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Automated, reproducible, titania-based phosphopeptide enrichment strategy for label-free quantitative phosphoproteomics.

ABSTRACT: An automated phosphopeptide enrichment strategy is described using titanium dioxide (TiO2)-packed, fused silica capillaries for use with liquid chromatography (LC)-mass spectrometry (MS)/MS-based, label-free proteomics workflows. To correlate an optimum peptide:TiO2 loading ratio between different particle types, the ratio of phenyl phosphate-binding capacities was used. The optimum loading for the column was then verified through replicate enrichments of a range of quantities of digested rat brain tissue cell lysate. Fractions were taken during sample loading, multiple wash steps, and the elution steps and analyzed by LC-MS/MS to gauge the efficiency and reproducibility of the enrichment. Greater than 96% of the total phosphopeptides were detected in the elution fractions, indicating efficient trapping of the phosphopeptides on the first pass of enrichment. The quantitative reproducibility of the automated setup was also improved greatly with phosphopeptide intensities from replicate enrichments exhibiting a median coefficient of variation (CV) of 5.8%, and 80% of the identified phosphopeptides had CVs below 11.1%, while maintaining >85% specificity. By providing this high degree of analytical reproducibility, this method allows for label-free phosphoproteomics over large sample sets with complex experimental designs (multiple biological conditions, multiple biological replicates, multiple time-points, etc.), including large-scale clinical cohorts.

SUBMITTER: Richardson BM

PROVIDER: S-EPMC3533261 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports.

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Automated, reproducible, titania-based phosphopeptide enrichment strategy for label-free quantitative phosphoproteomics.

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