2009
DOI: 10.1074/mcp.m800394-mcp200
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The Organelle Proteome of the DT40 Lymphocyte Cell Line

Abstract: A major challenge in eukaryotic cell biology is to understand the roles of individual proteins and the subcellular compartments in which they reside. Here, we use the localization of organelle proteins by isotope tagging technique to complete the first proteomic analysis of the major organelles of the DT40 lymphocyte cell line. This cell line is emerging as an important research tool because of the ease with which gene knockouts can be generated. We identify 1090 proteins through the analysis of preparations e… Show more

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Cited by 55 publications
(60 citation statements)
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“…LOPIT uses the iTR AQ technology to measure distribution patterns of proteins from self-generating iodixanol density gradients [66] and is summarized in Figure 2. This technique also allows simultaneous assignment of proteins to multiple organelles and has been used in the authors' laboratory to assign proteins to organelles in plants, Drosophila and animal cell culture [67][68][69]. Four or eight fractions, enriched with different organelles, are selected for comparison and protein distributions are determined by measuring their relative abundance using iTRAQ quantification.…”
Section: Subcellular Locationmentioning
confidence: 99%
“…LOPIT uses the iTR AQ technology to measure distribution patterns of proteins from self-generating iodixanol density gradients [66] and is summarized in Figure 2. This technique also allows simultaneous assignment of proteins to multiple organelles and has been used in the authors' laboratory to assign proteins to organelles in plants, Drosophila and animal cell culture [67][68][69]. Four or eight fractions, enriched with different organelles, are selected for comparison and protein distributions are determined by measuring their relative abundance using iTRAQ quantification.…”
Section: Subcellular Locationmentioning
confidence: 99%
“…The high homologous recombination rate together with the ease of propagation make DT40 ideal for characterizing the biochemical roles of protein domains and residues. Indeed, large molecular complexes, protein interactomes and even whole organelle proteomes have been successfully identified from wild type and various mutant DT40 cell lines (Hall, Hester, Griffin, Lilley, & Jackson, 2009;Mosedale et al, 2005;Ohta et al, 2010). In the context of centrosome biology, the use of DT40 cells have proved to be equally valuable, helped by the fact that centrosome morphology and centrosomal genes are highly conserved between vertebrates and mammals (Barr, Kilmartin, & Gergely, 2010;Dantas, Wang, Lalor, Dockery, & Morrison, 2011;Inanc et al, 2013;Shang et al, 2013;Sir et al, 2011Sir et al, , 2013Wang, Dantas, Lalor, Dockery, & Morrison, 2013).…”
Section: Introductionmentioning
confidence: 98%
“…Missing data and the impact of imputation have not been thoroughly addressed in proteomics, let alone in spatial proteomics. Published LOPIT studies (7,18,20) have excluded proteins that presented missing values across replicated experiments. PCP studies (8,21) have limited the computation of their 2 metric to pairs of fractions (defined as the squared deviation of the normalized profile for all peptides divided by the number of data points), thus increasing the bias by reducing the number of data points.…”
Section: Figmentioning
confidence: 99%
“…This is a useful exercise to undertake, especially in such an emerging field as spatial proteomics data analysis. The first applications of large-scale organelle proteomics data analysis were protein correlation profiling efforts (8,21) that calculated the 2 metric using in-house tools and LOPIT (7,18,20) that applied partial least squares discriminant analysis using the commercial SIMCA software (Umetrics, Umea, Sweden). Trotter et al (9) implemented custom R code (12) and used the SVM algorithm from the kernlab package (33), but no code for others to repeat this state-of-the-art procedure is provided.…”
Section: Figmentioning
confidence: 99%