Fig 1.
FGF19-mediated regulation of liver protein expression resolved by quantitative proteomics.
(A) Schematic representation of the experimental outline to determine the hepatic proteomic profile of mice treated with FGF19 or Veh for 12 h. (n = 3) (B) Frequency plot of proteins identified in vehicle-treated Wt mice based on their total log2 heavy/light normalized ratio. The plot is representative of mean Wt untreated condition to show the basal efficiency of the heavy spike-in added to the light samples. Percentage of proteins with a log2 heavy/light normalized ratio included in interval (-1,+1) is shown. (C) Protein ranking based on changes of the log2 light/heavy normalized ratio induced by FGF19 when comparing FGF19 treatment for 12h to vehicle control. Number of proteins, of which expression was decreased (≤ -1.5 fold), unchanged or increased (≥1.5 fold) are indicated. (C) Volcano plot depicting the protein changes induced by FGF19 after 12h treatment. Plots are accompanied by tables listing the significant upregulated or downregulated proteins with fold change >1.5 (n = 3; p<0.05).
Fig 2.
FGF19 modulates expression of proteins involved in metabolism and cell survival.
(A) IPA of pathways enriched in mice treated with FGF19 for 12h compared to vehicle control. For the analysis, proteins with fold change ≥1.3 FGF19 over vehicle were included. Pathways related to physiology or disease that were significantly enriched (p-value < 0.01) are ranked in function of their activation z-score and grouped into functional classes. (B) Venn Diagram representation of proteins changed upon FGF19 treatment that are involved in metabolism and cell survival/cancer, inferred from the metabolic (#) and cell survival (*) pathways depicted in panel A. Fold change upon FGF19 treatment for proteins classified in metabolism, cell survival/cancer pathways or both is shown.
Fig 3.
FGF19 stimulation affects mRNA expression of genes involved in metabolism and cell survival.
(A) Schematic representation of the experimental outline to determine gene expression changes occurring upon FGF19 treatment for 0, 15 min, 1h, 2h, 4h and 12h. (B) Hepatic expression of genes involved in metabolism (Cyp7a1, Acox1, Acsl3), proliferation (Egfr, c-Fos, Hdlbp, Anxa2) or both (Stat3, Apoa4, Apoe, Fas, Gtpbp4) was determined by Real Time qPCR. (n = 5–6). Data are normalized to Gapdh expression and expressed as mean ± SEM.
Fig 4.
FGF19 regulates Stat3 expression and phosphorylation at Tyr705.
Western blot analyses of Stat3 protein (A) and phospho-Stat3 (Tyr705) (B) at 0h, 15 min, 1h, 2h and 12h after FGF19 treatment. Quantification for Stat3 is shown as relative protein signal normalized to tubulin. Data are expressed as mean ± SD. Each lane represents one mouse liver.
Fig 5.
FGF19 elicits expression changes in target genes of tumorigenic regulators.
(A) Ingenuity upstream regulator analysis applied to protein changes observed upon FGF19 treatment for 12h. Prediction of upstream regulators is based on the overlap between the dataset proteins and the genes that are regulated by a transcription factor/hormone/compound, based on the knowledge included in Ingenuity database (overlap p-value <0.01). Green bars, upstream regulators with positive activation z-score; grey bars, upstream regulators with negative activation z-score.
Table 1.
TGFB1 targets regulated by FGF19.