SimpliFi is live now! (Commercial cloud software) for data interpretation and sharing!

 

Disclaimer: I've been a long time alpha/beta tester for this commercial product. That ultimately means that I've been using this Cloud based tool kit for free for years and occasionally providing useful (?) feedback to the developers. 

They've never once asked me to blog about it but I'm about to stop being a freeloader and buy an annual license and some credit hours. Also, it might have been live for a while and I only just discovered that 1) it was and 2) That $800/year and $0.20/credit is something I can afford (academic pricing?) For most of my stuff the $200/1000 credit hours goes a long way. 

$800 puts it just about the same price for a big group negotiated bundle deal is for Ingenuity. I've paid less each year for Ingenuity, but then I've only been able to log on super early in the morning because we had limited licenses. I like this so so so much better than Ingenuity. 

SimpliFi, however, is designed for proteomics (and metabolomics and can do transcriptomics) but I've only ever pushed the one button. 

Why I like this? It's smart and simple. You just load your CSV or TSV or Excel or whatever into it and then it can generally recognize exactly what you're looking at. It says stuff like "this is your accession column and I think these are your quantification columns" if it is wrong or you want to ignore a sample, you just un-highlight them. 

In my opinion, the figures are also publication ready 

And biology is easy to get to (in some cases, of course) - in this one my drug definitely screws with the nucleus (found that out myself, but it's cool that SimpliFi would have found it had I initially used it) 

Also! I can load data into this and make a link and send it to collaborators and they can just dig through their own data themselves! That part doesn't use credits - only the data normalization, clustering, that sort of stuff, and if you're doing small n experments it doesn't cost a lot of them.

Why you might not like it? 

When it is detecting batch effects - I don't know how - there isn't a paper (yet?) When it is normalizing your input data - I don't know how it is doing it. When it is looking for run order effects (like your signal dropping over time?) I don't know how. If you don't like black boxes. This isn't for you. 

It also might cost a million dollars/year for industry, I don't know. 

Deeper spatial proteomics with MALDI and collagenase digestion!

 

MALDI mass spectrometry is beautiful and can have really impressive spatial resolution these days, but a single spectrum can only look at so many things at once. Even if you had an amazing ion capacity and dynamic range, once you divide that by thousands of tryptic peptides (and matrix) ions that are around you're not going to see much past the absolute highest intensity stuff. 

I think the very best we ever saw from a single MALDI shot in Namandje's lab was 100 peptides(?) and I think reasonable FDR wouldn't have been so kind. That was also a very large sampling size with FTMS readout (high resolution and high capacity but low dynamic range - sort of averages out). 

What if you could simplify your proteomic matrix so there was just less peptides hanging around? We've seen some interesting stuff recently for single cell loads where bigger peptides are better. Sounds like MALDI is something that could also benefit. 

What about collagenases proteomics? 

What? 

Yes, collagenase. The stuff you use to rapidly extract DNA from tissue for quick genotype tests? Yup! 

Unlike our friend trypsin that cuts at K and R and makes nice medium sized peptides, this protein is a lot pickier. It cuts at G-P-X domains - and while I'm very unclear on whether this would be helpful outside of regions where there is lots and lots of collagen - this study focused on the tricky proteomics of Extra Cellular Matrix ,or ECM (which appears to be lots and lots and lots of collagen).

Cool - so how on earth do you analyze peptides produced from this weird enzyme off of a MALDI spectrum? You can make a ridiculous number of guesses - or - you can do LCMS and use a lot of standard proteomic tools to understand the peptides and move backwards! 

This study was a lot of work, btw.... LCMS is used to understand the peptide sequences including where and how they charge and their ion mobility - then the LCMS is used to inform the peptide picking from the MALDI. 

End result? They analyze some patient FFPE tissues at 20um resolution and come back with hundreds of peptides identified by MALDI matching. When compared to trypsin collagenase helps them identify nearly 2x the peptides in the ECM and digesting directly off of tissue slices for LCMS is way more relevant than in solution digestion. There is a lot of biology here that they seem excited about that is outside of my wheelhouse, but there is some neat stuff here because the collagenase peptides often +1 charge in ESI and MALDI so they're straight-forward matches. 

Ultimately, sometimes MALDI papers seems like pretty pictures and not a whole lot else, but this is not one of those. This looks like a really innovative way to get completely new insights from those FFPE blocks. 

Tutorial alert - Mind your Spectra - how to deal with isobaric peptides!

 

This is a solid new resource for figuring out if your search engine is lying to you about those modified peptides. Case study? That miserable region of histones where everything is conserved and everything can have multiple PTMs and - worst of all -people really truly care about which PTM is where! 

It looks like Lab Developed Tests for diagnostics are back on the table in the US?!?

 

For an old post on what a Lab Developed Test (LDT) is vs an In Vitro Diagnostic (IVD) you can go here. 

And...in what was an altogether extremely bad day for the FDA with thousands of people finding out when they tried to use their badges and they simply didn't work - they also lost a federal appeal in this recent ruling.

The American Clinical Lab Association sued to overturn FDA's new rules for moving all new (?) or all (?) diagnostics to IVD designation. So....for those of us who put Aim 4 of our grants things like "and then we'll move this to an FDA approved medical device LCMS system..." we don't have to come up with something more clever to write for how to translate our findings. 

To the thousands of HHS/NIH/FDA employees who just found out they were cut by a heartless and misinformed administration, I'm sorry and I hope you can continue making the world a better place in a better role for yourselves.