Normalization of Metabolomics Data Using DNA Concentration : Implementation of a Hoechst 33342-Based DNA Quantification and Integration of DNA Extraction into a Simultaneous Proteo-Metabolome -Liquid-Liquid Extraction (SPM-LLE)

Abstract

Normalization is a critical step in MS-based metabolomics to ensure accurate and comparable data across varying cell numbers and sample processing conditions. This study aims to evaluate DNA quantification as a robust, reproducible, and workflow-compatible normalization strategy, alongside comparisons to protein content and metabolite signal intensity. Using cultured cancer cell lines, we tested DNA quantification via Hoechst 33342 fluorescence across a serial dilution of cells. Samples were collected during different stages of a methanol–chloroform liquid–liquid extraction (SPM-LLE) protocol. The effects of sonication, PBS stabilization, and short-term freezing at 4 °C, −20 °C, and −80 °C were evaluated. DNA fluorescence showed a strong correlation with cell number, but signal saturation occurred at higher concentrations. The most reproducible results were observed when sampling occurred prior to phase separation. Mechanical disruption via tip sonication increased DNA yield in selected phases, while PBS acted as a stabilizer. Metabolite amounts also increased with cell number, affirming proportional accumulation in line with extraction efficiency. Protein quantification similarly correlated with cell count. Several amino acids (e.g., alanine, glutamate) displayed high linearity with both protein and DNA content, supporting their potential as normalization candidates. Freezing DNA samples for up to seven days showed no significant degradation. This study supports DNA quantification as a reliable and efficient normalization method for metabolomics, especially within a single-sample workflow. Compared to protein- or metabolite-based normalization, DNA offers higher compatibility and reduces sample processing complexity. These findings align with hybrid normalization strategies that combine DNA, protein, and internal standards for improved accuracy. Future directions include validation in 3D cultures and organoid systems, where novel disruption and isotopologue tracking approaches could be gaining relevance.Masterarbeit Universität Innsbruck 202