Monday, September 23, 2019

cobia -- Cofragmentation Risk Prediction for MetaProteomics!

Okay -- I don't know who thought of this, but it's seriously smart.

Wait -- I do know who thought of it -- it was probably one of these people?!??


People doing metaproteomics don't exactly have the same advantages over everyone doing "normal" proteomics.

Normal proteomics example:  Weird biologist grows rapidly mutating cancer cell line that kind of sort of has some sort of similarity to human cancer cells after 45 years of being passaged in tubes by other weird biologists. But when they bring you protein from it, it's probably close to 100% that version of the cancer cell line (and whatever cow serum they grew it in -- and --well, let's face it -- probably mycoplasma -- I'M KIDDING! Geez....)

Metaproteomics example: I found this mud over here and I extracted protein from it. Can you compare it to the proteins from this weird rock we found in the Andes in 2008?

In metaproteomics you often don't know the starting material. If you're lucky, maybe someone did some 16s Ribosomal RNA stuff on it and you can narrow it down a little. Often, that's the whole point of metaproteomics -- what organisms are actually here and how many?

If you think you've got coisolation issues with your yeast digest, can you imagine what the coisolation (yo -- and in this case I mean peptides that are fragmented along with other peptides when you don't want them there) issue you have when your mud has 4,000 different species of mud bacteria...and yeast...and fungi...and some archaea...and some virus...and some decomposing tree...?

Okay -- so here is the framework for this great idea -- what if you could develop some sort of metric for how bad coisolation might be? Like -- maybe get an idea if your peptides might be more or less prone to disappearing into the background. This is critical because if your peptides are more coisolated (and their ID scores or whatever decrease) then it looks like that peptide -- and possibly that organism -- aren't there and it biases your results!

I don't get the maths stuff. What I do get is that when they apply this metric on all sorts of historic data they can refine and improve the metaproteomics data. I also get that you can get all the code here.

Okay -- and this is where I thought I was going to get to finally insert a video about Halifax (where this great work was done!) by one of my all time favorite comedy troupes...and then before I hit "post" I thought I'd watch it again. And...well... maybe the number of random "F-bombs" is too high for a direct link. You'll have to find it yourself, potty mouth.




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