Tracking predator cues in marine prey!

 

I liked this paper from the very first sentence...

Abstract

Prey rely on chemical cues to detect predators, especially in coastal ecosystems where danger is concealed by turbid waters. Juvenile oysters (Crassostrea virginica) respond to blue crab (Callinectus sapidus) chemical cues by growing stronger shells, while mud crabs (Panopeus herbstii) reduce foraging to avoid detection. 

...because...what...? 

Did you know that? No, I did not. This is the paper, and this isn't what I expected to learn about at lunch today. I expected to be at a liver center seminar but it's so hot in Pittsburgh (a small city in the Appalachian mountains) to safely have school. I tell you what, the climate collapsing isn't going to be boring. Also, kindergarten remote learning is a lot of dancing.

Wait. Okay, how do you set up an experimental design for something like this? 

Oysters were settled onto 4.5 cm × 4.5 cm marble tiles and allowed to grow for 1 week in 1250 L mesocosms with flow-through seawater prior to experimentation. Oyster spat were then transferred to aquaria and repeatedly exposed to 1 mL mixtures of blue crab urine from crabs that subsisted on either an oyster or mud crab diet (n = 3 mixtures in block 1 and n = 9 mixtures in block 2 per predator diet), settled seawater (negative control; n = 3 mixtures in block 1 and n = 9 mixtures in block 2), or a positive control of predator water 

Ummm....okay, that makes sense, but it's sorta funny, right? 

Oh. Okay, I had all sorts of dumb ideas about how they'd ever get the molecules in the sea water. What they do instead is see what oysters make thicker cells in response to crab A or crab B's urine and then they save back some of the urine that they analyze. Then they can track down the molecule that the oysters respond to. They use NMR for the metabolomics. So - no proteomics here - but it is in Journal of Proteome Research so it counts. 

NMN + Sugar = Reduced hypobaric hypoxia!

Despite the weird repository used for the data in this new paper, it's still pretty cool in this context.

Imagine that you're trying to climb Everest and your goal is to have mice carry all your stuff. Maybe you can't afford a human to carry the stuff? Maybe you're just really mean to animals. 

Everything is going great, until about 1/3 of the way up you discover that these mice are getting really lazy. Do you have an oxygen tank for a mouse? NO? I think you're just doing this because you don't like animals. 

Okay, but I wouldn't type all of this because I don't have a solution, right? What if it's a solution you can get at a gas station?!? Check this out. 

Through extensive trial and error of the stuff you can absolutely get behind the counter at shady gas stations, this team came up with the solution. 

Nicotinamide mononucleotide (NMN) and sugar! To prove that this made the mice better at carrying stuff, they chopped a bunch of them up and then did a bunch of multiomics on the resulting tissue. 

Metabolomics and lipidomics were performed on an Exploris 120 and the Proteomics of just the tendons and ligaments were performed on an Orbitrap Eclipse. 

Something interesting is that they used a specific kit for extracting proteins from the ligaments and tendons. I don't know if it's any good, but it is interesting to me that such a thing (and a company I've never heard of) exists. You can find it here. 

The end findings are extended to humans as the mechanism and how to reduce hypobaric hypoxia in us as well. Given the ENORMOUS differences in how humans and mice respond to these conditions...

(for real, mice drop their body temperatures at high elevations, on purpose. Humans generally never change their body temperatures.... human do a funny thing with a word I can't remember where we jack our body pressure way up to compensate for extremely high altitudes, which is part of the reason we need time to compensate and recover at high altitudes. Here's a good link to a whole lot of reasons we have to be cautious interpreting rodent and humans in these kinds of experiments) 

... this could be a stretch, but I like a good over the counter solution to problems, so if anyone ever talks me into running a race in Colorado again I'll try pumping myself more of more NMN and sugar than I normally do just to find out, I guess. 

...iHUPO single cell initiative TIMSTOF Ultra2 methods don't seem to perform super well in my hands.....

 

I'm back at this great iHUPO single cell initiative paper again, I guess. Sorry if you aren't interested, but it's TIMSTOF Ultra2 vs Astral on standards and real single cells, so I'm interested. 

Another thing that caught my interest was how very different the instrument method on the TTU2 is compared to the basically default instrument method we have ran for single cells for about 18 months.

Above you can see our method on the left and the method from the iHUPO paper on the right. The format is a little different since I had to cut the darned table out of a PDF. Which is always a joy. 

But you'll see that we use 8 cycles and we run from something like 0.65 to 1.4 and the iHUPO method runs 5 cycles and from 0.65-1.3. 

