Quantitative Analyses
Accurate mass measurement:
MS/MS not necessary once AMT
tag is validated
-scalable to less expensive MS-
only spectrometers
Permits creation of databases of
AMTs for different proteins in
different tissues
- in essence the databases are
“lookup tables”
Transforms LC/MS into an “array
technology”
Provides quantitative and
qualitative data
Smith et al, Proteomics 2,513 (2002)
100 fm to 100 pm proteins
spiked into serum
- excellent linearity of
response
- accurate quantitation
When peptide matches are obtained
using AMT tags .. unique matches
of a mass spectral peak occurs 88%
of the time. Not only are AMT tag
matches unique in most cases, the
coverage of the proteome is high;
3,500 unique peptide AMT tags are
found on average per capillary LC
run. From the results of the AMT
tag database search, 900 ORFs
detected using LC-TOFMS, with
500 ORFs covered by at least two
AMT tags.
Match of peptide RT and MW
with AMT qualitatively identifies
a protein
Measurement of peptide
intensity quantitates protein
Each of the 12,609 spots is a
validated AMT for D.
radiodurans
Each defines a protein in the
genome
LC/MS Accurate Mass and Time Tags (AMTs) Deinococcus radiodurans, Smith JASMS 2003
Overview of Label Free Quantitation
LC
Separation
Acquisition of
MS Data
Import Raw
Data
Data Alignment
& Feature
Extraction
Import Raw
MS/MS Data
Annotation &
Peptide/Protein
Analysis
Statistical
Analysis of
Differences
Acquisition of
Selected
MS/MS Data
Via Targeted
Analysis
Peptide
Identification
(Database
Search Engine)
(courtesy Rosetta Biosoftware)
LC retention time
mas
s-to
-char
ge
(m/z
) ra
tio
Gel-Free Label Free Proteomics
High Resolution, Accurate Mass 3D Peptide Mass Map X and Y coordinates identify the peptide
Y coordinate (mass-to charge ratio) is fixed to <5 ppm error
X coordinate (LC Retention Time) has more variability (typically < 60 seconds)
An isotope group of
a peptide
•Intensity (AUC) of SIC of peptide is the quantitative measure
•Must be accurately measured across statistically significant sample
cohort
Results of Data Alignment based on
Accurate Mass and Retention Time Raw
Data
Aligned
Data
111,015 Features
Aligned across 16
LC/MS Analyses
of Cell Lines
How to QC this vast
Amount of Data?
Aligned Data
Combined by
Biological Condition
QC of Individual Isotope Groups pairwise t-tests of significance of peak area
measurement
Label Free Intensity Plots differential expression visualization
Cluster Analysis of Label Free
Quantitation Datasets
• Cluster Analyses
– Examine large data sets
and determine if items
behave similarly
– Data belonging to the
same cluster are similar
at some level
– Data sets in different
clusters are less similar
at some level
– Make a preliminary
assessment of possible
relationships between
clusters and identify
data sets for further
investigation
Proteins
Tre
atm
en
t G
rou
ps
Differential Protein Expression
• Differential protein expression studies are key for – Identifying biomarkers of disease and treatment response
– Elucidating biological pathways
– Identifying and validating protein drug targets
• Essentially all differential proteomics studies have studied relative protein expression – Isotope labeling methods
– Label free methods
• Differential proteomic expression studies based on absolute quantitation have yet to be fully exploited
• These workers made the notable and unexpected
observation:
– “the average MS signal response for the three
most abundant peptides per mole of protein is
constant within a coefficient of variation of less
than 10%”
– “Given an internal standard, this relationship is
used to calculate a universal response factor
(counts/mole)”
Intensity Distribution of Peptides from One Protein Response Per fmol for a Six Protein Mixture
Biological “Validation” by Determining Stoichometric Ratios
Absolute Quantification of Proteins by LCMSE
A Virtue of Parrallel MS Acquistion
Jeffrey C. Silva, Marc V. Gorenstein, Guo-Zhong Li, Johannes P.C. Vissers, Scott Geromanos
Molecular & Cellular Proteomics, 5:144-156, 2006.
