Rawputator – A New Tool to Combine Proteomic Data Mining
with Method Development, Result Validation and Quality Control
PP443
Martin Zeller, Bernard Delanghe, Christoph Henrich, Torsten Ueckert
Thermo Fisher Scientific, Bremen, Germany
The big advantage of having all that information in the
search output is the additional connection to the search
score. This can be used to evaluate the system
performance.
Overview
Purpose:
FIGURE 5. Plot of peptide charge state ratios.
date
11/6/10 0:22
11/6/10 2:33
11/6/10 4:43
11/6/10 6:44
11/6/10 8:44
11/6/10 10:45
11/6/10 12:30
11/6/10 14:16
11/6/10 16:02
11/6/10 17:32
11/6/10 19:03
11/6/10 20:34
Implementation of proteomics data evaluation for quality
control and method optimization.
FIGURE 2. Rawputator node in Proteome Discoverer
software.
Methods:
Hybrid linear ion trap-OrbitrapTM mass spectrometer with
specialized proteomics software.
Results:
Rawputator tool delivers quantitative system performance
assessment, method optimization and result verification.
Introduction
One of the biggest recurring questions in proteomics in a
high-throughput environment is whether or not all
parameters in the acquisition method are set optimally and
the acquired data meets your quality criteria. Good
practice therefore is to include quality controls in between
the samples to assess the system performance. Figure 1
shows the system in a proteomic workflow which
comprises sample preparation as well as LC, MS and data
analysis.
Why quality control?
• Optimum performance of the analytical system for
the reproducible analysis of complex samples
• Identification of the source of the sub-optimal
performance and variability
Extraction of the dynamic parameter:
- Precursor S/N
- TIC
- Ion inject time
- Elapsed scan time
- Effective collision energy [eV]
- Lockmass correction
Additional „costs“:
- ~ 6% .msf file size increase
- < 3 min per search job (complex cell
lysate sample, 13665 MS/MS)
dataset proteins
90 min 1
676
90 min 2
672
90 min 3
675
75 min 1
634
75 min 2
599
75 min 3
644
60 min 1
601
60 min 2
601
60 min 3
638
45 min 1
553
45 min 2
552
45 min 3
550
Quality Control Concept
Lockmass Correction
One example is to plot the lockmass correction over time
(see Figure 3). Low (internal) lockmass correction values
indicate on the one hand a valid external mass calibration
and on the other hand indicate appropriate external mass
calibration intervals.
FIGURE 6. Outlook on a quality control system within
Xcalibur / Proteome Discoverer software.
FIGURE 3. Lockmass correction over time.
date
11/6/10 0:22
11/6/10 2:33
11/6/10 4:43
11/6/10 6:44
11/6/10 8:44
11/6/10 10:45
11/6/10 12:30
11/6/10 14:16
11/6/10 16:02
11/6/10 17:32
11/6/10 19:03
11/6/10 20:34
• Evaluation of the impact of the changes or
improvements in the analytical system
• Documentation of the system performance metrics to
support the assessment of the proteomic differences
between biologically interesting samples
Figure 6 shows a concept for the implementation of quality
control as system suitability test as a system check before
samples are analyzed and a concept for including a quality
control sample in the sample queue. After the data
acquisition of the quality control sample is finished, a
quality control check is done automatically and the system
is stopped if it does not fulfill minimum quality
requirements.
dataset proteins
90 min 1
676
90 min 2
672
90 min 3
675
75 min 1
634
75 min 2
599
75 min 3
644
60 min 1
601
60 min 2
601
60 min 3
638
45 min 1
553
45 min 2
552
45 min 3
550
1. System suitability test
QC sample and QC analysis, QC sample re-injection after
corrective actions if system shows low performance
QC sample
Methods
QC ok?
QC analysis
YES
real samples
NO: Restore system performance
Sample Preparation
Different enzymatic degradation preparations of complex
proteomes were prepared using standard protocols.
2. Quality control sample in sample sequence
Liquid Chromatography
QC sample in sequence (and sequence pause if QC
shows low system performance)
All samples were separated by a Thermo Scientific
EASY-nLC II liquid chromatograph using a peptide trap
(C18 BioBasic, 100 μm inner diameter, 2 cm length) and a
C18 analytical column (C18 BioBasic, 75 μm inner
diameter, 10 cm length, both NanoSeparations, NL), at a
flow rate of 300 nL/min using standard data-dependent
acquisition methods.
Mass Spectrometry
Proteomic data sets were acquired using a Thermo
Scientific LTQ Orbitrap Velos hybrid mass spectrometer.
Data Analysis
Data analysis was done using Thermo Scientific Proteome
Discoverer software evaluation version 1.3.
FIGURE 1. Proteomic workflow.
Sample preparation
Proteome
Mass spectrometry
Data analysis
Charge state ratios
One example for a digestion quality check is the plot of the
charge state ratios of all ions triggered for MS/MS. Figure 4
shows a plot of all precursor ions triggered for MS/MS per
charge state and identified peptides per charge state for a
single run. If the same enzyme is used for digestion and
other instrument parameters are not changed then the ratio
of the triggered precursor ions (2+/3+, 2+/4+, 3+/4+, ...)
should be on the same level (see Figure 5). This plot also
allows the identification of possible outliers. In this example
the same sample is analyzed in triplicates with different
gradient lengths. The number of identified proteins is for
the 90-min and 45-min runs at the same level but for the
75-min and 60-min runs one outlier per triplicate can be
spotted. For 75-min run 2 and for 60-min run 3 shows
deviation from the normal distribution for the precursor ion
charge states as well as in the number of identified
proteins.
FIGURE 4. Number of precursor ions triggered for
MS/MS and identified peptides per charge state.
QC sample
real samples
QC analysis
QC ok?
NO: Pause sequence, restore system performance and reinject samples
Conclusion
New Rawputator node allows
 Extraction of additional dynamic precursor ion
information
 Diagnosis of instrument performance (LC + MS) and
sample integrity
 Identification of outliers
 Method development and optimization
References
Ionization (ESI)
Precursor ions
Identified peptides
1. Rudnick PA et al. Performance metrics for liquid
chromatography-tandem mass spectrometry systems
in proteomics analyses. Mol Cell Proteomics. 2010
Feb;9(2):225-41.
12000
10000
Digest
YES: Continue with sample injections
Full MS
8000
6000
2. Köcher T, Pichler P, Swart R, Mechtler K. Quality
control in LC-MS/MS. Proteomics. 2011
Mar;11(6):1026-30.
MS/MS
4000
2000
0
Identification
Quantitation
2+
3+
4+
charge state
Results
Rawputator Node in Proteome Discoverer Software
The Rawputator node can be easily added to any
database search workflow within Proteome DiscovererTM
software and extracts from the raw file additional dynamic
precursor ion parameter per MS/MS spectrum as shown in
Figure 2. The extracted values are stored in the .msf
search output format. The additional time for the extraction
is almost neglectable as well as the file size increase of
the .msf output.
5+
6+
All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.
This information is not intended to encourage use of these products in any manners that might infringe the intellectual
property rights of others.