scholarly journals Saccharomyces cerevisiae and S. kudriavzevii Synthetic Wine Fermentation Performance Dissected by Predictive Modeling

2018 ◽  
Vol 9 ◽  
Author(s):  
David Henriques ◽  
Javier Alonso-del-Real ◽  
Amparo Querol ◽  
Eva Balsa-Canto
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Predictive Modeling ◽  
Wine Fermentation ◽  
Fermentation Performance

scholarly journals Effect of high Cu2+ stress on fermentation performance and copper biosorption of Saccharomyces cerevisiae during wine fermentation

2019 ◽  
Vol 39 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Xiangyu SUN ◽  
Lingling LIU ◽  
Tingting MA ◽  
Jing YU ◽  
Weidong HUANG ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Wine Fermentation ◽  
Fermentation Performance

scholarly journals Mapping global shifts in Saccharomyces cerevisiae gene expression across asynchronous time trajectories with diffusion maps

2021 ◽  
Author(s):  
Taylor Reiter ◽  
Rachel Montpetit ◽  
Ron Runnebaum ◽  
C. Titus Brown ◽  
Ben Montpetit
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Patterns ◽  
Pinot Noir ◽  
Wine Fermentation ◽  
Gene Expression Patterns ◽  
Expression Data ◽  
Site Specific ◽  
Time Series Gene Expression ◽  
Specific Factors

AbstractGrapes grown in a particular geographic region often produce wines with consistent characteristics, suggesting there are site-specific factors driving recurrent fermentation outcomes. However, our understanding of the relationship between site-specific factors, microbial metabolism, and wine fermentation outcomes are not well understood. Here, we used differences in Saccharomyces cerevisiae gene expression as a biosensor for differences among Pinot noir fermentations from 15 vineyard sites. We profiled time series gene expression patterns of primary fermentations, but fermentations proceeded at different rates, making analyzes of these data with conventional differential expression tools difficult. This led us to develop a novel approach that combines diffusion mapping with continuous differential expression analysis. Using this method, we identified vineyard specific deviations in gene expression, including changes in gene expression correlated with the activity of the non-Saccharomyces yeast Hanseniaspora uvarum, as well as with initial nitrogen concentrations in grape musts. These results highlight novel relationships between site-specific variables and Saccharomyces cerevisiae gene expression that are linked to repeated wine fermentation outcomes. In addition, we demonstrate that our analysis approach can extract biologically relevant gene expression patterns in other contexts (e.g., hypoxic response of Saccharomyces cerevisiae), indicating that this approach offers a general method for investigating asynchronous time series gene expression data.ImportanceWhile it is generally accepted that foods, in particular wine, possess sensory characteristics associated with or derived from their place of origin, we lack knowledge of the biotic and abiotic factors central to this phenomenon. We have used Saccharomyces cerevisiae gene expression as a biosensor to capture differences in fermentations of Pinot noir grapes from 15 vineyards across two vintages. We find that gene expression by non-Saccharomyces yeasts and initial nitrogen content in the grape must correlates with differences in gene expression among fermentations from these vintages. These findings highlight important relationships between site-specific variables and gene expression that can be used to understand, or possibly modify, wine fermentation outcomes. Our work also provides a novel analysis method for investigating asynchronous gene expression data sets that is able to reveal both global shifts and subtle differences in gene expression due to varied cell – environment interactions.

scholarly journals Saccharomyces cerevisiae gene expression during fermentation of Pinot noir wines at industrially relevant scale

2021 ◽  
Author(s):  
Taylor Reiter ◽  
Rachel Montpetit ◽  
Shelby Byer ◽  
Isadora Frias ◽  
Esmeralda Leon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Patterns ◽  
Pilot Scale ◽  
Pinot Noir ◽  
Wine Fermentation ◽  
Gene Expression Program ◽  
Gene Expression Patterns ◽  
Grape Must ◽  
Expression Program

