The biggest absolute quantification study ever! A tale of 100 QconCATs for nearly 2,000 proteins
Lawless C, Holman SW, Brownridge P, Lanthaler K, Harman VM, Watkins R, Hammond DE, Miller RL, Sims PF, Grant CM, Eyers CE, Beynon RJ, Hubbard SJ. (2016) Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring. Mol Cell Proteomics. 2016 Jan 10. pii: mcp.M115.054288
Defining intracellular protein concentration is critical in molecular systems
biology. Although strategies for determining relative protein changes are
available, defining robust absolute values in copies per cell has proven
significantly more challenging. Here we present a reference dataset quantifying
over 1800 S. cerevisiae proteins by direct means using protein-specific
stable-isotope labelled internal standards and selected reaction monitoring (SRM)
mass spectrometry, far exceeding any previous study. This was achieved by careful
design of over 100 QconCAT recombinant proteins as standards, defining 1167
proteins in terms of copies per cell and upper limits on a further 668, with
robust CVs routinely less than 20%. The SRM-derived proteome is compared with
existing quantitative data sets, highlighting the disparities between
methodologies. Coupled with a quantification of the transcriptome by RNA-seq
taken from the same cells, these data support revised estimates of several
fundamental molecular parameters: a total protein count of ~100 million
molecules-per-cell, a median of ~1000 proteins-per-transcript, and a linear model
of protein translation explaining 70% of the variance in translation rate. This
work contributes a 'gold-standard' reference yeast proteome (including 532 values
based on high quality, dual peptide quantification) that can be widely used in
systems models and for other comparative studies.
Defining intracellular protein concentration is critical in molecular systems
biology. Although strategies for determining relative protein changes are
available, defining robust absolute values in copies per cell has proven
significantly more challenging. Here we present a reference dataset quantifying
over 1800 S. cerevisiae proteins by direct means using protein-specific
stable-isotope labelled internal standards and selected reaction monitoring (SRM)
mass spectrometry, far exceeding any previous study. This was achieved by careful
design of over 100 QconCAT recombinant proteins as standards, defining 1167
proteins in terms of copies per cell and upper limits on a further 668, with
robust CVs routinely less than 20%. The SRM-derived proteome is compared with
existing quantitative data sets, highlighting the disparities between
methodologies. Coupled with a quantification of the transcriptome by RNA-seq
taken from the same cells, these data support revised estimates of several
fundamental molecular parameters: a total protein count of ~100 million
molecules-per-cell, a median of ~1000 proteins-per-transcript, and a linear model
of protein translation explaining 70% of the variance in translation rate. This
work contributes a 'gold-standard' reference yeast proteome (including 532 values
based on high quality, dual peptide quantification) that can be widely used in
systems models and for other comparative studies.