Quantification of Individual Lipid Species in Lipidomics

Quantification in omics generally falls into two categories, i.e., relative and absolute quantifications. The former measures the pattern change of the lipid species in a lipidome, which can be used as a tool for readout after stimulation or for biomarker discovery. The latter determines the mass levels of individual lipid species, and then each individual lipid subclass and class of a lipidome. Measurement of the changed mass levels of individual lipid elass, subelass, and molecular species is critical for elucidation of biochemical mechanism(s) responsible for the changes and for path-way/network analysis in addition to serving as a tool for readout after a perturbation or for biomarker diseovery. Thus, only the latter case is extensively discussed in this and the following chapters. 

Many modern technologies (including MS, nuclear magnetic resonance spectroscopy, fluorescence spectroscopy, chromatography, and microfluidic devices) have been used in lipidomics for quantification of lipid species in biological systems [1], Clearly, ESI-MS has evolved to be one of the most popular and powerful technologies for quantitative analyses of individual lipid species [2-5]. 

Modern mass spectrometry with an ESI source possesses many advantages for structural characterization and identification of analytes with high sensitivity as discussed in the last two parts. Moreover, the majority of mass spectrometers can not only very accurately measure the mass-to-eharge ratio of an ion but also accurately determine the molar ratios of isotopologues of an analyte. Here, isotopologues 

Lipidomics Comprehensive Mass Spectrometry cf lipids. First Edition. Xianlin Han. 2016 John Wiley Sons, Inc. Published 2016 by John Wiley Sons, Inc. 

The accurate determination of the molar ratios of isotopologues of an analyte by MS indicates that this powerful tool can be used for accurate quantification of a compound if an isotopologue of the compound in a known amount (which should be within a linear dynamic range relative to the compound) is present in the same solution with the compound. This statement specifies the multiple requirements for quantification by ESI-MS as follows  

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These points are extensively discussed in this chapter and in Chapter 15. However, the conclusion is that ESI-MS can be used as a tool for quantification under certain conditions. In practice, ESI-MS has become one of the most popular methods for quantitative analyses of individual lipid species in lipidomics, thereby greatly... 

These principles of shotgun lipidomics can only be achieved in conjunction with the major feature of direct infusion, that is, ESI-MS analysis of lipids is conducted at a constant concentration of the solution. This feature in shotgun lipidomics provides many advantages for lipid analysis, particularly for the quantification of individual lipid species. Some of these advantages are as follows. First, constant interactions between lipid species are maintained under a constant concentration condition therefore, contribution of individual lipid species to the ion current in an ESI source is constant, thereby leading to a constant ratio of ion peak intensities between lipid species of a class. Such a constant ratio can be achieved under different experimental conditions (see Chapter 4), on different MS instruments, and in different laboratories. Second, also due to the constant interactions between lipid species under the condition, ion suppression between each other within a lipid class or between lipid classes is constant. Third, lipid aggregation, which is a big concern for lipid quantification, can be well controlled and minimized. 

Characterization of lipid structures is a major and essential part of lipidomic research. This is largely due to the identification and even quantification of individual lipid species present in biological samples that ultimately depend on the information learned from the extensive characterization of representative authentic lipid species of individual class. Accordingly, characterization of common ions of lipid species from the majority of the cellular lipid classes is summarized in this part. 

Quantification of lipids by ESI-MS through a lipidomic approach is an interdisciplinary task that largely determines the amounts of intact individual species in a biological sample based on the selected internal standard(s) and a normalizer (although other relative measurements are also used (see below)). Unfortunately, the measurements of the contents of both the internal standard and the normalizer contain experimental errors. These errors impact the lipid quantification. Collectively, by this approach for lipidomic analysis, the amounts of individual lipid species in a selected sample size can be determined if appropriate internal standards are added prior to extraction with a tolerant experimental error, in which correction for any bias in extraction recovery, molecular species-dependent ionization efficiencies, and other factors is considered within a variation of 10%. 

The third factor is to set up the MS (or MS/MS) parameters to identify and quantify the eluted individual lipid species as many as possible. The particular features in LC-MS analysis are that the lipid concentrations in eluents are constantly changing, and identification and quantification of lipid species have to be done in a very limited time frame. These features are in contrast to shotgun lipidomics therefore, totally different settings and methodologies from those in shotgun lipidomics have to be employed. 

For those who would like to employ shotgun lipidomics (particularly MDMS-SL) for identification and quantification of individual species of a class, familiar with the fragmentation patterns of individual lipid classes, could enable them to design MS/MS scans for building-block analysis in the PIS, NLS, or both modes to selectively identify individual molecular species of a lipid class of interest. 

Many lipid classes can be quantified by this improved shotgun lipidomics approach. Quantification of individual species of a lipid class is conducted based on the summed abundance of its major fragment(s) in comparison to the counterpart of the spiked internal standard of the class. The effects of different isotopologue... 

Finally, MDMS-SL possesses other advantages in comparison to the tandem MS-based shotgun lipidomics. For example, the second step of quantification in MDMS-SL can apply any or all head group-related PIS and/or NLS of the lipid class, if present and sensitive enough, for quantification of individual species in the second step. This redundant process is very useful to refine the data and serves as an internal validation of the determined results. Moreover, with the second step of quantification, an over 5000-fold linear dynamic range for many lipid classes can be readily achieved [36] due to the second step of quantification serving as a relay for the dynamic range. 

First, it is always better to optimize the collision energy that can balance the fragment intensities of all the ions of the entire class of interest for quantification of lipid species by tandem MS in shotgun lipidomics even more than one internal standards are employed in the method. Similarly, optimization of the SRM/MRM conditions for individual species in an LC-MS/MS method is not recommended when interest is to quantify all the species of a class, unless a calibration curve for each individual species is established under the identical conditions, since optimization of MRM conditions for individual lipid species leads to an incomparable response factor of the species of interest to that of the selected internal standard. In both cases of shotgun lipidomics and LC-MS/MS analyses, different collision energies applied for different species could lead to substantial errors in quantitative analysis, as discussed previously [22]. Careful attention to CID energy must be exercised if accurate quantification is a goal. 

In addition to a few aforementioned limitations such as the requirement of an instrument possessing a high duty cycle capability, establishment of numerous standard curves, and preseparation of a lipid class of interest, the requirement of predetermination of the elution time of individual species to set up the pairs of transitions indicates that the SRM/MRM method is only suitable for targeted lipidomics analysis. Moreover, the effects of differential matrices between biological samples and the standard solution on quantification are unknown. Finally, dynamic ion suppression (see Chapter 15) resulting from the interactions between unresolved lipid species during an LC run should also be recognized. 

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