University of Nevada, Reno

About: University of Nevada, Reno is a education organization based out in Reno, Nevada, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 13561 authors who have published 28217 publications receiving 882002 citations. The organization is also known as: University of Nevada & Nevada State University.

The R2R3-MYB Transcription Factors MYB14 and MYB15 Regulate Stilbene Biosynthesis in Vitis vinifera

Abstract: Plant stilbenes are phytoalexins that accumulate in a small number of plant species, including grapevine (Vitis vinifera), in response to biotic and abiotic stresses and have been implicated in many beneficial effects on human health. In particular, resveratrol, the basic unit of all other complex stilbenes, has received widespread attention because of its cardio-protective, anticarcinogenic, and antioxidant properties. Although stilbene synthases (STSs), the key enzymes responsible for resveratrol biosynthesis, have been isolated and characterized from several plant species, the transcriptional regulation underlying stilbene biosynthesis is unknown. Here, we report the identification and functional characterization of two R2R3-MYB-type transcription factors (TFs) from grapevine, which regulate the stilbene biosynthetic pathway. These TFs, designated MYB14 and MYB15, strongly coexpress with STS genes, both in leaf tissues under biotic and abiotic stress and in the skin and seed of healthy developing berries during maturation. In transient gene reporter assays, MYB14 and MYB15 were demonstrated to specifically activate the promoters of STS genes, and the ectopic expression of MYB15 in grapevine hairy roots resulted in increased STS expression and in the accumulation of glycosylated stilbenes in planta. These results demonstrate the involvement of MYB14 and MYB15 in the transcriptional regulation of stilbene biosynthesis in grapevine.

How important are terrestrial organic carbon inputs for secondary production in freshwater ecosystems

Abstract: 1. Many freshwater systems receive substantial inputs of terrestrial organic matter. Terrestrially derived dissolved organic carbon (t-DOC) inputs can modify light availability, the spatial distrib ...

Gene expression signatures and small-molecule compounds link a protein kinase to Plasmodium falciparum motility.

Abstract: Calcium-dependent protein kinases play a crucial role in intracellular calcium signaling in plants, some algae and protozoa. In Plasmodium falciparum, calcium-dependent protein kinase 1 (PfCDPK1) is expressed during schizogony in the erythrocytic stage as well as in the sporozoite stage. It is coexpressed with genes that encode the parasite motor complex, a cellular component required for parasite invasion of host cells, parasite motility and potentially cytokinesis. A targeted gene-disruption approach demonstrated that pfcdpk1 seems to be essential for parasite viability. An in vitro biochemical screen using recombinant PfCDPK1 against a library of 20,000 compounds resulted in the identification of a series of structurally related 2,6,9-trisubstituted purines. Compound treatment caused sudden developmental arrest at the late schizont stage in P. falciparum and a large reduction in intracellular parasites in Toxoplasma gondii, which suggests a possible role for PfCDPK1 in regulation of parasite motility during egress and invasion.

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Abstract: The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.