On this episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer discuss their recent experience at the 2025 US Human Proteome Organization conference or US HUPO. Their conversation covers:

·      The rising use of multiple proteomics platforms

·      Advances in multiomics

And

·      What they hope to see at the next US HUPO

Chapters:

00:00 – Introduction

01:47 – Things Parag and Andreas were most excited about going into US HUPO

06:19 - Trends Parag observed at US HUPO

·      A bifurcation between studies that focused on measuring many proteins and those that focused on a specific biological process

·      People increasingly using multiomics to wholistically understanding biology as opposed to a means of comparing the different omes

·      A shift to researchers using multiple proteomics platforms

11:44 – The rising prominence of proteoforms at US HUPO

15:50 – The future of proteomics as informed by US HUPO

18:06 – What Parag and Andreas hope to see at the next US HUPO

19:57 - Outro

Foreign.

human Proteome Organization Conference or USHoopo.

Their conversation, the rising use of multiple proteomics platforms, advances in multiomics, and what they hope to see at the next US Hoopoe.

Now here are your hosts, Parag Malik and Andreas Humer.

Welcome to Translating Proteomics.

As you may know, Andreas and I recently attended one of the world's premier proteomics conferences hosted by the US Human Proteome Organization in Philadelphia.

These conferences are incredibly exciting events where you get to hear from people expertly using and developing proteomics to advance our understanding of biology.

Attending these conferences gives you the unique opportunity to meet with thousands of the best proteomics researchers in the world who are truly at the cutting edge of biomedical research.

Today, we're giving you a sort of inside look at the conferences by sharing our key takeaways and what we think they mean for the field.

One of the things I'd like to point out just before we really dive in is that US Hoopoe really is one of my favorite meetings to go to.

It has a tremendous focus on early career research, advancing careers of scientists in proteomics.

The environment and culture of the conference is incredibly warm and supportive and it really is a community that is trying to globally advance proteomics as both the toolkit and the application.

Just to start off, Andreas, what were you hoping to learn going into this US Hoopoe?

I was actually going to Hoopoe to see how the field was talking about the complexity of the proteome.

In the past, many presentations catered to the notion that we can find important biology if we just get a little bit more sensitive or have better algorithms to interpret the data and make incremental improvements into technology.

However, this notion is slowly being replaced with the perspective that we need new tools and we need new approaches.

So I'll give you one example.

Where proteome complexity is best highlighted is actually in the continuing challenge around analyzing proteins from human plasma from a biological and diagnostic perspective.

There's obviously a lot of excitement around human plasma proteome and the research area and the way we think about addressing the proteome complexity has been reignited now with the arrival of new tools, affinity based methods, joining a mass spectrometry based methods which also by, you know, improve throughput and sample prep through sample preparation and faster more sensitive mass spectrometers.

But those tools that came to the market the last 18 months have now really complemented what Mass spectrometry can do.

So really thinking through and seeing this complementary approach to addressing complexity in the human plasma proteome was very important and very interesting to see during oppo.

That's interesting.

Really what you're talking about is a new trend in proteomics moving away from the perception of, oh, we need to get deeper.

Once we get deeper, we're going to see something to now saying, you know what, we have the capacity to interrogate the proteome quite deeply.

And so now we're not waiting anymore for either incremental advances in technology or transformative advances in technology.

But we're, we're applying what we've got and, and uncovering things.

And so that slight mind shift around, we're almost there towards, all right, we're poised to already be advancing our understanding of the proteome in biology.

I agree.

It's really the standard now.

But you can also go almost 5,000 proteins deep into plasma.

And so I think, as you say, we have now the tools to reproducibly observe a very large portion of the Hemoplasma proteome, to actually conduct very large scale studies.

And I think that is really a major development that has been coming for almost, almost over two decades.

So thinking about the conference, what were you expecting to learn or what were you most excited about to learn when going into this Hupo season, I'm always.

Really curious to hear two things I'm listening for.

What are the technological advances that the field has made?

And two, how have those advances led to advances in our understanding of biology?

And what have people done to really push our understanding of the proteome and its role in fundamental biomedical processes?

And I think that from, from that standpoint, I saw both of those firmly on display at the meeting this year.

There were a number of really exceptional talks, both pushing the boundaries of scale, thousands of sample studies speed really moving very quickly.

But also you saw talks such as by, by folks like Forest White who were really digging deeply into signaling processes and using proteomics methods as a critical part of the preclinical workflow, transitioning ultimately into clinical workflow.

