Issue 15, 2020

Multidimensional protein characterisation using microfluidic post-column analysis

Abstract

The biological function of proteins is dictated by the formation of supra-molecular complexes that act as the basic machinery of the cell. As such, measuring the properties of protein species in heterogeneous mixtures is of key importance for understanding the molecular basis of biological function. Here, we describe the combination of analytical microfluidic tools with liquid chromatography for multidimensional characterisation of biomolecules in complex mixtures in the solution phase. Following chromatographic separation, a small fraction of the flow-through is distributed to multiple microfluidic devices for analysis. The microfluidic device developed here allows the simultaneous determination of the hydrodynamic radius, electrophoretic mobility, effective molecular charge and isoelectric point of isolated protein species. We demonstrate the operation principle of this approach with a mixture of three unlabelled model proteins varying in size and charge. We further extend the analytical potential of the presented approach by analysing a mixture of interacting streptavidin with biotinylated BSA and fluorophores, which form a mixture of stable complexes with diverse biophysical properties and stoichiometries. The presented microfluidic device positioned in-line with liquid chromatography presents an advanced tool for characterising multidimensional physical properties of proteins in biological samples to further understand the assembly/disassembly mechanism of proteins and the nature of complex mixtures.

Graphical abstract: Multidimensional protein characterisation using microfluidic post-column analysis

Supplementary files

Article information

Article type
Paper
Submitted
04 Mar 2020
Accepted
13 Jun 2020
First published
26 Jun 2020
This article is Open Access
Creative Commons BY-NC license

Lab Chip, 2020,20, 2663-2673

Multidimensional protein characterisation using microfluidic post-column analysis

T. Scheidt, T. Kartanas, Q. Peter, M. M. Schneider, K. L. Saar, T. Müller, P. K. Challa, A. Levin, S. Devenish and T. P. J. Knowles, Lab Chip, 2020, 20, 2663 DOI: 10.1039/D0LC00219D

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