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Agilent Lipidomics
Workflow Overview
MS Data Lipidomics Workflows
A
MS/MS Data Qualitative Workflow
MS/MS Data Lipidomics Workflows
B
MS/MS Data Profiling Workflow
Find features in one file by MFE or Auto
MS/MS inMH Qual
Do an MS/MS SimLipid ID search
Find statistically significant features
with MPP
a Qualitative orkflow
d features one file by MFE in H Qual
o an MS SimLipid D search
Find features in multiple
files by MFE in MH Qual
Do an MS/MS SimLipid ID
search
With MS/MS ID Confirmation
Do an MS Data Profiling Workflow preferred ion
list
MS Data Profiling Workflow
Find features in multiple
files by MFE in MH Qual
Find statistically significant features
with MPP
Do an MS SimLipid ID search
Confirm features by recursive analysis in MH Qual
Find features by
Auto MS/MS in MH Qual
Confirm MS IDs with an MS/MS SimLipid search
Introduction to Lipidomics 2Required Items 7MS Lipidomics Workflows 8MS/MS Data Lipidomics Workflows 11For More Information 13
Introduction to Lipidomics
Introduction to Lipidomics
“Lipidomics” is one of the four components that make up the field of “metabolom-ics” research. Metabolites are the end products of all biological/cellular processes, and “metabolome” refers to the collective set of all metabolites generated in a bio-logical system (cell, tissue, organ or organism). Metabolomics is the scientific study to characterize and identify the metabolome. The metabolome is comprised of four major classes of biological molecules: sugars, amino acids, nucleotides, and lipids.
The systematic study of the entire lipid profile of a cell/tissue/organ/organism is referred to as lipidomics. Mass spectrometry is one of the most widely used technol-ogies in lipidomics research for the identification as well as quantitation of thou-sands of lipid molecules that constitute the full lipid complement of a biological system, called the “lipidome”.
“Discovery lipidomics” experiments involve examining an untargeted suite of lipids, finding the ones with statistically significant variations in abundance within a set of experimental versus control data samples, and determining their chemical structure. Pathway analysis lets you connect the lipid with a biological process or condition.
Discovery lipidomics involves the comparison of lipidomes between control and test groups to find differences in their profiles. Discovery lipidomics is a subset of discov-ery metabolomics and uses the same steps for analyses: profiling, identification, and interpretation.
Meaningful answers to lipid discovery experiments require not only mass spectrom-etry but also specialized data analysis software that facilitates cheminformatics, bio-informatics and statistical analyses, as well as a search program using an extensive lipid database.
Help for your lipidomics experiments
The Agilent Lipidomics Workflow Guide shows you how to use Agilent cheminfor-matics and statistical analyses software products, as well as a non-Agilent lipid database program, to derive meaningful answers to your lipidomics questions more efficiently than using typical mass spectral data analysis and identification pro-grams.
The guide gives you instructions in the form of workflows for using Agilent MassHunter Qualitative Analysis to isolate lipid features or compounds for further analysis; Agilent Mass Profiler Professional to reduce the compound set to only the most relevant and significant; and SimLipid from PREMIER Biosoft International to search an extensive lipid database to identify the lipids important for your experi-ment.
MassHunter Qualitative Analysis (MH Qual) software lets you automatically find and extract all spectral and chromatographic information (molecular feature extraction - MFE) from a sample, even when the components are not fully resolved. It combines this information into a set of features, or compounds. You can then export results into other applications, such as Mass Profiler Profes-sional or SimLipid.
Mass Profiler Professional (MPP) is a powerful data reduction, statistical analy-sis, and visualization tool that lets you identify statistically significant answers to
2
Introduction to Lipidomics
simple questions presented to complex data sets: data sets constituting your lipi-domics discovery experiments.
SimLipid, a product of PREMIER Biosoft International, is a lipid search program that lets you rapidly search an extensive lipid database. Agilent and PREMIER Biosoft have worked together to integrate the lipid identification at MS and MS/MS levels using SimLipid software in the Compound Exchange Format (CEF), which is unique to Agilent. This allows for seamless portability of the lipid output data between different Agilent programs and SimLipid.
Overview of the workflows The Agilent Lipidomics Workflow Guide takes you through five lipidomics workflows that help you with your lipidomics experiments depending on your specific goals and type of mass spectral data: three MS data workflows and two MS/MS data work-flows.