There was also a really amazing talk by Mark Blazer from Brigham and Women's where really talking about heart disease.

And so you saw proteomics having impact across the wide spectrum of biomedical diseases.

Some of my key observations in trends that I was seeing this year, one that we were seeing more of these very large scale studies being presented, I actually saw this year more than ever a bit of a bifurcation that I think was intentioned between a set of studies that were very, very large scale and a set of studies that were very focused and narrowly looking at biology on purpose because they were testing a specific hypothesis.

I think one other trend that I observed was really about multiomics that we saw a tremendous number of presentations on people integrating proteome and metabolome, proteome and transcriptome.

In the past a lot of the multiomics studies had been focused on what's the relationship between the transcriptome and the proteome as opposed to how do these different pieces of information add together as a synergistic whole to help us understand biology better.

The third really significant trend that I saw was a multi platform view of proteomics.

It was no longer I do absolutely everything with one particular mass spectrometry technique.

It was a mix of multiple techniques, whether it was BioID or DIA alongside DDA and some PTM analysis as well as we seeing groups bringing in OLINK and other technologies together with the mass spectrometry.

And so that that multi omic and multi platform.

This really was a huge transition that I saw this year.

One other thing that I didn't see that just is a note of awareness for me to pay attention to in the future.

With the advances in many of these technologies, it isn't totally clear how to integrate them with each other.

The data characteristics amongst these modalities are very distinct from each other.

The scale of these technologies are very different from each other.

Also the quality attributes of do I really trust this quantitative difference to be biologically meaningful or even just statistically meaningful?

You saw a wide range of different approaches with some groups really reliant upon a single fragment ion in a DIA spectrum to declare something, a confident identification and quantification and other groups saying no, I need to see 6, 10 peaks or in order to be really confident and aggregating across.

So I did feel like there was some dispersion in our standards as a community around what is a high confidence quantitation, how do we know?

And maybe there's some additional work that we need to do as a field on defining quality for experimental data.

Yeah, I think Parag observed the same discrepancies in being able to combine the data and the insights from various platforms.

I think that's still an evolving area of research.

How do you make sure the protein measured on one platform is really represented on another platform?

Whether that's from the identification perspective or from the quantitative perspective.

And we see still very many Venn diagrams in that space that don't have a lot of overlap.

But I suspect that there's actually a scientific reason underpinning that those observations that in fact some of these platforms may actually pick up differences in proteoforms, for example, that are not easily reflected in the current way that we present those data in terms of protein groups or protein readouts.

So it's going to be interesting to see how that evolves in the next few years and we should probably come back and look at that, as you said.

Absolutely.

There was a.

So in a session that was focused on proteomics beyond mass spectrometry, we had a number of studies presented there that were a mix of multiple platforms.

And the question when you find discordances when you're looking at the exact same protein, is it because of changes in the proteoform that we have post translational modifications in places where affinity reagents might bind, is it because we have changes in isoforms that change which peptides are observed in the diagnosis?

So I think there's a lot of, there's a lot of work to understand where we can reasonably integrate the platforms and how.

But it's exciting that people are moving towards a multi platform view as opposed to this is my method and this is the only method I use.

Hopefully in the future we see this reflected in more presentations, but also more technologies that focus on proteoforms.

Capturing those small details.

I definitely saw a much larger emphasis on proteforms at this meeting and in general I saw a greater emphasis on not just can we measure this protein, but what is the right resolution that we need to measure this protein in order to capture the biology.

So there is definitely some, some divergence amongst one set of research which is hey, I measured 2,000 proteins or 3,000 proteins or 4,000 proteins and claiming success just by sheer n versus hey, I put this all together and here's what I learned and it's nice to see that evolution towards more and more of the here's what I learned about the biology rather than simply the I measured more proteins than you did.

What did you see at usupo around protein farms in particular?

I think in terms of proteoforms it really started very early on in the meeting with this future of proteomics and Neil sharing a view that we need an atlas for proteoforms and that we need to start thinking about not just the abundance of proteins in general, but how one modification, a combination of a splice variation or a truncation and a multiple phosphorylation, what does that do to protein function?

How does that maybe impact protein localization?

And I think those are questions that emerging tools like what we're developing in Nautilus are going to be able to help us to answer.

And I think what I saw also is that there really are two pieces to that puzzle.

One is the elaboration of what are the proteforms that are out there.

There's a piece of the puzzle which is what is the landscape of post translational modifications which ultimately combine to form proteoforms.

