Proteome-Wide Protein Expression Profiling Across Five Pancreatic Cell Lines

Abstract

Objectives: Mass spectrometry-based proteomics enables near-comprehensive protein expression profiling. We aimed to compare quantitatively the relative expression levels of thousands of proteins across 5 pancreatic cell lines.

Methods: Using tandem mass tags (TMT10-plex), we profiled the global proteomes of 5 cell lines in duplicate in a single multiplexed experiment. We selected cell lines commonly used in pancreatic research: CAPAN-1, HPAC, HPNE, PANC1, and PaSCs. In addition, we examined the effects of different proteases (Lys-C and Lys-C plus trypsin) on the dataset depth.

Results: We quantified over 8000 proteins across the 5 cell lines. Analysis of variance testing of cell lines within each data set resulted in over 1400 statistically significant differences in protein expression levels. Comparing the data sets, 10% more proteins and 30% more peptides were identified in the Lys-C/trypsin data set than in the Lys-C-only data set. The correlation coefficient of quantified proteins common between the data sets was greater than 0.85.

Conclusions: We illustrate protein level differences across pancreatic cell lines. In addition, we highlight the advantages of Lys-C/trypsin over Lys-C-only digests for discovery proteomics. These data sets provide a valuable resource of cell line-dependent peptide and protein differences for future targeted analyses, including those investigating on- or off-target drug effects across cell lines.

Figure 1. Experimental overview of the SPS-MS3 analysis

Five pancreatic cell lines were propagated in duplicate. Proteins were extracted and digested either with Lys-C and trypsin sequentially or Lys-C only (producing two separate datasets). The resulting peptides were labeled with TMT, pooled, and fractionated via basic pH reversed-phase high performance liquid chromatography (BPRP-HPLC) prior to MS3 analysis.

Figure 2. Comparing proteins and peptides between the Lys-C/trypsin and the Lys-C-only datasets

Venn diagrams illustrating the A) protein and B) peptide overlap for the Lys-C/trypsin and the Lys-C-only datasets.

Figure 3. Hierarchical clustering of relative protein expression levels across all ten samples

The heat maps and associated dendrograms for A) Lys-C/trypsin and B) Lys-C-only datasets. Across each row of the heat map, the relative protein expression levels are displayed, such that each row sums to 100%. The scale corresponds to the percentage of total signal across all channels.

Figure 4. K-means clustering and associated Gene Ontology categories

We performed K-means clustering on statistically significant proteins (Benjamini-Hochberg-corrected ANOVA p<0.05) and extracted 5 clusters, which represent proteins of relatively high abundance in each of the 5 cell lines: A) CAPAN-1, B) HPAC, C) HPNE, D) PANC1, and e) PaSC.

Figure 5. Peptide characteristics comparison between Lys-C/trypsin and Lys-C datasets

We compared the A) Peptide length, B) XCorr score, C) PPM (parts per million mass deviation) per peptide, D) precursor intensity, E) peptide mass, and F) charge state between the Lys-C/trypsin versus the Lys-C-only datasets.

Figure 6. Correlation plots across datasets

Correlation plots and corresponding correlation coefficients (r) were determined for the average relative abundance value of replicates for each protein in all five cell lines: A) CAPAN-1, B) HPAC, C) HPNE, D) PANC1, and E) PaSC.