Lipid Species Quantification
Mass spectrometric quantification without internal standards (ISs) is not possible
Requirements for internal standards (ISs)
- Not present in the samples
- Addition prior lipid extraction
- At least one per lipid class (as defined by LIPID MAPS classification) is desirable
- High structural similarity to analytes
- Similar number of carbons
- Similar number of double bonds
- Simultaneous ionization with the analyte is desired
- Structural identical stable isotope labelled standards are considered as gold standard
Concentration of lipids, solvents and additives in ESI-methods
- Concentration of lipids in the infusate influences their response – especially at too high concentrations also suitable ISs cannot compensate
- Solvent composition and additives may contribute considerably to ionization efficiency (see Koivusalo et al.)
Correction of isotopic abundance
- Type I: Isotopic pattern resulting from naturally occurring isotopes
- Most commonly an increasing number of 13C-atoms decreases the proportion of the monoisotopic peak
- Correction factors based on natural isotope abundance of the elements should be applied to correct the response
- Type II: Overlap from isotopomers of other species
- Typically species with one additional double bond lead to isobaric interference
- Correction factors based on natural isotope abundance of the elements should be used in a sequential algorithm starting from the low mass species
- Ultra high resolution instruments may resolve this overlap
- Correction factors are different for MS/MS:
- Usually a monoisotopic fragment ion is used for quantification which needs to be considered when natural isotope abundance of the precursor ion is calculated
- Both Type I and II need to be considered
- For Type II: isobaric overlap may result from both charged product ions and neutral loss fragments (typically when they contain a variable number of double bonds)
Consideration of analytical response
- Analytical response of lipid species is not only determined by its lipid class but also other structural elements like:
- Bond types (ester vs. ether)
- Number of double bonds
- Length of acyl chain (independent of type I isotope effect)
- Evaluation of analytical response by authentic standards with the respective structural features
- Comparison of analytical response at high and low concentrations
- Evaluation whether the sample matrix influences the analytical response
- Use of reference standards with certified concentration are desirable
- Conventional standard solutions should be checked concerning their chemical identity and quantity (by independent methods like GC methods for fatty acid quantification; phosphate determination for phospholipids)
- Development of response factor models based on experimental data (preferred) or application of response factors for structural similar species could be applied for species where no standard is available
Normalization of data
- Data should be normalized to appropriate internal standard and the sample amount
- Details on normalization should be provided with the data
- Since normalization is not a problem specific to lipidomics it is recommended to use most commonly applied normalization methods for the individual sample material
- Commonly applied normalization:
- Liquids are usually normalized to the volume
- Serum/plasma are normalized to the volume
- Cells are normalized to cell number, protein, DNA
- Tissues are normalized to wet weight, protein
Type of quantification
- Should be mentioned together with the data
- Preferred unit is mol normalized as described above (e.g. molar, µM, pmol/µg protein)
- Levels of quantification:
- Level 3: non-matching IS (= other lipid class than analyte or no co-ionization of analyte and IS)
- Level 2: matching IS (= lipid class of analyte and IS are identical and co-ionization of analyte and IS)
- Level 1: matching IS together with consideration of species-specific analytical response
- Relative quantification (%): normalization to total amount of a lipid class or all measured lipid classes; it should be mentioned which type of data are used for normalization