Deep proteome and transcriptome mapping of a human cancer cell line

Abstract

While the number and identity of proteins expressed in a single human cell type is currently unknown, this fundamental question can be addressed by advanced mass spectrometry (MS)-based proteomics. Online liquid chromatography coupled to high-resolution MS and MS/MS yielded 166 420 peptides with unique amino-acid sequence from HeLa cells. These peptides identified 10 255 different human proteins encoded by 9207 human genes, providing a lower limit on the proteome in this cancer cell line. Deep transcriptome sequencing revealed transcripts for nearly all detected proteins. We calculate copy numbers for the expressed proteins and show that the abundances of > 90% of them are within a factor 60 of the median protein expression level. Comparisons of the proteome and the transcriptome, and analysis of protein complex databases and GO categories, suggest that we achieved deep coverage of the functional transcriptome and the proteome of a single cell type.

Figure 1

Deep proteomic analysis of HeLa cells. (A). Proteome preparation workflow included protein separation by gel filtration followed by three FASP digestions per fraction, followed by strong anion exchange fractionation. Each fraction was analyzed by LC MS/MS on an LTQ-Orbitrap Velos mass spectrometer. (B) Summary of protein and peptide identifications obtained in the two experiments.

Figure 2

Comparison of proteomics and RNA-Seq data. (A) Distribution of FPKM data before filtration (green), filtered data with an FPKM threshold of 1 (blue) or based on the 95% confidence interval (ΔFPKM, black). FPKM values of the identified proteins are shown in red. (B) Distribution of abundance of proteins (iBAQ intensities) identified with FDR of 1%. (C) Venn diagram of the number of expressed genes on the mRNA level and on the protein level. (D) Proportions of proteins and transcripts annotated to various cellular compartments and molecular functions. (E) A density scatter plot of iBAQ intensities versus FPKM values. The color code indicates the percentage of points that are included in a region of a specific color.

Figure 3

Quantitative analysis of expressed genes. (A) Cumulative protein mass from the highest to the lowest abundance proteins. (B) Ranked protein abundances from the highest to the lowest. (C) Gene ontology analysis of cellular compartments annotations including the percent of the annotated genes in the genome, the percent of the identified proteins and the percent of the protein mass that is attributed to these annotations. (D) Same as (C) but for Gene Ontology biological process annotations. (E) Scatter plot of iBAQ intensities versus FPKM values with highlighting of structural proteins and proteins in basic cellular machineries. (F) Same as (E) but highlighting of metabolic and regulatory proteins.