Saccharomyces cerevisiae metabolism produces ethanol and other compounds during the fermentation of grape must into wine. Thousands of genes change expression over the course of a wine fermentation, allowing S. cerevisiae to adapt to and dominate the fermentation environment. Investigations into these gene expression patterns have previously revealed genes that underlie cellular adaptation to the grape must and wine environment involving metabolic specialization and ethanol tolerance. However, the majority of studies detailing gene expression patterns have occurred in controlled environments that may not recapitulate the biological and chemical complexity of fermentations performed at production scale. Here, an analysis of the S. cerevisiae RC212 gene expression program is presented, drawing from 40 pilot-scale fermentations (150 liters) using Pinot noir grapes from 10 California vineyards across two vintages. A core gene expression program was observed across all fermentations irrespective of vintage similar to that of laboratory fermentations, in addition to novel gene expression patterns likely related to the presence of non-Saccharomyces microorganisms and oxygen availability during fermentation. These gene expression patterns, both common and diverse, provide insight into Saccharomyces cerevisiae biology critical to fermentation outcomes under industry-relevant conditions. Importance This study characterized Saccharomyces cerevisiae RC212 gene expression during Pinot noir fermentation at pilot scale (150 liters) using industry-relevant conditions. The reported gene expression patterns of RC212 are generally similar to that observed in laboratory fermentation conditions, but also contain gene expression signatures related to yeast-environment interactions found in a production setting (e.g., presence of non-Saccharomyces microorganisms). Key genes and pathways highlighted by this work remain under-characterized, raising the need for further research to understand the roles of these genes and their impact on industrial wine fermentation outcomes.

scholarly journals Investigation of the dominance behavior of Saccharomyces cerevisiae strains during wine fermentation

2013 ◽  
Vol 165 (2) ◽  
pp. 156-162 ◽  
Author(s):  
Benedetta Perrone ◽  
Simone Giacosa ◽  
Luca Rolle ◽  
Luca Cocolin ◽  
Kalliopi Rantsiou
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Wine Fermentation ◽  
Dominance Behavior

scholarly journals Urea Hydrogen Peroxide Reduces the Numbers of Lactobacilli, Nourishes Yeast, and Leaves No Residues in the Ethanol Fermentation

2000 ◽  
Vol 66 (10) ◽  
pp. 4187-4192 ◽  
Author(s):  
N. V. Narendranath ◽  
K. C. Thomas ◽  
W. M. Ingledew
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Hydrogen Peroxide ◽  
Particulate Matter ◽  
Normal Gravity ◽  
Fermentation Performance ◽  
Urea Hydrogen Peroxide ◽  
Nadh Peroxidase ◽  
Resistant Mutants ◽  
Assimilable Nitrogen ◽  
Bactericidal Agent

ABSTRACT Urea hydrogen peroxide (UHP) at a concentration of 30 to 32 mmol/liter reduced the numbers of five Lactobacillus spp. (Lactobacillus plantarum, L. paracasei,Lactobacillus sp. strain 3, L. rhamnosus, andL. fermentum) from ∼107 to ∼102CFU/ml in a 2-h preincubation at 30°C of normal-gravity wheat mash at ∼21 g of dissolved solids per ml containing normal levels of suspended grain particles. Fermentation was completed 36 h after inoculation of Saccharomyces cerevisiae in the presence of UHP, even when wheat mash was deliberately contaminated (infected) withL. paracasei at ∼107 CFU/ml. There were no significant differences in the maximum ethanol produced between treatments when urea hydrogen peroxide was used to kill the bacteria and controls (in which no bacteria were added). However, the presence of L. paracasei at ∼107 CFU/ml without added agent resulted in a 5.84% reduction in the maximum ethanol produced compared to the control. The bactericidal activity of UHP is greatly affected by the presence of particulate matter. In fact, only 2 mmol of urea hydrogen peroxide per liter was required for disinfection when mashes had little or no particulate matter present. No significant differences were observed in the decomposition of hydrogen peroxide in normal-gravity wheat mash at 30°C whether the bactericidal agent was added as H2O2 or as urea hydrogen peroxide. NADH peroxidase activity (involved in degrading H2O2) increased significantly (P = 0.05) in the presence of 0.75 mM hydrogen peroxide (sublethal level) in all five strains of lactobacilli tested but did not persist in cells regrown in the absence of H2O2. H2O2-resistant mutants were not expected or found when lethal levels of H2O2 or UHP were used. Contaminating lactobacilli can be effectively managed by UHP, a compound which when used at ca. 30 mmol/liter happens to provide near-optimum levels of assimilable nitrogen and oxygen that aid in vigorous fermentation performance by yeast.

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