A label-free proteome analysis strategy for identifying quantitative changes in erythrocyte membranes induced by red cell disorders

Abstract

Red blood cells have been extensively studied but many questions regarding membrane properties and pathophysiology remain unanswered. Proteome analysis of red cell membranes is complicated by a very wide dynamic range of protein concentrations as well as the presence of proteins that are very large, very hydrophobic, or heterogeneously glycosylated. This study investigated removal of other blood cell types, red cell membrane extraction, differing degrees of fractionation using 1-D SDS gels, and label-free quantitative methods to determine optimized conditions for proteomic comparisons of clinical blood samples. The results showed that fractionation of red cell membranes on 1-D SDS gels was more efficient than low-ionic-strength extractions followed by 1-D gel fractionation. When gel lanes were sliced into 30 uniform slices, a good depth of analysis was obtained that included identification of most well-characterized, low-abundance red cell membrane proteins including those present at 500 to 10,000 copies per cell. Furthermore, the size separation enabled detection of changes due to proteolysis or in vivo protein crosslinking. A combination of Rosetta Elucidator quantitation and subsequent statistical analysis enabled the robust detection of protein differences that could be used to address unresolved questions in red cell disorders.

Anatomy of the red cell membrane skeleton: unanswered questions

“…11 Some of the important ones are described in Table 1. The integral membrane proteins are organized into macromolecular complexes centered on band 3, the anion-exchange channel.…”

New insights on hereditary erythrocyte membrane defects

“…RBC membrane is composed by a fluid double layer of lipids in which approximately 20 major proteins and at least 850 minor ones are embedded. 4 The membrane is attached to an intracellular cytoskeleton by protein-protein and lipid-protein interactions that confer the erythrocyte shape, stability and deformability. The transmembrane proteins have mainly a transporter function.…”

Identification of secreted proteins that reflect autophagy dynamics within tumor cells

“…Raw files were imported and analyzed for label-free quantification in the Rosetta Elucidator software suite, as previously described. 56 A minimum protein intensity cut-off of 1£10 4 was used to minimize noise from weak mass spectrometry signals as these are typically variable. Derivation of 95% confidence intervals for technical replicate data was performed as previously described.…”

“…Derivation of 95% confidence intervals for technical replicate data was performed as previously described. 56,57 Briefly, to define significance thresholds, data were normalized using the median of log10 intensity ratio from technical replicate comparisons, and the intensity dependence of protein variation across technical replicates in each cell line was determined using a sliding window approach with protein intensities pooled into groups of 15. The standard deviation trend as a function of the mean intensity was fitted to an exponential curve and the 95% confidence boundaries for each cell line were derived from this curve, with the assumption that each protein follows a lognormal distribution.…”

“…The standard deviation trend as a function of the mean intensity was fitted to an exponential curve and the 95% confidence boundaries for each cell line were derived from this curve, with the assumption that each protein follows a lognormal distribution. 56 These boundaries were then overlaid on protein intensity scatterplots comparing the interstitial fluid versus the media, whereby outlying proteins represented those which preferentially reside to a given cell culture compartment.…”