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 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. MS/MS triggered by IDA vs MS/MS collected without MS dependence 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. 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. MS/MS spectra can result in very rich signal intensities even if the precursor ion has a very low signal intensity These files sizes are very small yet contain a very high # of MS/MS spectra per cycle Quantification is carried out by complementary product ion information from the MS/MS spectrum and IS correction can be applied This technique is supported by LipidView™ Software v1.1 for automated identification and quantitation of lipids using comprehensive library searching and MarkerView™ Software for PCA analysis and other statistical outputs

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

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

Lipid Maps Consortium Uncovering The Human Plasma Lipidome Quehenberger et al, J Lipid Res. 2010 Nov;51(11):3299-305.

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.

Lipid Analysis by Direct Infusion on the TripleTOF™ 5600 System

Fast Q1 precursor selection step-wise through mass range MS/MSALL Information Independent Data Collection Product Ions from Every Precursor Q1 Q2 Fast Q1 precursor selection step-wise through mass range CID Fragmentation Direct infusion, flow injection, and lipid-class targeted LC techniques

MS/MSALL Product Ions from Every Precursor In Order How to calculate cycle time? 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 (one cycle)

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 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 User creates this inclusion list and names the file to exactly the .dam file name.txt 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 the Analyst project

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

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

MS/MS of Every Precursor Ordered in Time Mining the Raw Data in PeakView Software PROCESS < Fragment and Neutral Loss Filter

MS/MSALL Fragment and Neutral Loss Filter in PeakView Software TAG Profiling neutral loss filter = 245.20 Open MS/MS all data file in TIC mode PROCESS> Fragment and Neutral Loss Filter Precursor ion, fragment ion, and neutral loss filters Set threshold and mass tolerance. neutral loss filter = 273.20 TAG 52:2 + NH4 TAG 50:2 + NH4 TAG 50:1 + NH4 TAG 54:3 + NH4 neutral loss filter = 299.20 neutral loss filter = 325.20

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

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 High Resolution TOF MS

Formula Finder Results from MS/MS spectrum Accurate Mass Tools in PeakView™ Software 1 IDA explore  MH- -CH3 - product ion of 936.6 m/z 2 FA 22:6 3 - XIC of 936.6 m/z PC 44:12 + AcO- 4 Formula Finder Results from MS/MS spectrum Flow of Lipid Identification from LC-MS/MS Workflow Use of Lipid Catalogue and Calculators Ultilities for Fragment Interpretation

Lipid Analysis by Direct Infusion Using LipidView™ Software

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. AB Sciex now offers a complete software package dedicated to the analysis of Lipid data, called LipidView Software. It features a lipid fragments database composed of over 600 fragment ions across 44 lipid classes and over 23000 individual lipid species. There are specialized utilities to browse the lipid database by lipid name or by mass and the software supports the batch processing of electrospray data from all AB Sciex Instruments.

Lipid Database for Accurate Mass Collection of building blocks of lipid molecules and their arrangements within lipid classes and lipid categories. 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. Lipid Catalogue Utility

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. 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. Lipid Calculator Utility

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

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

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 Acquisition Mode # of Glycerophospholipids identifications # of Glycerol lipid identifications # of Sphingolipid identifications # of Sterol Lipid identifications Liver Negative mode MS/MSALL 800 3 0* Positive mode MS/MSALL 152 125 40 12 Brain 1147 239 112 119 Totals Liver (total = 1132) Brain (total = 1620) 952 1386 128 n=5 replicates analyzed per extract; only confirmed and common lipid species reported 0* = not included in search

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

Principal Component Analysis Multivariate Analysis Tools in MarkerView™ Software Scores Plot Loadings Plot principal component analysis [PCA] for multivariate datasets to compare the lipid ids across multiple samples and sample groupings. The scores plot on the right allows you to visualize the measurements that discriminate between the groups and identify outliers through each PCA test. The loadings plot shown on the right provides you with valuable insight into variables that lead to sample clustering and illustrates which lipids represent the significant differences between groups. So, this analysis benefits from the lipid id and m/z annotation from our lipids software for easier interpretation. Additionally, non-identified peaks can also be parsed from the dataset and subjected to PCA analysis for the discovery of novel lipid identifications that may be implicated in the lipidome studied. 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

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