An interactive R-based custom quantification program for semi-quantitative analysis of triacylglycerols in bovine...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Bioinformatics

Background:

• Accurate quantification of triacylglycerols (TAGs) is crucial for understanding lipid metabolism and nutritional science.
• Existing methods for analyzing complex lipid mixtures, such as those in bovine milk, often lack transparency and reproducibility.

Purpose of the Study:

• To develop and validate an open-source R-based custom quantification program (CQP) for the semi-quantification of TAGs in bovine milk lipid extracts.
• To ensure transparency and reproducibility in LC-MS data analysis through user-written R scripts and interactive web-based reporting.

Main Methods:

• Utilized R programming language and RStudio with the 'xcms' package for peak integration and retention time alignment in LC-MS data.
• Developed user-written R-based custom quantification programs (CQP) for semi-quantification of 29 TAG regioisomers using internal standards.
• Employed various calibration models, including linear, polynomial, and power fits, with different bracketing strategies to determine optimal quantification.

Main Results:

• The custom quantification programs demonstrated high coefficients of determination (r² > 0.99) for TAG quantification, with double-bracketed linear fits showing the least percentage difference to known concentrations.
• The CQP generated verifiable and reproducible webpages detailing every data processing and quantification step, including interactive figures.
• Publicly available data (DOI) and R code facilitate independent verification and adaptation of the quantification methodology.

Conclusions:

• The developed R-based CQP provides a transparent, reproducible, and customizable solution for semi-quantification of TAGs in LC-MS analyses.
• Open-source software and publicly accessible data promote scientific rigor and facilitate further research in lipidomics and related fields.