The workflows belong to two categories: qualitative workflows and profiling work-flows.
A “qualitative workflow” is a simple workflow to help you quickly find out if your samples contain a known category and class of lipids.
A “profiling workflow” is more complex and involves sample replicates to facili-tate statistical analysis. A profiling workflow helps to reduce the number of com-pounds that can be identified from thousands to the statistically relevant ones that are responsible for the differences in your discovery experiment samples.
A profiling workflow also includes the identification step of a discovery experi-ment but not the interpretation step. Other guides cover Pathway Architect, the Agilent program whose purpose is to help with interpretation.
The Agilent Lipidomics Workflow Guide is a supplement to the Metabolomics Dis-covery Workflow Guide. The explanations of the discovery metabolomics workflow for MS data given in the latter guide are the foundation for understanding the lipid-omics profiling workflows for MS and MS/MS data.
Some workflows are more useful than others depending on the goals of your study, and the later workflows build on the steps of the previous workflows.
3
Introduction to Lipidomics
MS Data Qualitative Workflow
If you want to quickly see if a lipid category or class is present in your MS data, you use the simple MS Data Qualitative Workflow, which uses only the Qualitative Anal-ysis program and SimLipid. See Figure 1.
Figure 1 MS Data Qualitative Workflow
MS Data Profiling Workflow A typical Agilent lipidomics profiling workflow for MS data is illustrated in Figure 2, starting with molecular feature extraction (MFE) for finding compounds. The results files are imported into MPP for quality control, statistical analysis and visualization to show only the most significant compounds for the experiment.
The SimLipid CEF file can be used by MPP and Pathway Architect for a biological pathways analysis.
Figure 2 MS Data Profiling Workflow
Find features in one file by
MFE in MH Qual
Do an MS SimLipid ID search
Find features in multiple
files by MFE in MH Qual
Find statistically significant features
with MPP
Do an MS SimLipid ID search
Confirm features by recursive analysis in MH Qual
4
Introduction to Lipidomics
MS Data Profiling Workflow with MS/MS ID Confirmation
The specific goals of the MS data lipidomics profiling workflow with MS/MS ID con-firmation are:
1 Do an MS data profiling workflow to produce a preferred ion list and an initial set of identified compounds.
2 Use the preferred ion list derived from the first goal to run LC/MS/MS in Auto MS/MS mode on a few representative samples of the original sample set and then run a Find by Auto MS/MS analysis on the MS/MS data with MH Qual.
3 Confirm lipid compound identification with SimLipid using the MS/MS data set for the representative samples used to acquire the MS data.
Because you are confirming the identities of relevant compounds found in all the MS data samples for your discovery experiment, you need only run the LC/MS/MS on one sample or a few representative samples of the set.
Figure 3 MS/MS ID Confirmation for MS Data Profiling Workflow
MS/MS Data Qualitative Work-flow
With this workflow you can use either MFE for MS/MS data or Find by Auto MS/MS with Auto MS/MS data.
Figure 4 MS/MS Data Qualitative Workflow
Do an MS Data Profiling Workflow preferred ion
list
Find features by
Auto MS/MS in MH Qual
Confirm MS IDs with an MS/MS SimLipid search
Find features in one file by MFE or Auto
MS/MS inMH Qual
Do an MS/MS SimLipid ID search
5
Introduction to Lipidomics
MS/MS Data Profiling Work-flow
This workflow is different in one important way from its MS counterpart. In order to find the compounds of greatest statistical significance for your experiment with MPP, you first search for and identify all the compounds in the MH Qual file with SimLipid and export the data to a SimLipid annotated CEF file, which you then import into MPP.
Figure 5 MS/MS Data Profiling Workflow
Find statistically significant features
with MPP
Find features in multiple
files by MFE in MH Qual
Do an MS/MS SimLipid ID
search
6
Required Items
Required Items See the Metabolomics Discovery Workflow Overview for a description of the required hardware and software, as well as optional software, for working with the lipidomics workflows.
The only additional software you need is SimLipid 3.3 or later. To follow the instruc-tions in the Lipidomics Workflow Guide you must have first purchased SimLipid 3.3 or later from PREMIER Biosoft International. You can purchase the software at www.premierbiosoft.com. Follow the installation instructions on the web site.
