The metabolic syndrome is a collection of risk factors including obesity

The metabolic syndrome is a collection of risk factors including obesity insulin resistance and hepatic steatosis which occur together and increase the risk of diseases such as diabetes cardiovascular disease and cancer. accurate and reproducible quantitation of the targeted proteins across 36 different samples (12 conditions and 3 biological replicates) generating one of the largest quantitative targeted proteomics data sets in mammalian tissues. Our results revealed rapid response to high-fat diet that diverged early in the feeding regimen and evidenced SAHA a response to high-fat diet dominated by the activation of peroxisomal β-oxidation in C57BL/6J and by lipogenesis in 129Sv mice. at 0 week (T0). T1 refers to animals after 6 weeks of high-fat diet and T2 corresponds … Unsupervised hierarchical clustering of all protein abundance changes showed two clearly distinct groups corresponding to the studied mouse strains thus confirming the importance of the genetic background as the main determinant modulating the response to high caloric intake. The subset of identified proteins that more strongly contributed to the separation of the mouse strains were mainly metabolic enzymes belonging to the tricarboxylic acid SAHA cycle glycolysis β-oxidation fatty acid biosynthesis and glycogen metabolism (Figure 2A; Supplementary Table S4A). Similar results were obtained when the data were subjected to a principal component (PC) analysis although in that case also proteins distinguishing different time points and treatments could be identified (Figure SAHA 2B; Supplementary Table S4B). Three PCs were required to distinguish among strains time points and treatments showing that there is enough variation in the abundance of the measured peptides and proteins to reflect the different conditions of the study (PC-1: 64.0%; PC-2: 10.4%; PC-3: 5.7% of the total variation). Each PC was orthogonal to the previous ones and uncovered complementary variation. Together the three components explained over 80% of the total variation (Figure 2B dashed ellipses). These analyses showed that although the observed variation is mostly due to differences among mouse strains time points and treatments still have a significant contribution to sample variability. These observations confirmed the rich information content of the acquired data and provided us with a first overview of the system under study. Further detailed evaluation SAHA of the observed differences in the targeted proteome among mouse strains time points and treatments is described in the next sections. Comparison of mouse strains to elucidate the differential effect of the high-fat diet The quantitative data set acquired for the targeted proteins was initially used to evaluate the changes in protein abundance within each mouse strain after 6 and 12 weeks of high-fat diet under condition. In both strains several proteins exhibited significant changes in abundance after 6 (T1) and 12 weeks (T2) of high-fat diet. Most of the observed changes were found in proteins involved in the β-oxidation (DHB4 in C57BL/6J) and fatty acid biosynthetic pathways as well as in proteins involved in glucose metabolism (Figure 3A and B; Supplementary VBCH Table S5). Moreover some proteins involved in the insulin-signaling pathway such as transcription factors SRBP1 and EIF3L and kinase MK01 showed significant abundance changes by mass spectrometry either in one (EIF3L in C57BL/6J) or both mouse strains (MK01 and SRBP1) (Figure 3B; Supplementary Figure S2). Overall the fed C57BL/6J mice showed a more significantly altered targeted proteome after several weeks of high-fat diet than the fed 129Sv mice. Figure 3 (A) Changes in protein abundance after 6 (T1) and 12 weeks (T2) of high-fat diet in C57BL/6J (B6) and 129Sv (S9) mice fed at different time points. Gray-colored features … Among proteins with different fold changes in the two mouse strains after either 6 or 12 weeks treatment we observed numerous proteins that showed opposite quantitative trends in response to high-fat diet (Figure 4A and C). This was the case of several enzymes related to the TCA cycle SAHA (ODP2 ODPA ODPB CISY) and of some key proteins involved in the lipid biosynthetic pathway such as FAS and “type”:”entrez-protein” attrs :”text”:”Q8R5C9″ term_id :”81879166″ term_text :”Q8R5C9″Q8R5C9 (ACACB) which showed increasing abundance levels in C57BL/6J whereas.