Transcript MS/MS ALL Fragment and Neutral Loss Filter in PeakView Software

Infusion MS/MSALL Workflow;
TripleTOF™ 5600 System for Lipid Analysis
Brigitte Simons,
Sr. Applications and Sales Specialist at AB SCIEX
Infusion MS/MSALL Workflow On 5600
Basic Methodology
1. Lipid species confirmation is best carried out by high resolution MS/MS
acquisition – MS is not sufficient as precursor ion information alone is
compromised by high matrix interferences and isotopic overlap of many
lipid species (across many classes) in a small mass range.
2. MS/MS triggered by IDA vs MS/MS collected without MS dependence
a.
MS/MS collected without a dependence on MS survey information provides a an
easy acquisition technique that can be applied generically to any experiment of
desired polarity, ionization technique, or mass range.
b.
Every precursor ion is captured by MS/MS and nothing is missed - CE is applied
throughout a sweep to accumulate optimum ion current through many product ions.
c.
MS/MS spectra can result in very rich signal intensities even if the precursor ion has
a very low signal intensity
d.
These files sizes are very small yet contain a very high # of MS/MS spectra per cycle
3. Quantification is carried out by complementary product ion information from
the MS/MS spectrum and IS correction can be applied
4. This technique is supported by LipidView™ Software v1.1 for automated
2
identification and quantitation of lipids using comprehensive library
searching and MarkerView™ Software for PCA analysis and other
statistical outputs
© 2011 AB SCIEX
Infusion MS/MSALL Workflow
What’s the Benefit From this Feature?
− No method development and highly reproducible technique
− Can be applied to acquisitions of any ionization mode (ESI, APCI,
Positive, Negative, etc)
− Everything is sampled by high resolution, you don’t miss anything!
− Can be carried out in < 3 min
− Is applicable to direct infusion, flow injection and directed lipid class
LC techniques
− An MS technique that is scalable and represents ease of high
throughput
EASY
BUTTON
3
© 2010 AB SCIEX
Tested and Published Quantitative Technique
Where to find content for customers
− AB SCIEX Technical Note
– https://na10.salesforce.com/sfc/#version?selectedDocumentId=069F0000000N72q
− Publication in Metabolites 2012, 2(1), 195-213;
doi:10.3390/metabo2010195
– http://www.mdpi.com/2218-1989/2/1/195/
− ASMS 2012 Posters:
Lipidomics Analysis of a Subset of Human Serum Samples from the Dallas Heart Study
Jeff Mcdonald1; Brigitte Simons2; Stefan Thibodeaux3; Jennifer Krone2; Phillip Sanders3
1UT Southwestern Medical Center, Dallas, TX; 2AB SCIEX, Concord, ON; 3Eli Lilly, Indianapolis, IN
Information Independent MS/MS Data Collection of All Precursors Using Time-of-Flight Mass Spectrometry.
Brigitte Simons; Eva Duchoslav ; Lyle Burton; Tanya Gamble; Ron Bonner
AB SCIEX, Concord, CANADA
4
© 2010 AB SCIEX
Lipid Maps Consortium
Uncovering The Human Plasma Lipidome
Quehenberger et al, J Lipid Res. 2010 Nov;51(11):3299-305.
5
© 2011 AB SCIEX
Lipid Maps Consortium
Uncovering The Human Plasma Lipidome
−
Complete quantitative analysis of
over 580 lipids using MRM and
PIS/NL on 4000 QTRAP® Systems
− Synthetic lipid internal standards
available from Avanti Polar Lipids,
developed on QTRAP® 5500
Systems
− Complete list of MRM methods
available in Suppl. Methods for
each of 8 lipid classes
− Lead to the reviews on the future of
MS techniques for lipidomics
− Ion mobility MS
− Time-of-flight MS for quant/qual
− Tissue imaging
Applications of mass spectrometry to lipids and membranes.
Harkewicz R, Dennis EA.
Annu Rev Biochem. 2011 Jun 7;80:301-25.
