2004
DOI: 10.1038/nbt993
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Direct proteomic mapping of the lung microvascular endothelial cell surface in vivo and in cell culture

Abstract: Endothelial cells can function differently in vitro and in vivo; however, the degree of microenvironmental modulation in vivo remains unknown at the molecular level largely because of analytical limitations. We use multidimensional protein identification technology (MudPIT) to identify 450 proteins (with three or more spectra) in luminal endothelial cell plasma membranes isolated from rat lungs and from cultured rat lung microvascular endothelial cells. Forty-one percent of proteins expressed in vivo are not d… Show more

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Cited by 401 publications
(397 citation statements)
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“…In-depth studies of membrane proteins have proven to be difficult because of their low abundance and hydrophobicity 1,4 . However, recent advances in proteomic technologies make it possible to investigate proteins in this cell compartment, including previously unannotated membrane proteins, to an impressive depth [4][5][6][7][8][9] . In this study, we applied colloidal silica-bead coating 10 to enrich for conserved cell-surface-associated proteins in mouse neonatal and human fetal ventricular cardiomyocytes.…”
Section: Resultsmentioning
confidence: 99%
“…In-depth studies of membrane proteins have proven to be difficult because of their low abundance and hydrophobicity 1,4 . However, recent advances in proteomic technologies make it possible to investigate proteins in this cell compartment, including previously unannotated membrane proteins, to an impressive depth [4][5][6][7][8][9] . In this study, we applied colloidal silica-bead coating 10 to enrich for conserved cell-surface-associated proteins in mouse neonatal and human fetal ventricular cardiomyocytes.…”
Section: Resultsmentioning
confidence: 99%
“…For example, it has been observed that two replicate MudPIT analyses will produce two sets of protein identifications with ,65% overlap [28,29]. Thirty-five percent of the proteins in the second analysis are likely to be novel compared to the first.…”
Section: Analytical Incompletenessmentioning
confidence: 99%
“…By merging the two datasets along with the use of stricter SEQUEST filters (see Methods) for the PMT tags, the overall confidence of the resulting peptide/protein identifications (i.e., AMT tags) was improved. Combining multidimensional analyses has been shown elsewhere to increase the completeness of a proteomic analysis [32,37,38]. Recent analyses of human plasma and other samples provided the basis for estimating the false-positives rates for SEQUEST results, although the filter rules were similar, but not identical to those used here for populating the PMT tag database [39,40].…”
Section: Putative Mass and Time (Pmt) Tag Databasementioning
confidence: 95%