And so there's a discovery effort there, but then there's an action oriented, forward looking effort.

We're saying, okay, if I want to look at a proteoform family or a proteform group in a higher throughput manner across a larger number of samples, perhaps more sensitively, that's where additional technologies can help and be really additive with the existing top down mass spectrometry methods.

Yeah, and agree my observations actually parallel what you just described.

And I think what really the trend is that I see is that the posters that used to catalog huge numbers of PTMs in tissue discovered are now replaced by a much more fine grained, high resolution map of what does this actually mean in the sample, what kind of protein form is present in the sample.

And there's obviously many new methods being developed.

One in particular that I thought was very interesting is the investigators used a top down PRM type approach, which means they monitored in Ms.

Ms.

Mode a particular cross protein family member and were able to actually observe several proteforms of this particular protein.

And obviously there are other posters in top down addressing the field of proteoforms.

I should also mention that there's at least three or four posters on single molecule methods that are starting now to explore the application of proteforms.

And obviously two of those posters were from Nautilus where we discussed the presence but also the characterization of tau proteforms in neural tissue.

And so I think the field is rapidly advancing towards a set of new tools that not only can comprehensively cover a traditional protein list, but they're also starting to really provide a high resolution map of proteins or functional forms of proteins.

So Andreas, as you're capturing your thoughts and what you saw and you think of this conference as a bit of A springboard for the next five years.

What did you see at the meeting that informs where do you think the field's going to go in the next five years, next 10 years?

The organizers actually had specifically scheduled a meeting that I attended, a workshop that talked about the future of proteomics and there were three speakers that peaked into the future, including my co host Parag.

Here.

There were three perspectives which included the study of protoforms and the high resolution map of the proteome.

And that was advocated by Neil Kelleher from Northwestern University.

There was also a perspective around the future of proteomics in the context of medicine and how proteomics would integrate into medicine, where proteomics is another important axis of reducing suffering and guiding decisions in health and well being.

Perspective that was put forward by Jennifer Vanike from Mount Sinai.

And then the first perspective was from you, Parag.

What was your perspective?

I thought that was a really fun session and huge thanks to John Yates for organizing it and taking advantage of bringing together a really wide, wide set of perspectives.

I really tried to focus on the very longer term view.

We've seen a lot of advances in this last year around the role that AI is playing throughout society.

And what I tried to elaborate were how could AI help us with both proteomics researchers and biomedical research in general, thinking about the way that we write papers and thinking about the way that we design experiments, anticipating 10 years from now entities like cloud labs that are able to execute experiments and AI tools that are able to help us understand.

All right, help us refine our questions to design the most efficient, impactful set of experiments and how to analyze and interpret that data.

So really I, I focused on that, that intersection between AI and, and proteomics slash biomedicine.

So Andreas, we've talked a little bit about the far future of proteomics.

Just to wrap up today, based on what you saw at ushupo, what are you anticipating seeing?

What would you like to see at US HUPO next year?

I would like to see the continued trend of scientists using multiple methods, multiple approaches to really study proteins and proteomes in detail.

And then I think the other trend that we mentioned here is that we hopefully see a continued focus on disease specific questions rather than simply just method development efforts.

And so I think the next few years what we'll see is a much bigger focus on how do we actually functionally understand the proteome and do this as comprehensively as possible.

That's super.

I think for me, what I'd really like to see next year is very much along the same lines.

I love seeing the stories where it's very clear that the proteome is in the driver's seat of the biology, whether it's changes in a particular protein's abundance leading to something or its changes in signaling.

And how can we use the full canon of technologies of site specific labeling, of chemoproteomics, of spatial proteomics, of intracellular multiple compartment proteomics to tell a really detailed story about protein based regulation and how it interacts with other OMs to drive a very clear biological phenotype.

I love those stories.

I love seeing us expanding on them and would really love to see more of that next year.

Well see you and all other listeners at the next Topo conference.

Absolutely.

Absolutely.

Well, thank you everyone for joining us today on this episode of Translating Proteomics.

Please do hit us back in the comments.

What were your favorite things that you saw at us?

Hoopoe?

What are the things you'd love to see going forwards?

And I look forward to chatting with you again on our next episode of Translating Proteomics.

Also, to let you know, in the future, we're planning to do a question and answer Ask Me Anything version of Translating Proteomics.

So if you have any thoughts or questions, please do shoot those over to us at TranslatingProteomicsAudalyst Bio.

TranslatingProteomicsAudrobat Bio.

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