I feel like we tried a ton of different methods and ramp times and finally ended up with basically the default method plus 50% more ramp time worked better for everything in our hands. But we optimized on mouse hepatocytes last year, but those are kind of big and also kind of friendly (there are like 550 proteins that you can detect even if the instrument is vastly underperforming, because they make up about 90% of the total protein content. Compare that to human plasma where 1 protein makes up about 90% and you'll see what I mean).

We run a longer ramp time which gives us a full ramp at a speed of 6.37 Hz according to the software, so each precursor gets measured over 6 times/second, right? 

The iHUPO method is faster and has smarter looking windows 

It gets something in the 9.34 Hz and uses bigger windows at the low and high end of the mass range. 

I was super pumped to run something that looks so good on paper, and....it's kind of meh....

To be fair, this is just K562 standard at 200pg. BOOOOOORRRRING, but we get a steep drop off when we go from 40SPD to 80SPD on the EvoSep One. And I've never even tried 120SPD until now. Maybe with a 50% faster method it makes sense? 

This is a terrible way to display data, but I've got like 15 free minutes on a Sunday night to type this up. 

There are only 2 replicates of the 80SPD for each. EvoTips are expensive, yo. But we run the 80SPD standard method all the time. It's...like...our standard method.... and these results look normal. 

At 80SPD the iHUPO method drops off nearly 4k precursors and 450 protein groups? Ouch. 

I ran more of the remaining tips on the instrument in 120SPD because we don't have benchmarks for this and it's not ...as...bad....but ouch. It's still totally worse. 

Obviously, we're using an EvoSep and they used a funny preformed gradient on a Vanquish Neo. And quantitative accuracy measures more than protein numbers. 

BTW, this is just command line DIA-NN running at the end of each file. Nothing special. No MBR, no whatever. 

But if you're looking at this paper and thinking WHOA, the Astral gets better data than the TIMSTOF, I'd take it with a grain of salt. This doesn't look like the best method to me, and instrument comparisons are dumb anyway. 

Did an Abird outperform a FAIMS Duo source in this new study?

 

I recently blogged about this new preprint and while going over it in more detail to see how we could improve our workflows I had to be impressed by one of the findings I didn't mention. 

Two of the Asstral / Astral (spelled different by geography, I guess) systems had the FAIMS 2 Duo system and one of them didn't. Instead, it had the humble Abird system.

Abird has been around a long time and some labs use it on every system and other labs laugh about it seeming like a silly idea to reduce your background signal. 

In a couple of places in this single cell study the one Astral equipped with Abird OUTPERFORMED the 2 Astrals with FAIMS. For some context, the one time I had access to FAIMS on an Orbitrap Exploris 480 the reason we didn't like it was that we couldn't generate enough nitrogen for the silly thing. To make up for it we rolled in big liquid N2 dewars which cost us about $250 every 3 days or so if we used the FAIMS. In one month we could have paid for an Abird. 

I don't know what a Duo costs (I hear they often bundle it in with new systems almost for free, but if you want to add one to an existing system it can be in the HPLC price range), but if you're looking for better proteomics results at an ultra-low load level this seems like a low cost investment. (BTW, I don't know if it works on anything aside from Thermo systems). Excerpt from preprint. 

Wait. How many proteins are in the nucleus?

 

Ummm...okay... so I stand corrected.... Thank you ProteinAtlas! 

https://www.proteinatlas.org/humanproteome/subcellular/nucleoplasm

So...I'm surprised by a whole lot of this. I'd personally expected that when we got around to doing single nuclei proteomics that there wouldn't be a lot there. 

Something like 

HISTONES

and all the AHNAKs

and that would be about it. Sure, some transcription factors, but they're low copy number at the best of times.

And there is a whole lot more going on there which doesn't make much sense to me at all, and that's okay.

So far we've seen two studies with single nuclei proteomics, one published and one that I'm sure will show up any day now.

In this one, Derks et al., used multiplexed DIA reagents on a TIMSTOF SCP and optimized out some carrier channel levels for the nuclei. Across the study I count around 1,800 protein groups in their data, however the actual protein IDs are missing from a lot of the processed data. I assume that's so they can do unbiased clustering downstream. SCP-Viz requires an identifier to perform clustering which makes it harder for me to reanalyze the data, but it's still a big number. Mun et al., 

did a far smaller number of nuclei, but did it with label free diaPASEF. I've got to dig back into their numbers but they were also far larger than I'd expected (see eroneous assumptions above...)

Discovery proteomics with O-Link reveals new HCC markers?

 

When I think of proximity extension assays (PEA) which is either famous because of O-Link - or is? O-Link, I think of purely using it for large population studies or for validating discoveries by high depth mass spectrometry based proteomics.

But...could you use it in place of mass spec proteomics? Because that is basically what this group did here. 

