Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

biochemistry, genetics and molecular biology

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

Clinical Proteomics, Volume 15, No. 1, Article 14, Year 2018

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.
Statistics
Citations: 9
Authors: 9
Affiliations: 3
Identifiers
Research Areas
Noncommunicable Diseases
Study Design
Cohort Study