With their enthusiasm, creativity and fresh perspective, young researchers are often drivers of innovation. Early-career scientists are more likely to study 'hot and novel' topics compared with their older counterparts, according to a text analysis of more than 20 million biomedical papers in the last 70 years, published in the US National Bureau of Economic Research.
At the same time, the odds can sometimes be stacked against young scientists, who face a host of challenges their veteran colleagues may not: establishing credibility, building prestige, and gaining access to grants and other resources. To give the most promising ones a leg up, the National Research Foundation Singapore (NRF) launched the eponymous NRF Fellowship in 2008. Since then, more than 100 early-career researchers from all over the world, in fields ranging from infectious diseases to microelectronics, have been awarded fellowships.
In 2020, three A*STAR scholars continued to uphold that tradition of excellence. Sarah Luo, Caroline Wee and Kaicheng Liang were each awarded a S$3 million grant to respectively carry out ground-breaking research in metabolic circuits, gene-diet interactions affecting food choice, and tissue pathology. The powerhouse trio will conduct their research in Singapore at an A*STAR host institution of their choice over the next five years. In this feature, we delve into the impact and inspiration behind their work.
Mapping the mechanisms of metabolism
As anyone who’s ever tried to stuff themselves during a buffet will know, we can tire of the same food rather quickly, no matter how good it tastes. But is there some internal mechanism beyond our conscious taste system that tells the brain we’ve had too much of a particular kind of food?
This mechanism, and how it occasionally malfunctions and leads to disordered eating behaviors and metabolic diseases, is what Sarah Luo, Senior Research Fellow at A*STAR's Singapore Bioimaging Consortium (SBIC), intends to explore. Her research will define the neural circuits between the brain and the different organs involved in metabolic regulation, with a particular emphasis on the liver. Following this, Luo will investigate how dysregulation in such circuits can lead to health conditions like obesity and diabetes.
“Our brains act as master regulators of metabolism,” Luo said. “But how does the brain get information from the body to coordinate its regulatory function?” Studies on metabolic neural circuits have so far emphasized communication between the brain and the gut, with its associated microbiome, but Luo chose to focus on a nearby, lesser-spotlighted neighbor.
“The liver is a major metabolic organ; it receives digested nutrients from the stomach and intestines and processes these in response to the body’s changing needs. So it’s in a prime location to sense incoming metabolic substrates,” Luo explained. “I am investigating how the liver acts as a nutrient sensor and feeds metabolic information back to the brain, as well as how the brain, in turn, regulates liver function through neural circuits.”
Mapping body-brain circuits may be basic science, but the techniques required are far from fundamental. Luo will be studying peripheral neural circuits in mice from the molecular and cellular to system-wide levels. She intends to conduct single-cell analysis of the neurons connecting the liver and brain to identify unique gene signatures, and use a new tissue-clearing technology that will render the brain and liver transparent for clearer circuit imaging. She will also use single-cell imaging of neural activity to identify neurons that respond to infused nutrients such as sugars or fats.
“Evidence has accumulated that dysregulated neural circuits can contribute to metabolic diseases,” Luo said. “If your nutrient sensors are desensitized, you could end up in a vicious cycle where your brain acts in a nutritionally deprived state even though you are already consuming a lot of fatty and sugary food.” By mapping these circuits, Luo hopes to contribute to emerging therapies for metabolic diseases, such as developing neural devices that can stimulate relevant peripheral nerves in patients.
Fish are friends in understanding food
In science, inspiration can come from anywhere. In Caroline Wee’s case, it was from briefly experimenting with the trendy ketogenic diet. This low-carbohydrate, high-fat diet many swear by forces the body to burn a different type of fuel—fat, instead of the usual sugar—which has been said to promote weight loss and other health benefits. Trying out these ‘keto’ meals, Wee observed changes in her appetite and cravings. However, she was surprised at the lack of understanding of underlying mechanisms. Such observations sparked her interest in dissecting how our genes and diet interact to affect our appetite and food decisions.
