Accelerating Research in Life Sciences PREMIER Biosoft Accelerating Research in Life Sciences 1 1

A High Throughput Lipid Characterization Tool using MS Data 2 2

Major features Comprehensive database containing 40, 298 lipids, 1,509,305 structure-specific in-silico MS/MS characteristic ions, and over 5,200 target masses of PIS/NLS A software tool capable of supporting Shotgun, MALDI-, LC-, MS and MS/MS workflows Identify lipids for 10,000 MS/MS scans in a batch Isotope peak correction to facilitate accurate quantitation of lipids Portable reports in Microsoft excel, HTML, CSV, JPG, PNG files. 3 3

SimLipid® DB: You Can Customize 4

Create a new project Specify a project name and click “Create” 5 5

Import data from native as well as standard data files Import Shimadzu (.lcd) files 6

Shortcut for importing “Shimadzu” data Browse to the location of Shimadzu files, select the files (multiple selection is possible) and click “Open” 7 7

Selection of scans & specify range for each sample within a file 1.Select a sample within a file 2. Select All Scans of a sample, to select all the scans in one click 4. Click “Load Scan”

Averaged Scans Loaded in Project Management Panel

Model Experiment Design for targeted lipid identification 3. Shortcut to Model Experiment Design 2. Analyze > Lipid Quantitation > Model Experiment Design 4. Select only average profiles for experiment design and press “OK” 1. Select the Lipid Quantitation node 10

Model Experiment Design 1. Specify Experiment Name Specify error tolerance for mapping Target Mass entered with Target Mass stored in the database 2. Specify Sample Name 5. Click to transfer all the information into selected profiles table 3. Select a sample 7. Press “OK” 4. Select all scans Polarity and Target Mass and Scan Type information is read automatically from the file 6. Click on Map Target Mass Database option to map the target masses with SimLipid's target fragment database. 11

Target Mass Mapping – review the mapped fragments Results obtained for Target Mass = 241.1 12

Target Mass Mapping – review the mapped fragments Specify error tolerance for performing Exact Mass search with the SimLipid Database. 13

Specify peak correction parametres & click “OK” to perform search 14

A high throughput search ID number is generated HTP ID 15 15

Check HTP Status and Load Results Load HTP Results Click this button to check HTP search status 16

Check HTP Status and Load Results Click this button to check HTP search status 17

Check HTP Status and Load Results Load HTP Results 18

Result View of PIS/NLS_241.1_Neg Note that Glycerolipids with PI class is only reported Experiment name Sample name Notice the hierarchy of experiment, sample and and replicates 19

Mark Internal Standard 1. Select a lipid to be marked as internal standard 2. Select Mark/Unmark/Edit Internal Standard button 3. Specify the amount of Internal Standard 20

Align scans in a sample 1. Analyze > Lipid Quantitation > Align Scans in Sample Select the experiment name from the drop down list Select the PIS/NLS/Full Scan nodes to be aligned for a sample 21

Scans aligned at sample level Note here the Internal Standard PC (34:2) is aligned from all the scans in the sample 22

Generate Comp. x Conc. Report 2. Select the fragment type and lipid abundance option for generating Comp. X Conc. report 3. Select “Heat Map” to generate heatmap 1. Click on “Comp. X Conc. Report” button 4. Select file type 5. Click OK 23

Export Results 1. File > Export Results > Project 2. Select file type 3. Click OK 24

Results Exported into MS Excel File 25

Samples Alignment in an Experiment 26

Align Samples in an Experiment Use shortcut button to align samples Analyze > Lipid Quantitation > Align Samples 1. Select the Experiment Name 2. Select the Samples to be aligned 3. Select the alignment options 4. Click OK

Lipids Aligned at Sample Level Lipids aligned from all three samples i.e. Sample 3, 4 & 5 28

Quantitation at Experiment Level

Quantified lipids at experiment level

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