On this episode of Translating Proteomics, host Parag Mallick speaks with special guests doctors Ben Neely and Ben Orsburn, leaders in the proteomics community and hosts of “The Proteomics Show” podcast. Their insightful conversation focuses on the role of communication in proteomics and covers:

·      Impactful things they’ve learned while hosting The Proteomics Show

·      How their communication efforts have changed their research

·      Barriers to proteomics becoming more popular in the life sciences and in the broader public

Chapters:

00:00 – 03:04 – Intro

03:04 – 07:23 – Why the Bens created "The Proteomics Show"

07:23 – 10:42 – Ways the proteomics show has impacted the Bens’ research

10:42 – 16:44 – Every scientist is interesting!

16:44 – 20:36 – Ways the Bens' communication efforts have changed their research

20:36 – 25:08 – Trends in proteomics

25:08 – 35:34 – Barriers to communication between the proteomics community and others in the life science

34:34-48:34 - Barriers to communication between the proteomics community and the broader public

48:34 - End - Outro

Resources

• The Proteomics Show - Ben Neely and Ben Orsburn host this podcast sponsored by the Human Proteomics Organization. On it, they interview proteomics researchers in a “fireside chat” format. Their conversations cover not just the latest research, but also their guests’ motivations, hobbies, and histories. Definitely check it out!
• News in Proteomics Research - Ben Orsburn's blog on the latest developments in proteomics.
• Proteomics, the next truly massive investment opportunity - Forbes article on the potential of proteomics.
• The Magic School Bus Rides Again - Recently rebooted version of The Magic School Bus. Will we see an episode featuring proteomics?

Who? All right, let's try that again. Tyler, are you. Are you recording?

Yes, we're good now. Okay.

All right. It popped up and said recording in progress halfway through, while I was, while I was talking. What is the. Oh.

Our show is called Translating Proteomics. Thank you. All right. All right. Welcome back to Translating Proteomics.

Ben Neely is a research chemist at the National Institute of Standards and Technology in Charleston, South Carolina. At nist, he focuses on the development of new materials for omics applications and the generation of standardized data across non model species.

He additionally works to develop methods for emerging proteomics applications. Does a lot of work in data independent acquisition and metaproteomic analysis.

He got his PhD and postdoc from the Medical University of South Carolina, where he focused on environmental microbiology.

We're also joined by Ben Orsburn, an assistant professor at the University of Pittsburgh, where he uses and develops single cell proteomics techniques to study human biology and pharmacology. He did his graduate work at Virginia Tech and his postdoc at Hopkins.

He held a variety of industry positions and was a principal investigator at Johns Hopkins. And throughout his career, Ben has leveraged his knowledge of mass spectrometry, proteomics, and protein informatics to advance biology and medicine.

He also runs a hugely popular blog called News in Proteomics Research, where he covers the latest developments in proteomics.

And I would be absolutely remiss in mentioning if I didn't mention that the Bends are the co hosts of the Proteomics Show, a podcast sponsored by the Human Proteomics Organization, and to my knowledge, the very first proteomics podcast in the world. It is an exceptional podcast and we're really delighted to do a crossover.

Today, they interview proteomics researchers in a fireside chat format and their conversations cover not just research, but everything about their guests, their hobbies, their motivations, histories. And you should definitely check it out. It is fantastic. And so both of you, welcome so much to Translating Proteomics.

I'm so delighted that you're here today.

Yeah, thanks for having us.

And thanks for the intro. It made me feel really smart there for a second. Probably just that I didn't have lunch.

It is entirely accurate in every way. I'd love to dive in today just to chat about the proteomics show and how it came about.

And what your goals are for it, and I'll turn it over to whichever of you wants to take that first.

I feel like that's you, Osborne.

Yeah. Okay. So I ended up having a really crappy commute for a while. And the drive into Baltimore isn't always the most fun thing in the world.

And there's a stretch of road that's actually called the Thunderdome, because there, for a length stretch of time, one person would not leave, you know, alive every day. So, you know, so this nice 45 minutes to an hour and a half drive, I just thought it would be really fun to have, like, the.

You know, something to listen to. Ben and I were sitting outside us Hoopoe. Charleston. Yeah. In the middle of the day, and then we're just like, okay, we're just gonna do it.

I think that was the. The conversation like nobody else is gonna do. So we're just gonna start a podcast and see what happens. We had no idea.

Other people to do it.

What?

Yeah. The goal is we wanted it, but no one did it.

Right.

Yeah. So did you.