Key to Wee’s project is the diminutive zebrafish, a tropical freshwater fish with a genetic and anatomical structure surprisingly similar to humans. Wee, who is a Research Fellow at A*STAR's Institute of Molecular and Cell Biology (IMCB), has worked extensively with zebrafish, having chosen them for their simplicity and capacity for high-throughput experimentation. The fish is also transparent at their larval stages, allowing her to comprehensively examine whole-brain and body mechanisms controlling feeding behavior.
“There’s evidence that both an animal’s nutritional needs and the nutrient cues it’s exposed to can change the amount and type of food it chooses to eat. But as we all know, biology is complex; for example, a high-fat diet could enhance or suppress appetite depending on the context,” Wee said. “One such important context is our genetic makeup,” she continued, noting that many human studies have identified genes correlating with dietary preferences and effects, but have yet to successfully establish causality. Furthermore, the microbes in our guts, as well as environmental factors such as stress, are also important players in these decisions.
A neuroscientist by training, Wee plans to use optical, molecular and circuit dissection techniques to explore the underlying gut-brain signaling mechanisms. Then, by selectively mutating genes associated with, say, fat preference or obesity in humans, Wee hopes to draw causal links between genetic makeup, metabolism and eating behaviors. “This will really open the door towards precision medicine and nutrition, where the fish can then be used to screen for therapeutics that target specific genetic predispositions,” she added.
Apart from identifying potential therapies and interventions for humans, Wee hopes her research will also benefit her aquatic subjects. With food security concerns at the fore and Singapore aiming to produce 30 percent of its nutritional needs by 2030, Wee intends to apply her work directly in aquaculture, particularly fish farming. “Fish feeding and growth optimization is a big bottleneck in food production,” she explained. “If we can figure out when, what and how best to feed these fish, we could expect to see huge gains in aquaculture health and productivity, directly benefiting local industries and society.”
Using AI for an extra pair of eyes
When cancer patients undergo surgery, doctors try as much as possible to remove all traces of cancerous tissue. Their margin of error is literally microscopic—any malignant cells unwittingly left behind will result in the disease’s recurrence. To reliably check for cancerous tissue, pathologists sometimes carry out microscopic analysis during surgery, a time-consuming process in an event where every minute counts.
Speeding up this process is what Kaicheng Liang, a Team Leader and Research Scientist at A*STAR's Institute of Bioengineering and Nanotechnology (IBN), aims to do. His research looks into developing tiny endoscopic devices for high-resolution optical imaging, which will facilitate the instantaneous diagnosis of cancerous tissue among other applications in tissue pathology. “I want to put these devices inside the body and get pictures of tissue that are so detailed, it’s almost like real microscopy,” Liang explained. “With this real-time information, doctors can get faster feedback during surgery and make better decisions, which hopefully will lead to better outcomes for patients."
To ensure the pictures of tissue are not just taken but also examined in real time for instantaneous diagnoses, Liang will combine machine learning with endoscopic microscopy. For example, the technology can rank pictures by severity so surgeons know which areas to first prioritize. Artificial intelligence (AI) can also help doctors to overcome another key challenge: that of high-speed imaging during surgery leading to lower resolutions. Machine learning can be used to enhance these images, though care must be taken to ensure the AI makes responsible inferences for accurate cancer diagnoses, Liang said.
Another hurdle lies in making the devices small enough for different types of surgery, including keyhole surgery. To meet this size requirement without compromising too much on image quality, Liang intends to incorporate micro-sized motors and use their mechanical motion to improve imaging performance. To this end, working with doctors, engineers and other researchers will be crucial and Liang has already begun building a network of collaborators within IBN and A*STAR as well as the broader Singapore-based biomedical ecosystem. “I’ve been pleasantly surprised by how easy it is to form collaborations, with IBN and A*STAR being such interdisciplinary places,” he said.
Lasting collaborations will be essential as Liang’s project, a type of use-inspired basic research, could take up to a decade—from working prototypes in limited patient trials within five years to eventual approval by the US Food and Drug Administration. “I’ll still be alive then,” he said, unfazed. “I’ve got easily 30 years of this work to go. I can definitely see this happening within my lifetime.”