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Mina, A. I.

Publications and source records attributed to Mina, A. I..

2 recordsLinked to original sources

Obesity-linked PPARγ S273 phosphorylation promotes insulin resistance through Growth Differentiation Factor 3

Overnutrition and obesity promote adipose tissue dysfunction, often leading to systemic insulin resistance. The thiazolidinediones (TZDs) are a potent class of insulin-sensitizing drugs and ligands of PPAR{gamma} that improve insulin sensitivity, but their use is limited due to significant side effects. Recently, we demonstrated a mechanism by which TZDs improve insulin sensitivity distinct from receptor agonism and adipogenesis: reversal of obesity-linked phosphorylation of PPAR{gamma} at Serine 273. However, the role of this modification has not been tested genetically. Here we demonstrate that mice encoding an allele of PPAR{gamma} which cannot be phosphorylated at S273 are protected from insulin resistance, without exhibiting differences in body weight or TZD-associated side effects. Indeed, hyperinsulinemic-euglycemic clamp experiments confirm improved insulin sensitivity, as evidenced by increased whole-body glucose uptake. RNA-seq experiments reveal PPAR{gamma} S273 phosphorylation specifically enhances transcription of Gdf3, a BMP family member. Ectopic expression of Gdf3 is sufficient to induce insulin resistance in lean, healthy mice. We find that Gdf3 can impact metabolism by inhibition of BMP signaling. Together, these results highlight the diabetogenic role of PPAR{gamma} S273 phosphorylation and focuses attention on a putative target, Gdf3.

cell biology↗

CalR: A Web-based Analysis Tool for Indirect Calorimetry Experiments

We report a web-based tool for analysis of indirect calorimetry experiments which measure physiological energy balance. CalR easily imports raw data files, generates plots, and determines the most appropriate statistical tests for interpretation. Analysis with the general linear model (which includes ANOVA and ANCOVA) allows for flexibility to interpret experiments of obesity and thermogenesis. Users may also produce standardized output files of an experiment which can be shared and subsequently re-evaluated using CalR. This framework will provide the transparency necessary to enhance consistency and reproducibility in experiments of energy expenditure. CalR analysis software will greatly increase the speed and efficiency with which metabolic experiments can be organized, analyzed according to accepted norms, and reproduced--and will likely become a standard tool for the field. CalR is accessible at https://CalR.bwh.harvard.edu.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC=\"FIGDIR/small/213967_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@c27058org.highwire.dtl.DTLVardef@15dbe84org.highwire.dtl.DTLVardef@1870019org.highwire.dtl.DTLVardef@17a17c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