Systematic Profiling of Ale Yeast Protein Dynamics across Fermentation and Repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is amongst the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout two fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.


22
between Batches 1 and 15 depicted using volcano plots with log2 fold change (x-axis) and Benjamini-Hochberg adjusted p-value (y-axis).C) Dotplots with the top enriched GO terms for the matched starting time point across Batch 1 and Batch 15.D) Dotplots with top enriched GO terms across Batch 15 3h and Batch 1 6h time points.GO term analysis was performed on the biological function terms with a 5% FDR threshold and filtering terms to an adjusted p-value (Benjamini-Hochberg correction) of <0.05.Sizes of dots correspond to the ratio genes detected to the total genes annotated for a particular GO term.Table 1.List of deletions and affected genes with chromosomal coordinates to the nearest 100bp.generation of precursor metabolites and energy lysine biosynthetic process lysine biosynthetic process via aminoadipic acid lysine metabolic process mitochondrial ATP synthesis coupled electron transport organic acid biosynthetic process organic acid metabolic process oxidative phosphorylation oxoacid metabolic process respiratory electron transport chain small molecule metabolic process alcohol biosynthetic process alcohol metabolic process cellular alcohol biosynthetic process cellular alcohol metabolic process cellular lipid biosynthetic process cellular lipid metabolic process ergosterol biosynthetic process ergosterol metabolic process lipid biosynthetic process lipid metabolic process organic hydroxy compound biosynthetic process organic hydroxy compound metabolic process phytosteroid biosynthetic process phytosteroid metabolic process secondary alcohol biosynthetic process secondary alcohol metabolic process steroid biosynthetic process steroid metabolic process sterol biosynthetic process

Figure 4 .
Cataloging abundance changes in metabolic pathways.A) Pairwise Pearson correlation between proteins involved in the glycolysis and tricarboxylic acid (TCA) cycle pathways.B) LFQ protein abundance (y-axis) as a function of time (x-axis) for enzymes involved in pyruvate metabolism.Time points colored by batches 1 (red) and 15 (blue) C) Steps in pyruvate metabolism in yeast.D) Changes in fatty acid oxidation and E) very long chain fatty acid synthesis enzyme abundances, over both batches and during final conditioning, as log2 of row mean normalized abundance.Supplementary Figure 5. Subcellular proteome analysis.A) Barplots representing the numbers of yeast proteins (x-axis) annotated by subcellular/organellar location (y-axis).Data curated from the Yeast GFP Fusion Localization database 40 and B) Fraction of proteins in each subcellular/organellar location detected in at least one time point across the brewing time course.C) Densities of all Pearson correlation values calculated across all pairs of proteins across each annotated subcellular location and organelles.D) Histogram of the distribution of yeast protein complex sizes.Data obtained from Yeast complexome.E) Density plot showing the fraction of yeast protein complexes detected in the fermentation time course.Protein complex data curated from the EBI Complexome database 41 .23 Supplementary Tables acid biosynthetic process alpha−amino acid metabolic process anion transmembrane transport aspartate family amino acid biosynthetic process aspartate family amino acid metabolic process ATP synthesis coupled electron transport carboxylic acid biosynthetic process carboxylic acid metabolic process cellular amino acid biosynthetic process cellular amino acid metabolic process cellular respiration electron transport chain energy derivation by oxidation of organic compounds alpha−amino acid biosynthetic process alpha−amino acid metabolic process aspartate family amino acid biosynthetic process aspartate family amino acid metabolic process ATP synthesis coupled electron transport carboxylic acid biosynthetic process carboxylic acid

Table 2 .
List of time points sampled with mass spectrometry.

Table 3 .
Sum of LFQ values for each detected protein matched with sequencing coverage of corresponding gene.

Table 4 .
Correlation between detected protein levels and sequencing coverage.

Table 5 .
Protein detection statistics by time point.

Table 6 .
Log2 fold change normalized to the mean abundance values for all detected proteins across both Batch 1 and Batch 15 time points.

Table 7 .
Clustering of proteins that changed at least two-fold over the mean in any time point.

Table 8 .
List of GO terms enriched in each cluster.

Table 9 .
Summary of differentially expressed proteins across time points.

Table 10 . List of GO terms (biological process) for differentially expressed proteins across select time points.Table 11 .
Top 100 metabolic pathways from SGD Yeast Pathways.

Table 12 .
Number of proteins identified from different subcellular locations.

Table 13 .
Yeast protein complex detection statistics across time course dataset.