Quantitative live cell imaging + proteomics shows real time influenza progression!

This brand new study at Nature something or other is timely, interesting and shows a combination of techniques complementing each other I'd never have thought of!

Live cell imaging? That can't help with proteomics...I mean...how does looking at the surface of a cell help?

It turns out that, live cell imaging (light microscopy!) has gotten massively sophisticated! Those images at the top are Rab11 foci!  So... live cell imaging of protein complexes inside a normal human cell. That's pretty awesome all on it's own, right?

What could make it even better? Involving proteomics, obviously, but -- you know -- let's leave that part out of the title. THEN let's do something that is right at the front of everyone's mind right now -- influenza!!

If that doesn't make you want to read this, we probably can't be friends.

Rab11 is a protein that maintains other proteins at the cell surface and helps recycle the vesicles. This group shows how the influenza virus messes up Rab11(a?) function by what appears to be messing up the dyneins. You can't figure out that it's the dyneins by even the fanciest of light microscopes, but you can by immunoprecipitation-mass spec assays! Speaking of which, I'd like to direct your eyes to a great way to display data from IP-MS/AE-MS.

Whoever did the plots for the study knows how to drive home the results and conclusions. But if that isn't enough for you, all the data is available at PRIDE via ProteomeXchange here.

Take it all together? And we've got a better understanding of how influenza screws up a key and massively evolutionarily conserved system. Could you have done this study with just protoemics? Probably! However, the light microscopy is surprisingly useful toward driving the point home and the images are stunning. I'd probably put something snarky about how this is a good lesson in catering to the people who still don't understand why we're still going on about that mass spectroscopy stuff, but I'm almost over this goshdarned virus and my mood is much better, so I won't.

Phosphorylation sites that alter thermal protein stability.....

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And another great example?!?  Phosphopeptides that alter protein thermo-stability? And their bulk identification?

The biggest advance for us with all these recent studies is that these techniques are starting to seem a whole lot less daunting from a sample prep and execution standpoint. And, if you look at the results from the earliest studies to these newer ones, the advances in the chromatography and mass spec hardware really illustrates how far we've come. Now we're (well...some people in Seattle rumored to be talented are...localizing the exact phosphorylation sites that are causing structural shifts in protein 3D structure enough to affect something as primary as thermal changes? 

!!! Wait!! This isn't even the only study THIS WEEK!!  Here is the second one. 

EPIC-XS -- Why Europe will always be #1 in Proteomics -- Proposal Deadline 3/31/20!!

Ignore my rambling and just click this big button! Deadline is March 31 for proposals!! 

EPIC-XS.EU

Did you know the US vastly outspends the EU in mass spectrometry each year? Totally true. Don't ask me how I know. I can't tell you.

Who gets all the Science and Nature papers and, way more importantly,  the studies where you're like "holy shit...we can do that with a mass spec?!??"  Sure...we do okay...I don't mean that just because you're here in 'Murica you can't do something great  but deep down we know that the Europeans run proteomics and we're just trying to keep up by outspending them.

And I think PRIME-XS is a huge reason for why they're ahead right now and EPIC-XS is the reason we'll never catch up.

What is it? It's PRIME-XS powered up!
What was PRIME-XS? It is a way to connect the best and most meaningful and project that are the very most likely to be solved with proteomics technologiest to the best practitioners on an entire continent. (Here is a breakdown of some of the things PRIME-XS did!)

Imagine you're at a US university and you just discovered something big and you need to do some proteomics to finish the project. What do you do?

Option 1: Find a core or service lab: Maybe you go to a core lab and they help you out and everything is great.

But what if what you need is something truly special and hard and new? Cores are -- for the most part -- things that need to make up funds to justify their existence. They (we) have to go through samples and method development is expensive. You may not be able to find someone you could afford to develop this new technology for you. And if you can afford it -- time and time and time again, what do you actually do?

