More metabolomics? Geez, Ben, read some proteomics papers! Sorry, this is what I'm doing in my free time right now! And doing metabolomics this year has yielded more interesting things than the last 5+ years of proteomics runs I've evaluated on a certain organism I think about in my free time.
In this paper described in the title, Stewart Graham et al., appear to have reached a similar position. The samples they work with are Huntington's disease. Another awful nefarious neurodegenerative condition.
This is interesting. So metabolomics has been done on these samples before.
Someone did NMR...and found nothing.
Someone else did metabolomics with a QTOF...and found nothing...
So...why on earth would you think that you should get some precious human brain samples and do Orbitrap metabolomics on it? Cause...maybe the Orbitrap is the BEST metabolomics tool in the world? And you'll find stuff with it that nothing else can find? Maybe!
In this study, these researchers use an Orbitrap Elite and do positive mode only. They tuned the instrument with a couple of low mass metabolites. They don't elaborate much here. You can gain some stuff on an Orbitrap with an S-lens if you tune the front lens. Don't mess with the others. Just lock them in the correct settings. (Hint: thats why we don't tune a Q Exactive, the S-lens is locked in the correct settings. Those are on the blog here somewhere, right?) [[ Edit: here is a link to the S-lens ideal settings : 2,3,9,15,20,800,front-lens! If you've got an LTQ with an S-lens hang that document up somewhere nearby! ]]
They run the instrument in MS1 only mode (as far as I can tell) and used a resolution of 60k. You might argue that with a high field Orbitrap that has its overhead in the front of the instrument that it would make sense to run 120k, but 60k looks pretty darned nice here!
They run some pooled samples to improve the statistics, convert the files to mZxmL (or something) and run the data through XCMS and use a ton of stats I don't understand.
To review: NMR didn't find anything. A Q-TOF analysis didn't find anything. An Orbitrap found 200+ features that were differentially regulated and significant enough that they went back, reran these and targeted for fragmentation. At MS1 of 60k you can basically tell what a lot of these metabolites are but fragmentation and mzCloud can verify these identities (and figure out the ones that you are unsure about).
They put their 15 favorites in a table.
Then they put their 8 favorite pathways THAT ARE MESSED UP IN THIS DISEASE in the final table. And this is just the soluble metabolites. That ionize in positive mode. And elute in reverse phase!
Seriously. If you have a biological model and you're thinking...well the metabolome can't be involved here cause So and so et al., did 4,000 Q-TOF runs on it. Umm....you might want to just take a look. If you're reading this you probably have an Orbitrap...
No comments:
Post a Comment