Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics

By Paola Picotti, Bernd Bodenmiller, Lukas N. Mueller, B. Domon, R. Aebersold. Cell, 2009

795 citations recorded by the source corpus.

Summary 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 which were 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.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/69c34e0042310aeb298c29abcb0fd4494a7d78a8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Spectroscopy

Citations in the corpus

The Skyline Ecosystem: Informatics for Quantitative Mass Spectrometry Proteomics (2017, methodology): “Computational estimation of optimal CE based on precursor m/z and a simple linear equation (Equation 1) is useful for both triple quadrupole (Picotti et al. 2010) and quadrupole time-of-flight instruments (Griffin et al. 1991; Prakash et al. 2009).”
Correlation of mRNA and protein in complex biological samples (2009, positive): “Selected reaction monitoring (SRM) on a hybrid triple quadru-pole/ion trap mass spectrometer recently allowed the identiﬁcation and quantiﬁcation of low-abundance proteins in a whole cell lysate of Saccharomyces cerevisiae [24].”
Decoding signalling networks by mass spectrometry-based proteomics (2010, methodology): “In yeast, this method identified 90% of targeted proteins, including a protein with an estimated 41 copies per cel”
Deep proteome and transcriptome mapping of a human cancer cell line (2011, background): “Large differences in expression levels of different metabolic enzymes have also been observed in recent targeted proteomics experiments in yeast (Picotti et al, 2009).”
Condition-Dependent Cell Volume and Concentration of Escherichia coli to Facilitate Data Conversion for Systems Biology Modeling (2011, background): “Current omics technologies resemble a great source for such data [5,6,7].”
Comparative Proteomic Analysis of Eleven Common Cell Lines Reveals Ubiquitous but Varying Expression of Most Proteins (2012, background): “These data can serve as a library of protein identifications and quantifications, as well as a resource for high-resolution MS/MS spectra that can be used for targeted proteomic analyses (5, 29, 30).”
Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* (2012, methodology): “In contrast, targeted proteomics is well suited for the reproducible detection and accurate quantification of sets of specific proteins in many samples as is the case in biomarker or systems biology studies (13–15).”