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

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.

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

Applied and Environmental Microbiology ◽

10.1128/aem.00036-21 ◽

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.

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

10.1101/2021.01.11.426308 ◽

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

AbstractDuring a wine fermentation, Saccharomyces cerevisiae transforms grape must through metabolic activities that generate ethanol and other compounds. Thousands of genes change expression over the course of a wine fermentation to allow 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 vast majority of studies detailing gene expression patterns have occurred in controlled environments that do not recapitulate the biological and chemical complexity of fermentations performed at production scale. Here, we present an analysis of the S. cerevisiae RC212 gene expression program across 40 pilot-scale fermentations (150 liters) using Pinot noir grapes from 10 California vineyards across two vintages. We observe a core gene expression program 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 at industry-relevant scales.ImportanceThis study characterized Saccharomyces cerevisiae RC212 gene expression during Pinot noir fermentation at pilot scale (150 liters) using production-relevant conditions. The reported gene expression patterns of RC212 is generally similar to that observed in laboratory fermentation conditions, but also contains 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.

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Charting Shifts in Saccharomyces cerevisiae Gene Expression across Asynchronous Time Trajectories with Diffusion Maps

mBio ◽

10.1128/mbio.02345-21 ◽

2021 ◽

Author(s):

Taylor Reiter ◽

Rachel Montpetit ◽

Ron Runnebaum ◽

C. Titus Brown ◽

Ben Montpetit

Keyword(s):

Gene Expression ◽

Saccharomyces Cerevisiae ◽

Gene Expression Data ◽

Pinot Noir ◽

Expression Data ◽

Analysis Method ◽

Diffusion Maps ◽

Content Type

In this work, Saccharomyces cerevisiae gene expression was used as a biosensor to capture differences across and between fermentations of Pinot noir grapes from 15 unique sites representing eight American Viticultural Areas. This required development of a novel analysis method, DMap-DE, for investigation of asynchronous gene expression data.

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MODA: MOdule Differential Analysis for weighted gene co-expression network

10.1101/053496 ◽

2016 ◽

Cited By ~ 4

Author(s):

Dong Li ◽

James B. Brown ◽

Luisa Orsini ◽

Zhisong Pan ◽

Guyu Hu ◽

...

Keyword(s):

Gene Expression ◽

Expression Patterns ◽

Synthetic Data ◽

R Package ◽

Gene Expression Patterns ◽

Specific Gene ◽

Biological Processes ◽

Expression Data ◽

Differential Analysis ◽

Transcriptomic Data

1SummaryGene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different conditions. We have implemented an R package called MODA (Module Differential Analysis) for gene co-expression network differential analysis. Based on transcriptomic data, MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes. The usefulness of the method is also demonstrated by synthetic data as well as Daphnia magna gene expression data under different environmental stresses.

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Mining Frequent and Associated Gene Expression Patterns from Spatial Gene Expression Data: A Proposed Approach

Communications in Computer and Information Science - Contemporary Computing ◽

10.1007/978-3-642-14834-7_12 ◽

2010 ◽

pp. 119-130

Author(s):

M. Anandhavalli ◽

M. K. Ghose ◽

K. Gauthaman

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Expression Data

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Spore germination in Saccharomyces cerevisiae: global gene expression patterns and cell cycle landmarks

Genome Biology ◽

10.1186/gb-2007-8-11-r241 ◽

2007 ◽

Vol 8 (11) ◽

pp. R241 ◽

Cited By ~ 34

Author(s):

Daphna Joseph-Strauss ◽

Drora Zenvirth ◽

Giora Simchen ◽

Naama Barkai

Keyword(s):

Gene Expression ◽

Saccharomyces Cerevisiae ◽

Cell Cycle ◽

Spore Germination ◽

Expression Patterns ◽

Global Gene Expression ◽

Gene Expression Patterns

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An Integrated Time Series Gene Expression Data Analysis Pipeline with a Fuzzy Clustering method to assess Expression Patterns

2007 IEEE International Fuzzy Systems Conference ◽

10.1109/fuzzy.2007.4295564 ◽

2007 ◽

Author(s):

P. Yankilevich ◽

P. R. Barrero ◽

I. Zwir

Keyword(s):

Gene Expression ◽

Expression Patterns ◽

Expression Data ◽

Clustering Method ◽

Gene Expression Data Analysis ◽

Analysis Pipeline ◽

Time Series Gene Expression ◽

Fuzzy Clustering Method ◽

Integrated Time Series ◽

Data Analysis Pipeline

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Different Gene Expression Patterns of Hexose Transporter Genes Modulate Fermentation Performance of Four Saccharomyces cerevisiae Strains

Fermentation ◽

10.3390/fermentation7030164 ◽

2021 ◽

Vol 7 (3) ◽

pp. 164

Author(s):

Chiara Nadai ◽

Giulia Crosato ◽

Alessio Giacomini ◽

Viviana Corich

Keyword(s):

Gene Expression ◽

Saccharomyces Cerevisiae ◽

Fermentation Process ◽

Expression Patterns ◽

Gene Expression Pattern ◽

Gene Expression Patterns ◽

Specific Gene ◽

Facilitated Diffusion ◽

Fermentation Performance ◽

Expression Levels

In Saccharomyces cerevisiae, the fermentation rate and the ability to complete the sugar transformation process depend on the glucose and fructose transporter set-up. Hexose transport mainly occurs via facilitated diffusion carriers and these are encoded by the HXT gene family and GAL2. In addition, FSY1, coding a fructose/H+ symporter, was identified in some wine strains. This little-known transporter could be relevant in the last part of the fermentation process when fructose is the most abundant sugar. In this work, we investigated the gene expression of the hexose transporters during late fermentation phase, by means of qPCR. Four S. cerevisiae strains (P301.9, R31.3, R008, isolated from vineyard, and the commercial EC1118) were considered and the transporter gene expression levels were determined to evaluate how the strain gene expression pattern modulated the late fermentation process. The very low global gene expression and the poor fermentation performance of R008 suggested that the overall expression level is a determinant to obtain the total sugar consumption. Each strain showed a specific gene expression profile that was strongly variable. This led to rethinking the importance of the HXT3 gene that was previously considered to play a major role in sugar transport. In vineyard strains, other transporter genes, such as HXT6/7, HXT8, and FSY1, showed higher expression levels, and the resulting gene expression patterns properly supported the late fermentation process.

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