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High reproducibility of analyses is contrasted by divergence of sub-proteomes affected by PrP-deficiency in the five models.

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posted on 21.06.2016, 19:50 by Mohadeseh Mehrabian, Dylan Brethour, Declan Williams, Hansen Wang, Hélène Arnould, Benoit Schneider, Gerold Schmitt-Ulms

(a) Hierarchical clustering of proteins (vertical tree) and samples (horizontal tree) of the five global proteome datasets based on TMT-based steady-state protein level abundance ratios of wild-type versus PrP-deficient samples. Note that this analysis was restricted to proteins that were identified and quantified on the basis of a minimum of three TMT signature ion profiles in all four cell models. The heat map color code depicts protein ratios in log2 space, with proteins whose levels correlate directly or inversely with PrP levels shown in blue and red, respectively (see legend for details). (b) Tree diagram obtained by hierarchical clustering of protein level ratio profiles in the 15 samples analyzed. The analysis revealed a close relationship of profiles belonging to biological replicates (indicated by short branches connecting them) and relatively low similarities across cell models. (c) Enlarged view of subset of hierarchical cluster depicting similarity in expression profile of members of the histone family across the five mouse models studied. (d) Hierarchical clustering groups members of the protein families of cellular myosins, and mircrotubule associated proteins in small distinct clusters. (e) Pearson correlation analyses of protein abundance ratios reveals a pronounced direct correlation between samples of the same cell model but relatively weak correlations of PrP-dependent changes to the cellular proteome across cell models. Note the weakly negative Pearson coefficients (up to -0.202) in comparisons of samples derived from N2a and 1C11 models, which indicates that PrP-deficiency in these models may manifest in opposite changes in the abundance ratios of a subset of proteins.