Localization of the pre-squalene segment of the isoprenoid biosynthetic pathway in mammalian peroxisomes

Previous studies have indicated that the early steps in the isoprenoid/cholesterol biosynthetic pathway occur in peroxisomes. However, the role of peroxisomes in cholesterol biosynthesis has recently been questioned in several reports concluding that three of the peroxisomal cholesterol biosynthetic enzymes, namely mevalonate kinase, phosphomevalonate kinase, and mevalonate diphosphate decarboxylase, do not localize to peroxisomes in human cells even though they contain consensus peroxisomal targeting signals. We re-investigated the subcellular localization of the cholesterol biosynthetic enzymes of the pre-squalene segment in human cells by using new stable isotopic techniques and data computations with isotopomer spectral analysis, in combination with immunofluorescence and cell permeabilization techniques. Our present findings clearly show and confirm previous studies that the pre-squalene segment of the cholesterol biosynthetic pathway is localized to peroxisomes. In addition, our data are consistent with the hypothesis that acetyl-CoA derived from peroxisomal β-oxidation of very long-chain fatty acids and medium-chain dicarboxylic acids is preferentially channeled to cholesterol synthesis inside the peroxisomes without mixing with the cytosolic acetyl-CoA poo

Turnover of histones and histone variants in postnatal rat brain: effects of alcohol exposure

Abstract Background Alcohol consumption during pregnancy is a significant public health problem and can result in a continuum of adverse outcomes to the fetus known as fetal alcohol spectrum disorders (FASD). Subjects with FASD show significant neurological deficits, ranging from microencephaly, neurobehavioral, and mental health problems to poor social adjustment and stress tolerance. Neurons are particularly sensitive to alcohol exposure. The neurotoxic action of alcohol, i.e., through ROS production, induces DNA damage and neuronal cell death by apoptosis. In addition, epigenetics, including DNA methylation, histone posttranslational modifications (PTMs), and non-coding RNA, play an important role in the neuropathology of FASD. However, little is known about the temporal dynamics and kinetics of histones and their PTMs in FASD. Results We examined the effects of postnatal alcohol exposure (PAE), an animal model of human third-trimester equivalent, on the kinetics of various histone proteins in two distinct brain regions, the frontal cortex, and the hypothalamus, using in vivo 2H2O-labeling combined with mass spectrometry-based proteomics. We show that histones have long half-lives that are in the order of days. We also show that H3.3 and H2Az histone variants have faster turnovers than canonical histones and that acetylated histones, in general, have a faster turnover than unmodified and methylated histones. Our work is the first to show that PAE induces a differential reduction in turnover rates of histones in both brain regions studied. These alterations in histone turnover were associated with increased DNA damage and decreased cell proliferation in postnatal rat brain. Conclusion Alterations in histone turnover might interfere with histone deposition and chromatin stability, resulting in deregulated cell-specific gene expression and therefore contribute to the development of the neurological disorders associated with FASD. Using in vivo 2H2O-labeling and mass spectrometry-based proteomics might help in the understanding of histone turnover following alcohol exposure and could be of great importance in enabling researchers to identify novel targets and/or biomarkers for the prevention and management of fetal alcohol spectrum disorders

Relationship between hepatic and mitochondrial ceramides: a novel in vivo method to track ceramide synthesis

Ceramides (CERs) are key intermediate sphingolipids implicated in contributing to mitochondrial dysfunction and the development of multiple metabolic conditions. Despite the growing evidence of CER role in disease risk, kinetic methods to measure CER turnover are lacking, particularly using in vivo models. The utility of orally administered 13C3, 15N l-serine, dissolved in drinking water, was tested to quantify CER 18:1/16:0 synthesis in 10-week-old male and female C57Bl/6 mice. To generate isotopic labeling curves, animals consumed either a control diet or high-fat diet (HFD; n = 24/diet) for 2 weeks and varied in the duration of the consumption of serine-labeled water (0, 1, 2, 4, 7, or 12 days; n = 4 animals/day/diet). Unlabeled and labeled hepatic and mitochondrial CERs were quantified using liquid chromatography tandem MS. Total hepatic CER content did not differ between the two diet groups, whereas total mitochondrial CERs increased with HFD feeding (60%, P < 0.001). Within hepatic and mitochondrial pools, HFD induced greater saturated CER concentrations (P < 0.05) and significantly elevated absolute turnover of 16:0 mitochondrial CER (mitochondria: 59%, P < 0.001 vs. liver: 15%, P = 0.256). The data suggest cellular redistribution of CERs because of the HFD. These data demonstrate that a 2-week HFD alters the turnover and content of mitochondrial CERs. Given the growing data on CERs contributing to hepatic mitochondrial dysfunction and the progression of multiple metabolic diseases, this method may now be used to investigate how CER turnover is altered in these conditions

Gaussian Process Modeling of Protein Turnover

We describe a stochastic model to compute in vivo protein turnover rate constants from stable-isotope labeling and high-throughput liquid chromatography–mass spectrometry experiments. We show that the often-used one- and two-compartment nonstochastic models allow explicit solutions from the corresponding stochastic differential equations. The resulting stochastic process is a Gaussian processes with Ornstein–Uhlenbeck covariance matrix. We applied the stochastic model to a large-scale data set from ¹⁵N labeling and compared its performance metrics with those of the nonstochastic curve fitting. The comparison showed that for more than 99% of proteins, the stochastic model produced better fits to the experimental data (based on residual sum of squares). The model was used for extracting protein-decay rate constants from mouse brain (slow turnover) and liver (fast turnover) samples. We found that the most affected (compared to two-exponent curve fitting) results were those for liver proteins. The ratio of the median of degradation rate constants of liver proteins to those of brain proteins increased 4-fold in stochastic modeling compared to the two-exponent fitting. Stochastic modeling predicted stronger differences of protein turnover processes between mouse liver and brain than previously estimated. The model is independent of the labeling isotope. To show this, we also applied the model to protein turnover studied in induced heart failure in rats, in which metabolic labeling was achieved by administering heavy water. No changes in the model were necessary for adapting to heavy-water labeling. The approach has been implemented in a freely available R code