((This image was floating around un-acknowledged on Google Images. It is a CopyRight of Steve Graepel and originally appeared here. This image used without permission, but better that I hunted down the guy who created it, right? (As always, let me know if this is a problem and I'll take it down!))
Okay -- so those degraded peptides?? THOSE ARE A SUPER BIG DEAL! What if a big team decided to do something crazy and profile those???
BOOM. Here ya' go!
I'll be honest, I'm not 100% sure how they did this. I believe the proteosomes were purified and then the degraded peptides were knocked loose from them somehow. Then MaxQuant was used for an enzyme non-specific search of the entire proteome. Multiple rounds of digested proteomes were used for comparison to make sure they were on the right track.
And -- I can't even wrap my head around all the potential here, but I'm going to try.
1) The "dark proteome" stuff -- which might have a different definition now than the one I normally put with it. I consider it all the stuff that passes MIPS (or Peptide Match) -- so it isotopically looks like a peptide, elutes off c18 when a peptide should, but we don't know what the
The protesomes are, presumably, active ALL THE TIME. So a lot of the background peptides may have just been profiled in this paper!
2) How these differ between disease states could open up a whole new field in diagnostics! The proteosomes are tightly regulated by a series of complex processes (typically modulated by ubiquitin, as far as we can tell, right?) Some proteins are labeled for degradation just because they're old (there is an N-terminal instability thing that marks old proteins) or they're degraded as part of the specified, complex, and poorly understood mechanisms.
What if we didn't need to learn the degradation patterns themselves and could just monitor the degraded peptides coming out of the system??? These authors do this here and show the potential this may have -- there are big differences in different diseases!
I'm super psyched to discuss this paper with people who understand the biology behind this and congrats to this team for ---
The first Tweet is my perception of this great paper. The second Tweet -- well -- that's pretty funny...
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