Brian Munsky, a Colorado State University assistant professor of chemical and biological engineering, has received an $800,000 National Science Foundation Early Career Development Award to support his research into modeling gene regulation processes.
The five-year NSF award is one of the most prestigious scientific honors for early-career faculty to support groundbreaking research and teaching.
The award will support Munsky’s unique approach to integrate predictive computational models with precise single-cell data and to investigate one of molecular biology’s most fundamental processes – the translation of individual mRNA molecules to form functional proteins.
“For the first time in history, we can watch the real-time creation of new proteins in single living cells. With detailed mechanistic models, we can also recreate these processes in a computer and understand them like never before,” Munsky said. “Protein translation is central to nearly every biological question, so, understanding this process could revolutionize biotechnology applications ranging from the development of new drugs and vaccines, to the optimization of crops for greater yields, or improved resistance to drought or disease.”
Munsky relates to a famous quote from physics icon Richard P. Feynman that was written at the top of his blackboard at the time of his death: “What I cannot create, I cannot understand.” Feynman sought to remind us that only by reproducing a complex behavior with a theoretical or computational model can we ever hope to truly understand that phenomenon, Munsky said.
Modern, single-molecule microscopy experiments reveal that even the simplest biological processes are every bit as complex as the quantum mechanics and quantum electrodynamics studied by Feynman. So why not use computational models to expose complicated biological processes, too? That’s where Munsky comes in.
History of quantitative biology at CSU
As a Richard P. Feynman Distinguished Postdoctoral Fellow in Theory and Computing at the Los Alamos National Laboratory from 2010-2013, Munsky developed some of the first computational models capable of quantitatively predicting the random activation and deactivation of genes in single cells and in myriad different genetic and environmental circumstances.
“When most biologists believed that gene activation was too complex and too random to be predicted, I made it my mission to predict the unpredictable,” said Munsky.
Predictive models of these random single-cell fluctuations could provide the key to understand and prevent the mechanisms by which bacteria develop resistance to antibiotics or how cancer cells develop resistance to chemotherapies.
Since joining CSU in 2014, Munsky and his collaborators have made substantial progress to advance predictive stochastic or random models for the most basic gene regulation processes. In 2016, Munsky and Timothy Stasevich, assistant professor of biochemistry and molecular biology at CSU, won a prestigious WM Keck Foundation Award to measure and computationally reproduce the dynamics of protein translation at single-cell and single-molecule resolution. Drawing on their unique capabilities to measure and model the precise dynamics of single-mRNA translation, the Stasevich and Munsky teams have made rapid progress to understand, predict and eventually control the unique mechanisms that viruses use to hijack human cells.
In 2017, Munsky was awarded a National Institutes of Health grant to build new software to analyze and interpret single-cell measurements of cellular signals and gene transcription responses. Shortly after, Munsky worked with collaborator Gregor Neuert at Vanderbilt to show how rigorous computational analysis of single-cell experiments could dramatically reduce the amount of data needed to interpret and predict spatial and temporal dynamics of single-cell gene regulation in biological pathways closely related to those implicated in several cancers and autoimmune diseases.
One of the world’s fastest growing disciplines
In parallel with his research to develop predictive models of gene regulation, Munsky has spent 10 years running the q-bio Summer School — one of the world’s most well-known short programs to help graduate students and postdocs apply quantitative models to understand biological systems. More than 500 graduate students have passed through the q-bio program, and like Munsky, many have achieved leadership roles in academic and industrial biotechnology research.
Munsky’s new NSF Career Award will help support development of a new undergraduate q-bio summer school program debuting at CSU in June 2021.
“Quantitative biology is one of the world’s fastest growing research disciplines, yet there are virtually no training opportunities accessible to undergraduates,” Munsky said. “By introducing talented young mathematicians, physicists and engineers to the beauty, rigor and transformative potential of quantitative biology today, we will build a collaborative community capable to tackle the most important biotechnology challenges of tomorrow.”