NewsMedical speaks with Julien Wist about how NMR-based metabolomics could strengthen infectious disease surveillance, zoonotic threat detection, and pandemic preparedness. Drawing on his work in molecular phenotyping and collaborations across the International Phenome Center Network, Wist discusses the clinical promise of rapid metabolic screening, lessons from COVID-19, and how platforms from Bruker BioSpin could help bring robust, scalable phenotyping closer to frontline healthcare.
Could you please introduce yourself and your current work?
I’m Julien Wist, a professor of computational spectroscopy at Universidad del Valle in Colombia and an adjunct professor at the Center for Computational and Systems Medicine in Australia.
Over the past five years, I have focused on developing new technologies for measuring the molecular phenome, with the goal of improving our understanding of human biology and supporting preventive medicine through more effective health monitoring.
For zoonotic infections, what kinds of early systemic changes can metabolomic profiling reveal that are typically missed by virology, genomics, or standard clinical chemistry?
I don’t tend to think of other technologies as “missing” the target. In biological discovery, all available data has value - even if integrating it remains a challenge. The real test comes when translating those markers into clinical use. To be effective in practice, biomarkers must be robust, but just as importantly, they need to be quick to measure so they can meaningfully inform treatment decisions.
Reflecting on recent pandemics and the reality of lockdowns and quarantines (I personally spent a total of four weeks in quarantine in 2020), it becomes clear that we need tools capable of detecting active viral infections within minutes. This kind of speed is critical, for example, in determining whether a passenger can safely board a flight. These tools must also be cost-effective, enabling frequent monitoring, potentially every few hours, to quickly identify and isolate new cases.
Metabolic phenotypes deliver such kind of information, in the form of anti-viral compounds that are produced by the body at very early stages of infection and readily eliminated in the urine. Such a technology could be a game-changer in the event of a new pandemic.
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Using COVID‑19 as a model, what are the strongest examples from your work where NMR‑based metabolomic signatures directly changed how clinicians thought about a “respiratory” zoonosis?
NMR-based molecular phenotyping quickly revealed the systemic nature of COVID-19, allowing us to anticipate the risk of long-term sequelae before they were widely recognized, and, as it turned out, those concerns were well founded. Because NMR-based phenotyping can be applied to large and clinically diverse cohorts, it enables comparisons across different medical conditions, helping to identify shared disease signatures and inform treatment decisions even before the underlying mechanisms are fully understood.
At the same time, the inflammation signatures and viral infection markers we identified while studying SARS-CoV-2 have implications that extend well beyond COVID-19. And it is fair to say that the healthcare emergency accelerated our work towards translation into the NMR benchtop system, and as a result, many key biomarkers could now be measured at a fraction of the cost.
How realistic is it to use metabolic phenotyping as a front‑line triage or surveillance tool in such contexts, and which specific panels do you see as most informative?
It is realistic, and as a matter of fact, we have already installed a NMR benchtop system in a hospital ward for testing. Addressing the remaining technical challenges, particularly around sample collection, is likely to be more straightforward than driving a shift in mindset within the clinical community.
We should aim to use all available data rather than limiting ourselves to predefined panels, especially when the technology can capture comprehensive molecular information in a single experiment. The greater challenge lies in ensuring data quality. Our models will only be as strong as the medical records clinicians are able to share. To build robust and reliable models, we need to systematically compare molecular data with well-annotated clinical information.
What aspects of the International Phenome Center Network (IPCN) pre‑existing infrastructure or culture most enabled the rapid, high‑quality metabolic profiling effort once SARS‑CoV‑2 arrived?
Scientific networks are incredibly valuable because collaboration is built on trust, and networks help establish and strengthen that trust among their members. This enables faster progress by allowing researchers to share raw data, parameter sets, and protocols in real time, without the delays typically associated with the publication process.
In the case of the IPCN, this exchange is even more seamless because all members use the same technology. What works in one lab can be readily applied in another, and datasets are inherently compatible - meaning your data can directly extend mine. This creates a powerful network, not just of collaborators, but of distributed capabilities across the globe. It allows biospecimens to be analyzed locally while contributing to a broader, globally integrated understanding of disease.
Turning to technology, what do you see as the core advantages of NMR‑based metabolomics, particularly on the Bruker Avance IVDr platform, over purely MS‑based approaches when it comes to large‑scale, standardized phenotyping for emerging zoonoses?
Today, NMR-based phenotyping is much more robust and can be deployed in multiple sites that produce comparable data. Only a handful of MS-targeted assays could say the same.
NMR is often dismissed due to its low sensitivity, but this is more of a limitation for biological exploration than for clinical translation. Diseases tend to have a strong impact on the body and are therefore relatively easy to detect, even if they are harder to fully understand.
As a result, biomarkers are often not highly disease-specific, particularly those measured in systemic fluids such as blood and urine. In this context, a robust NMR-based panel is sufficient to screen patients in a triage setting. This does not exclude the subsequent use of more complex and time-consuming MS experiments to obtain complementary diagnostic information.
These follow-up experiments can be performed on the same samples, since NMR is non-destructive.
From your hands‑on experience, which features of the Bruker Avance IVDr platform were most critical to achieving reproducible results during the COVID‑19 emergency?
That would be the external calibration procedure with electronic spiking that allows for absolute quantification.
Where do you think the Bruker Avance IVDr NMR platform could be most strategically deployed to maximize their impact on surveillance and early characterization of new zoonotic pathogens?
Well, this depends on what system we choose to deploy.
The Bruker Fourier 80 benchtop platform has a massive advantage in terms of costs, operation, and maintenance. If the application is for airport quarantine, there is no choice. If NMR becomes mainstream for triage at the hospital, even the Bruker Avance IVDr (600 MHz) platform could be economically viable.
What evidence or validation studies would you prioritize now to convince health systems and funders that investing in NMR metabolomics should become a core pillar of future infectious disease surveillance, zoonotic threat detection, and broader health emergency preparedness strategies?
Again, this depends on the application.
If we can make it work for detecting active viral infections, there is no doubt that acceptance would increase. But some more biological understanding is needed.
We have made some progress recently by showing that those markers are excreted very quickly from the body, meaning individuals will be negative quickly once the viral load is under control. This is an important point for a test. But we still need to establish which viruses trigger these markers and that the test is not confounded by other medical conditions, such as bacterial infections, etc.
How do you envision the role of metabolic phenotyping evolving as a key element in global infectious disease surveillance over the next decade?
If you had asked me five years ago to look for markers of active viral infection in urine using NMR, I would have politely declined. But NMR-based phenotyping is cost-effective, and it makes sense to phenotype all available biobanks and place instruments directly in clinical wards.
At our last IPCN meeting in September 2025, we set a goal of acquiring one million phenomes. It will be interesting to see what emerges from that scale of data.
About the Speaker
Julien Wist is a Professor of Computational Spectroscopy at the Universidad del Valle in Colombia and an Adjunct Professor at the Center for Computational and Systems Medicine in Australia. His research focuses on developing technologies to measure the molecular phenome, with the aim of advancing our understanding of human biology and enabling more effective health monitoring. Through his work, he seeks to support the development of preventive medicine and personalized healthcare approaches.
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