6
© 2011 AB SCIEX
Lipid Analysis by Direct Infusion on the
TripleTOF™ 5600 System
7
© 2010 AB SCIEX
MS/MSALL Information Independent Data
Collection
Product Ions from Every Precursor
Direct infusion, flow injection, and lipidclass targeted LC techniques
8
Q1
Q2
Fast Q1 precursor selection step-wise
through mass range
CID Fragmentation
© 2011 AB SCIEX
MS/MSALL
Product Ions from Every Precursor In Order
− How to calculate cycle
– Mass range
– Step size to cover
mass range
– TOF MS/MS
accumulation time
(~50 – 100 ms)
– Looping in a TOF MS
scan (~ 200 ms)
Precursor mass m/z
time?
Time (one cycle)
9
© 2011 AB SCIEX
Acquisition Set-up
MS/MSALL
− Install MS/MSall mode Script from this location:
− C:\\program files\Analyst\scripts
− Restart Analyst Service
− Turn on MS/Msall mode from Scripts Menu in Analyst TF
− Restart Analyst Service
− Important: using the .poap txt file
− The ordered acquisition of MS/MS is carried out by
inclusion list triggered IDA whereby the MS/MS is
exclusively dictated by ordered masses in the inclusion
list
─ Inclusion list is created by excel and contains 3
columns: m/z, # of MS scans, # of cycles
─ It provides the appropriate mass defect as you
increase m/z
─ It can be modified to provide a larger step or
cover a different mass range
─ IMPORTANT: .poap file must have the same
name as the acquisition method (.dam) file name
and be saved to the Acquisition Methods folder in
10 the Analyst project
User creates this
inclusion list and
names the file to
exactly the .dam
file name.txt
© 2011 AB SCIEX
Acquisition Parameters
MS/MSALL
− A generic acquisition technique using Information
Independent Logic and collecting 1000 MS/MS/cycle
− Inclusion-based list depicting a mass at every 1 Da step
− User indicates how frequent to acquire MS scan and how
many cycles to complete.
− CE is always a sweep; 50 ± 30 eV to capture all fragments
User creates this
inclusion list and
names the file to
exactly the .dam
file name.txt
11
© 2010 AB SCIEX
MS/MS of Every Precursor Ordered in Time
Looking at the Raw Data in PeakView Software
− Open Analyst TF raw data file displaying the TIC
− SHOW>LC-MS Contour Plot
Total Ion Chromatogram
High Resolution MS/MS of
every mass
12
© 2010 AB SCIEX
MS/MS of Every Precursor Ordered in Time
Mining the Raw Data in PeakView Software
− PROCESS < Fragment and Neutral Loss Filter
13
© 2010 AB SCIEX
MS/MSALL
Fragment and Neutral Loss Filter in PeakView Software
TAG Profiling
− Open MS/MS all data
file in TIC mode
neutral loss filter = 245.20
neutral loss filter = 273.20
− PROCESS> Fragment
and Neutral Loss Filter
neutral loss filter = 299.20
− Precursor ion, fragment
ion, and neutral loss
filters
neutral loss filter = 325.20
− Set threshold and mass
tolerance.
TAG 50:2
+ NH4
TAG 52:2
+ NH4
14
TAG 50:1
+ NH4
TAG 54:3
+ NH4
© 2011 AB SCIEX
MS/MSALL
Fragment and Neutral Loss Filter
Precursors of 184.0733 m/z
Precursors of 264.235 m/z
Precursors of neutral loss 141.0 m/z
15
© 2011 AB SCIEX
PeakView’s IDA Explore Mode
Negative Mode TOF MS and MS/MS
Rat brain extracts (# 2) ~ 0.4 ng/mL
29 360 resolution
Ordered MS/MS view
High Resolution
MS/MS of 846.7 m/z
Resolution 29 932
Resolution 28 793
16
High Resolution TOF MS
© 2010 AB SCIEX
Formula Finder
Accurate Mass Tools in PeakView™ Software
1
IDA explore
 MH- -CH3
FA 22:6
3
PC 44:12 + AcO-
- product ion of
936.6 m/z
2
- XIC of 936.6
m/z
4
Formula Finder Results
from MS/MS spectrum
17
Flow of Lipid Identification from LC-MS/MS Workflow
Use of Lipid Catalogue and Calculators Ultilities for Fragment Interpretation
© 2011 AB SCIEX
Lipid Analysis by Direct Infusion Using
LipidView™ Software
18
© 2011 AB SCIEX
Software Solutions for Automated Lipid
Analysis
Enabling the Identification and Quantitation of Lipid MS Data
Software Highlights:
– More than 50 lipid classes containing 25,000+
lipid species represented in a lipid fragments
database.