Did you try to encourage specific people and say, hey, you should do a podcast? And they just didn't pick up the mantle? Or you were just thinking it in your head there really needs to exist a podcast about proteomics.

We just thought it. Strong, strong thoughts.

I don't. I don't listen to podcasts. It's not. It's not a medium that. But I was like, okay, well, I really try to read a paper every single day.

And it's like, man, can I just get around that and listen to a paper? Right. Can I learn something about proteomics and then not read paper? Right.

No, that's. That's amazing. And I guess just thinking, taking that one step further, how does the. First off, what are the goals of the podcast?

What are you trying to do? What do you. What do you want to get out of the podcast?

Goals?

Well, I'll give you my goal. My goal is. I think this actually goes back.

The other part of that conversation was like, what if we had this show and it gave us an excuse to talk to, like, cool people? Like, that was. And I think, like. Like, the person actually been mentioned in Charleston was actually someone we had as a guest.

And I think that that was the goal. I mean, it's. You know, we've given.

I think we've talked about this some, but, you know, the doing something for yourself is kind of an easy way to do it.

So, I mean, I think there may be some other Goals that, you know, been like, we had a season where there were some goals, but I think mostly, to me, I think it's pretty selfish. Like, it gives me an excuse to talk to people that are very interesting. And, like, people seem to not hate it.

I think it's the exact opposite. I think people love it and they are religious followers of it to the point that you.

You did a live podcast at US Hoopoe in the past, and it was incredibly well attended.

Yeah, that.

I wasn't there. I was sick. But, you know, but. But that is my favorite one because I didn't have to listen to my own voice.

But even like. But even like, that one, like, we didn't want to do that.

Like, so Ben was supposed to be there, but they were like, they were like, oh, we really want you to do a live podcast. We're like, why? Who is going to show up and listen to us? Because even if you go back, like, the first.

So we started talking about, like, in Charleston and the next year we were at usupo and we had done, like, the episodes, and it was like, we knew people listened, but it was weird to have all these people come up. Do you remember in Chicago, and like, they're like, oh, I love your show. I'm like, you kind of look at them weird. And then.

And then in Portland, they wanted us to do a live show, and we did it. And yeah, you're right. Like, this room was packed in. Osborne, you weren't there, but they were just like, yeah, it was. It was.

It's weird for the engagement because I. I, for one, don't think about people like, who's on the other end. Like, I try not to think about it, but.

Yeah, well, it definitely has turned you into proteomic celebrities, which is sort of a strange concept that there exist proteomic celebrities. But if, you know, in the pantheon of proteomic celebrities, I think your. Your podcast has.

Has helped bring proteomics not just to other proteomics people, but. But to the wider community. So we'll come back to that later, but I'd love to.

Also, you mentioned having selfish interests and wanting to chat with people, but they're also. I guess there's a little bit. Ben, you mentioned it would be fun to be able to listen to and talk about papers.

And so are there other aspects scientifically and with regards to your research where there's been some interplay or between the podcast and your own research?

I have an example right now that. What. We were interviewing this. So we. We did A little sub season for Hupo's early career researchers. And so they were all undergrads, right.

I guess one of them had just graduated, so he's doing a semester, you know, so these, these young students and, and, and one was telling us about how they'd flow, sorted all the different cell types in a mouse brain and was doing proteomics on them. We actually randomly sorted cells from mouse brains from wild type of CRISPR knockouts.

We're having trouble making sense of the data JC Price just sent me two days ago, unpublished data that is the rank abundance of all of the proteins from every cell type in the brain. And, and we're absolutely going to collaborate on this because now my paper makes sense. Right. Well, that's Colton's paper.

But, you know, and I actually have something to show at US Hoopoe because it's planning to show this and it's just like, here's some gobbledygook and there's a big, you know, PCA of 4,000 cells, but I don't know what any of them are. So. Yes. So I've got a good example from.

Right now from that, from that same show this morning I went to my colleague and presented to him the whole C half. So this is Chad Heyer and he was talking about the iodine and the C half labeling and protein stability.

So yeah, again, like, I, I think we lean into our show. Like we don't pick them normally, we've picked a few, but they just kind of, you know, they're.

It's the result of other organizing and picking and prioritizing. But for, I think, like Ben just said, we're definitely heavily influenced by these people that we're talking to.

So what if we better or worse, I guess.

Right.

You know, and Ben kind of alluded to this, but, you know, we, we did have a targeted season where we went in with goals where it was like, okay, the test, like, could we use this as an outreach tool? And so we did it. We did this little, you know, what is it, six episodes or something where each one was, you know, what. What is a protein?

