Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics - PubMed (original) (raw)
Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics
Paola Picotti et al. Cell. 2009.
Abstract
The rise of systems biology implied a growing demand for highly sensitive techniques for the fast and consistent detection and quantification of target sets of proteins across multiple samples. This is only partly achieved by classical mass spectrometry or affinity-based methods. We applied a targeted proteomics approach based on selected reaction monitoring (SRM) to detect and quantify proteins expressed to a concentration below 50 copies/cell in total S. cerevisiae digests. The detection range can be extended to single-digit copies/cell and to proteins undetected by classical methods. We illustrate the power of the technique by the consistent and fast measurement of a network of proteins spanning the entire abundance range over a growth time course of S. cerevisiae transiting through a series of metabolic phases. We therefore demonstrate the potential of SRM-based proteomics to provide assays for the measurement of any set of proteins of interest in yeast at high-throughput and quantitative accuracy.
Figures
Figure 1. Cellular concentrations of the set of measured proteins
Protein abundances are derived from Ghaemmaghami et al. (2003). Proteins detected by SRM assays are sorted by abundance to show the even distribution across the whole range of concentration (blue solid circles). Proteins for which the absolute abundance was measured using isotopically-labelled standards are indicated on top of the graph (open circles).
Figure 2. Analysis of the SRM signal gain obtained by peptide fractionation
Peptide fractionation was achieved by off-gel electrofocusing of a total yeast digest in 24 wells, using 3–10 pI strips. For each peptide the signal gain compared to the unfractionated peptide mixture resulting from the highest SRM transition and the highest-concentration fraction is reported using a logarithmic scale (left axis). Vertical bars show the mean signal gain in each fraction. The peptide pI associated to each fraction is also reported (right axis) as mean +/−standard deviation, as derived from a large-scale shotgun proteomic experiments in which more than 55,000 yeast peptides were identified across the 24 OGE fractions (data not shown).
Figure 3. SRM analysis of a biological protein network
(A) Schematic representation of a core protein network (glycolysis/gluconeogenesis/TCA cycle/glyoxylate cycle) in the central carbon metabolism of S. cerevisiae. Proteins are colored according to their absolute abundances as measured by Ghaemmaghami et al. (2003). (B) Distribution of the cellular abundances of the 45 proteins composing the network. For each protein a SRM assay was developed and applied to detect the protein in an unfractionated yeast digest, using scheduled SRM, in a single MS analysis. (C) LC-SRM chromatogram comprising the whole set of SRM assays for proteins in the network. Each peak represents an SRM assay that detects a tryptic peptide of one of the target proteins in the total yeast digest.
Figure 4. Time-course analysis of the central carbon metabolism protein network along the dynamic growth profile of S. cerevisiae in a glucose-rich medium
(A) Growth profile , as followed by monitoring the optical density at 600 nm (OD600) of the culture, and the extracellular glucose and ethanol concentrations. (B) Different growth phases occurring during S. cerevisiae growth in a glucose-rich medium. The growth profile is plotted using a log10 scale, to better highlight the transition regions. Protein sampling time-points are represented as open squares in panels A and B (T1, 6.5 hrs; T2, 7.6 hrs; T3, 8.7 hrs; T4, 9.6 hrs; T5, 10.6 hrs; T6, 11.7 hrs; T7, 19.8 hrs; T8, 25.0 hrs; T9, 33.7 hrs; T10, 43.2 hrs). (C) Measured abundance profiles for all the proteins in the protein network under study, along the growth curve. Mean abundance changes out of three biological replicates with respect to time point 1 (6.5 hrs) are plotted using a log10 scale. Profiles of the three clusters deriving from the clustering analysis are shown in color. A schematic representation of the system under study highlights proteins belonging to each cluster in the corresponding color. (D–F) Abundance profiles for each protein belonging to cluster 1 (D), 2 (E) and 3 (F). Abundance changes relative to time point 1 are represented as mean (three biological replicates) +/− standard deviation.
Figure 5. Comparison between targeted proteomics and gene expression data
(A) Correlation between a protein and the corresponding transcript abundance fold change. Each point represents a given protein at a given time point. Four regions are highlighted: 1) protein and transcript abundance are both increasing; 2) both decreasing; 3) protein abundance increases while transcript abundance decreases, and 4) protein abundance decreases and transcript abundance increases. (B–H) Overlay of a protein and the corresponding transcript abundance profiles. Representative examples are selected out of the 4 regions highlighted in panel A. Protein abundance changes are reported as mean (three biological replicates) +/−standard deviation. Transcript abundance changes are from DeRisi et al, 1997, after the realignment described in the Experimental Procedures.
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