Option 2: You buy your own mass spec....
....and you spend 3-5 years learning how to use it...
...or you spend 3-5 years and a lot of money and you never learn how to use it....
OR -- and this is the worst --- you find out that you weren't right -- that proteomics or mass spectrometry couldn't help you. It's the wrong technology for the job. But you needed loads of experience with the technology to find it is the wrong match.

EPIC-XS offers Option 3:  Access to the expertise to complete your project.

This is my understanding of it: You describe your research and propose your work and an independent panel reviews it and figures out if it is a project that proteomics and mass spec can solve -- and if your project is picked it connects you with the people who have the instruments and expertise to pull your project off AND the funds to do it!

Could you argue that this is like a bunch of labs that are friends who figured out how to rig the system to get themselves the coolest collaborations that could be found on an entire continent? Sure you could! And it's totally and completely brilliant.

And the efficiency for the granting agencies is absurd. Option 2 is inefficient and expensive and, in the end, only good for the shareholders of the instrument companies.

If we want to compete we need a parallel in the US. Which probably won't happen. Instrument manufacturer's have lobbyists.....

But for the EU side -- send this to anyone who has a cool project -- send in your own -- support this amazing project! 

And...yes...I'm totally enjoying my controversial blog post titles!

NanoPore Proteomics -- Is it closer than we thought to replacing LCMS???

I had the distinct pleasure much earlier in my career in becoming a grandmaster in microarray technology -- right after everyone (except -- maybe the NCI) had realized the technology was massively inferior to the newly emerging "next gen" sequencing technologies.

I'll still stand by my QC pipeline for tens of thousands of microarrays by really unsophisticated statistics (powered by huge n!) even if it has, to date, been cited once, possibly making it the highest $$$ per citation in human history.

I love mass spectrometry. LOVE it. And about 18 months ago we saw the first data that conclusively proved that shotgun proteomics could compete head to head with the original "next gen" genomics/transcriptomics technology -- RNA-Seq.

However, if you weren't aware RNA-Seq is starting to fall by the way-side. It's not going to go away anytime soon, but the writing is on the wall that recent improvements in "long read technologies" will soon replace them. PacBio long read sequencing data (which I will read into proteomics data with zeal over anything from an Illumina platform!! The reading frames are soooo long!! Check it out!) is great, but the big thing -- maybe the biggest thing of the future is a humble little thing called the NanoPore.

If you haven't seen it, I bet you will soon.

No joke -- that's it. You can sequence DNA with that thing. On the far right of it? That is a standard USB port. It uses the power of a USB port to sequence DNA/RNA. And -- it is the future of genomics.

However -- could it be the next step in Proteomics???

These authors seem to think so -- and the argument is compelling!

Now -- this idea has been kicked around for a while and I think the conclusion is "yeah -- this is totally going to happen, but maybe 10-20? years from now?"  Sitting here after reading this? I'd move that timeline up.

LCMS (which the authors refer to as BU-MS, for Bottom Up Mass Spectrometry) has a lot of weaknesses. We're improving them, but the outside world is getting very tired of them and, to be honest, I'm starting to think we'll never fix them.

LCMS Shotgun proteomics people will not:
1) Use the same extraction digestion methods
2) Use the same instrument parameters
3) Use the same data processing methods

And there are good reasons for these and we have lots of usefulness in solving little studies, but -- in the end -- this isn't going to be good enough for the rest of the world and they're looking for a way to replace the whole way we do things.

While I'm having my feverish rant for the 1-4 hours I'll be awake today according to this week's trend, the replacement for proteomics is NOT SomaScan. We don't need a GWAS for proteomics. We already have a couple. They're called "SWATH" and "MS-e".

However -- this is worth looking at. Or at least being prepared for!

7,500 proteomic runs on ONE column -- the final nail in the coffin of NanoFlow?

I was just writing something about how the blog was on hiatus and it occurred to me that I didn't actually have to do a good job of summarizing every paper that I read. I could just put it here and suggest you read it because it's aweome! (...brain fatigue...and maybe a high fever...)

