Currently, unbiased protein identification is mostly performed by directly coupling reversed-phase liquid chromatography (RPLC) via electrospray ionization to a mass spectrometer. In contrast to the innovations in mass spectrometric instrumentation, cutting-edge technology in RPLC has generally not been well adopted. Here, we describe the effects of increased peak capacities on the number of identified proteins and peptides in complex mixtures utilizing collision-induced dissociation on an LTQ-Orbitrap Velos, providing a rationale for using advanced RPLC technology in LC-MS/MS. Using two different column lengths and gradient times between 1 and 10 h, we found a linear relation between the obtained peak capacities and the number of identified peptides. We identified on average 2516 proteins in the tryptic digest of 1 μg of HeLa lysate using an 8 h gradient on a 50 cm column packed with 2 μm C18 reversed-phase chromatographic material.

The majority of proteome-wide studies rely on the high separation power of two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS), often combined with protein prefractionation. Alternative approaches would be advantageous in order to reduce the analysis time and the amount of sample required. On the basis of the recent advances in chromatographic and mass spectrometric instrumentation, thousands of proteins can be identified in a single-run LC-MS/MS experiment using ultralong gradients. Consequently, the analysis of simple proteomes or clinical samples in adequate depth becomes possible by performing single-run LC-MS/MS experiments. Here we present a generally applicable protocol for protein analysis from unseparated whole-cell extracts and discuss its potential and limitations. Demonstrating the practical applicability of the method, we identified 2,761 proteins from a HeLa cell lysate, requiring around 10 h of nanoLC-MS/MS measurement time.

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BackgroundGenome‐wide transcriptome analyses have given systems‐level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post‐transcriptional gene regulation and its effects on protein‐complex stoichiometry are lagging behind.ResultsHere, we employ deep sequencing and the isobaric tag for relative and absolute quantification (iTRAQ) technology to determine transcript and protein expression changes of a Drosophila brain tumor model at near genome‐wide resolution. In total, we quantify more than 6,200 tissue‐specific proteins, corresponding to about 70% of all transcribed protein‐coding genes. Using our integrated data set, we demonstrate that post‐transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein‐protein interaction data and show that post‐transcriptional mechanisms significantly enhance co‐regulation of protein‐complex subunits beyond transcriptional co‐regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co‐regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analyzing the co‐regulation of potential subunits.ConclusionsOur comprehensive transcriptome and proteome data provide a valuable resource for quantitative biology and offer novel insights into understanding post‐transcriptional gene regulation in a tumor model.