Faculty awarded funding for high-risk, high-reward research
The National Institutes of Health (NIH), the primary funding agency for biomedical research in the United States, recently recognized three University of Wisconsin–Madison faculty members with its New Innovator Award. The agency announced a total of 58 awards and UW–Madison is tied for second place among all public universities in the nation for the number of faculty receiving them.
Darcie Moore, professor of neuroscience; Nasia Safdar, professor of medicine; and Srivatsan “Vatsan” Raman, professor of biochemistry, will receive more than $6.8 million in total funding for studies that are unconventional yet carry the potential to transform the medical field. Unlike standard research project grants, the New Innovator awards do not require preliminary data and pay out in full in the first year of each five-year project so that work can move forward swiftly.
“Having three UW faculty members awarded highly competitive NIH Director’s New Innovator Awards speaks to the success of our campuswide efforts to recruit the best and brightest early-career research investigators to UW–Madison,” says Cynthia Czajkowski, a neuroscience professor and associate vice chancellor for research in the biological sciences.
The award is part of NIH’s High-Risk, High-Reward Research Program, a funding mechanism the agency says is designed to “(catalyze) scientific discovery by supporting compelling, high-risk research proposals that may struggle in the traditional peer review process despite their transformative potential.”
The three New Innovator Award recipients join Jan Huisken, a professor of biomedical engineering at the Morgridge Institute for Research, who will receive one of 10 Transformative Research awards under the NIH High-Risk, High-Reward Research Program.
Funding from the umbrella program is drawn from the NIH Common Fund, which was established by the NIH Reform Act of 2006 with the idea of supporting forward-thinking cross-disciplinary research. UW–Madison has also taken similar steps to provide incentives for research projects that are risky but may to lead to significant outcomes.
For instance, in 2015, UW–Madison launched the UW2020 Initiative, which uses proceeds from the university’s technology transfer office to fund multidisciplinary teams of researchers proposing innovative research that hasn’t yet received federal grants. Moore and Raman are among UW2020 co-investigators.
In 2017, the university also established strategic funding for the UW Microbiome Initiative; Safdar is among 12 principal investigators supported by that program.
For the NIH High-Risk, High-Reward Research Program, Moore is using novel approaches to determine why aging stem cells become less effective at regeneration; Safdar is leading a team of health care researchers and systems engineers to create a computational model that fights the spread of Clostridium difficile (C diff), a gastrointestinal germ that stubbornly persists in hospitals; and Raman is using high-throughput experiments and computational tools to define the rules by which proteins switch between active and inactive states.
Read more about each project:
Not all stem cells are equal: Understanding the toll of aging on neural stem cells
Moore’s study focuses on why neural stem cells segregate certain proteins unevenly between their two daughter cells when they divide and on why neural stem cell proliferation and new neuron production decrease in the brain with age.
She initially discovered the asymmetry during her postdoctoral fellowship in Zurich, Switzerland, while investigating a diffusion barrier she identified in dividing cells. In the neural stem cells of old mice, this diffusion barrier becomes weaker and the cells are less able to compartmentalize proteins associated with cellular aging. Because aged neural stem cells divide less and make fewer neurons, this may contribute to dysfunction.
“We found polyubiquitinated proteins, or proteins destined for degradation, were segregated to only one daughter cell after the cell divided, and we have subsequently identified many other cargoes that behave similarly,” she says.
With the funding, Moore’s team will assess the mechanisms of asymmetric cargo segregation, use automated microscopy to identify segregated cargoes and further assess their roles, and determine how these processes function in the adult mouse brain.
“Understanding how neural stem cells function normally, as well as in disease and with aging, will help us to identify ways to therapeutically target them to improve their numbers, potentially improving cognitive function,” Moore says.
These findings are critical to developing future therapeutic options for people, she adds: “If you don’t set the foundation, you can’t build a house.”
Computer-based simulation helps hospitals stop germ transmission
As an epidemiologist and infectious disease physician, Safdar has seen far too many patients suffer from Clostridium difficile (C diff) infections, which affect half a million Americans each year. The bacterium causes debilitating, difficult-to-treat diarrhea and infections can also be fatal, causing 29,000 deaths in the U.S. and costing over $1 billion annually.
In a cruel twist of fate, the bacterium thrives in hospitals.
“It got the name because it’s difficult to culture in the laboratory, but its spores are resistant to almost any disinfectant you can think of,” says Safdar.
Hospitals have tried a multitude of interventions to prevent transmission of the bacteria to hospitalized patients, including rapid testing and treatment when cases are first suspected, rigorous cleaning protocols, protective gear for health care workers, and emphasizing correct hand hygiene techniques.
“Unfortunately, the effects of these interventions have been highly variable and modest,” says Safdar.
Safdar is collaborating with a team that includes two UW–Madison engineering professors, Oguzhan Alagoz and Pascale Carayon, to take a systems engineering approach to address the ways the germ spreads.
In 2015, the team created a computational model to simulate C diff transmission in a hospital ward over time. The team will strengthen the simulation model with more data sets from an acute-care hospital, a veteran’s hospital and a children’s hospital, which differ in their C diff transmission risks.
“The goal is to create a simulation model that can be generalized. Every hospital is different, so we want a hospital representative to be able to enter parameters about their facility and predict which steps will be most effective for reducing C diff infections at their site,” Safdar says.
Sensing a switch: Defining the rules and playbook of protein function
Raman’s project is focused on protein allostery, which is the process by which a protein senses and conveys a signal that causes a change in a different part of itself. This shift controls its subsequent activity.
“Allosteric proteins are nature’s switches,” Raman, explaining that allostery is a fundamental property of all proteins. “Allosteric proteins regulate many essential cellular processes required for life.”
When a protein switches between “off” and “on” states, there can be dramatic consequences for gene expression. And just like a broken light switch plunges a room into darkness, unresponsive allosteric proteins can be responsible for many diseases because they can no longer effectively regulate activities inside a cell.
Almost half of all current drug targets are allosteric proteins, says Raman, and yet little is understood about how allostery itself works. His laboratory is deciphering the fundamental rules governing the process by using machine learning and other strategies to look for patterns among different allosteric proteins, probing the role of every amino acid.
If successful, computer modeling could allow Raman’s team to predict the impact of a mutation in an allosteric protein, and how to alleviate any detrimental effects. Deducing these molecular rules could prove challenging, but Raman doing so has applications in biomedicine and biotechnology. Additionally, drug discovery projects informed by allostery data could lead to more specific drugs with fewer side effects, he says.
“The broader vision of my laboratory is to develop these tools to advance precision medicine,” Raman says. “Every day we sequence the genomes of patients with diseases, but we have no clue which protein mutations affect function, and how they do so. Wouldn’t it be great if we could create a ‘lookup table’ or a database of mutations that a physician could use to interpret a patient’s genome?”