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Contributions of epsinR and gadkin to clathrin-mediated intracellular trafficking.

Hirst J, Edgar JR, Borner GH, Li S, Sahlender DA, Antrobus R, Robinson MS - Mol. Biol. Cell (2015)

Bottom Line: The precise functions of most of the proteins that participate in clathrin-mediated intracellular trafficking are unknown.Using the epsinR knocksideways data, we were able to estimate the copy number of all major intracellular CCV proteins.Both phenotypes provide new insights into the regulation of intracellular CCV formation, which could not have been found using more conventional approaches.

View Article: PubMed Central - PubMed

Affiliation: Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom.

No MeSH data available.


Related in: MedlinePlus

PCA of the SILAC data. (A) PCA was used to compare the global effects of epsinR, gadkin, AP-1, and GGA2 knocksideways on CCV composition. Ten data sets were included: the three epsinR and three gadkin data sets from this study and the two AP-1 and GGA2 data sets from our previous study (Hirst et al., 2012). The behavior of 875 proteins common to all 10 sets was used to group individual experiments according to overall similarity. Repeat experiments of the same knocksideways cluster closely, and the AP-1 and epsinR knocksideways experiments cluster, showing that they affect CCV composition in a similar way. The GGA2 and gadkin knocksideways experiments have different effects and cluster separately. (B) PCA on the epsinR and gadkin knocksideways data sets alone, comparing how individual proteins are affected across the six data sets. Some proteins (e.g., hydrolases) are shifted more toward gadkin (purple star); others (e.g., AP-1 subunits) are shifted more toward epsinR (yellow star).
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Figure 7: PCA of the SILAC data. (A) PCA was used to compare the global effects of epsinR, gadkin, AP-1, and GGA2 knocksideways on CCV composition. Ten data sets were included: the three epsinR and three gadkin data sets from this study and the two AP-1 and GGA2 data sets from our previous study (Hirst et al., 2012). The behavior of 875 proteins common to all 10 sets was used to group individual experiments according to overall similarity. Repeat experiments of the same knocksideways cluster closely, and the AP-1 and epsinR knocksideways experiments cluster, showing that they affect CCV composition in a similar way. The GGA2 and gadkin knocksideways experiments have different effects and cluster separately. (B) PCA on the epsinR and gadkin knocksideways data sets alone, comparing how individual proteins are affected across the six data sets. Some proteins (e.g., hydrolases) are shifted more toward gadkin (purple star); others (e.g., AP-1 subunits) are shifted more toward epsinR (yellow star).

Mentions: We were surprised by the global effects of both the epsinR knocksideways and the gadkin knocksideways. However, because in both cases AP-1 itself was strongly depleted, one possibility was that the phenotypes were an indirect consequence of the loss of AP-1. To try to tease apart potential differences between the different knocksideways profiles, we analyzed the data from both the present study and our earlier knocksideways study (Hirst et al., 2012) using principal component analysis (PCA). PCA allows one to compare multiple data sets, and therefore it can reveal patterns of similarities and differences that are otherwise difficult to discern. We compared ∼900 proteins identified in common among the knocksideways experiments on AP-1 (two data sets), GGA2 (two data sets), epsinR (three data sets), and gadkin (AP1AR; three data sets), of which ∼100 were likely to be genuine CCV proteins. The coclustering of the AP-1 and epsinR data sets in the PCA plot (Figure 7A) indicates that knocking either one of them sideways had very similar effects on the CCV proteome, consistent with epsinR being a component of the core machinery like AP-1. In contrast, the gadkin knocksideways phenotype was clearly distinguishable from both the AP-1/epsinR knocksideways phenotype and the GGA2 knocksideways phenotype.


Contributions of epsinR and gadkin to clathrin-mediated intracellular trafficking.

Hirst J, Edgar JR, Borner GH, Li S, Sahlender DA, Antrobus R, Robinson MS - Mol. Biol. Cell (2015)

PCA of the SILAC data. (A) PCA was used to compare the global effects of epsinR, gadkin, AP-1, and GGA2 knocksideways on CCV composition. Ten data sets were included: the three epsinR and three gadkin data sets from this study and the two AP-1 and GGA2 data sets from our previous study (Hirst et al., 2012). The behavior of 875 proteins common to all 10 sets was used to group individual experiments according to overall similarity. Repeat experiments of the same knocksideways cluster closely, and the AP-1 and epsinR knocksideways experiments cluster, showing that they affect CCV composition in a similar way. The GGA2 and gadkin knocksideways experiments have different effects and cluster separately. (B) PCA on the epsinR and gadkin knocksideways data sets alone, comparing how individual proteins are affected across the six data sets. Some proteins (e.g., hydrolases) are shifted more toward gadkin (purple star); others (e.g., AP-1 subunits) are shifted more toward epsinR (yellow star).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Figure 7: PCA of the SILAC data. (A) PCA was used to compare the global effects of epsinR, gadkin, AP-1, and GGA2 knocksideways on CCV composition. Ten data sets were included: the three epsinR and three gadkin data sets from this study and the two AP-1 and GGA2 data sets from our previous study (Hirst et al., 2012). The behavior of 875 proteins common to all 10 sets was used to group individual experiments according to overall similarity. Repeat experiments of the same knocksideways cluster closely, and the AP-1 and epsinR knocksideways experiments cluster, showing that they affect CCV composition in a similar way. The GGA2 and gadkin knocksideways experiments have different effects and cluster separately. (B) PCA on the epsinR and gadkin knocksideways data sets alone, comparing how individual proteins are affected across the six data sets. Some proteins (e.g., hydrolases) are shifted more toward gadkin (purple star); others (e.g., AP-1 subunits) are shifted more toward epsinR (yellow star).
Mentions: We were surprised by the global effects of both the epsinR knocksideways and the gadkin knocksideways. However, because in both cases AP-1 itself was strongly depleted, one possibility was that the phenotypes were an indirect consequence of the loss of AP-1. To try to tease apart potential differences between the different knocksideways profiles, we analyzed the data from both the present study and our earlier knocksideways study (Hirst et al., 2012) using principal component analysis (PCA). PCA allows one to compare multiple data sets, and therefore it can reveal patterns of similarities and differences that are otherwise difficult to discern. We compared ∼900 proteins identified in common among the knocksideways experiments on AP-1 (two data sets), GGA2 (two data sets), epsinR (three data sets), and gadkin (AP1AR; three data sets), of which ∼100 were likely to be genuine CCV proteins. The coclustering of the AP-1 and epsinR data sets in the PCA plot (Figure 7A) indicates that knocking either one of them sideways had very similar effects on the CCV proteome, consistent with epsinR being a component of the core machinery like AP-1. In contrast, the gadkin knocksideways phenotype was clearly distinguishable from both the AP-1/epsinR knocksideways phenotype and the GGA2 knocksideways phenotype.

Bottom Line: The precise functions of most of the proteins that participate in clathrin-mediated intracellular trafficking are unknown.Using the epsinR knocksideways data, we were able to estimate the copy number of all major intracellular CCV proteins.Both phenotypes provide new insights into the regulation of intracellular CCV formation, which could not have been found using more conventional approaches.

View Article: PubMed Central - PubMed

Affiliation: Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom.

No MeSH data available.


Related in: MedlinePlus