Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast

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Abstract
A combination of high-resolution mass spectrometry, 'SILAC' labelling and computational proteomics has been used to achieve an important goal in proteomics: the complete identification and quantification of a proteome. The analysis reveals a proteome made up of 4,399 individual endogenous proteins, essentially the complete proteome in terms of proteins expressed in normally growing yeast cells. The levels of these proteins in haploid cells were compared to the levels in diploid cells. Among other differences, cell wall components are significantly down-regulated in diploids — in line with the fact that diploid cells are twice as large as haploid cells but do not have twice the surface area. Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins1,2. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable3. Here, using advances in computational proteomics, instrument performance and sample preparation strategies, we compare protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts. Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. Stable-isotope labelling by amino acids in cell culture (SILAC) quantification4,5 was very accurate across the proteome, as demonstrated by one-to-one ratios of most yeast proteins. Key members of the pheromone pathway were specific to haploid yeast but others were unaltered, suggesting an efficient control mechanism of the mating response. Several retrotransposon-associated proteins were specific to haploid yeast. Gene ontology analysis pinpointed a significant change for cell wall components in agreement with geometrical considerations: diploid cells have twice the volume but not twice the surface area of haploid cells. Transcriptome levels agreed poorly with proteome changes overall. However, after filtering out low confidence microarray measurements, messenger RNA changes and SILAC ratios correlated very well for pheromone pathway components. Systems-wide, precise quantification directly at the protein level opens up new perspectives in post-genomics and systems biology.