Relative Protein Expression
• Provides data on protein expression changes between two or more samples within the same experiment
• Requires direct comparison of proteolytic peptides or marker ions from proteolytic peptides
– Provides relative abundance ratios of the same protein between different samples
– Data does not extrapolate beyond the experiment • Experiments are isolated “islands of information”
Absolute Protein Expression
– ‘omic scale
• Calculation of the absolute amount of
the proteins present (ng or fm) in a
sample
– Permits determination of stoichiometry of
proteins in macromolecular complexes
– Permits extrapolation of results to different
experiments in different labs
Absolute Quantitation at the Protein Level
- E. coli lysate spiked with 4 exogenous proteins
0.01
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57 (
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CO
LI
RL
31_E
CO
57 (
+4)
NF
SA
_E
CO
LI
EC
OT
_E
CO
LI
RL
24_E
CO
57 (
+1)
GN
TY
_E
CO
57 (
+5)
GL
RX
4_E
CO
57 (
+2)
CA
N_E
CO
LI
ER
PA
_E
CO
57 (
+5)
GL
TB
_E
CO
LI
YT
FN
_E
CO
LI
TO
P1_E
CO
LI
RH
SB
_E
CO
LI
GP
MB
_E
CO
57 (
+1)
KD
PD
_E
CO
LI
T1R
K_E
CO
LI
MA
SZ
_E
CO
LI
AR
NB
_E
CO
57
AR
NB
_E
CO
LI
AR
NB
_E
CO
L6
YB
JD
_E
CO
LI
YN
CB
_E
CO
LI
YD
DA
_E
CO
LI
YD
BA
_E
CO
LI
RH
SA
_E
CO
LI
YH
GF
_E
CO
LI
PU
TA
_E
CO
LI
HD
HA
_E
CO
57 (
+1)
PH
SM
_E
CO
LI
WC
AI_
EC
OL
IR
HO
_E
CO
57 (
+2)
AT
CU
_E
CO
LI
6P
GL
_E
CO
LI
PU
R7_E
CO
57 (
+2)
AR
OD
_E
CO
LI
HL
DD
_E
CO
57 (
+4)
DP
O2_E
CO
LI
NU
OF
_E
CO
LI
RM
LA
1_E
CO
LI
PT
HP
_E
CO
57 (
+2)
GL
PB
_E
CO
57 (
+3)
RB
SK
_E
CO
57 (
+1)
YH
DW
_E
CO
57 (
+1)
PU
R5_E
CO
57 (
+4)
NA
DE
_E
CO
57 (
+2)
AD
PP
_E
CO
57 (
+2)
PD
XJ_E
CO
57 (
+1)
YC
IE_E
CO
LI
IHF
B_E
CO
57 (
+2)
BC
CP
_E
CO
57 (
+2)
RL
30_E
CO
57 (
+4)
YU
BF
_E
CO
57 (
+1)
protein name
30025020015010050
protein count (n)
'Mix 1_avg_ng'
'Mix 2_avg_ng'
Absolute Quantitation for Measurement of
Fold-Changes E. coli spiking Experiment
6
7
89
1
2
3
4
5
6
7
89
10
2
av
g p
rote
in o
n-c
olu
mn
(n
g)
TN
AA
_E
CO
57 (
+1)
EF
TU
_E
CO
57 (
+2)
GL
PK
_E
CO
57 (
+1)
PH
S2_R
AB
IT
CH
60_E
CO
57 (
+3)
EF
G_E
CO
57 (
+4)
DC
EB
_E
CO
57 (
+1)
DC
EA
_E
CO
L6 (
+1)
DN
AK
_E
CO
57 (
+2)
AD
H1_Y
EA
ST
AL
BU
_B
OV
IN
RB
SB
_E
CO
LI
AH
PC
_E
CO
57 (
+2)
RP
OB
_E
CO
57 (
+4)
AL
DA
_E
CO
LI
IDH
_E
CO
LI
CIS
Y_E
CO
L6 (
+1)
MD
H_E
CO
57 (
+4)
EN
O_E
CO
57 (
+5)
CL
PB
_E
CO
57 (
+2)
RS
1_E
CO
57 (
+2)
PG
K_E
CO
57 (
+2)
EN
O1_Y
EA
ST
DG
AL
_E
CO
L6 (
+1)
RP
OC
_E
CO
57 (
+2)
HD
EB
_E
CO
L6 (
+1)
AC
EA
_E
CO
L6 (
+1)
PP
CK
_E
CO
L6 (
+1)
AC
ON
2_E
CO
LI
PF
LB
_E
CO
LI
EF
TS
_E
CO
57 (
+2)
GC
SP
_E
CO
57 (
+1)
AD
HE
_E
CO
57 (
+1)
GL
YA
_E
CO
57 (
+2)
GL
PQ
_E
CO
LI
UV
RA
_E
CO
57 (
+2)
OD
P1_E
CO
57 (
+1)
TIG
_E
CO
57 (
+1)
OS
MY
_E
CO
L6 (
+1)
DL
DH
_E
CO
57 (
+2)
RL
7_E
CO
57 (
+2)
OD
P2_E
CO
LI
GP
MA
_E
CO
57 (
+2)
OD
O2_E
CO
57 (
+1)
6P
GD
_E
CO
LI
CH
10_E
CO
57 (
+2)
TP
X_E
CO
57 (
+2)
PU
R9_E
CO
57 (
+1)
protein name
403020100
protein count (n)
'Mix 1_avg_ng'
'Mix 2_avg_ng'
Figure 1.Fundamentals of isotope-dilution
