Project description:In this study, we characterize the protein uptake and degradation pathways of S. cerevisiae to better understand its impact on protein secretion titers. We do find that S. cerevisiae can consume significant (g/L) quantities of whole proteins. Characterizing the systems with metabolomics and transcriptomics, we identify metabolic and regulatory markers that are consistent with uptake of whole proteins by endocytosis, followed by intracellular degradation and catabolism of substituent amino acids. Uptake and degradation of recombinant protein products may be common in S. cerevisiae protein secretion systems, and the current data should help formulate strategies to mitigate product loss.
Project description:Dynamic 3' UTRs variation mediated by APA is one of the major determinants of post-transcriptional regulation. Though some progress has been made in understanding its function in mammalian cells, the role of APA in the model organism S. cerevisiae, which lack of miRNAs, is a matter of debate. Unlike mammalian cells, most of S. cerevisiae genes tend to express mRNAs with longer 3′ UTRs in proliferating cells. Further analysis demonstrated that 3' UTRs length and mRNA expression were negatively correlated in different growth conditions. By combining APA sequencing and polysome profiling, we observed that mRNA isoforms with shorter 3' UTRs with a higher translational efficiency in proliferating cells but not quiescent. Further analysis demonstrated that different function genes translational efficiency control by APA are differential modulated and closely related with growth conditions. Furthermore, we observed the correlation between asRNAs and translational efficiency of different length 3′ UTR transcripts, suggests asRNAs may involve in the regulation of translational efficiency mediated by APA. Thus, this study indicates conservation of molecular function of APA in different Eukaryotes, highlighting the importance of APA in regulating gene function.
Project description:The RNA interference (RNAi) pathway is found in most eukaryotic lineages but curiously is absent in others, including that of Saccharomyces cerevisiae. Here, we show that reconstituting RNAi in S. cerevisiae causes loss of a beneficial dsRNA virus, known as killer virus. Incompatibility between RNAi and killer viruses extends to other fungal species, in that RNAi is absent in all species known to possess dsRNA killer viruses, whereas killer viruses are absent in closely related species that retained RNAi. Thus, the advantage imparted by acquiring and retaining killer viruses explains the persistence of RNAi-deficient species during fungal evolution. Examine mRNA abundance of S. cerevisiae wild-type (DPB249), +AGO1 (DPB252), +DCR1 (DPB255) and +AGO1, DCR1 (DPB258).
Project description:Quantitative MS analysis of acetylation in yeast using SILAC labeling and MaxQuant. Download Index of Raw files first. We used quantitative mass spectrometry to analyze acetylation dynamics and stoichiometry in Saccharomyces cerevisiae. We found that acetylation accumulated in growth-arrested cells in a manner that depended on acetyl-CoA generation in distinct subcellular compartments. We used stable isotope labeling with amino acids in cell culture to quantify differences in protein, acetylation, and phosphorylation abundance by MS. Proteins from whole cell lysates were digested to peptides and acetylated peptides enriched using a polyclonal anti-acetyllysine antibody. Peptide fractions were analyzed by reversed-phase liquid chromatography coupled to high resolution liquid chromatography‐tandem mass spectrometry (LC-MS/MS) and raw MS data were computationally processed using MaxQuant.
Project description:Reprogramming a non-methylotrophic industrial host, such as Saccharomyces cerevisiae, to a synthetic methylotroph reprents a huge challenge due to the complex regulation in yeast. Through TMC strategy together with ALE strategy, we completed a strict synthetic methylotrophic yeast that could use methanol as the sole carbon source. However, how cells respond to methanol and remodel cellular metabolic network on methanol were not clear. Therefore, genome-scale transcriptional analysis was performed to unravel the cellular reprograming mechanisms underlying the improved growth phenotype.