Did you just hear that the lab down the hall spent $4M in Hi-Seq reagents last year...the same year you got turned down for a $500k instrument upgrade you desperately needed for targeted throughput? Do you think maybe you'd be taken more seriously if you spent a ton more on reagents this year? Well -- do I ever have a solution for you! SILAC label your cells AND TMT label them like they did in this new study!
I'm being facetious, of course. People don't love spending money on RNA-Seq hand over fist because it's expensive. They throw money at this technology because it is a very important buzz word to have in any study and because the signal to noise ratio is so low you only have to cross your eyes just a little bit and you'll be able to get whatever you want out of it.
(Just in case you don't know me, I should clarify I'm kidding. I do think the ratio of institutional spending for transcriptomics for proteomics is woefully miscalibrated, but I'm obviously biased).
Back to the seriousness of this great study. Why would you want to SILAC and TMT lable? Besides the fact that you could simulate 33-plexing your data? Pulse chase SILAC allows us to see what is going on in a cell at different time points because the heavy labeled amino acids can be added to the media and the proteins will uptake the labels at different rates. The ratio between heavy to light peptides can indicate protein turnover and other things.
Pulsed SILAC is great for things that turnover on the day-to-hour range and many cellular systems work on that kind of time scale. However, many protein systems such as proteoform regulation (explored in this great study) happen on a much much faster scale. By lysing the cells and labeling at shorter time points these authors get higher resolution (on a time scale) measurements on the protein dynamics.
While I'm very glad I'm not the person who had to process this data for the first time, the method looks surprisingly straight-forward. In case you're also a ProteomeXchange lurker and you've seen some interesting data files that you're eagerly awaiting a publication on, I'm sad to report the instrument method is also pretty typical. The separation is normal reversed phase using formic acid and DMSO. SPS MS3 on the tribrid is used to keep the quantification quality top notch and with 24 SAX fractions the complexity in each fraction -- despite all the labels -- is low enough for the time hit to be worth it.
What do they get out of all this work? Possibly the most comprehensive analysis of protein turnover dynamics in human cells? Not too shabby.
All the RAW and MaxQuant processed data is on ProteomeXchange here and will go live when the full version of the study is released by MCP.
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