Optimization of Folch, Bligh-Dyer, and Matyash Sample-to-Extraction Solvent Ratios for Mammalian Cell- and Plasma-Based Lipidomics Studies
John Bowden, Candice Z. Ulmer, Christina Jones, Richard A. Yost, Timothy J. Garrett
In order to investigate changes in the lipidome, analysis by ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC-HRMS) typically requires the extraction of lipid content from sample matrices using optimized, matrix-specific conditions. The Folch, Bligh-Dyer, and Matyash methods, while promising approaches, were originally tailored to specific matrices (brain tissue, fish muscle, and E. coli, respectively). Thus, the sample-to-solvent ratios for these methods should be vetted for the sample matrix of interest prior to employment. This study evaluated the appropriate sample-to-extraction solvent ratios for mammalian cellular and plasma-based lipidomics studies. This work also evaluated the multi- omic capability of each biphasic lipid extraction method in an effort to provide a workflow capable of increasing analyte coverage in a single analysis, thus providing a more complete understanding of complex biological systems. Results showed that the Folch method was better suited for the extraction of polar and non-polar lipids from mammalian cells, more specifically, Jurkat T-lymphocyte cells. An increase in the plasma sample-to-solvent ratio from 1:4, 1:10, 1:20, to 1:100 (v/v) resulted in a gradual increase in the peak area of metabolite (aqueous layer) and lipid (organic layer) species for each extraction method interrogated in this study. The Bligh-Dyer and Folch methods yielded comparable results for the 1:20 and 1:100 (v/v) plasma sample-to-solvent ratios for both, metabolite and lipid species.
, Ulmer, C.
, Jones, C.
, Yost, R.
and Garrett, T.
Optimization of Folch, Bligh-Dyer, and Matyash Sample-to-Extraction Solvent Ratios for Mammalian Cell- and Plasma-Based Lipidomics Studies, Analytica Chimica ACTA, [online], https://doi.org/10.1016/j.aca.2018.08.004, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=924616
(Accessed June 2, 2023)