– More than 600 characteristic lipid fragments
lists are included.
– Lipid catalogue and lipid calculator utilities are
included.
– Support of lipid bioinformatics in medium
sample throughput with a seamless link to
multivariate analysis tools in MarkerView™
software.
– Building of target screening methods from
identification results, with special focus on
accurate mass data.
– Semi-quantitative profiling with flexible use of
internal standards.
19
© 2010 AB SCIEX
Lipid Database for Accurate Mass
− Collection of building blocks of lipid molecules
and their arrangements within lipid classes
and lipid categories.
Lipid Catalogue Utility
− Information on lipid collision-induced
dissociation (CID) fragmentation.
− Isotope correction factor.
− Headgroup (HGS), neutral loss, and long
change base (LCB) specific scan types.
− Fatty acids (FA).
− Detailed fragmentation information for each
lipid species in both polarities.
− Common adduct forms.
20
© 2011 AB SCIEX
Lipid Database for Accurate Mass
− Prediction of lipid molecules based on the
experimental m/z in either positive or negative
polarity within lipid classes and lipid
categories.
Lipid Calculator Utility
− Information on formula composition and lipid
class.
− Mass accuracy and common species can be
used to refine the search result.
− Fatty acids (FA) and double bonds.
− Common adduct forms.
21
© 2011 AB SCIEX
MS/MSALL
Automated Lipid Identification and Response Correction in
LipidView™ Software
brain
liver
− Automated lipid identification and relative quantification
− Lipid class profiles (semi-quantitative) to measure ratios between
samples
22
© 2011 AB SCIEX
MS/MSALL
Product Ions from Every Precursor In Order
− Mean and % CV
measurements across
samples instantly
calculated for each lipid
− Excellent reproducibility
is seen for lipid-class
specific internal
standards
23
© 2011 AB SCIEX
MS/MSALL
Automated Lipid Identification and Response Correction in
LipidView™ Software
Table 1. A summary of the number of confirmed and common unique molecular
lipid species identified by LipidView™ Software across the lipid extracts using
MS/MSALL workflow.
Lipid Extract
Liver
Brain
Totals
Acquisition Mode
# of
Glycerophospholipids
identifications
# of Glycerol lipid
identifications
# of Sphingolipid
identifications
# of Sterol Lipid
identifications
Negative mode
MS/MSALL
800
3
0*
0*
Positive mode MS/MSALL
152
125
40
12
Negative mode
MS/MSALL
1147
0*
0*
0*
Positive mode MS/MSALL
239
112
119
3
Liver (total = 1132)
Brain (total = 1620)
952
1386
128
112
40
119
12
3
n=5 replicates analyzed per extract; only confirmed and common lipid species reported
0* = not included in search
24
© 2011 AB SCIEX
Linking Lipid Data to Statistical Analysis
Reporting and Exporting Lipid Profiling Data
Through this function, you
can export all data to
MarkerView Software, as
peak intensities or areas
25
© 2011 AB SCIEX
Principal Component Analysis
Multivariate Analysis Tools in MarkerView™ Software
Scores Plot
Loadings Plot
− Scores plot provides a visual distribution of the features and degree of
discrimination between the sample groups
− Loadings plot shows the variables (lipids) that lead to sample
clustering
26
© 2011 AB SCIEX
Principal Component Analysis
Multivariate Analysis Tools in MarkerView™ Software
Differential Profiling
t-test Log Plot
− Extraction of lipids from the data that show significant variation can be
profiled across the samples
− Log-fold change is visualized in t-test of liver lipids plotted against brain
27
© 2011 AB SCIEX