Proteome-wide quantitative multiplexed profiling of protein expression: carbon-source dependency in Saccharomyces cerevisiae

Abstract

The global proteomic alterations in the budding yeast Saccharomyces cerevisiae due to differences in carbon sources can be comprehensively examined using mass spectrometry-based multiplexing strategies. In this study, we investigate changes in the S. cerevisiae proteome resulting from cultures grown in minimal media using galactose, glucose, or raffinose as the carbon source. We used a tandem mass tag 9-plex strategy to determine alterations in relative protein abundance due to a particular carbon source, in triplicate, thereby permitting subsequent statistical analyses. We quantified more than 4700 proteins across all nine samples; 1003 proteins demonstrated statistically significant differences in abundance in at least one condition. The majority of altered proteins were classified as functioning in metabolic processes and as having cellular origins of plasma membrane and mitochondria. In contrast, proteins remaining relatively unchanged in abundance included those having nucleic acid-related processes, such as transcription and RNA processing. In addition, the comprehensiveness of the data set enabled the analysis of subsets of functionally related proteins, such as phosphatases, kinases, and transcription factors. As a resource, these data can be mined further in efforts to understand better the roles of carbon source fermentation in yeast metabolic pathways and the alterations observed therein, potentially for industrial applications, such as biofuel feedstock production.

FIGURE 1:

TMT9-plex analysis of S. cerevisiae grown on three carbon sources. The procedure was as follows: 1) Three starter cultures of minimal media with raffinose as the carbon source were each inoculated with a single colony. Cultures were grown overnight in raffinose media. Cultures were centrifuged, washed in deionized water, and diluted to an OD₆₀₀ of 0.1/ml in growth media containing galactose, glucose, or raffinose. At OD₆₀₀ of 0.6/ml, cultures were harvested, cells were lysed, and proteins were extracted via mechanical lysis and chloroform-methanol precipitation. 2) Proteins were digested with LysC and trypsin and labeled with TMT reagents. 3) The pooled samples were separated using BPRP chromatography. 4) Desalted peptides were subjected to HPLC and TMT-MS³–based mass spectrometry.

FIGURE 2:

Global protein expression analysis. (A) Heat map and dendrogram show the relative expression levels across the nine TMT channels and the clustering, respectively, of the 4765 quantified proteins. To the right of the heat map are three example proteins that show increased protein abundance in each of the three carbon sources investigated. The data were normalized to the average TMT relative abundance values from the glucose cultures. (B) Principal component analysis correlates well with the clustering of the replicates. (C) Histograms show the distribution of the fold changes between galactose and raffinose, glucose and raffinose, and galactose and glucose. Gal, galactose; Glu, glucose; Raf, raffinose; TMT RA, tandem mass tags relative abundance; *, p value < 0.01.

FIGURE 3:

k-Means clustering and associated KEGG pathways. k-Means clustering of protein subsets with statistically significant alterations in abundance from cultures grown in media containing (A) galactose, (B) glucose, and (C) raffinose. Listed on the right are the KEGG pathways that were represented by the proteins in the associated k-means cluster. Each trace represents the abundance profile of a single protein. Gal, galactose; Glu, glucose; Raf, raffinose.

FIGURE 4:

All proteins comprising the galactose catabolism pathway were quantified in our data set. The colored bars indicate the relative abundance of the protein across the nine channels, with each triplicate of bars representing protein abundance in cultures grown in media containing galactose, glucose, or raffinose.

FIGURE 5:

Comparing proteins from characterized and uncharacterized ORFs. (A) Bar chart comparing quantified and differentially expressed characterized and uncharacterized ORFs. (B) Proportion of differentially expressed uncharacterized ORFs (n = 63), which are up-regulated when grown on a particular sugar. (C) Examples of uncharacterized ORFs demonstrating statistically significant (p value < 0.01) differences in abundance with growth on different sugars within our data set. Error bars represent ± SD for triplicates. TMT RA, tandem mass tags relative abundance.