abstract

Abstract

Quantitative Lipidomics standards kits, which contain over 50 labeled molecular species across thirteen classes, provide more accurate quantitation with reduced quantitative bias.  The System Suitability kit enables the user to assess the sensitivity of the assay and the reproducibility (robustness) of the platform. Also included are the SelexION Technology Tuning kit, and the QC Spike Standards kit, which contains unlabeled molecular lipid species that can be added to the QC control plasma to create a study QC sample.

introduction

Introduction

Quantitative lipid analysis has numerous challenges due to the inherent complexity of the lipidome, including high complexity, and the presence of many isobaric interferences. It has been shown also that the diversity of fatty acid chain lengths and degrees of unsaturation result in differential fragmentation efficiency which impacts quantitation.¹

Traditionally a single internal standard per class had been used as a strategy in quantitating lipid molecular species, however the diversity of fatty acid chain lengths and degrees of unsaturation for molecular species that provide differential fragmentation efficiency were unaccounted for, which fundamentally impacts quantitation. The Quantitative Lipidomics Standards (QLS) kits presented here, which contain over 50 labeled molecular species across thirteen classes, neutralize this quantitative bias and allow for more accurate measurement (Figure 1).

In addition to the labelled internal standards, additional kits have been developed which allow a user to assess the reproducibility and sensitivity of their system before running samples. The System Suitability kit enables the user to assess the sensitivity of the assay and the reproducibility (robustness) of the platform. For quality control analysis throughout an LC-MS/MS or FIA assay or long-term study, the QC Spike standard provides a defined list of lipids to monitor and historically track instrument performance.

Figure 1. Internal standards to normalize quantitative data. In the Internal Standards kit, each lipid class has multiple internal standards at concentrations that reflect those found in plasma. The lipid classes included are shown in Table 1. The individual concentrations of each lipid in the mixture is provided for each lot in the vendor documentation.

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The use of differential mobility separation (SelexION^® Technology) has been shown to provide excellent lipid class separation that helps reduce isobaric interference between classes.² The SelexION^® Technology Tuning kit allows the automated optimization of the differential mobility spectrometry (DMS) cell which aids in definitive lipid identification.² In addition to FIA or direct infusion workflows, these standards can be employed in LC-MS/MS workflows. The Global HILIC Method⁴ uses class based elution to overcome matrix effects and insufficient standards needed to properly quantify lipid species. These unique internal standards kits were designed to overcome these gaps in the quantitative lipidomics field.

Table 1.  Available quantitative lipidomics standards kits.

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conclusion

Conclusions

The Quantitative Lipidomics standards kits offers the following benefits:

• Comprehensive coverage across thirteen lipid classes employing over 50 internal standards, a complete and novel approach to lipid quantitation
• Enhanced specificity through enabling the use of the SelexION Technology to eliminate isobaric interferences from overlapping lipid species within the same m/z range.² Also, the use of HILIC chromatography provides class based separation to improve confidence in identification.⁴
• Improved quantitation that has less bias through the application of the novel multiple labeled internal standards per class strategy.¹ By employing multiple lipid internal standards per lipid class, the unequal fragmentation response from increasing chain-length and desaturation is corrected to provide accurate quantitation and improved results.
• Reproducibility and robustness can be easily monitored and recorded to provide confidence in data quality.

references

References

1. Murphy et al. (2001) Analysis of Nonvolatile Lipids by Mass Spectrometry, Chem Rev 101, 479-526.
2. Differential Mobility Separation for Improving Lipidomic Analysis by Mass Spectrometry. SCIEX technical note RUO-MKT-02-4802-A.
3. Lintonen et al. (2014). Differential mobility spectrometry-driven shotgun lipidomics. Analytical Chemistry 86(19): 9662-9.
4. Achieve Broad Lipid Quantitation using a High-Throughput Targeted Lipidomics Method. SCIEX technical note RUO-MKT-02-8482-B.