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Boppart, S. A.

Publications and source records attributed to Boppart, S. A..

2 recordsLinked to original sources

Bile acid excess impairs thermogenic function in brown adipose tissue

Bile acids (BAs) not only facilitate fat digestion but also protect against obesity. Here, we show that a genetic mouse model for BA overload (Farnesoid X receptor; Small heterodimer double knockout (DKO)) exhibits mitochondrial dysfunction resulting in a thermogenic defect. By housing DKO mice at thermoneutrality, the poor mitochondrial function in brown fat protects them from diet-induced obesity. Compared to control, we find higher adipose BA levels with excess accumulation of taurocholic acid in the DKO mice. We report that the expression of genes responsible for BA de novo synthesis, conjugation and transporters and accumulation of BAs are present in both brown and white adipocytes. We determine that BA overload is sufficient to cause adipocyte mitochondrial dysfunction and induce the expression of cellular senescence genes in vitro. Taken together, we uncover that BA levels within the adipose tissue may modulate its overall function. HighlightsO_LIMouse model of BA overload exhibits adipose defects, which is partially restored by housing at thermoneutrality. C_LIO_LIBAs are present in detectable concentrations in both BAT and WAT. C_LIO_LIAdipocytes express genes responsible for de novo synthesis, conjugation and transport of BAs, and accumulate BAs. C_LIO_LIPathological accumulation of BAs impairs mitochondrial function leading to thermogenic defect. C_LI

physiology

Dynamic signatures of lipid droplets as new markers to quantify cellular metabolic changes

The metabolic properties of live cells are very susceptible to intra- or extra-cellular perturbations, making their measurements challenging tasks. We show that the dynamics of lipid droplets (LDs) carry information to measure the lipid metabolism of live cells. Coherent anti-Stokes Raman scattering microscopy was used to statistically quantify LD dynamics in living cells in a label-free manner. We introduce dynamic signatures of cells derived from the LD displacement, speed, travel length, and directionality, which allows for the detection of cellular changes induced by stimuli such as fluorescent labeling, temperature change, starvation, and chemical treatment. Histogram fittings of the dynamic signatures using lognormal distribution functions provide quantification of changes in cellular metabolic states. The LD dynamics also enable separation of subpopulations of LDs correlated with different functions. We demonstrate that LD dynamics are new markers to quantify the metabolic changes in live cells.

biophysics