Skip to main content
Premium Trial:

Request an Annual Quote

Roche Researchers Develop Five-Plex SILAC Method for Quantifying Tyrosine Phosphorylation Dynamics


A team of Roche researchers has developed a five-plex SILAC method for quantifying the dynamics of tyrosine phosphorylation.

The method, which was detailed in a paper published last week in Molecular & Cellular Proteomics, expands SILAC labeling from the traditional three-plex to five-plex by using a mixture of light and heavy isotopically labeled lysines, arginines, and tyrosines to divide a sample into five distinct populations.

With the technique, the researchers are able to profile the dynamics of tyrosine phosporylation across five time points in a single experiment, instead of having to combine data from two separate three-plex experiments, as was previously customary, Manuel Tzouros, first author on the paper and lab head in mass spectrometry and proteomics at Roche Pharmaceuticals, told ProteoMonitor.

As key players in cell signaling, receptor tyrosine kinases have emerged as important drug targets and, as such, pharma researchers are often interested in studying phosphorylation events linked to these molecules, investigating, for instance, changes in protein phosphorylation levels in response to treatment with a particular drug.

While in some cases, a basic comparison of treated versus untreated samples may suffice, oftentimes, Tzouros noted, researchers are after a more dynamic view of signaling responses and are therefore interested in obtaining measurements at multiple time points.

Typically, he said, he and his colleagues are asked to make measurements at five time points within a given window, requiring them to multiplex five different samples. Prior to developing the five-plex SILAC methods, this level of multiplexing required two separate three-plex experiments – an approach that often led to challenges integrating the two different datasets on the back end.

"On paper [such an integration] looks quite easy," Tzouros said. Due, however, to the stochastic nature of mass spec analysis, each of the two experiments will result in somewhat different sets of identified peptides. "And it can be quite tricky to merge these two things together," he said.

For instance, he noted, if a phosphopeptide of interest is quantified in one SILAC experiment but not the other, researchers are left with a dataset in which there are measurements at only three time points for that analyte, rather than the desired five.

This is particularly a problem with lower abundance phosphopeptides, which are more likely to be passed over during a given mass spec run. Combining two datasets "works really well for high abundance proteins," Tzouros said. "That's no problem. It's when you go deeper and tackle the lower abundance ones that you start to have missing values and you don't get your five data points."

In the MCP paper, the researchers tested the five-plex SILAC in an analysis of a breast cancer cell line treated with the EGFR-targeted tyrosine kinase inhibitor erlotinib, marketed by Roche as Tarceva. Via mass spec analysis on a Thermo Fisher Scientific Orbitrap Velos instrument, they generated time profiles for 318 unique phosphopeptides belonging to 215 proteins.

Their findings correlated with the previous literature on the effect of erlotinib on EGFR signaling, Tzouros noted, validating the method.

While SILAC labeling is the standard technique Tzouros and his colleagues use for such quantitative time course experiments, he noted that recent advances have made some other quantitative proteomics methods potentially worth a look, as well.

For instance, he suggested that the NeuCode technique developed by University of Wisconsin-Madison researcher Joshua Coon "is really interesting and certainly something we would try to do here."

Presented in a paper published in Nature Methods in February, the NeuCode method uses differences in the nuclear binding energy of different isotopes to label amino acids and could enable multiplexing of up to 21 samples in a single experiment (PM 3/1/2013).

To apply the technique, however, Tzouros said his lab will need a higher-end mass spec instrument than they currently have access to. For their NeuCode work, the Coon lab used a Thermo Scientific Orbitrap Elite specially modified to offer 500,000 resolution, and the 21-plex estimate is based on use of an instrument with 1 million resolution.

Tzouros said that his lab has put in a request for funds to purchase one of Thermo Fisher's new Orbitrap Fusion instruments, which comes with 450,000 resolution standard, but it remains to be seen whether they will receive them.

Were they to purchase the Fusion, it could make isobaric labeling techniques like TMT and iTRAQ labeling attractive, Tzouros said. As opposed to SILAC and NeuCode, which rely on the incorporation of isotopes into particular amino acids, isobaric labeling tags digest peptides with reagents that fragment during MS2 to produce signals corresponding to the amount of peptide present in a sample.

However, because quantitation is done at the MS2 level, precursor interference can be a problem. Non-target precursors can fall into the fragmentation window for a given peptide, and the reporters released by these additional precursors can interfere with the reporters released by the target peptide, making quantitation unreliable in some cases.

Given this problem, Tzouros said, he has "not really been pushing to adopt isobaric labeling."

One potential way around this issue is to remove the precursor interference by doing another round of fragmentation and performing the quantitation at the MS3 level, instead of MS2. Typically, though, the added cycle time required for MS3 quantitation greatly reduces the number of peptides that can be measured, limiting the approach's usefulness.

Early analyses, however, suggest that the Fusion is fast enough to overcome this limitation (PM 6/14/2013).

"The fact that you can now do MS3 quantitation with isobaric labeling makes it look interesting for us again," Tzouros said.