Why do proteomics what proteomics can't do? You know, and then, and you know, and I think that we'll look at the stats.

I assume that was a really short episode.

Oh, oh, no. So it was six. Six different episodes, I guess.

No, I meant the specific one on what programmers can't do.

Oh. Oh.

It's actually ridiculous because we started off just talking about like, it can change the oil in Your car, like, it can do everything. Like it. It's completely. Did it. It failed at that question.

Yeah. The response from a stats perspective is really like, the. The listenership is really good.

But it didn't hurt having Matthias Mann as one of the guests. Right. So I don't know where the numbers were before, but it definitely looked like we got a boost there.

That's really interesting.

And so if you think about over the course of these many, many episodes, what is the most surprising thing you've learned from your guests, either about your guests or about science itself?

Nobody will believe me when I say this, but I think that every scientist is actually really interesting. And. And it. And sometimes you have to dig a little bit, but everybody's got, like.

Like something outside of the lab that they're passionate about, and that's really fun to get to.

Right. And they all will start off without fail and say, I am boring. This is going to suck. And then we will talk, and they'll have a blast.

I mean, I think maybe I can't think of anyone that hasn't said, like, oh, this was not fun. And, you know, each one, I don't know what the ma. Like, what the formula is, but sometimes we definitely unravel a little more.

You know, whether it's Ralph Bradshaw talking about Ghost Cities or John Price, me trying to talk to him about how he went to the high school where Napoleon Dynamite was filmed. Like, whatever it is. Like. Like Ben saying, like, every person has this fun thing, and so what I love.

And if you go way, way back to the show, like, and you can kind of see this as Ben and I have developed over whatever 70 episodes is, you. Osborne tends to be. He's like the technic. Like, he. You know, more technical things, I feel like. And he will go deep. Well, okay, whatever. But you're.

You'll go deep, and I will, like, tug on these other strings that might be like, why did Chad hire. Build a. A thing? You know, a T shirt cannon. But then. But then, like, we'll both. Like, we're both going into both of those areas.

But I think that was, like, the original priority. Like, we wanted to be really technical. I was more interested in the personal side, but now it's this really fun blend. But yeah, I.

I completely agree with Ben. People are always interesting, and they're always convinced they're not. And except for you, pr. Like, you, like, know that you're.

I feel like you're like, yes, I have this, like, amazing.

Like, there's some people that you Know, you're like, okay, sure, this is obvious, but most people, they just think they're lame and they have nothing to give. And then we sit down with them for an hour and, and they have a blast.

So I would love to tug on that thread just a little bit more because that is something that is, I feel like really limiting in the world, which is there is a perception of what a scientist is and it's a very one dimensional view. And it's, you know, they're in their lab coat, they're really stuffy, they're dry people. All they do is science all day long.

And I think that's actually discourages a lot of people from getting into science because they feel like they are these complex multidimensional people and they can't be both that and a scientist. It's an either or choice.

And I think there's this also layered perception of that you have to be the 0.1% of the smartest people that you've ever interacted with in your life. And I occasionally go and speak at these rural high schools, right. And like try to encourage kids to do science. Right.

And, and you know, and I have kind of a character that I do like, hey, you know, like, you know, I came from a way worse school than this. I didn't get great grades and you know, and I can do this, right? Like, you can do this too. Why aren't you thinking about it? Right?

And so that they have this perception, it's like, okay, well, you know, well, okay, the valedictorian, she's gonna do it, right? Like maybe she can be a scientist, but actually, yeah, and that's it. That's the only person that could do it, but also that they're boring.

I think that's also very important.

And I, I mean, I kind of, I mean, I know we, I say that we don't really have a focus, but sometimes I will catch myself, like it feels like a PSA to like young researchers because I do think the current generation is more aware of like, I mean, self care balance, that there's more diversity, that there's more ways to be a scientist.

And sometimes like I feel that like, I know we probably say we'll do like just the last one, like, like emphasizing that not moving for your job is fine. Right?

Like I, I almost feel like in some way our, our, these guests allow us to say these other things that you don't hear about are fine and the people do it and, and they are, even if they're not like Successful, like you said, by whatever standard. That's crazy. They're. They're sciencing. Right. They're. They're having a life.

And, and so I think, yeah, that, I think that is an important thing, is not just to show people they can do it, but also, if you're a scientist, is to show them all the ways that you can do it.

