Monday, March 14, 2016

Proteogenomics reveals cool insights into hibernating mammals!

It's almost climbing season in the NorthEast! I got out with a good friend over the weekend. It is the new record for the earliest date in the year that I have EVER climbed in Maryland. See, even when we are systematically trying to heat up our planet in some bizarre act of stubborn childish defiance that will definitely kill us all -- there are some silver linings!  I got an 85F day the first week in March!

Wait...what was I talking about? Oh yeah!  Hibernation!

So, around where I grew up and where some of the best rock in the world is, we have a lot of these guys!  

...and this time of year they wake up really hungry and the first thing they do is have a huge and painful looking bowel movement (click for more info on bear fecal plug..why? I don't know..cause its interesting?).... so they tend to be jerks.

Do we know an awful lot about hibernation? NOPE!  Heck, we didn't even know what those big foot long fecal plugs were made of until just a few years ago.

Sounds like a job for PROTEOGENOMICS!!

In this brand new study in JPR from K.J. Anderson et al., this team of researchers investigates the effects of the hiberation process on a nice model mammal. As you can imagine, bears are terrible models, so they used a 13-lined squirrel (much less of a jerk)

They got some squirrels, took some protein (I skipped how, on the grounds of that guy above being so darned cute) and they iTRAQ 8-plex labeled them, as so.

Now. Proteogenomics comes in...cause of course we don't have a good curated genome for that cute little guy. And maybe not for any hibernating mammal. So they took what sequences they could get from NCBI, did their own RNA-Seq analysis of these squirrels, threw in the cRAP database and they had themselves a FASTA.

Now, the University of Minnesota has done a lot of proteogenomics. I still don't have a good feel for how the heck they do it. A lot of algorithms were used here. A lot in Galaxy-P, some Protein Pilot(??) and they pulled in some DAVID for downstream analysis.

In the end, though, they wind up with a bunch peptide/database matches, some single mutations that make sense and are observable with high confidence at the peptide level and an overall nice story of how hibernating mammals reduce toxic nitrogen waste products during months of inactivity.

We also get another data point that shows: 1) Yes, transcriptomics is cool useful stuff 2) but without the proteomics to see what is REALLY happening, you've got a lot of spurious data that doesn't really show at the functional (protein!) level.

No comments:

Post a Comment