mass spectrometry for quantification. (A)
Amount of the native or endogenous peptide
in the sample is quantified using the ratio of
the mass spectrometric response to the
endogenous peptide and the SIS peptide and
the initial amount of the SIS peptide spiked
into the sample. (B) In SRM, only specific
product ions from collision-induced
dissociation events are recorded. The top
panel illustrates the operations of an ion-trap
mass spectrometer, whereas the bottom panel
illustrates the operations of a triple quadrupole
mass spectrometer for SRM. Note that
operations in an ion-trap are 'sequential in
time' for a given population of injected ions,
whereas in a triple quadrupole, each
quadrupole specializes in carrying the three
operations simultaneously on the ions that are
continuously conveyed. Parent ion m/z,
product ion m/z, and elution-time criteria from
SRM enable selectivity and sensitivity for the
detection of specific peptides in complex
mixtures from biological sources. Recording
multiple product ion trasitions, as in multiple
reaction monitoring, can further increase the
selectivity. SIS: Stable isotope-labeled
standard; SRM: Selected reaction monitoring.
A Simple Explanation of Selected Reaction Monitoring for
Quantitative Analysis
Mayya and Han, Expert Rev Proteomics 3(6), 597-610 (2006)
(A) In the regular MRM mode of acquisition,
the mass spectrometer records product ion
transitions intended from the SIS peptide
and the endogenous peptide in alternate
scans.
(B) The mass spectrometer can be
instructed to record multiple product ion
transitions from multiple SIS and
endogenous peptide pairs and continue to
do so in each acquisition cycle for the entire
duration of chromatography. This allows
multiplexed quantification. However, the
reduced sampling frequency can
compromise sensitivity, reproducibility and
accuracy of quantification.
(C) The chromatographic duration can be
subdivided into time-segments or slices
wherein different endogenous peptides are
quantified using corresponding acquisition
cycles. However, the method is limited by
the peak capacity of the online
chromatographic method and requires
highly reproducible elution times.
(D) It is practically difficult to achieve
consistent elution times of peptides in
complex mixtures on a routine basis. A
hybrid 'staggered multiplexing’ is an
optimum strategy as it attempts to maximize
the elution time-window for the peptides and
also to minimize the number of MRMs in
each acquisition cycle. The peptide-pairs in
each acquisition cycle are indicated for
illustrating the 'staggered’ nature of
acquisition.
Fig. 2. Calibration curves for quantifying heavy-labeled pure AAC
and TNFα peptides. The ion signals for different amounts of pure
synthetic heavy peptides were measured using LC–MS and used to
determine the linear range of quantification on the linear ion trap
instrument. Duplicate analyses were performed for each amount of
peptide injected. Error bars show the range for each measurement.