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Grapes have been cultivated for wine production for millennia. Wine production involves a complex biochemical process where sugars in grapes must be converted into alcohol and other compounds by microbial fermentation, primarily by the yeast Saccharomyces cerevisiae. Commercially available S. cerevisiae strains are often used in winemaking, but indigenous (native) strains are gaining attention for their potential to contribute unique flavors. Recent advancements in high-throughput DNA sequencing have revolutionized our understanding of microbial communities during wine fermentation. Indeed, transcriptomic analysis of S. cerevisiae during wine fermentation has revealed a core gene expression program and provided insights into how this yeast adapts to fermentation conditions. Here, we assessed how the age of vines impacts the grape fungal microbiome and used transcriptomics to characterize microbial functions in grape must be fermented with commercial and native S. cerevisiae. We discovered that ~130-year-old Zinfandel vines harbor higher fungal loads on their grapes compared to 20-year-old Zinfandel vines, but fungal diversity is similar. Additionally, a comparison of inoculated and uninoculated fermentations showed distinct fungal dynamics, with uninoculated fermentations harboring the yeasts Metschnikowia and Pichia. Transcriptomic analysis revealed significant differences in gene expression between fermentations inoculated and not inoculated with a commercial S. cerevisiae strain. Genes related to metabolism, stress response, and cell adhesion were differentially expressed, indicating varied functionality of S. cerevisiae in these fermentations. These findings provide insights into S. cerevisiae function during fermentation and highlight the potential for indigenous yeast to contribute to wine diversity. IMPORTANCE: Understanding microbial functions during wine fermentation, particularly the role of Saccharomyces cerevisiae, is crucial for enhancing wine quality. While commercially available S. cerevisiae strains are commonly used, indigenous strains can offer unique flavors, potentially reflecting vineyard terroir. By leveraging high-throughput DNA sequencing and transcriptomic analysis, we explored the impact of vine age on the grape mycobiome and characterized microbial functions during grape fermentation. Our findings revealed that older vines harbor higher fungal loads, but fungal diversity remains similar across vine ages. Additionally, uninoculated fermentations exhibited diverse fungal dynamics, including the beneficial wine yeasts Metschnikowia and Pichia. Transcriptomic analysis uncovered significant differences in S. cerevisiae gene expression between inoculated and uninoculated fermentations, highlighting the potential of indigenous yeast to enhance wine diversity and inform winemaking practices.

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Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time-lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate-limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses.

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Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to "cross-protect" bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors.

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Gene expression is controlled primarily by interactions between transcription factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured well by thermodynamic models of regulation. These models, however, neglect regulatory crosstalk: the possibility that noncognate TFs could initiate transcription, with potentially disastrous effects for the cell. Here, we estimate the importance of crosstalk, suggest that its avoidance strongly constrains equilibrium models of TF binding, and propose an alternative nonequilibrium scheme that implements kinetic proofreading to suppress erroneous initiation. This proposal is consistent with the observed covalent modifications of the transcriptional apparatus and predicts increased noise in gene expression as a trade-off for improved specificity. Using information theory, we quantify this trade-off to find when optimal proofreading architectures are favored over their equilibrium counterparts. Such architectures exhibit significant super-Poisson noise at low expression in steady state.

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Based on the measurements of noise in gene expression performed during the past decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON and an OFF state. As experiments are becoming increasingly precise and the deviations from the two-state model start to be observable, we ask about the experimental signatures of complex multistate promoters, as well as the functional consequences of this additional complexity. In detail, we i), extend the calculations for noise in gene expression to promoters described by state transition diagrams with multiple states, ii), systematically compute the experimentally accessible noise characteristics for these complex promoters, and iii), use information theory to evaluate the channel capacities of complex promoter architectures and compare them with the baseline provided by the two-state model. We find that adding internal states to the promoter generically decreases channel capacity, except in certain cases, three of which (cooperativity, dual-role regulation, promoter cycling) we analyze in detail.

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