Planta Med 2015; 81 - PA7
DOI: 10.1055/s-0035-1545136

Lipidomic analysis of different cotton seed oil genotypes using novel analytical and informatics tools

V Shulaev 1, MD Jones 2, D Sturtevant 1, PJ Horn 1, J Crossley 1, KD Chapman 1, K Yu 2, M Wrona 2, G Isaac 2
  • 1Department of Biological Sciences, College of Arts and Sciences, University of North Texas, Denton, TX 76203
  • 2Waters Corporations, 34 Maple Street, Milford, MA 01757

In this study, sub-2 µm particle CO2 based supercritical chromatography (UltraPerformance Convergence Chromatography, UPC2) was investigated for the separation of free fatty acids, neutral and polar lipids in cottonseed extract. Typically, plant metabolomic profiling distinguishes heterogeneous distribution of neutral lipids; such as triacylglycerols and diacylgylcerols at different conditions. The data were collected using high and low collision energy simultaneous data collection on a time-of-flight MS which allowed the characterization of lipids by precursor and product ion alignment. We investigated lipids present in a control and mutant cotton seed oil extracts. The sub-2 µm particle supercritical CO2/ToF-MS method was modified to retain the neutral lipids by reducing the starting percentage of modifier. The modifier was ramped to elute the polar lipids, which are known to be present as membrane lipid classes in cotton embryos. The lipid profiles of the different seed oil genotypes were investigated using novel informatics software to determine the pattern and composition of the different lipid species. The software adopts an intuitive workflow approach to performing comparative metabolomics and lipidomics data analysis. The workflow starts with raw data file loading, then retention time alignment and deconvolution, followed by analysis that creates a list of features. The features are then identified with compound searches and explored using multivariate statistical methods. Differential analysis of results across several cotton seed oil genotypes can quickly be performed, thereby facilitating identification and quantitation of potential biomarkers. Potential markers that discriminate the different cotton genotypes were identified.