A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards

Abstract

Absolute protein quantification using mass spectrometry (MS)-based proteomics delivers protein concentrations or copy numbers per cell. Existing methodologies typically require a combination of isotope-labeled spike-in references, cell counting, and protein concentration measurements. Here we present a novel method that delivers similar quantitative results directly from deep eukaryotic proteome datasets without any additional experimental steps. We show that the MS signal of histones can be used as a “proteomic ruler” because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells. As a result, our proteomic ruler approach adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell. We compare our protein quantifications with values derived via the use of stable isotope labeling by amino acids in cell culture and protein epitope signature tags in a method that combines spike-in protein fragment standards with precise isotope label quantification. The proteomic ruler approach yields quantitative readouts that are in remarkably good agreement with results from the precision method. We attribute this surprising result to the fact that the proteomic ruler approach omits error-prone steps such as cell counting or protein concentration measurements. The proteomic ruler approach is readily applicable to any deep eukaryotic proteome dataset—even in retrospective analysis—and we demonstrate its usefulness with a series of mouse organ proteomes.

A Liquid-to-Solid Phase Transition of the ALS Protein FUS Accelerated by Disease Mutation

“…Next, we used mass spectrometry to determine the physiological concentration of FUS in HeLa cells ( Figure S1A). We found that the concentration is around 2 mM, with a technical precision between replicates of 2.24 ± 0.7 mM and an estimated accuracy of 2-to 3-fold (Wi sniewski et al, 2014). This makes FUS one of the top 5% of proteins in terms of protein abundance.…”

Cell-Type-Resolved Quantitative Proteomics of Murine Liver

“…For the nearly 8,311 RNA-protein matches (RPKM > 1.0), we obtained a correlation of 0.60 between RNASeq and our iBAQ values (Pearson correlation coefficient, R = 0.60; Figure 2D). The correlation was 0.52 when we calculated protein-RNA copy numbers from the same data sets (R = 0.52; Figure 2E) on the basis of individual protein intensities (Wi sniewski et al, 2014). These transcriptome-proteome correlations were stronger than the correlations of about 0.43 reported for the liver of two rat strains (Low et al, 2013).…”

Histone Interaction Landscapes Visualized by Crosslinking Mass Spectrometry in Intact Cell Nuclei

“…The workflow described above was used also for the analysis of the in vitro crosslinked samples using databases generated from the protein sequences obtained from the bottom-up analysis of the recombinant protein samples. The bottom-up proteomics files to calculate the proteins copy numbers were analyzed with MaxQuant (version 1.5.5.0)(40) using the database described above and with Perseus (version 1.5.5.0) using the proteomic ruler plugin (41). The standard searching parameters were used: protease Trypsin, 2 allowed missed cleavages, precursor mass tolerance of 4.5 ppm, fragment mass tolerance of 20 ppm, and carbamidomethyl on C was set as static modification, oxidation on M, acetylation on K, methylation on K and R and N-terminus acetylation were set as variable modifications.…”

“…As anticipated, the fraction of identifiable nuclear crosslinks increased to 85% in the insoluble fraction. To uncover the depth our crosslinking methodology is reaching, we calculated the protein copy numbers from the nuclear proteome from the combined fractions using the proteomic ruler approach (41), and transferred the copy numbers from the second set to the detected crosslinks. As expected, the crosslinked dataset does not completely reach the full depth of the nuclear proteome, but excitingly is delving already close to halfway in the dynamic range of the proteins copy number down to ~1.5e4 proteins per cell (supplemental Fig S3B).…”