Project description:Excess/residual urea is a pervasion problem in wine and Sake fermentation. We sought to reduce residual urea levels (to reduce ethyl carbamate leves) by engineering the Sake yeast strain K7 to constitutively express either the urea amidolyase (Dur1,2) or urea importer (Dur3). We sought to then compare the gene expression profiles of the metabolically engineered yeast strains to the parental strain during fermentation. Engineered strains would hopefully have gene expression profiles that were minimally different from the parental strain.
Project description:The goal of this study is to apply the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-Seq data from 10x Genomics platform was analyzed to dissect this problem at multiple scales. Data indicates that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance
Project description:Excess/residual urea is a pervasion problem in wine and Sake fermentation. We sought to reduce residual urea levels (to reduce ethyl carbamate leves) by engineering the Sake yeast strain K7 to constitutively express either the urea amidolyase (Dur1,2) or urea importer (Dur3). We sought to then compare the gene expression profiles of the metabolically engineered yeast strains to the parental strain during fermentation. Engineered strains would hopefully have gene expression profiles that were minimally different from the parental strain. Yeast strains were used to ferment Chardonnay grape must and total RNA harvested at 24 hrs into fermentation. 10 ug of total RNA was made into cDNA, and then labelled cRNA, with the Affymetrix GeneChip one cycle target amplification and labelling system. Fragmented cRNA was then hybridized to an Affymetrix YGS98 array in biological duplicate.
Project description:The goal of this study is to apply the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-Seq data from both the SMART-seq/Fluidigm and 10x Genomics platforms were analyzed to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance
Project description:The goal of this study is to apply the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-Seq data from both the SMART-seq/Fluidigm and 10x Genomics platforms were analyzed to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance
