Mass accuracy is a key parameter of mass spectrometric performance. TOF instruments can reach low parts per million, and FT-ICR instruments are capable of even greater accuracy provided ion numbers are well controlled. Here we demonstrate sub-ppm mass accuracy on a linear ion trap coupled via a radio frequency-only storage trap (C-trap) to the orbitrap mass spectrometer (LTQ Orbitrap). Prior to acquisition of a spectrum, a background ion originating from ambient air is first transferred to the C-trap. Ions forming the MS or MS n spectrum are then added to this species, and all ions are injected into the orbitrap for analysis. Real time recalibration on the "lock mass" by corrections of mass shift removes mass error associated with calibration of the mass scale. The remaining mass error is mainly due to imperfect peaks caused by weak signals and is addressed by averaging the mass measurement over the LC peak, weighted by signal intensity. For peptide database searches in proteomics, we introduce a variable mass tolerance and achieve average absolute mass deviations of 0.48 ppm (standard deviation 0.38 ppm) and maximal deviations of less than 2 ppm. For tandem mass spectra we demonstrate similarly high mass accuracy and discuss its impact on database searching. High and routine mass accuracy in a compact instrument will dramatically improve certainty of peptide and small molecule identification.

Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable. 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) quantification 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.

Protein phosphorylation is a fundamental regulatory mechanism that affects many cell signaling processes. Using high-accuracy MS and stable isotope labeling in cell culture-labeling, we provide a global view of the Saccharomyces cerevisiae phosphoproteome, containing 3620 phosphorylation sites mapped to 1118 proteins, representatively covering the yeast kinome and a multitude of transcription factors. We show that a single false discovery rate for all peptide identifications significantly overestimates occurrence of rare modifications, such as tyrosine phosphorylation in yeast. The identified phosphorylation sites are predominantly located on irregularly structured and accessible protein regions. We found high evolutionary conservation of phosphorylated proteins and a large overlap of significantly over-represented motifs with the human phosphoproteome. Nevertheless, phosphorylation events at the site level were not highly conserved between yeast and higher eukaryotes, which points to metazoan-specific kinase and substrate families. We constructed a yeast-specific phosphorylation sites predictor on the basis of a support vector machine, which - together with the yeast phosphorylation data - is integrated into the PHOSIDA database (www.phosida.com).

Complex protein mixture analysis

A mass spectrometry analysis of the yeast proteome shows that complex mixture analysis is not limited by sensitivity but by a combination of dynamic range and by effective sequencing speed.