The Analytical Philosopher

Did you always want to be a scientist?
 

I’ve always been interested in science and found it intriguing. In many ways, I think we’re all scientists – we’re all experimenting, generating hypotheses, and testing them. My grandfather, who was a chemist and a significant influence in my life, encouraged me to think about doing experiments – even when I was very little! But as I grew older, I developed interests in other areas – I was drawn to philosophy in particular. I think if more jobs were available in philosophy and it were more practical, maybe I would have pursued that. I also pursued medicine as it seemed like applied science, but I realized that routine aspects of medicine – seeing patients in the clinic – was not as focused on experimentation as I’d hoped. So, my path to scientific research was definitely roundabout.

Reflecting on your time at Scripps, what were some key lessons you took away?
 

One major lesson was learning to challenge established ideas. As a postdoc, I remember going into Richard Lerner’s office to discuss the results of an imaging experiment. It wasn’t particularly well designed or well executed, but the result was seemingly unexpected. I showed him this black page with a little green speckle, expecting him to tell me it was complete rubbish. But he instead told me how amazing it could be – that it might mean we have to rethink everything we know about neurotransmission. The way Richard – a world renowned scientist – evaluated my seemingly low-quality piece of data in terms of its potential revolutionary impact was extraordinary, and really stuck with me. He wasn’t telling me to publish right away, but he did encourage me to be open to new ideas and test them further. 

I also worked closely with Gary Siuzdak, who had a similar mindset. He and others at Scripps encouraged everyone to discuss crazy ideas that fly in the face of the textbooks, the icons, and centuries of dogma. Most of the time, they don’t go anywhere. But, occasionally, there’s a new discovery at the end of the road.  

As a scientist, you have to be able to think about new data without being biased by conventional ideas, allowing you to generate exciting hypotheses, but also be cautious – you don’t want to broadcast radical conclusions before you have adequate data to support them. You have to be simultaneously skeptical and non-skeptical, which almost seems like a paradox! But if you look at the most successful scientists, that seems to be a shared quality.

It seems like you’ve been open to new directions in your career, like transitioning from medical school to mass spectrometry. How do you reflect on these changes?
 

I’ve basically always followed what's interesting. You can't really contain science, try as we might. There are practical concerns of course. If you have a lab with a certain set of tools and expertise in the team, it makes sense to utilize your available resources. But that can limit your horizons. I’ve always tried to focus on the question and see where we end up. You might end up in a totally unfamiliar area, but that’s exciting and can be lots of fun! I love to learn new things. 

I remember going to my first ASMS and just being totally overwhelmed with excitement. I had no idea you could do all these things with mass spectrometry! Now when I go to ASMS, it’s certainly exciting and interesting, but the amount of new information is much less than it first was. To this day, I still love going to new conferences totally out of my field – it brings back that euphoric feeling of having my mind blown by a whole new area of science and introduces me to new ways of thinking.  

I also think there’s a real scientific benefit to exploring new terrain. I once read that when you hear an unfamiliar language, you perceive a pattern that is inaccessible to someone who speaks the language. In the same way, when you’re embedded in a scientific field, it’s often very difficult to get outside of established paradigms because you get trapped into conventional thinking. But when you enter a new field for the first time, your perspective is completely different to someone who can already “speak the language.” You hear the melody and the rhythm without understanding the words. That’s why I always tell students when they're first starting a new project to carefully journal and log all of their reflections, because those early impressions can be the most transformative.

Is there more we can do to facilitate interdisciplinary work?
 

In my experience as a scientist, which is short relative to the history of science, I’ve seen the community become much more interdisciplinary. Collaborative and multidisciplinary work is now much more welcomed and mainstream. However, challenges remain, particularly around issues of credit. Everyone wants to know exactly what contributions were made, and there's still the constraint that only one person can be the first or last author on a manuscript. Similarly, there can only be one contact PI on a grant. I think we are still a bit too rigid about credit – who gets recognized for what.

Being part of the academic system, I understand the need for quantifiable measures when evaluating contributions, like counting papers and grants for tenure. I appreciate that these metrics are important for assessing someone's contributions to science, but I also think they can be at odds with fostering the collaborative, interdisciplinary work that is increasingly important in our field.

When tackling these problems, do you think more about the potential applications or is it driven by pure scientific curiosity?
 

It’s definitely a mix of both. While the scientific curiosity is always there, I’m also deeply interested in the potential applications. For example, rethinking how we define diseases – moving away from viewing them as localized abnormalities and seeing them as systemic pathologies – could revolutionize how we approach treatment. If diseases like cancer or Alzheimer’s are understood as metabolic dysfunctions that involve all organs and not just the brain or the tumor, it opens up new therapeutic avenues beyond the traditional, localized treatments.

Going back to Plato, there’s an analogy here with The Republic. It’s about understanding that the body functions as an interconnected system, much like a society, and addressing dysfunction requires a holistic approach, as Plato argued. We’re exploring therapies that target organs seemingly unrelated to the disease, such as pharmacologically manipulating the liver to treat skin cancer. It’s a different approach that challenges some conventional ways of thinking but it could lead to important breakthroughs.

What would you say is the most exciting discovery you’ve made in your career?
 

What I've learned is that, for scientists, the most exciting thing is usually what we're currently working on. It’s fascinating – when you talk to Nobel laureates who have accomplished extraordinary things, like redefining fields, and ask them about the most exciting thing they've done, they rarely mention what earned them the Nobel Prize. Instead, they talk about the experiment they were working on yesterday or what they’re trying to figure out today.

I think that the day a scientist says their most exciting work was something from 10, 40, or 50 years ago is the day they're no longer enthralled by discovery. Nevertheless, to try to address your question more concretely, when we think about metabolism, especially in the context of metabolomics, we tend to imagine every cell operating with its own autonomous metabolic program. However, what's really interesting to me is realizing that these pathways aren’t just occurring autonomously in every cell. Instead, cells share metabolic burdens among themselves as a community. The metabolism of one cell complements another, ensuring they don’t compete but work synergistically. For instance, you wouldn’t want neurons and astrocytes, two adjacent cell types in the brain, to compete for the same resources. Evolution has addressed this by making their metabolisms synergistic and highly complementary, where the output of one cell becomes the input of another.

Understanding this cell-level metabolic synchronization is critical, and it's been particularly fascinating to study in the context of cancer. A few years ago, we demonstrated that a single localized tumor can alter the metabolism of cells throughout the entire body, which I still find astonishing. It’s not just the cancer cells with altered metabolism as we typically think; the presence of a tumor impacts every other healthy cell too. Understanding how this works is a huge challenge, but it's something we're very excited about exploring.

Do you have a main ambition for the next five to ten years?
 

I think the next big step is to move beyond static snapshots of metabolism to capturing its dynamic nature. We need to understand what molecules are being exchanged between which cells and tissues. This will require developing better technologies to track metabolic processes in real-time, leveraging isotopes to trace the origin and flow of metabolites. The goal is to get a holistic view of how metabolism operates within the body and which tissues are chemically coupled to one other.

Is there anything else you’d like to add?
 

I’d just like to mention a recent effort introduced by the NIH called the Multi-Omics of Health and Disease Consortium. You asked me about interdisciplinary work earlier, and I think this is a great example of the kinds of challenges we can tackle together through team science. It’s a major effort involving eight different groups with complementary expertise, aimed to advance multi-omics research. We will be generating nine different types of omics data in parallel on the same sets of samples, collected from patients at multiple time points during disease progression. I’m really excited about what we are doing and look forward to seeing what we can discover.