SimLipid 3.3 is a lipids identification tool whose new features were specifically designed to accommodate Agilent CEF files. Although SimLipid 3.3 can also import data files for lipid identification from other companies, it has these advan-tages when working with Agilent files:• Imports up to 100 data files containing “compounds”, rather than raw spectra,
making the analysis more effective and efficient.• Performs a neutral mass search at the MS1 level for MS/MS data• Uses adducts in the MS1 level data for MS/MS identification• Identifies lipids at any stage of the lipidomics discovery workflow• Exports CEF files to be used in Agilent data analysis software, including Path-
way Architect.
7
MS Lipidomics Workflows
MS Lipidomics Workflows
You can choose between three MS data lipidomics workflows: an MS data qualita-tive workflow, an MS data profiling workflow and an MS data profiling workflow with MS/MS confirmation of the MS data SimLipid identification.
MS Data Qualitative Workflow
The MS Data Qualitative Workflow includes two steps:
Step 1: Find features in one file by MFE in MH Qual
Compounds, also known as molecular features, are extracted from your data based on mass spectral and chromatographic characteristics. The process is referred to as Molecular Feature Extraction (MFE). Molecular feature extraction quickly and automatically generates a complete, accurate list of your compounds, which includes molecular weight, retention time, m/z, and abundance.
Step 2: Do an MS SimLipid ID search
SimLipid lets you easily search thousands of compounds in the MFE CEF file with its High Throughput Search. With SimLipid you can further restrict the search based on retention time, mass range, compound number, error tolerance, thresh-old, ion species, lipid category and lipid class.
1. Find features in one file by MFE in MH Qual.
a Create a method to Find Compounds by Molecular Feature.
b Save your Find Compounds by Molecular Feature method.
It is recommended you save the method using a name that is readily distin-guished from the names that you will use later in the next two workflows.
c Run the method.
2. Do an MS SimLipid ID search.
a Import the Agilent MS MFE CEF file into SimLipid.
b Do a high-throughput MS search on multiple compounds.
Only 1000 compounds can be processed at one time.
c Repeat step b until all compounds in the file are searched.
d Export the results to a CEF file.
Note: To do an MS Search on a single compound see the instructions in Chapter 2 of the Lipidomics Workflow Guide.
8
MS Lipidomics Workflows
MS Data Profiling Workflow
This MS data lipidomics workflow includes three steps, the first of which is the same first step as the MS Data Qualitative Workflow but done with multiple files.
Step 1. Find features in multiple files by MFE in MH Qual
Step 2. Find statistically significant features with MPP
This step reduces the number of compounds to only those that are significant for your profiling experiment.
You can reduce the compound set even further by doing a recursive analysis in MH Qual and then another filtering and statistical analysis with MPP.
Agilent recommends you go through as many steps of this lipidomics workflow with your MS data as you intend before identifying your lipids.
Step 3. Do an MS SimLipid ID search
Even though SimLipid is searching a single MPP CEF file in this workflow, the instructions are the same as those for a MH Qual CEF file.
1. Find features in multiple files by MFE in MH Qual.
Follow the same instructions as for the MS Data Qualitative Workflow for “Find fea-tures in one file by MFE in MH Qual.” on page 8 but with the changes listed in the Lipidomics Workflow Guide.
Also see the Metabolomics Discovery Workflow Guide for the instructions to export your data as a CEF file, set up workflow actions for DA Reprocessor, confirm method settings and run your data with DA Reprocessor.
2. Find statistically significant features with MPP.
a Create a new experiment.
b Import the data with the Experiment Creation Wizard.
c Group the samples with the Experiment Creation Wizard.
d Filter, align and normalize the sample data.
e Do the differential analysis.
f Export the data for identification.
g Save your project.
3. Do an MS SimLipid ID search.
Follow the instructions in the MS Data Qualitative Workflow for “Do an MS SimLipid ID search.” on page 8.
9
MS Lipidomics Workflows
MS Data Profiling Workflow with MS/MS ID Confirmation
This is the third MS lipidomics workflow with SimLipid identification. It comprises the MS Data Profiling Workflow with an MS/MS ID confirmation of the compounds identified using the MS Data Profiling Workflow with SimLipid identification.
Step 1. Do an MS Data Profiling Workflow
Step 2. Find features by Auto MS/MS in MH Qual
With a preferred ion list derived from the MS MPP results and SimLipid identifica-tion results, you can do an LC/MS/MS acquisition on one sample or a few repre-sentative samples of the same sample set, to produce MS/MS data for auto/targeted feature finding in the Qualitative Analysis program. Finding features for the representative sample(s) with MS/MS data leads to improvement in the accuracy of your compound identification.
