Abstract
A quantitative proteomics study employing SILAC technology was carried out to identify protein expression level differences between drug resistant and sensitive HeLa cells. Data analysis was performed with the aid of a newly developed SILAC dataset analysis program named SILACtor. Results are presented with an emphasis on the statistical considerations taken into account for study design and data interpretation.
METHODS:
HeLa cells (drug resistant and sensitive sublines) were grown on isotopically light or heavy DMEM media. Heavy and light cell lysates were mixed at 1:1 ratios. Protein samples were prepared in biological triplicate for both forward (sensitive heavy: resistant light) and reverse (sensitive light: resistant heavy) SILAC experiments. Proteins were reduced, alkylated and subsequently digested with trypsin. Peptide LC-MS/MS analysis was carried out in technical duplicate. Relative peptide quantification was performed using SILACtor which calculated average peptide ratios from technical replicate analyses. Protein ratios were obtained by averaging constituent peptide ratios. ANOVA was performed on resulting protein ratios using the statistical computing package R.
RESULTS:
A total of 856 proteins common to the drug resistant and sensitive cell lines were identified and quantified. ANOVA analysis revealed 374 proteins displaying significantly (p<0.01) altered expression levels between the cell lines. Native biological variation of protein levels was determined to fall with a +/−1.25 fold change at the 99% confidence level.
CONCLUSIONS:
Quantitative proteome analyses using SILAC followed by statistical analysis of the data resulted in the identification of several hundred proteins displaying altered expression levels between drug resistant and sensitive cells. Integration of this data with a network of known protein-protein interactions, and biological pathways allows for a biological systems view of proteome changes which occur with drug resistance. Several of these proteins have been previously implicated in resistance towards platinum-based and other drugs, while many represent new potential markers or therapeutic targets.