A microfluidic device for the automated derivatization of free fatty acids to fatty acidmethylesters

Abstract

Free fatty acid (FFA) compositions are examined in feedstock for biodiesel production, as source-specific markers in soil, and because of their role in cellular signaling. However, sample preparation of FFAs for gas chromatography-mass spectrometry (GC-MS) analysis can be time and labor intensive. Therefore, to increase sample preparation throughput, a glass microfluidic device was developed to automate derivatization of FFAs to fatty acid methyl esters (FAMEs). FFAs were delivered to one input of the device and methanolic-HCl was delivered to a second input. FAME products were produced as the reagents traversed a 29 μL reaction channel held at 55 °C. A Design of Experiment protocol was used to determine the combination of derivatization time (T(der)) and ratio of methanolic-HCl:FFA (R(der)) that maximized the derivatization efficiencies of tridecanoic acid and stearic acid to their methyl ester forms. The combination of T(der) = 0.8 min and R(der) = 4.9 that produced optimal derivatization conditions for both FFAs within a 5 min total sample preparation time was determined. This combination of T(der) and R(der) was used to derivatize 12 FFAs with a range of derivatization efficiencies from 18% to 93% with efficiencies of 61% for tridecanoic acid and 84% for stearic acid. As compared to a conventional macroscale derivatization of FFA to FAME, the microfluidic device decreased the volume of methanolic-HCl and FFA by 20- and 1300-fold, respectively. The developed microfluidic device can be used for automated preparation of FAMEs to analyze the FFA compositions of volume-limited samples.

Isobaric 6-plex and tosyl dual tagging for the determination of positional isomers and quantitation of monounsaturated fatty acids using rapid UHPLC-MS/MS

“…Fatty acids have traditionally been converted to their methyl esters and analyzed by gas chromatography with mixed reaction efficiency. [4][5][6] Alternative methods have used MS and gas phase modifications or novel fragmentation techniques, but these often require specific instrumentation which can limit widespread method adoption. [7][8][9] Double bond derivatization has been performed to produce diagnostic ions by epoxidation, 10 ozonolysis, [11][12][13] and the Paternò Büchi 14,15 reactions.…”

Low-Cost 3D-Printed Reactionware for the Determination of Fatty Acid Content in Edible Oils using a Base-Catalyzed Transesterification Method in Continuous Flow

“…The possibility of using flow chemistry for manufacturing biodiesel through transesterification has been illustrated (Guan et al 2009). In 2012, Duong and Roper (Duong and Roper 2012) developed a microfluidic chip using conventional photolithography and wet etching techniques, specifically for the derivatization of free fatty acids with methanolic-HCl, to produce the corresponding fatty acid methyl esters. However, the high fabrication costs associated with microreactors (Mason et al 2007) in conjunction with exorbitantly priced commercial flow equipment (Bannock et al 2014;Akwi and Watts 2018) has led to the development of low-cost reactionware for flow chemistry purposes.…”

Development and validation of a robust automated analysis of plasma phospholipid fatty acids for metabolic phenotyping of large epidemiological studies

“…However, none of these methods automated both the phospholipid extraction and FAME derivatization and applied this to very large sample sets [14]. Since fatty-acid profiling by gas chromatography (GC) using FAME derivatization first became established, improvement in sample throughput has been sought, and this is still an active area of research [15,16]. This study is the first report of an automated method for fatty-acid analysis of the phospholipid fraction of human plasma, which includes both phospholipid extraction and FAME derivatization, and has been successfully applied to date to more than 28,000 samples of the InterAct project (detailed information about the subjects can be found in the cohort description [17]).…”