Flow field-flow fractionation: Recent applications for lipidomic and proteomic analysis

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)

Abstract

Flow field-flow fractionation (FlFFF) is a versatile size-based separation method suitable for biological macromolecules including proteins/protein aggregates, DNA, subcellular organelles, extracellular species, and whole cells. This review introduces briefly the basic principles of FlFFF and its recent applications for proteomic and lipidomic analysis, which are described in two parts: (1) off-line coupling of FlFFF with MS and other bioanalytical methods, and (2) on-line FlFFF with MS. The first part includes applications for lipoproteins, exosomes, and subcellular organelles for the size-dependent analysis of proteins and lipids in narrow size-fractions collected during FlFFF, followed by independent analysis including western blotting and nanoflow liquid chromatography-electrospray ionisation-tandem mass spectrometry (nLC-ESI-MS/MS). The second part highlights the on-line FlFFF-MS, in which a miniaturised FlFFF channel is coupled to ESI-MS/MS for the high-speed lipid analysis of lipoproteins and to inductively-coupled plasma MS for the direct analysis of metals in metalloproteins from blood plasma.

Original languageEnglish
Pages (from-to)19-28
Number of pages10
JournalTrAC - Trends in Analytical Chemistry
Volume118
DOIs
Publication statusPublished - 2019 Sept

Bibliographical note

Funding Information:
This study was supported by grant NRF-2018R1A2A1A05019794 from the National Research Foundation (NRF) of Korea .

Funding Information:
This study was supported by grant NRF-2018R1A2A1A05019794 from the National Research Foundation (NRF) of Korea.

Publisher Copyright:
© 2019 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Spectroscopy

Fingerprint

Dive into the research topics of 'Flow field-flow fractionation: Recent applications for lipidomic and proteomic analysis'. Together they form a unique fingerprint.

Cite this