Yeah, I think that's such a huge message. I'll just briefly mention my lab does do a lot of work with trying to bring opportunities to underserved communities and underserved students.

And it's really one of the privileges of having that platform is being able to do that. And I had a student one summer who again, first generation student, his parents never finished high school, et cetera.

And he came into the lab and at the end of the summer he came up and said, I really was nervous about this. I thought that what scientists were, was they were all these brilliant Albert Einstein people. And now I see that that's not true.

And I was like, thank you.

Yeah, which part's a compliment.

But it really did change his trajectory. Like all of a sudden science was approachable to him and scientists were approachable and something he could picture himself being.

It wasn't this, you know, off on a tier sort of. Sort of concept. And so even though he phrased it exceedingly badly, the impact was awesome. Great.

I'd love to change gears just a second to think about other you, Ben Orsburn, in addition to the podcast, you do have other communications that you do through your blog, et cetera.

And I'm just curious about how the combination of being more active in communication has changed how you think about your research and yourself as a PI and scientist.

Oh, you know, the communications, I mean, honestly. So the blog was a complete surprise, right?

When I left my academic postdoc to go to an applied industry postdoc at the nci, there was going to be no chance to publish, Right.

And so I started this thing in my first postdoc where I was like, okay, I'm gonna read a paper every day because I can't compete with anybody here because I'm not as smart as they are, but I'm going to just acquire all this information. And then I was like, oh, I'm just put it online, right. And so. And I just kept doing that.

And people sometimes later found that, and it's funny how often I've used it. Recently I have, you know, I have an entire paper that was. Was inspired by a Twitter conversation back when Twitter Was good.

And I acknowledge, you know, it was a discussion of some work that Sam Pain had done. And then, you know, instead of, you know, what you normally do with Sam Pain stuff, you just copy it. Word, word and somewhere else. Right.

But I was like, okay, well, I'm going to reproduce this study on a time of flight instrument. And then. And it's really fun. And you know, and I acknowledge the proteomics Twitter's community, specifically people that were.

That contributed the conversation. One was an undergrad that just like chipped in and it really shaped that entire study. And so I really do use that stuff.

And sometimes I like to put a preprint up that I know is incomplete and then sit back and see how people respond to it for the second draft. Right. So I think we can leverage those things. I'm not sure that it's the most, you know, always like always the.

Maybe the smartest thing to do from a, from a perception, from, from your own marketing perspective, like putting something out there is like, whoa, okay, that's kind of dumb, right? Or this could use some serious work. But.

But at the end of the day, if your goal is just like doing better science and you've got really thick skin, I just use it. Right? So.

Right.

That's kind of a ramble.

No, that was, that was fantastic. And this, this concept of what is the role of what is your job as a scientist?

And I, I think that aspect of our job is actually to take feedback and to be better. And so that it's not about the checkbox of the publishing of the papers. It's about making the best science we possibly can.

And sometimes that gets lost along the way. And it's easy to let your ego get in the way and be like, oh man, I just got trashed.

But that is actually, you know, that productive discourse, that productive, not cynical, not mean, but productive. Critical evaluation is actually essential to us doing the best science.

And so it's great that you actually have created an extra vehicle for doing that.

That was a lot smarter than what I said. I like how you said it better.

It's yours. I give it to you. I'm curious also, just in terms of you've through your long experiences in the field.

This is not me calling you old, but both of you, how have you seen what are the trends that you've observed in proteomics in particular, how it has evolved either through conversations with your guests or just your own observations of the field?

I mean, I think, I think Ben's more. I mean, I can Speak to, like, the show, right. Or.

You know, we talk about, you know, Ms. Convert pretty awizard, kind of bringing together file formats at the same time. You had a lot of instrument advances. That was a big moment.

You had open data. You know, pride really became like, a big deal later. You know, we had preprints, like, so. So now is a very different time. I.

If you want to listen to funny things, listen to episodes. When we have, like, older people talk about the 90s and I get everything wrong. But about the last 10 years, you know, it's. I think there's the.

I don't feel like we need to talk so much about instrumentation and we can talk more about biology and the questions you ask within the show. I think the things that really excite me are the spatial.

Like, I still go back to it, but, like, combining spatial metabolomics with proteomics, like, how do you do. How do you find new pathways? We take all of our results and we rely on these really pretty janky databases to try to provide insight.

And, you know, so I think we're, like, we're finally graduating to be able to ask these really cool questions. That's my vibe on the field is maybe less talk of numbers and more talk of science.

Yeah, I think that, you know, it's really cool to watch the field as it goes, right. And as it. And we're seeing more biological studies, you know, it's. We see a lot.

