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Development of a Microfluidic Platform for Trace Lipid Analysis

The inherent trace quantity of primary fatty acid amides found in biological systems presents challenges for analytical analysis and quantitation, requiring a highly sensitive detection system. The use of microfluidics provides a green sample preparation and analysis technique through small-volume f...

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Detalles Bibliográficos
Autores principales: Davic, Andrew, Cascio, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996208/
https://www.ncbi.nlm.nih.gov/pubmed/33668377
http://dx.doi.org/10.3390/metabo11030130
Descripción
Sumario:The inherent trace quantity of primary fatty acid amides found in biological systems presents challenges for analytical analysis and quantitation, requiring a highly sensitive detection system. The use of microfluidics provides a green sample preparation and analysis technique through small-volume fluidic flow through micron-sized channels embedded in a polydimethylsiloxane (PDMS) device. Microfluidics provides the potential of having a micro total analysis system where chromatographic separation, fluorescent tagging reactions, and detection are accomplished with no added sample handling. This study describes the development and the optimization of a microfluidic-laser induced fluorescence (LIF) analysis and detection system that can be used for the detection of ultra-trace levels of fluorescently tagged primary fatty acid amines. A PDMS microfluidic device was designed and fabricated to incorporate droplet-based flow. Droplet microfluidics have enabled on-chip fluorescent tagging reactions to be performed quickly and efficiently, with no additional sample handling. An optimized LIF optical detection system provided fluorescently tagged primary fatty acid amine detection at sub-fmol levels (436 amol). The use of this LIF detection provides unparalleled sensitivity, with detection limits several orders of magnitude lower than currently employed LC-MS techniques, and might be easily adapted for use as a complementary quantification platform for parallel MS-based omics studies.