Home >> Blog >> Easing the Lipid Quantitation Challenges with SimLipid

Targeted Lipidomics- Easing the Lipid Quantitation Challenges

Meet Lipid Quantitation Challenges

December 15, 2020

Quantitation of lipids is significant because lipids have a widespread biological role in the body in terms of intracellular signalling or local hormonal regulation etc. Due to their structural complexity, attaining absolute quantitation of lipids is not feasible experimentally using mass spectrometry. As an alternative, relative quantitation of lipids has been the go-to approach for comprehensive lipidomic analysis. Among the different strategies (like Shotgun or untargeted approach), targeted lipidomics appears as a promising method for comprehensive lipid quantitation. The combination of utilizes Multiple Reaction Monitoring (MRM) transition list and a comprehensive internal standard (IS) strategy makes it real easy to accurately profile and quantify the lipids.

Targeted lipidomics helps to identify and quantitate lipids with both higher sensitivity and specificity. With the use of MRM mode under triple quadrupole mass spectrometry, low abundant lipids can be detected and quantified accurately. However, the bottleneck for this approach has been the data analytics due to the internal standard and quantitation calculations. These challenges are:

  1. Internal standard assignment-Ability to select one or multiple internal standards for the same or multiple lipid class.
  2. Normalization corrections based on IS- Normalize the ion abundance corrections based on the internal standards selected.
  3. Isotopic overlap corrections- There is possibility of overlapping of isotopic levels of lipids and a correction is needed to split the one or more overlapped lipids.
  4. IS sample amount-Need to record the spiked concentrations of IS for lipid quantitation calculations.
  5. Lipid concentration calculations-Using the correlation of ion abundances of IS and lipids, the lipid concentrations are calculated.
  6. Replicate/batch corrections-To remove redundant and missing peaks, the replicate data needs to be aligned across the replicates/samples.

SimLipid software offers a comprehensive quantification workflow solving these analytical challenges . To know more, click here.

Comment Share PREMIER Biosoft Facebook Link PREMIER Biosoft LinkedIn Link



* mandatory fields
Subscribe to Our Blog

customer service software technical support
Live Chat by Comm100