Advances in quantitative high-throughput phosphoproteomics with sample multiplexing

Abstract

Eukaryotic protein phosphorylation modulates nearly every major biological process. Phosphorylation regulates protein activity, mediates cellular signal transduction, and manipulates cellular structure. Consequently, the dysregulation of kinase and phosphatase pathways has been linked to a multitude of diseases. Mass spectrometry-based proteomic techniques are increasingly used for the global interrogation of perturbations in phosphorylation-based cellular signaling. Strategies for studying phosphoproteomes require high-specificity enrichment, sensitive detection, and accurate localization of phosphorylation sites with advanced LC-MS/MS techniques and downstream informatics. Sample multiplexing with isobaric tags has also been integral to recent advancements in throughput and sensitivity for phosphoproteomic studies. Each of these facets of phosphoproteomics analysis present distinct challenges and thus opportunities for improvement and innovation. Here, we review current methodologies, explore persistent challenges, and discuss the outlook for isobaric tag-based quantitative phosphoproteomic analysis.

Keywords: automation; high-throughput; tandem-mass tag.

FIGURE 1

General analytical schemes for phosphoproteomics sample processing. Several workflows are commonly used for phosphoproteomics analysis. Some workflows decrease the number of individual sample processing steps by labeling earlier in the workflow, but this is at the expense of additional use of labeling reagents (as the non-phosphorylated majority of peptides are also labeled). In these workflows, peptides are labeled first then either (A) enriched and fractionated or (B) fractionated and enriched prior to LC-MS3. We note that in each workflow, multiple enrichment and fractionation steps can be performed. Other workflows aim to conserve label at the expense of increased susceptibility to variability. Such workflows incorporate individual sample enrichments (C and D) prior to labeling and may include (B) fractionation post-labeling

FIGURE 2

Streamlined TMT workflow for SPS-MS3-based phosphoproteomics analysis. (A) Samples are lysed in 8 M urea-containing buffer with protease and phosphatase inhibitors. Proteins are isolated via precipitation, and proteolytically digested with Lys-C and trypsin. (B) The samples are labeled with TMT or TMTpro reagents in the digestion buffer (200 mM EPPS, pH8.5) plus 30% acetonitrile. These TMT labels act as a chemical barcode to track the origin of each protein from each sample. (C) Phosphopeptides are enriched by one or several methods. The flow-through from the enrichment (which is isobaric-tag labeled) can be used to profile the whole proteome of the sample under investigation. (D) Samples may be analyzed using SPS/RTS-MS3. The MS2 stage can include either lower Energy HCD (CE = 30–32) or multistage activation (MSA)-CID for peptide fragmentation to be analyzed in the ion trap. The MS3 stage consists of HCD-based fragmentation for Orbitrap-based mass analysis

FIGURE 3

Acquisition and data analysis strategies specific to phosphoproteomics. (A) Low-resolution (ion-trap) and high-resolution (Orbitrap) spectra for the same phosphopeptide sequentially fragmented with CID, CID-MSA, or HCD activation. (B) Peptide spectrum match scores for the phosphopeptide spectra in A. (C) Generalized workflow for identifying and validating phosphorylation sites. (D) Illustration of the challenge of phosphopeptide localization. Often, a single ion can be responsible for determining site-localization and is thus dependent on the fragmentation scheme used for acquisition. (E) Estimation of site localization can be accomplished through the use of decoy amino acids (amino acids with no nucleophile capable of covalently binding the phosphate) during the search. This target-decoy strategy can be used to estimate and report the false localization rate. (F) Phosphosite stoichiometry can be an important metric for determining biological relevance of phosphorylation sites

FIGURE 4

Recent advances and future innovations in phosphoproteomics analysis. (A) Ion mobility, specifically high-field asymmetric waveform ion mobility spectrometry (FAIMS), adds another dimension of fractionation. Here, ions are separated in the gas phase based on differences in mobility in high and low electric fields as they transit between an inner and outer electrode. (B) Real-time database searching (RTS) improves quantitative accuracy of phosphopeptide quantification when performing SPS-MS3 analysis. Here, the peptide fragment ions to be used for quantification are pre-selected (not simply the most intense in a given spectrum, as in traditional SPS-MS3), thereby reducing interference from precursors which are not those of interest. (C) High-throughput sample processing allows for hundreds of samples to be handled in parallel. Rather than processing samples in individual tubes, we anticipate the use of bead-based proteins extractions (e.g., SP3) and plate-based enrichment in which up to 96 samples can be processed in parallel. (D) Automation using laboratory robotics can greatly eliminate many of the repetitive manual steps associated with high-throughput sample processing. With the use of magnetic modules and/or vacuum filtration, all sample processing steps maybe accomplished in 96- or 384-well plates with limited human intervention. Automation can greatly reduce human error, improve reproducibility, and better allow methods to be replicated across laboratories