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Ashok, D.

Publications and source records attributed to Ashok, D..

2 recordsLinked to original sources

PDE9 Inhibition Activates PPARa to Stimulate Mitochondrial Fat Metabolism and Reduce Cardiometabolic Syndrome

Central obesity with cardiometabolic syndrome (CMS) is a major global contributor to human disease, and effective therapies are needed. Here, we show inhibiting cyclic-GMP selective phosphodiesterase-9A (PDE9-I) suppresses established diet-induced obesity and CMS in ovariectomized female and male mice. PDE9-I reduces abdominal, hepatic, and myocardial fat accumulation, stimulates mitochondrial activity in brown and white fat, and improves CMS, without altering activity or food intake. PDE9 localizes to mitochondria, and its inhibition stimulates lipolysis and mitochondrial respiration coupled to PPAR-dependent gene regulation. PPAR upregulation is required for PDE9-I metabolic efficacy and is absent in non-ovariectomized females that also display no metabolic benefits from PDE9-I. The latter is compatible with estrogen receptor- altering PPAR chromatin binding identified by ChIPSeq. In humans with heart failure and preserved ejection fraction, myocardial expression of PPARA and its regulated genes is reduced versus control. These findings support testing PDE9-I to treat obesity/CMS in men and postmenopausal women. SummaryOral inhibition of phosphodiesterase type 9 stimulates mitochondrial fat metabolism and lipolysis, reducing central obesity without changing appetite

physiology↗

MitoWave: Spatiotemporal analysis of mitochondrial membrane potential fluctuations during ischemia-reperfusion

Mitochondria exhibit non-stationary unstable membrane potential ({Delta}{Psi}m) when subjected to stress, such as during Ischemia/Reperfusion (I/R). Understanding the mechanism of {Delta}{Psi}m instability involves characterizing and quantifying this phenomenon in response to I/R stress in an unbiased and reproducible manner. We designed a simple ImageJ-MATLAB-based workflow called MitoWave to unravel dynamic mitochondrial {Delta}{Psi}m changes that occur during ischemia and reperfusion. MitoWave employs MATLABs wavelet transform toolbox. In-vitro Ischemia was effected by placing a glass coverslip for 60 minutes on a monolayer of neonatal mouse ventricular myocytes (NMVMs). Removal of the coverslip allowed for reperfusion. {Delta}{Psi}m response to I/R was recorded on a confocal microscope using TMRM as the indicator. As proof-of-principle, we used MitoWave analysis on ten invitro I/R experiments. Visual observations corroborated quantitative MitoWave analysis results in classifying the ten I/R experiments into five outcomes that were observed based on the oscillatory state of {Delta}{Psi}m throughout the reperfusion time period. Statistical analysis of the distribution of oscillating mitochondrial clusters during reperfusion shows significant differences between five different outcomes (p< 0.001). Features such as time-points of {Delta}{Psi}m depolarization during I/R, area of mitochondrial clusters and time-resolved frequency components during reperfusion were determined per cell and per mitochondrial cluster. We found that mitochondria from NMVMs subjected to I/R oscillate in the frequency range of 8.6-45mHz, with a mean of 8.73{+/-}4.35mHz. Oscillating clusters had smaller areas ranging from 49.78{+/-}40.64 m2 while non-oscillating clusters had larger areas 65.97{+/-}42.07m2. A negative correlation between frequency and mitochondrial cluster area was seen. We also observed that late {Delta}{Psi}m loss during ischemia correlated with early {Delta}{Psi}m stabilization after oscillation on reperfusion. Thus, MitoWave analysis provides a way to quantify complex time-resolved mitochondrial behavior. It provides an easy to follow workflow to automate microscopy analysis and allows for unbiased, reproducible quantitation of complex nonstationary cellular phenomena. Statement of SignificanceUnderstanding mitochondrial instability in Ischemia Reperfusion injury is key to determining efficacy of interventions. The MitoWave analysis is a powerful yet simple tool that enables even beginner MATALAB-Image J users to automate analysis of time-series from microscopy data. While we used it to detect {Delta}{Psi}m changes during I/R, it can be adapted to detect any such spatio-temporal changes. It standardizes the quantitative analysis of complex biological signals, opens the door to in-depth screening of the genes, proteins and mechanisms underlying metabolic recovery after ischemia-reperfusion.

cell biology↗