Fig 1: ANGPTL4 deficiency alters colonic inflammatory gene expression.(a,e) Using Partek Genomic Suite software, we generated a microarray heat map showing changes in gene expression among colon tissues from ANGPTL4+/+ and ANGPTL4−/− mice fed with Veh, DSS or SA (a) and among colons from ANGPTL4+/+ and ANGPTL4−/− mice treated with DSS, inflamed and non-inflamed colon biopsies from ulcerative colitis patients (GSE9452) (e). Transcripts were estimated using a log2 transformation and subjected to unbiased ANOVA to detect differentially expressed genes between samples. Only genes with a fold change <−1.2 or >1.2 were of significance. The genes were then hierarchical clustered based on significance to generate heatmaps. For (a), among the 434 transcripts associated with “gastrointestinal diseases” identified with the IPA database, 63% were found to be commonly regulated across the three treatment groups. For (e), 32% of the transcripts associated with “gastrointestinal diseases” were found to be shared among the groups, with the gene profile from DSS-induced inflammation in ANGPTL4−/− mice most closely associated with the inflamed UC biopsies. (b,f) A larger number of up-regulated genes was correlated with an increasing severity of colonic inflammation in the microarray analysis. (c) Gene ontology analysis of gene clusters (black boxes in (a)) indicated that the major pathways included IL-6-, IL-10- and TNF-related pathways. (d) IPA analysis ranked colitis, inflammation of the intestine and inflammatory bowel disease as the most closely associated gastrointestinal diseases, with leukocyte migration and infiltration as the predominant functions. (g) Among the genes that were commonly regulated between human and mouse colon samples (black box), most genes encode for components of the IL-1β, IL-6 and IL-4 pathways. (h) The IPA database ranked cellular movement, development, function, growth and proliferation as the top molecular processes involved, along with immune processes such as leukocyte activation, myeloid cell homeostasis and immune responses being the most significant biological functions involved. The numbers in the bar graphs in (d,h) represent the p-values of the process in the GO analysis, with the smallest p-value being the most significant. An in-depth overview is described in Supplementary Fig. S4.
Fig 2: Inhibiting TET activity protects human islets from ER stress, cell death and inflammatory responsesGene expression in human islets (n = three to four experiments, each with 4,000–8,000 islet equivalency (IEQ) from each nondiabetic donor after 48 h incubation with brefeldin A (BFA) (A) or thapsigargin (TG) (B) in the presence or absence of TET inhibitor Bobcat339 (Bobcat). The expression of all 12 tested genes, associated with ER stress and cell death were significantly greater in BFA vs. DMSO (∗∗∗∗p < 0.0001), but significantly reduced in the presence of BFA+Bobcat (ANOVA with Dunnett’s multiple comparison test, ∗∗∗∗p < 0.0001, ∗p < 0.05).The expression of 11 of the 12 tested genes were significantly greater in TG vs. DMSO (∗∗∗∗p < 0.0001), but significantly reduced in the presence of TG + Bobcat (ANOVA with Dunnett’s multiple comparison test,∗∗∗∗p < 0.0001, ∗∗p < 0.01).(C) Percent apoptotic and dead cells measured by flow cytometry in human islets cultured for 24 h with BFA with or without Bobcat339 (ANOVA with Tukey’s multiple comparison test,∗∗∗∗p < 0.0001, ∗∗p < 0.01).(D) The release of INS DNA with methylation marks indicating β cell origin 30 in human islets cultured for 24 h with BFA with or without Bobcat339 (∗∗∗∗p < 0.0001 ANOVA with Sidak’s multiple comparison test).(E) Percentage of dead or Indoleamine 2,3-dioxygenase (IDO+) islet cells measured by flow cytometry after 48 h culture with TNFa, IL-1β, IFNy, and IFNa. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001 vs. cytokines+DMSO, ANOVA with Tukey’s multiple comparison test data (mean ± 95% CI).The data shown are the individual experiments and represent the mean ± 95 percent confidence intervals.
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