Issue 34, 2018

Nanowell-mediated two-dimensional liquid chromatography enables deep proteome profiling of <1000 mammalian cells

Abstract

Multidimensional peptide separations can greatly increase the depth of coverage in proteome profiling. However, a major challenge for multidimensional separations is the requirement of large biological samples, often containing milligram amounts of protein. We have developed nanowell-mediated two-dimensional (2D) reversed-phase nanoflow liquid chromatography (LC) separations for in-depth proteome profiling of low-nanogram samples. Peptides are first separated using high-pH LC and the effluent is concatenated into 4 or 12 nanowells. The contents of each nanowell are reconstituted in LC buffer and collected for subsequent separation and analysis by low-pH nanoLC-MS/MS. The nanowell platform minimizes peptide losses to surfaces in offline 2D LC fractionation, enabling >5800 proteins to be confidently identified from just 50 ng of HeLa digest. Furthermore, in combination with a recently developed nanowell-based sample preparation workflow, we demonstrated deep proteome profiling of >6000 protein groups from small populations of cells, including ∼650 HeLa cells and 10 single human pancreatic islet thin sections (∼1000 cells) from a pre-symptomatic type 1 diabetic donor.

Graphical abstract: Nanowell-mediated two-dimensional liquid chromatography enables deep proteome profiling of <1000 mammalian cells

Supplementary files

Article information

Article type
Edge Article
Submitted
18 Jun 2018
Accepted
15 Jul 2018
First published
18 Jul 2018
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2018,9, 6944-6951

Nanowell-mediated two-dimensional liquid chromatography enables deep proteome profiling of <1000 mammalian cells

M. Dou, Y. Zhu, A. Liyu, Y. Liang, J. Chen, P. D. Piehowski, K. Xu, R. Zhao, R. J. Moore, M. A. Atkinson, C. E. Mathews, W. Qian and R. T. Kelly, Chem. Sci., 2018, 9, 6944 DOI: 10.1039/C8SC02680G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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