It is way too early for me to get my head wrapped around this one entirely. I've got part of it down and it is enough for me to say that I really like this new paper!
What I get (and like!): the concept of the "hidden proteome" -- it's this stuff!
This is a pie chart from a human file I've been messing around with -- about 100,000 MS/MS spectra and 28,000 or so match to PSMs. All that green stuff...that's the DARK PROTEOME (this sample is kind of weird, btw, that's why I'm messing with it). These authors state that in normal human plasma they can identify all but 25-30% of their MS/MS spectra using high resolution MS1 and MS/MS methods.
They attribute most of this variation to antibodies -- and have some remarkably interesting things to say about circulating antibodies that is heavily backed by citations (and all stuff I didn't know).
What!?!?! I know! Okay...now I'm actually getting the rest of this paper. I needed more coffee and to reread, I guess.
What they do to get to unknown stuff is to get the antibodies out of the plasma. They use an MG (melon?) column that crudely pulls out all the antibodies and associated proteins and I guess it pulls them out regardless of what their specificity is (goes after the non-variable region?)
They do normal LC-MS/MS (except high res with HCD and ETD) on the MG fraction as well as the unfractionated and de novo search all of it and use DeMix-Q (label free quan you can apply an FDR to!), and BLAST to filter the results. I might have this out of order. Still sleepy I guess.
The end results? Great! If they take their normal proteome and compare patient samples with a distinct and observable phenotype, they get nice clustering and differentiation. If they add in the results from this workflow -- the get AMAZING clustering and differentiation!
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