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SimLipid®


Waters® TQ-S MPIS/NLS-based Shotgun Lipidomics Methods

Automating lipid identification and quantitation using data from Waters® Xevo® TQ-S MPIS/NLS-based shotgun lipidomics methods

  • Database containing 40,298 lipid structures.
  • 5211 set masses (transitions) of PIS/NLS experiments for fatty acid chains, and head groups of lipid species from different classes and sub-classes.
  • Identify target lipids based on exact mass database search, and the target headgroup, or fatty acid chain corresponding to the set masses of the PIS/NLS experiments.
  • Isotope peak correction to facilitate accurate quantitation of lipids.
  • Align lipids across biological samples based on short name e.g., PC(28:2); name without double bond positions e.g., PC(18:1/18:1) instead of PC(18:1 (9Z)/18:1(9Z)).
  • Calculate normalized response of analytes w.r.t. the response of the internal standards that belong to the same class/subclass.
  • Heatmap, Concentration X Composition reports of lipid classes, and fatty acid chains.
  • Additional lipid ontology based filters, e.g., only even/odd numbers of double bonds, and carbon (C) atoms in the fatty acid chains of target lipids.
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A high throughput informatics tool for identification and relative quantitation of lipids using data from LC-, MALDI-, Shotgun-, Mass Spectrometry Workflows

The main biological functions of lipids include energy storage, acting as structural components of cell membranes, and participating as important signaling molecules.

Comparative studies of complex lipid mixtures found in cells and tissues could potentially reveal lipid biomarkers. The presence of lipids in membranes is reflective of the physiological state of an organism at a given time. Targeted and non-targeted approaches based on chromatography and mass spectrometry are employed for such studies. Both the approaches involve identification and measurement of lipids in the samples.

The challenges with mass spectrometry based lipidomics are the chemical complexity and large range of concentration of thousands of lipid species that are present in biological samples. Moreover, identification of lipids requires sophisticated software since automated interpretation of lipid MS/MS spectra is more challenging as compared to other biopolymers such as DNA, carbohydrates or peptides since lipids show much less standardized fragment mass spectra. Each lipid class has its own fragmentation patterns as well as ionization efficiency.

High Throughput DIA Data Processing with Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE along with Waters® TQ-S and Shimadzu LCMS 8060 are now supported!

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  • Robust Lipid Structure Database
  • Project Management and Data Visualization
  • High Throughput Lipid Structural Elucidation using MS, MS/MS and MSE Data
  • High Throughput DIA Data Processing- Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE
  • LC MS and LC- MS/MS (DDA) High Throughput Data Processing
  • Multiplexed Precursor Ion Scan (PIS) and Neutral Loss Scan (NLS) Triple Quadrupole Mass Spectrometry Methods Based Lipid Profiling and Quantitation - Waters® TQ-S, Shimadzu LCMS 8060
  • Normalize Analyte Peaks Based on Peaks of the Internal Standards; either analytes, and the internal standards belong to same lipid class or an analyte and one of the internal standards have the "closest retention time"
  • MALDI-FT-ICR-MS Lipidomics Analysis
  • Mass Spectra Annotation with Identified Lipids
  • Generate Report

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