Okay! Now this is a team that isn't afraid to ask the big questions! You can check it out in JPR here.
I don't know what a Cynops is, and -- honestly -- I probably won't like the answer. I'm fine with assuming it's linked to some of the most nostalgic scenes from after-school TV shows of my young life, such as --
-- strange that he'd be the only character to lose limbs multiple times....I guess....or convenient, since I guess he's the only one who could do that.....
Aww...nuts...I had to look up another paper, this is just a salamander....now I'm considering ethical implications that I totally shouldn't.....
To stop you from thinking about these as well --
--you're welcome!
This JPR study is really a re-analysis of this open access study from a few years ago, and this is where we'll find the proteomics details.
Not the details of where the samples came from!!! Don't read those!
The mysterious samples were labeled with iTRAQ reagent. Whether the labeling was done with 4-plex or 8-plex reagent is a tightly guarded secret....wait...I figured it out! They used channels 118,119 and 121 from an 8-plex kit. The samples are taken at 0, 2 and 6 hours when regeneration is supposed to be happening -- suggesting that Piccolo is much better at this than whatever this organism is.
The labeled peptides were separated into 30 SCX fractions and these fractions were ran on a 10cm column on a Q Exactive using a secret gradient and ultra top secret mass spectrometry parameters. (Meh -- "you just load the autosampler and press the button" -- have I ever told you guys about the guy I interviewed who said that to me during his interview to run an LTQ Orbitrap -- 😰he...umm....didn't get the job....) Data processing was performed in Proteome Discoverer 1.4 using Mascot with 20ppm MS1 tolerance and 0.1Da MS/MS tolerance, which may explain why the instrument method parameters weren't described. The Q Exactive probably didn't survive the fire that caused it to need search tolerances that wide. Proteins were considered significant using the device many proteomics people do that appears to shorten the life span of the statisticians who see our work. 1.5-fold in either direction is considered significant.
I'm joking about most of this of course! I prefer my search tolerances to reflect the maximum capabilities of the instrument that is producing the files, that's me. I'm also tired of the meetings with HR about why the stats guy is crying this time, but if you can get your biology story out of your experiment, that's all that really matters.
This group produced two peer-reviewed manuscripts out of these files and obviously drew some interesting biological implications from them. They integrated a dizzying amount of genetics data with it and validated results with rt-PCR, making it a well-rounded and validated story.
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