You know, we're, of course, still seeing me, I can get 8,000 proteins, I can get 8,015 proteins or whatever, right. But the fact that we're. We're seeing a lot of biology happening, I think the.

There are some things that the field has always done that haven't changed, though. And we are the worst communicators and all the science, right. Like, it's, it's inventing acronyms and it's, you know, it's.

It's like the, you know, the. You can hide as the mass spec wizard in the basement, right.

And you can make a career being cantankerous and, and, and dismissive because people walk into your, you know, your, Your dungeon and they don't know all the acronyms. Right. But when you see the people that are being really, really Successful. They're, they're not, they're ditching the acronyms.

They're the better communicators because that cool biology is out there. And those people know all, like they have impactful questions and if you can, if you can bridge that gap, right?

And you see, you know, Neil Kelleher has this who talk thing, right? That, and he never shows them, he never mentions a mass spectrum. He never shows one. Like there's nothing. Right. It never comes up.

And it's just like, I think, just always think about that, like, you know, how can we communicate better? Because I think we're still really, really bad at it.

Yeah, but so that's a. Go ahead, Ben.

Well, I was just gonna say, I mean, you see that with, you know, our favorite guest that, you know, took us so many episodes to realize are the people that don't do proteomics. Because they'll show up and talk about these questions they're asking.

And sometimes they'll say, God, wouldn't it be great if I could measure these protein isoforms and compare it to my genomic data? I'm like, you can do that. You could do that 10 years ago. But again, and Ben's then like, well, the reason is because we're not communicating.

They're not even asking for fancy things. I'm not the spatial metabolite.

That's really interesting. Why do you think in particular that there are these communication barriers both within the field and then beyond the field, from proteomics to other.

Is it that what we're doing is so hard and complicated? Is it. Why is that barrier there?

It's. Oh, soapbox. I don't remember about it, but we don't have a formalized education program in proteomics. Right.

You know, you can, you can go to just about any university in the United States and get a genetics degree, right? You cannot get a proteomics degree anywhere. So we don't have this unified language.

We don't have, you know, we don't have textbooks, we don't have this, this common language within ourselves. Right? And so then you have these, you know, the, that. Where did you, you know, where did you do your graduate work?

Where did you do your postdoc Right. And. And the technologies that were developed there under that name versus the. Versus something extremely similar that was developed somewhere else.

And I think we've got this. Right, like, so you've got this confusing nomenclature because we don't have this shared thing. And I, I think that's a lot of the problem, right.

That, that just doesn't exist. So that. Yeah, I think that's.

Yeah, yeah. And, and, and I don't think I'm one to like. I think people have probably thought about it more like, how do we end up where we are?

But it's also just that even if you go back and you hear the stories, everyone was like, they weren't a chemist, they weren't a biologist, they were this in between. So until very recently, was this even kind of what Ben's saying? It was a deceptive field.

It was almost like they were always in this weird no man's land. And then on top of that, just how hard it is, right, like to do start to finish proteomics, it's like I gotta be great in the wet side.

I have to be basically an electrical engineer, physicist, whatever, to run the instrument. Oh, and plumber. And it's just breaking. And then to analyze the data. I'm probably some sort of bioinformatician programmer.

And you've got people that are like siloed all over the world that are all being all these parts at once. And then someone comes in, is like, hey, can I run a sample? And we're always like, ugh. And to me.

And again, I'm not one to speak to this, but I think that's the problem. It's like that entry point.

Like, people talk about how they want proteons to do everything, but if, if someone runs and walks into your lab and says, I need you to do the sample, it is going to be like an hour conversation and you're probably going to say no. If they walk into a genomics lab and say run the sample, I think they're just going to say yes.

Maybe this is me oversimplifying it, but that's for me is we just have. We are conditioned. Again, maybe it's all these exceptions and acronyms and difficulties, but there's so many ways to do it.

And I think it just creates this barrier. If you talk about can universal methods or universal acquisition people in our field, I don't think want that or like that. And it's like just.

I don't think it's. Maybe it's not accomplishing maybe what you want it to accomplish.

So, yeah, no, that makes a lot of sense.

And I think part of what you're describing is that there is this incredible fragmentation around how proteomics is done just from lab to lab to lab to lab, because there are so many knobs and levers on the instrument and on the, on the HPLC up front, and there are even more knobs and levers on how you do the sample prep. And, and so, and everybody has experience from, oh, my lab does it this way and my progeny do it this way, as you mentioned.

