Comparative transcriptomic analysis reveals similarities and dissimilarities in saccharomyces cerevisiae wine strains response to nitrogen availability

Nitrogen levels in grape-juices are of major importance in winemaking ensuring adequate yeast growth and fermentation performance. Here we used a comparative transcriptome analysis to uncover wine yeasts responses to nitrogen availability during fermentation. Gene expression was assessed in three genetically and phenotypically divergent commercial wine strains (CEG, VL1 and QA23), under low (67 mg/L) and high nitrogen (670 mg/L) regimes, at three time points during fermentation (12h, 24h and 96h). Two-way ANOVA analysis of each fermentation condition led to the identification of genes whose expression was dependent on strain, fermentation stage and on the interaction of both factors. The high fermenter yeast strain QA23 was more clearly distinct from the other two strains, by differential expression of genes involved in flocculation, mitochondrial functions, energy generation and protein folding and stabilization. For all strains, higher transcriptional variability due to fermentation stage was seen in the high nitrogen fermentations. A positive correlation between maximum fermentation rate and the expression of genes involved in stress response was observed. The finding of common genes correlated with both fermentation activity and nitrogen up-take underlies the role of nitrogen on yeast fermentative fitness. The comparative analysis of genes differentially expressed between both fermentation conditions at 12h, where the main difference was the level of nitrogen available, showed the highest variability amongst strains revealing strain-specific responses. Nevertheless, we were able to identify a small set of genes whose expression profiles can quantitatively assess the common response of the yeast strains to varying nitrogen conditions. The use of three contrasting yeast strains in gene expression analysis prompts the identification of more reliable, accurate and reproducible biomarkers that will facilitate the diagnosis of deficiency of this nutrient in the grape-musts and the development of strategies to optimize yeast performance in industrial fermentations

Noise and interlocking signaling pathways promote distinct transcription factor dynamics in response to different stresses

All cells perceive and respond to environmental stresses through elaborate stress-sensing networks. Yeast cells sense stress through diverse signaling pathways that converge on the transcription factors Msn2 and Msn4, which respond by initiating rapid, idiosyncratic cycles into and out of the nucleus. To understand the role of Msn2/4 nuclear localization dynamics, we combined time-lapse studies of Msn2-GFP localization in living cells with computational modeling of stress-sensing signaling networks. We find that several signaling pathways, including Ras/protein kinase A, AMP-activated kinase, the high-osmolarity response mitogen-activated protein kinase pathway, and protein phosphatase 1, regulate activation of Msn2 in distinct ways in response to different stresses. Moreover, we find that bursts of nuclear localization elicit a more robust transcriptional response than does sustained nuclear localization. Using stochastic modeling, we reproduce in silico the responses of Msn2 to different stresses, and demonstrate that bursts of localization arise from noise in the signaling pathways amplified by the small number of Msn2 molecules in the cell. This noise imparts diverse behaviors to genetically identical cells, allowing cell populations to “hedge their bets” in responding to an uncertain future, and to balance growth and survival in an unpredictable environment