Step 3. Confirm MS IDs with an MS/MS SimLipid search
This step gives you instructions for importing the Auto MS/MS CEF files into SimLipid, and identifying the compounds with SimLipid to confirm the identifica-tion of those found for the MS data and to identify lipids you could not identify before.
1. Do an MS Data Profiling Workflow.
Follow the instructions in “MS Data Profiling Workflow” on page 9.
2. Find features by Auto MS/MS in MH Qual.
a Create an Auto MS/MS method in the Qualitative Analysis program.
b Save your Find Compounds by Auto MS/MS method.
It is recommended you save the method using a name that is readily distin-guished from the names that you use in the other workflows.
c Run the method.
3. Confirm MS data IDs by using SimLipid on MS/MS data.
a Import Agilent MS/MS Data into SimLipid.
b Do a high-throughput MS/MS search on multiple compounds for the representa-tive file(s).
Note: To do an MS/MS Search on a single compound see the instructions in Chap-ter 3 of the Lipidomics Workflow Guide.
10
MS/MS Data Lipidomics Workflows
MS/MS Data Lipidomics Workflows
For MS/MS data you can use one or both of the two lipidomics workflows, each of which includes lipid identification with SimLipid: MS/MS Qualitative Workflow and MS/MS Data Profiling Workflow.
MS/MS Data Qualitative Workflow
Step 1: Find features in one file by MFE or Auto MS/MS in MH Qual
This step is almost identical to step 1 of the MS Data Qualitative workflow except you enter a value for a parameter you need only for MS/MS data.
Step 2: Do an MS/MS lipid ID search
You can do an MS/MS search on MS/MS data with MS1 level spectra and MS2 level spectra, or you can perform a search with just MS/MS spectra. If you do a search with no profiling first, you may have to identify thousands of compounds to find the ones you seek.
1. Find features in one file by MFE or Auto MS/MS in MH Qual.
Follow the instructions in “Find features in one file by MFE in MH Qual.” on page 8 but with changes described in the Lipidomics Workflow Guide.
Or, if you have Auto MS/MS data, follow the instructions in “Find features by Auto MS/MS in MH Qual.” on page 10.
2. Do an MS/MS SimLipid ID search.
Follow the instructions for “Confirm MS data IDs by using SimLipid on MS/MS data.” on page 10.
MS/MS Data Profiling Workflow
This is the second MS/MS data lipidomics workflow with SimLipid identification.
Step 1. Find features in multiple files by MFE in MH Qual
This step is virtually identical to the first step in the MS/MS Data Qualitative Workflow except you use DA Reprocessor to run multiple files.
Step 2. Do an MS/MS SimLipid ID search
At present you must do this step prior to working with MPP because MPP strips out the MS/MS compound information from the MFE CEF file so that it is useless for identification, but MPP can use the annotated MS/MS information after iden-tification for its analysis algorithms.
Step 3. Find statistically significant features with MPP
After you import the annotated CEF files you can set up an experiment and do sta-tistical analyses on the CEF files to reduce the number of compounds to only those that are significant for the profiling experiment. Because you have already annotated the compounds you do not need to do another lipid identification.
11
MS/MS Data Lipidomics Workflows
1. Find features in multiple files by MFE in MH Qual.
Follow the instructions in “Find features in multiple files by MFE in MH Qual.” on page 9.
2. Do an MS/MS lipid ID search.
Follow the instructions in “Confirm MS data IDs by using SimLipid on MS/MS data.” on page 10, but for multiple files (Hint: Use Import Files in Batch Mode).
3. Find statistically significant features with MPP.
Follow the instructions for “Find statistically significant features with MPP.” on page 9.
12
For More Information
For More Information For more detailed instructions and references, see the Agilent Lipidomics Workflow Guide.
And for information on metabolomics, see these documents:• Agilent Metabolomics Discovery Workflow Guide
(Agilent publication 5990-7067EN, Revision B, October 2012)• Agilent Metabolomics Discovery - Workflow Overview
(Agilent publication 5990-7068EN, Revision B, June 2012)
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© Agilent Technologies, Inc. 2012Printed in USA, December 2012
www.agilent.com
*5991-1644EN*5991-1644EN