And so it's very hard to say, okay, this is the way that proteomics should be done for asking this canon of this set of questions.

Whereas I do think in genomics there's, you know, there's a pretty standard Kyogen kit you buy and you do a DNA extraction and there's a pretty standard Illumina library prep kit. And so we, we just don't have that level of consistency. And maybe part of it is because we're trying to eke out.

We just did a study in my lab, just for reference, where we were looking at different Eppendorfs or microfuge tubes from different vendors and we're like, okay, which one of these gives us the least losses to. And you know, the difference was like 3% across many of the low bind tubes. It was not a large effect, but it was an effect.

And I could imagine that that might push us to say, oh, well, I could get 3% better performance if I use this thing at the cost of uniformity across the field.

Yeah, absolutely.

Yeah.

Well, and, and that's, and that's, I've heard it, like the positive way of describing what we're talking about is we are in a innovating field. And like, that's, that's the thing. Like, we're just, we're innovators. We're in. And that's great.

But again, if your goal is to be like mainstream, at some point you gotta be like, listen guys, like the term just turned 30 years old. Like maybe we can kind of pull it back a little bit. Just let it, let it grow, let it, let it be old. It's 30.

Like, it's, it's getting towards middle age.

Or would you say it's the LCQ that came out? Or are you, are you, you know.

But they were running tryptic digest on paper, like tlc, whatever it was. And they were identifying these peptides. Prote. Proteins. The study of proteins always was the Spotlight. Yeah.

Talk about 70s 2D gels, you know, later that became obviously bigger. It was bigger before it somehow just died. And it was genomics. Right. In the 90s. So. No, I mean, I think the study of proteins.

I just don't know why no one, like, why are we not a topic? Like, that's my biggest pet peeve. Like, would you have like, name, you know, like, what's your field? You.

There's like genomics, trans everything, geography, ge geology. There's never proteomics. There's never proteomics. Like, what is up, guys?

Okay, I, I have a very different take on, on this question. You know, I, I would just, you know, and the, the students I had at Hopkins were pharmacology students. They were using proteomics as a tool.

And you can start with Dora to Becker, Jensen et al. Like, 12,000 proteins quantified and you know, within the same amount of time that it took to do an Illumina high C prime. Right.

And so from then, I think that that's when proteomics becomes. Because of the thing. It's a cool word and I've often described it as. It was kind of a lie and.

But it is aspirational, yes?

Yeah. So it was, it was, you know, there's protein mass spectrometry, right?

And then that we're at this point now where like, you know, proteomics is, is this, is this thing where people are completing, like, you know, you know, you know, you're not getting 50 or 100 at that kind of depth a day. But we're getting close, right? We're seeing 8,000 proteins on some of these instruments. They're doing, you know, 100 speed, right?

So we're seeing, you know, these other technologies are getting close to all the proteins that are there, and they're doing it realistically in a realistic timeframe. And I think that's proteomics. So I think that's. That's a relatively new thing.

That's a, That's a great take. I love that.

And Magnus hates when I say this.

I feel like I had some really lovely papers before that. And so I, I hate to discard all of those, including, like, my proteic peptide paper about what, you know, what peptides you can.

But it's easy for me because I.

Didn'T publish anything until the read.

But they actually. So I'd love to take this maybe one step further.

So we talked about the barrier with regards to the scientific community, how we have genetics departments, but we don't have proteomics departments, which is a fascinating thought.

I've always felt that where we are now is actually biochemistry hitting back at genetics, and so that proteomics sort of lived under the broader umbrella of biochemistry. And so that was good enough, but maybe that's not good enough.

Maybe we need to go even harder and differentiate the general umbrella of biochemistry from proteins sciences. You can come up with a better name for the department.

I mean, I tell people I'm an analytical biochemist because it feels more appropriate. And maybe that's still kind of aspirational, but, like, it feels more. That's what I'm doing. Because proteomics is just. Yeah, it's kind of nebulous.

And I don't know, I feel like. I mean, I tell this to strangers. I told it to a stranger this morning. They're like, what do you do? I'm like, I'm an analytical biochemist.

I measure your proteins in your blood. That works so and so.

So that. That concept of stranger. So we talked about communication within the scientific community, but what about the outside world?

I'm curious about what are the, what are the barriers that you see? Or what are. What do you see with regards to proteomics in the outside world? Is it there at all? If not, why not?

You know, well, here, I mean, you know, do you know how they. They re released? Like, they, they updated the magic the magic school bus and did not know that.

But now I'm excited.

