How former stock market trader Barry Scott sated his appetite for research by undertaking a PhD in bioinformatics.
How does someone make the leap from stock market trader to bioinformatician?
Having completed degrees in maths at Trinity College Dublin and Dublin City University, Barry Scott spent 14 years trading in the financial markets. He loved the autonomy of his work, the opportunities to innovate, and collaborating with colleagues in software development and data science.
He also loved the research element of his work. “You either made money or lost money in the markets so you could easily tell if your ideas had value,” Scott explains.
In his spare time, he completed biology courses which he found “fascinating”.
“The pace of change in biology is really fast and it’s increasingly becoming data intensive.
“I wondered whether I could transfer my data and quantitative skills to a domain where they could contribute to scientific breakthroughs.”
Scott returned to academia to complete a MSc in genetics and cell biology in University College Dublin, and he is now in his fourth year of a PhD in bioinformatics at Trinity.
He credits the success he enjoyed as a trader with giving him the confidence and resilience to navigate the challenges of interdisciplinary scientific research, “where diverse experiences propel innovation and progress”.
Here, Scott tells us about his work on biological datasets and how it has led to breakthroughs in obesity research.
Tell us about your current research.
My current research focuses on a molecule known as N-lactoyl phenylalanine, or Lac-Phe for short, which we’ve discovered increases following treatment with the diabetic drug metformin and also after eating. The path to these discoveries was anything but straightforward, marked by a series of serendipitous events.
I was working on an obesity dataset that my supervisor Prof Lydia Lynch at Princeton University had compiled from diabetic and non-diabetic volunteers. Intriguingly, we noticed that certain metabolites were elevated in the diabetic subjects. However, a curious case of one diabetic volunteer not showing expected high levels led to a breakthrough; the volunteer had not been taking their prescribed metformin, suggesting that it was metformin, not diabetes per se, that was impacting metabolite levels.
We pursued this lead, confirming our results in larger studies. Initially, the excitement waned when we discovered that the metabolites had been misidentified. The metabolites influenced by metformin were in fact related to lactate – which was known to be affected by metformin. However, chance intervened once more when a new study identified Lac-Phe, one of these lactate related metabolites, as an appetite suppressant. This aligned with metformin’s appetite-suppressing effects and opened a novel avenue of investigation into obesity management.
Our hypothesis gained further support when, after reviewing over a hundred datasets, I observed a consistent increase in Lac-Phe levels post-meals, suggesting its role as a satiety signal in this context too. This discovery set off a frantic race to publish our findings amidst fears of being ‘scooped’ by a Stanford research group, who had similar results pending publication in Nature Metabolism.
Encouraged by Prof Jon Long, the leader of the Stanford research group, Lydia swiftly contacted the editor of Nature Metabolism. We were told that if we could submit our findings quickly –confirming and extending the Stanford group’s work – we could be included in the upcoming issue. This led to a whirlwind period of intense writing and revision. Prof David Finlay, my supervisor at Trinity College Dublin, took the unusual step of personally crafting the figures, essential for conveying our findings effectively. Thanks to countless late nights and collaborative effort, our paper was successfully published, contributing a significant piece to the puzzle of how metformin influences metabolic pathways and appetite.
In your opinion, why is your research important?
The criticality of my research is illuminated against the backdrop of the obesity epidemic – a pivotal driver of type-2 diabetes, which now affects one in five Irish adults, according to the 2022 Eurostat report. This rise parallels a global increase in diabetes cases, tripling over two decades and imposing a considerable economic burden, as seen with the staggering €149bn allocated for diabetes management across EU healthcare budgets in 2019. The human toll is equally severe, with diabetes-related complications claiming 114,000 lives annually in Europe.
In this challenging context, my research is particularly significant as it sheds light on metformin’s mechanism of action, the most commonly prescribed medication for type-2 diabetes. Our discovery that metformin boosts levels of Lac-Phe, a natural appetite suppressant, opens new doors in understanding how this drug reduces hunger.
Simultaneously, GLP-1 receptor agonists such as semaglutide have emerged as transformative in managing obesity and type-2 diabetes. These medications work by mimicking an incretin hormone, leading to decreased appetite and improved insulin secretion. Exploring small molecule treatments that can emulate Lac-Phe’s effects might offer an orally available complement to GLP-1 therapies, potentially ushering in a new era of obesity and diabetes management.
By extending our understanding of how Lac-Phe operates and its modulation by metformin, we could be on the cusp of developing new anti-obesity strategies. Such interventions could be invaluable in the quest to curtail the expanding public health crisis posed by obesity and diabetes, offering a beacon of hope for safe, effective and inclusive treatments.
What are some of the biggest challenges or misconceptions you face as a researcher in your field?
One of the most significant challenges I encounter as a bioinformatician is the evolution of the field from being dominated by traditional wet lab experiments to one where large-scale data analysis is becoming increasingly crucial. The perception that true discovery is confined within the walls of a wet lab persists, yet bioinformatics opens a vast array of opportunities. The ability to analyse extensive datasets often outpaces the timeline of wet lab experiments, facilitating more rapid advancement in research.
However, this shift comes with a reliance on the foundational work of wet lab scientists. The quality and availability of data are paramount; without meticulously conducted experiments to produce these datasets, our capacity to extract meaningful insights would be severely limited. For instance, in our recent study regarding metformin’s impact on Lac-Phe levels, we leveraged open-source datasets to substantiate our findings. With these datasets – based on interventional studies – we were able to establish a causal relationship between metformin and increased Lac-Phe.
Yet, there remains a dependency on the generation of new experimental data to fill the gaps in our understanding. For example, while we could corroborate the increase of Lac-Phe due to metformin, elucidating the endogenous pathways leading to Lac-Phe production required targeted experiments that had not been previously conducted. This was adeptly addressed by the Long Lab at Stanford, whose experimental work provided the missing pieces.
Perhaps a misconception in our field is the underestimation of bioinformatics as merely a supplementary tool, rather than recognising its capacity as a powerful driver of discovery. Bridging the gap between bioinformaticians and experimentalists, and fostering collaborative efforts, is essential to overcome this challenge and to continue propelling the field forward.
How do you encourage engagement with your work?
Initially, I was quite reserved about promoting my research, partly due to my previous career in trading where discretion was paramount. However, as my work has progressed and yielded findings I am excited about, I have recognised the importance of sharing these insights broadly. Following the publication of our recent paper, I have become more proactive in engaging with the scientific community and the public.
I’ve started to utilise platforms like X more effectively, sharing updates and insights from our research to spark discussions and build connections within the field. This has opened up new avenues for dialogue and collaboration. Additionally, I’ve made it a point to reach out directly to fellow researchers whose datasets have informed our study, as well as those working in related areas who might find our results relevant.
This engagement not only helps in disseminating our findings more widely but also invites feedback and ideas that could shape future research directions. By moving away from the secretive nature of my past career, I am learning the value of openness and collaboration in science, which are essential for driving innovation and fostering a cumulative knowledge base.
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