Someone (I forget who -- and don't worry -- I'm not going to look it up and blame you) had the great idea of superconcentrating peptides and ionizing them with nanoliters of solvent per minute by electrospray ionization. This was invented for something called the LCQ or QTrap system. Young people, if you've never heard of these, don't worry -- they are terrible. Imagine 1 scan per second with 800ppm mass accuracy. Then forget I ever mentioned either.

Even worse? The sensitivity! It's TERRIBLE on those things. The solution? The nanoflow thing above.

And what happened next was amazing -- mass specs got NOT TERRIBLE! Heck, they got good, and then great! Accuracy and speed and sensitivity.

You know what didn't change, though? The stupid, complicated, NanoLC stuff! The instruments are hundreds (thousands?) of times more sensitive and we're still doing dumb and poorly reproducible stuff with our chromatography.

Is this the paper that finally ends it? 

Probably not -- cause -- HPLC systems are expensive, but I hope this will make you consider NOT buying a nanoLC with your next mass spec.

Summary?

11,000 proteins
11 samples (with TMT)
16 hours of run time on average
And a microflow (1mm x 15cm) column that shows NO decrease in performance over 7,500 runs.

My record for a nanoflow column is 6 weeks -- with a trap -- before the chromatography got all wonky. What's yours? I bet it isn't 7,500 runs!

Happy New Year! The blog will be back sometime soon!

Happy 2020!

The blog is currently on hiatus. Conor (@SpecInformatics) and I submitted something along the lines of 14 different papers in 2019 and at this point, 4? maybe 6? have been accepted.

I've been buried under reviewer comments, resubmissions, snarky comments and general fatigue for most of the year, which -- to be honest -- hasn't been really good for this blog.

This blog is supposed to be an homage to YOUR work and YOUR successes when YOU've made proteomics better and faster and more impactful for medicine and biology (and dozens of other fields where I{or almost anyone else, except you} would never have considered that something as fundamental as precise estimation of monoisotopic mass would make a difference and YOU showed it could and would).

Now that I'm doing this all day, every day and trying to compete with you (geez...ya'll are good at this stuff), the blog seems to fall by the wayside at the end of each day in lieu of making pretty R plots and uploading stuff to ProteomeXchange partner repositories.

It isn't going away and this isn't even the longest hiatus I've had in the years I've been typing in this weird orange box, but I need to catch up on some stuff before I can dedicate the suprising amount of time this odd hobby takes.

I'm also currently in Central America and have had flu like symptoms for several days and -- well -- I'd be lying if I said I was 100% sure that I knew what I was typing right now, but I have this vague impression I'm supposed to make a joke about drinking Bailey's out of a shoe.

Anyway, Happy New Year! And thanks for filling my days with amazing stuff to read about!!!

Optimizing/reducing in source fragmentation on 3 different Orbitrap systems!!

Talk about a useful study! If you're doing tryptic peptides, maybe this isn't all that useful, but if you are working on anything that is more fragile than that (glycopeptides? PARPylated? intact/native, metabolites...we could go on an on here) this is probably worth at least thinking about. 

On the letterbox systems (the ion tranfer tubes with the great big rectangular holes) we use lower RF% to start out with. For peptides on a Q Exactive or HF system, I typically err toward an RF of 50-60%. On the Lumos or Exploris we're typically doing 40-45% for peptides.

The great Katie Southwick explained RF% to me years ago (I need an ELI5 once in a while) as the amount of pulling force in through the very front of the instrument. Bigger things probably want a higher %RF but you have to keep in mind that there are downsides to that extra force and you could break apart smaller or more fragile things.

In this study, this group  takes some of the more fragile things that we all hate to work on -- lipids -- and painstakingly compare different systems with different source conditions.

The chart at the top is the one I find the clearest and most valuable out of this great study -- when I'm looking at something that is clearly fragile and I've looked at it on whatever instrument is available -- this provides some guidelines for normalizing a setting that I probably didn't pay enough attention to.

Urinary Peptidomics Reveals Diabetic Markers?!?!