It's really good. It's. It's. What's her face? Kate. Yeah. And she' frizzle. But like, in one of them, they're like crispr editing DNA.

And again, this show is for very small children. And my children totally, they're fine with it. They're like, yeah, genes. Messing with them gives you traits. Boom.

And like, why can't we just talk about some proteins, right? Like, how did that become a protein? No, it's. It's there. You never hit that level.

And I think too part of it, and I was kind of thinking about this, like, even when I was talking to the stranger today is, you know, I can sequence your genome today or tomorrow or last year. That's just what it is. Right. And that's kind of one of the reasons it's simpler. Right?

There's no caveat versus if I said I want to use your blood sample to understand something about you, it's like, well, you know, is it two hours postprandial? Did you just have an infection? Like, what. What time of the month is this? What. What season is this? What's your sex, age, blah, blah, blah. And it's.

And it's just inherently this like, fuzzy signal. And I think that's the. The problem too is like, it's hard to communicate that. That you. You say like, I could do all this stuff.

And then they turn around, say like, okay, do it. And you're like, oh, well, hold up. I don't. Like, normal. Like, what are normal levels? You know, that's. That's. Well, what is.

I don't know what normal is, you know, like, because I.

That's right. Well, because I think that you. What? Part of what you're talking about is that I can measure your genome and it's your genome.

I measure it once and I'm good. But your proteome is different in every cell in your body at every moment of every day.

And it's just a scale of complexity that is so much larger than the genome.

And Ms. Frizzle is not going to be able to do that. Like, it's just. It's too much. Right? She's not going to be able to do it. I don't know.

My hot take as to why, and I'm curious to get your reaction to it is that we had movies like Gattaca and Jurassic park and they were all about the genome. And so it's out there. And we have not had A movie about the proteome.

There was, there was the Expanse. There was that spoiler. There was that.

See that episode of the Expanse where they put the sample into the thing and it spits out uniprot numbers and that's the answer and like two people caught that. Just what it say? No one cares. But okay, keep going. Yeah, we need it. Keep. Okay, Osborne, go.

That the, you know, that it would be cool if they'd had, you know, they hadn't had a handmade mass spectrometer from the 70s, you know, as this like really terrifying looking thing that's obviously, you know, hand built as the picture. But you know, but yeah, it did attract interest, right. I think the title was the Massive Proteomics.

The Massive Investment Opportunity of proteomics or something like that. Right. And so you do see these things sneaking in and I think, you know, as much as I'm as I'm concerned about these big targeted panels, right.

Thermo just signed a thing, right? Whether Olink just set up 660,000 sample, right. Screen. It's going to take absolutely forever. The current throughput.

But that's putting proteomics in the public consciousness, right? We're thinking about the proteins there. You know, people keep repeating that, you know, 90% of drug targets are targeting proteins, right.

If, if those things, I think that's going to get that to, to kind of the, the public consciousness. But it is slow and it's complicated and kind of boring. Right?

Well, and it's kind of too like we already measure proteins, right? Like what's your A1C number? Right. Like the protein, you know, like we're, we're already doing it.

But yeah, I think there, there's a disconnect there because like you said, like we're all about Jurassic Park. I think was huge. They saw the ATCs and GS. We need the equivalent of that.

Well, so let's just dive into this a little bit more because it's clearly not enough. What happened with the. We're going to go deep into Jurassic park lore now. So what happened is they actually saw not a genetic mutation.

They saw probably an epigenetic change that led to changes in dinosaur behavior which were almost certainly caused by changes in their proteome. And so really Jurassic park was lying. It was not genetic alterations that were driving dinosaurs going nuts. It was proteomic alterations.

Missed opportunity.

I Haven't seen it since the 90s. But that makes a lot of sense, right? Huh.

Well, and that's right because in, in. And we found. I mean, yeah, so we can use like the reptile example, right?

Like they could be male or female based on temperature or, you know, that's like how I think alligators do that. Right? Like the. And I think in Jurassic park it was. I don't even know why they were frogs.

They were like crossed with frogs in some way.

And. Yes, but, but yeah, like, so there are these. And we. And again this came up on the show like someone had this problem where it was this very evident.

This is why you study proteins, right? Like your, your DNA is fine. And then you had to know this. You had to be able to study the trafficking or turnover. Was it the APOE thing?

But yeah, like it's, it's not just. Do you have it. Because this is the one that gets me is like we've got these snips and we're like, oh, well that's snp. And now you're toast.

