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A robust mass spectrometry method for rapid profiling of erythrocyte ghost membrane proteomes

Authors :
Haddy K. S. Fye
Paul Mrosso
Lesley Bruce
Marie-Laëtitia Thézénas
Simon Davis
Roman Fischer
Gration L. Rwegasira
Julie Makani
Benedikt M. Kessler
Source :
Clinical Proteomics, Vol 15, Iss 1, Pp 1-8 (2018)
Publication Year :
2018
Publisher :
BMC, 2018.

Abstract

Abstract Background Red blood cell (RBC) physiology is directly linked to many human disorders associated with low tissue oxygen levels or anemia including chronic obstructive pulmonary disease, congenital heart disease, sleep apnea and sickle cell anemia. Parasites such as Plasmodium spp. and phylum Apicomplexa directly target RBCs, and surface molecules within the RBC membrane are critical for pathogen interactions. Proteomics of RBC membrane ‘ghost’ fractions has therefore been of considerable interest, but protocols described to date are either suboptimal or too extensive to be applicable to a larger set of clinical cohorts. Methods Here, we describe an optimised erythrocyte isolation protocol from blood, tested for various storage conditions and explored using different fractionation conditions for isolating ghost RBC membranes. Liquid chromatography mass spectrometry (LC–MS) analysis on a Q-Exactive Orbitrap instrument was used to profile proteins isolated from the comparative conditions. Data analysis was run on the MASCOT and MaxQuant platforms to assess their scope and diversity. Results The results obtained demonstrate a robust method for membrane enrichment enabling consistent MS based characterisation of > 900 RBC membrane proteins in single LC–MS/MS analyses. Non-detergent based membrane solubilisation methods using the tissue and supernatant fractions of isolated ghost membranes are shown to offer effective haemoglobin removal as well as diverse recovery including erythrocyte membrane proteins of high and low abundance. Conclusions The methods described in this manuscript propose a medium to high throughput framework for membrane proteome profiling by LC–MS of potential applicability to larger clinical cohorts in a variety of disease contexts.

Details

Language :
English
ISSN :
15426416 and 15590275
Volume :
15
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Clinical Proteomics
Publication Type :
Academic Journal
Accession number :
edsdoj.29cdb70133a94a1480c9a963dd32a43b
Document Type :
article
Full Text :
https://doi.org/10.1186/s12014-018-9190-4