Now...if your protein or proteoform isn't in this panel and that's all you see, you've just wasted a lot of money and time. However, in this case the depth afforded the serum proteomics allows the discovery of some interesting new proteins in a small cohort. Which then seems to be supported when they run a slightly larger pile of  samples. So, in this case it looks like a win! 

Lyse your cells in 100% formic acid to get 40% more membrane proteins??

Okay. Chemically I do not understand why this would work. That's okay, I don't understand how a lot of things work....

They start out by laser capture microdissecting a pretty big area of cells. Something like 500 micron x 500 in 15 micron cuts. And you stop wondering why the cut is that big when you see the digests are loaded on a Q Exactive Classic. Man, I love those old things, but proteomics has moved forward a good bit since 2012. 

They seriously just put 5 microliters of 100% formic acid onto the slices and dry it off by speedvac and then LysC digest for 3 hours and then trypsin digest overnight. Big boost in membrane protein IDs over just DDM lysis alone.

Then they repeat it with smaller sections using an Astral. There might be two rounds of this to get to very small cuts. This ends up letting them see everyone's least favorite super important proteins, those awful SLC things. And it isn't a small list. They pick up several of them. 

If you are also struggling with low input preps under-representing membrane proteins, this might be worth checking out. I suspect you probably have LCMS grade formic acid sitting around somewhere. 

Multi-omics day on-site at Waters corporation!

 

Hey proteomics people! Did you know that Waters makes mass spectrometers? They totally do and, while I'm not at all sure how this happened, I got invited to drop in and meet scientists and see some talks and touch some instruments. 

I'm pretty sure I got to visit because of some impressive numbers out of the P10 instrument which looks like a compelling piece of proteomics hardware. I'm trying to talk them into running some dumb stuff on one of them for me. The day featured a small group of people with very different mass spectrometry interests getting to wander around the demo labs and touch things and see the Cyclic MS thing (that I know Padula has and likes, but I wasn't really sure what it was) and lift the MALDI and DESI sources that you can just move from one instrument to another. Which, I can't remember anyone else doing, but they were just sitting there.  

There were also fun customer talks from this guy https://info.liningtonlab.org/ at Simon Fraser. 

Did you know there was an effort to compile all identifications of all natural products on earth? And maybe if you had all of them together you could look to see if evolution has biases toward certain chemical scaffolds - which, it absolutely looks like it does. Super ridiculously cool talk. He did admit that most of the natural product efforts have probably not been published, but they've got 37,000 of them all pulled together. 

You should 100% check out the Natural Product Atlas here. 

Eric Gier, a grad student at in Facundo's lab at Georgia Tech showed his work using cyclic ion mobility to resolve oxylipins from brain injury models. Apparently which of those isomers is building up has a lot to do with how your brain recovers from impacts. Which makes the 100-150ms he showed he needed to really pull them apart into separate peaks not seem like a very reasonable use of time. 

While trying to figure out my hand writing and misspelling of Eric's last name in my notes, I stumbled across this JASMS paper featuring open source software for integrating data from the ion mobility roller coaster. 

One takeaway from the lab was that Waters instruments are a lot physically larger than I expected. The cyclic ion mobility system I saw was easily Astral size, but the new one is a benchtop. A very big benchtop. But they've clearly got their niches for these hardware. Moving native proteins and isomeric drugs around, purifying them by doing multipass IMS and then kicking out the ones they want for MS/MS? That's all stuff I saw people do and things I can't think of anything else that could do. 

Wait. Are we doing this wrong? An argument for SUPER MASS SPECTROMETRY!

 

This is an interesting one. 

What if it wasn't the most efficient to have proteomics mass spec instruments EVERYWHERE? 

Rather, what if mass spectrometry proteomics was, instead, a fully centralized system where each sample could be measured comprehensively on multi-capacity hardware without all the compromises that come with solo 150kg - 400 kg vacuum chambers? 

In the simulations presented here it seems to make a lot of sense!  

The author makes the argument for splitting the ion beam from a single sample and routing it through to multiple mass analyzers simultaneously. Considering this from the company that can route ions around a lab with lenses that resember a garden hose. This is not an endorsement, but you might not know that the Spion is a thing, and it's crazy. https://www.tracematters.com/technology

The biggest proteomic human atlas yet should reduce our reliance on transcripts to determine specificity!

 

I won't like that picture freaks me out a little, but here we are.

2,800 human samples analyzed at incredible depth. 

You have to be asking yourself that with a dataset this large and comprehensive, clearly we'll know for sure that the correlation is between transcript abundance from GTEX and this, right? 

Uuuuummmm..... yeah, it's...the same....though that 0.105 from the pancreas is....special.... (this is from Supplemental Table 4). There is SO much data to dig through here. 

I found out about the paper (how did I miss it??) when I stumbled onto this.