I'm like, is it like. Because it's really complicated and it does all this other stuff and, and, and yeah, I feel. And yeah, we do complex sub. We do complex pop sci.

We know people could understand it. I don't know how you convince them. Like, not only is it important, take the COVID vaccine. It made your body make a spike protein.

I think everyone had this weird lesson in how that works. I don't think it helps.

Yes.

Like, I don't think anyone still understands like what a protein is. They're like eh, tracker, you know, I don't know.

I mean, in part because your cereal box does list protein. Right. Your yogurt says this is how much protein. And so I wonder if that's actually working against us. It does not say how much DNA is in your yogurt.

There's probably some there, I guess.

Yeah, I bet.

Some, some, some leftover. But.

And so I think just even the concept that there are 20,000 plus different proteins, if you were to ask people in society, most people wouldn't know that.

Yeah, no question.

And I get the dietary protein thing a lot. Like if you start talking about proteins, like. Oh, you mean like plant protein or animal protein? Like what is that?

And I mean again, even think about like you can go and buy collagen or you can buy like it's all around us.

Yeah, just I can tell by your hair that you are an avid user.

Of collagen all the time. Just Today I just did it.

So.

So I think that's. That's a question. So as a community, are we doing enough to actually.

To influence the broader public conversation and bring proteomics to the forefront?

Okay, I think Ben and I are kind of maxed out.

Okay.

But as a community, I think we could do more.

No, you mean, like, we need to do more? But, but even. But like, think about, like, if you had a proteomics department, if you had a national institute, what's the NHL RGI or whatever.

Like, if you had the proteomics version of that. You know, I think that's when you start getting. They start. Like you said, it's like exposure.

Like, you know, we know where we send things, get it sequenced at the sequencing core. And then people are like, let me. How does my doctor know? Oh, I need to send this to the protein sequencing core. I think it just needs to.

If it would help though, if you had named resources around and then it would start sinking into people. But, man, I, I don't, I don't know. I mean, my kids know proteins, but like, I. Yeah, get Ms. Frizzle to, to do it.

Yeah.

Wait, no, no, wait, there's. I mean, we're not answering your question. I mean, okay, Osborne, you know, your dream is we need the program, right? We need a natural degree, right.

If people, people could get genetics degrees forever.

Right?

So is it a degree? Do they see it out and about funding institutes, whatever.

Right? Are there, Are there news articles saying about how a.

There, There are articles all the time about, oh, researchers found the, the gene that controls baldness. But I. You just don't see the same scale of, hey, we found the protein that is responsible for this disease or.

But that's why this. All these, you know, the last however many months for the UK Biobank is such a big deal. Like, and maybe that's.

You know, you need it to. Okay, so it's making an entrance again.

Yes.

How do we make it not, like, be bad?

Well, I think maybe as a community, we are also a little too careful there. We had a really bad false start. But how many thousands of papers about RNA SEQ have necessarily led to incredible scientific discoveries?

Yeah, no, people are quick to brush the RNA microarray under the table. And there were, there are hundreds of millions of dollars spent on, you know, on RNA microarrays that really weren't all that good at the time. Right.

The machining tolerance wasn't good enough. The algorithms weren't in place to do it really well. Not a lot of stuff came from this. Right. You can do 100x sequence coverage right.

Pretty easily now on these instruments, but we were able to do 20x sequence coverage 15 years ago. Is, is doing 100x solving the problem or is it just filling up hard drives? Right.

But, but we're maybe we're a little more forgiving of the fact that that hasn't had a lot of success. And then proteomics is, you know, only just now starting to have like some like really tangible effects. Right. That, that are getting out there.

I think though, there will be breakthroughs.

I feel like the glp one thing, you know, like we can argue like it's a protein, you know, like it's going to help enter the public conscious. We're gonna have these big studies happen that are going to enter companies are going to start offering these assays that are not just like a thing.

I mean, so it feels like it should, should be entering public conscience as a real thing, like as a just a day to day concept.

So that's a, that's a perfect place to end. I look forward to the conversation.

When somebody walks up to me and instead of saying, oh yeah, that's in your DNA, that's in your genes, they're like, oh, that's in your amino acids, that's in your proteins.

Like your PTM is wacky.

So thank you both so much for joining me today. This was super fun. I really appreciated all of your perspectives and so thank you again.

Thanks for having us on.

Absolutely. And as a reminder to the audience, this has been translating proteomics.

Please join the conversation, hit us up with comments, send us email and let's keep the conversation going.

Okay? Thank you guys. That was awesome. I'll stop us recording now.