Identification of molecular pathways affected by pterostilbene, a natural dimethylether analog of resveratrol

<p>Abstract</p> <p>Background</p> <p>Pterostilbene, a naturally occurring phenolic compound produced by agronomically important plant genera such as <it>Vitis </it>and <it>Vacciunium</it>, is a phytoalexin exhibiting potent antifungal activity. Additionally, recent studies have demonstrated several important pharmacological properties associated with pterostilbene. Despite this, a systematic study of the effects of pterostilbene on eukaryotic cells at the molecular level has not been previously reported. Thus, the aim of the present study was to identify the cellular pathways affected by pterostilbene by performing transcript profiling studies, employing the model yeast <it>Saccharomyces cerevisiae</it>.</p> <p>Methods</p> <p><it>S. cerevisiae </it>strain S288C was exposed to pterostilbene at the IC₅₀concentration (70 μM) for one generation (3 h). Transcript profiling experiments were performed on three biological replicate samples using the Affymetrix GeneChip Yeast Genome S98 Array. The data were analyzed using the statistical methods available in the GeneSifter microarray data analysis system. To validate the results, eleven differentially expressed genes were further examined by quantitative real-time RT-PCR, and <it>S. cerevisiae </it>mutant strains with deletions in these genes were analyzed for altered sensitivity to pterostilbene.</p> <p>Results</p> <p>Transcript profiling studies revealed that pterostilbene exposure significantly down-regulated the expression of genes involved in methionine metabolism, while the expression of genes involved in mitochondrial functions, drug detoxification, and transcription factor activity were significantly up-regulated. Additional analyses revealed that a large number of genes involved in lipid metabolism were also affected by pterostilbene treatment.</p> <p>Conclusion</p> <p>Using transcript profiling, we have identified the cellular pathways targeted by pterostilbene, an analog of resveratrol. The observed response in lipid metabolism genes is consistent with its known hypolipidemic properties, and the induction of mitochondrial genes is consistent with its demonstrated role in apoptosis in human cancer cell lines. Furthermore, our data show that pterostilbene has a significant effect on methionine metabolism, a previously unreported effect for this compound.</p

Voices Raised, Issue 06

Included in this issue: Immaculate Mary; Grants augment women’s research; Mentoring grows; Women’s Studies take root in the neighborhood; Solution-oriented VP to retire; Muslim students strive to educate, support; Don’t let stress ruin your holidays; Dining services dishes up more than you’d expect; Marianist Images Across Campus; Confronting Disrespect: We Owe it to Each Other.https://ecommons.udayton.edu/wc_newsletter/1005/thumbnail.jp

A fast ℓ1-solver and its applications to robust face recognition

In this paper we apply a recently proposed Lagrange Dual Method (LDM) to design a new Sparse Representation-based Classification (LDM-SRC) algorithm for robust face recognition problem. The proposed approach improves the efficiency of the SRC algorithm significantly. The proposed algorithm has the following advantages: (1) it employs the LDM ℓ1-solver to find solution of theℓ1-norm minimization problem, which is much faster than other state-of-the-art ℓ1-solvers, e.g. ℓ1-magic and ℓ1−ℓs . (2) The LDM ℓ1-solver utilizes a new Lagrange-dual reformulation of the original ℓ1-norm minimization problem, not only reducing the problem size when the dimension of training image data is much less than the number of training samples, but also making the dual problem become smooth and convex. Therefore it converts the non-smooth ℓ1-norm minimization problem into a sequence of smooth optimization problems. (3) The LDM-SRC algorithm can maintain good recognition accuracy whilst reducing the computational time dramatically. Experimental results are presented on some benchmark face databases

Analysis of Hypoxia and Hypoxia-Like States through Metabolite Profiling

In diverse organisms, adaptation to low oxygen (hypoxia) is mediated through complex gene expression changes that can, in part, be mimicked by exposure to metals such as cobalt. Although much is known about the transcriptional response to hypoxia and cobalt, little is known about the all-important cell metabolism effects that trigger these responses.Herein we use a low molecular weight metabolome profiling approach to identify classes of metabolites in yeast cells that are altered as a consequence of hypoxia or cobalt exposures. Key findings on metabolites were followed-up by measuring expression of relevant proteins and enzyme activities. We find that both hypoxia and cobalt result in a loss of essential sterols and unsaturated fatty acids, but the basis for these changes are disparate. While hypoxia can affect a variety of enzymatic steps requiring oxygen and heme, cobalt specifically interferes with diiron-oxo enzymatic steps for sterol synthesis and fatty acid desaturation. In addition to diiron-oxo enzymes, cobalt but not hypoxia results in loss of labile 4Fe-4S dehydratases in the mitochondria, but has no effect on homologous 4Fe-4S dehydratases in the cytosol. Most striking, hypoxia but not cobalt affected cellular pools of amino acids. Amino acids such as aromatics were elevated whereas leucine and methionine, essential to the strain used here, dramatically decreased due to hypoxia induced down-regulation of amino acid permeases.These studies underscore the notion that cobalt targets a specific class of iron proteins and provide the first evidence for hypoxia effects on amino acid regulation. This research illustrates the power of metabolite profiling for uncovering new adaptations to environmental stress