Well -- if you needed a protocol for doing urine peptidomics, all the way down to standardizing everything to the urine creatinine levels (90umol, if you were wondering) and wanted some WTFourier level proof that this is a good use of your time, may I present: 

1) I didn't know urine peptidomics was a thing
2) This group reduces and alkylate their endogenous peptides. I'm unclear on whether or not I think that is a good idea, but considering how this paper develops downstream, I'm just going to shut up and do exactly what they did.

Discovery was all done on a Q Exactive coupled to a slEasyNano 1000 using an interesting Agilent column I'm not familiar with (post SCX fractionation? SAX? I forget now and I've got stuff to do).

Validation? Well -- they tripled the speed of the mass spec and increased the speed of their separation by over 7 orders of magnitude with an EvoSep coupled to an HF-X. (I guess the EvoSep isn't 1e7 times faster, but is sure feels like the slEasyNLC is taking the length of a human lifetime to load a single sample.

All the data is up on ProteomeXchange and Panorama, but you should read this great paper and find the links yourself!

PISA -- Multiplex Thermal Proteome Profiling!

Want to massively increase the speed of your drug mechanism elucidation/ drug target workflow? Back your bags for PISA!

Nope. Not that one. This one! 

Proteomics Integral Solubility Alteration! (PISA is a much better name).

What's it do? It multiplexes Thermal Proteome Profiling -- in the context of drug treatment. Here is a post that will link you to two of the previous studies (including the Nature protocol for ThPP).

The idea is that if your drug binds to some proteins it's going to change the proteins inherent 3D stuff. One readout of that will be a change in the protein's behaviour at different temperatures. In ThPP (an acronym I may have just made up so I don't confuse this with the TPP thing on my desktop) you look for how things change in your proteome at different temperatures. Check out the protocol. It's tough is lots of room (in my mind) for human error to lead you to false positives.

One way in proteomics to reduce quantitative error? Multiplexing!

One way to reduce quantitative error in everything? More samples!

PISA uses both of these to end up with a TMT quantitative readout of how the proteome changes at a global level (with both 1D and 2D fractionation for TMT seamlessly integrated just as you'd expect from a TMT based experiment) with lots of replicates all multiplexed together.

The Case for Proteomics and Phosphoproteomics in the Clinic!

After a couple of days of somewhat successfully skirting any discussion of politics with my family for the holidays - with one extremely notable exception, I'm so pumped to type something that people with a similar mindset might read one day.

What about this for building some consensus?

Where are we now? What are the challenges ahead? What do we need to do next? Yo, I'll let them tell you what....

This review has study after study that has shown the promise of proteomics to impact patient health. Now -- you can probably guess where the big technological need is in the personalized space from the picture at the top. HLA peptides still suuuuuuuck. Blech. Yes. We need help on that side, but from many of the other areas we're good to go. We just need a shot. And ...as the paragraph above says ...more chances to prove that we know how to do this stuff.

I highlighted my favorite words: because you know what the medical community is good at? Openness to shifts. That's me being sarcastic, if you can't tell.

I love the angle on the phosphostuff here, because you sure don't here these cancer people in the clinic talking about protein abundance all that much -- they're all rambling about the "phospho status" of this protein or that one, and doing Westerns and ELISAs to check them. Which, yo, it's almost 2020. Western blots are fucking stupid. I'm not the first person to say that, but if you need someone to reference that statement to, I'm cool with you quoting me. Here's some semi-coherent reasons why. I'm pretty sure ELISAs are stupid as well, but I'm not sure I've ever actually done one, so I'm not sure I feel qualified to make such a strong statement.

A big thing that we're kind of missing in our realm might be the incorporation of -omics data with clinical data. We're not exactly running away with loads of stuff that can help us make these connections, but -- realistically -- we can steal that stuff from the GWAS people!  (There are good examples, of course, but they aren't integrated into a lot of the more common software programs.)

This is a beautiful, optimistic, and valuable review and -- I'm a few months late on posting it (11 months) but it is definitely worth a read!