Development of a robust sulfo-phospho-vanillin assay for sample normalization in LC-MS-based lipidomics

Abstract

Background

Lipidomics, the comprehensive analysis of lipid profiles in biological samples, is crucial for understanding cellular processes and disease mechanisms. However, variations in the amounts or concentrations of samples can significantly impact the accuracy of lipid quantification in comparative studies. To address this challenge, the normalization of samples before processing and analysis is essential. This study introduces a robust normalization method for lipidome analysis, leveraging an improved sulfo-phospho-vanillin (SPV) analysis technique.

Results

The enhanced SPV method provides a reliable colorimetric assay for determining total lipid content across diverse sample types. By optimizing the detection limits and reducing the required sample amount for the assay, we successfully applied this method to saliva and cellular samples where the concentrations of the starting materials can have large variations. Our findings demonstrate that SPV normalization significantly improves lipid feature detection and intensity consistency across samples without introducing analytical bias. This normalization process facilitates more accurate comparisons of lipid profiles.

Significance

Implementing SPV-based normalization presents a practical solution for enhancing the accuracy of lipidome analyses in comparative studies. This approach is not only effective but also accessible for research laboratories, requiring a relatively simple workflow and standard UV–visible spectroscopy equipment.