Scientists Have Developed a New Way To Study Aging Using Math
Researchers have developed mathematical tools to quantify how quickly cell proteins degrade, offering new insights into aging and disease. Their study categorizes proteins into three degradation rate groups and explores the implications for muscle development, starvation, and neurodegenerative diseases. This method advances our understanding of cellular processes.
New mathematical methods that show the rate at which cell proteins degrade could offer deeper insights into the aging process, according to a recent study co-authored by a researcher from Mississippi State alongside colleagues from Harvard Medical School and the University of Cambridge.
Galen Collins, assistant professor in MSU’s Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, co-authored the groundbreaking paper published in the Proceedings of the National Academy of Sciences, in April.
“We already understand how quickly proteins are made, which can happen in a matter of minutes,” said Collins, who is also a scientist at the Mississippi Agricultural and Forestry Experiment Station. “Until now, we’ve had a very poor understanding of how much time it takes them to break down.”
The paper in applied mathematics presents the new tools that quantify the degradation rates of cell proteins—how quickly they break down—helping us understand how cells grow and die and how we age. Proteins—complex molecules made from various combinations of amino acids—carry the bulk of the workload within a cell, providing its structure, responding to messages from outside the cell, and removing waste.
New Findings on Protein Degradation Rates
The results proved that not all proteins degrade at the same pace but instead fall into one of three categories, breaking down over the course of minutes, hours, or days. While previous research has examined cell protein breakdown, this study was the first to quantify mathematically the degradation rates of all cell protein molecules, using a technique called maximum entropy.
“For certain kinds of scientific questions, experiments can often reveal infinitely many possible answers; however, they are not all equally plausible,” said lead author Alexander Dear, research fellow in applied mathematics at Harvard University. “The principle of maximum entropy is a mathematical law that shows us how to precisely calculate the plausibility of each answer—its ‘entropy’—so that we can choose the one that is the most likely.”
“This kind of math is sort of like a camera that zooms in on your license plate from far away and figures out what the numbers should be,” Collins said. “Maximum entropy gives us a clear and precise picture of how protein degradation occurs in cells.”
Implications of Protein Degradation
In addition, the team used these tools to study some specific implications of protein degradation for humans and animals. For one, they examined how those rates change as muscles develop and adapt to starvation.
“We found that starvation had the greatest impact on the intermediate group of proteins in muscular cells, which have a half-life of a few hours, causing the breakdown to shift and accelerate,” Collins said. “This discovery could have implications for cancer patients who experience cachexia, or muscle wasting due to the disease and its treatments.”
They also explored how a shift in the breakdown of certain cell proteins contributes to neurodegenerative disease.
“These diseases occur when waste proteins, which usually break down quickly, live longer than they should,” Collins said. “The brain becomes like a teenager’s bedroom, accumulating trash, and when you don’t clean it up, it becomes uninhabitable.”
Dear affirmed the study’s value lies not only in what it revealed about cell protein degeneration, but also in giving scientists a new method to investigate cell activity with precision.
“Our work provides a powerful new experimental method for quantifying protein metabolism in cells,” he said. “Its simplicity and rapidity make it particularly well-suited for studying metabolic changes.”
Collins’s post-doctoral advisor at Harvard and a co-author of the article, the late Alfred Goldberg, was a pioneer in studying the life and death of proteins. Collins noted this study was built on nearly five decades of Goldberg’s research and his late-career collaboration with mathematicians from the University of Cambridge. After coming to MSU a year ago, Collins continued collaborating with his colleagues to complete the paper.
“It’s an incredible honor to be published in PNAS, but it was also a lot of fun being part of this team,” Collins said. “And it’s very meaningful to see my former mentor’s body of work wrapped up and published.”
Reference: “Maximum entropy determination of mammalian proteome dynamics” by Alexander J. Dear, Gonzalo A. Garcia, Georg Meisl, Galen A. Collins, Tuomas P. J. Knowles and Alfred L. Goldberg, 23 April 2024, Proceedings of the National Academy of Sciences.
DOI: 10.1073/pnas.2313107121
The study was funded by the National Institute of General Medical Sciences, the Cure Alzheimer’s Fund, the Lindemann Trust Fellowship, the English-Speaking Union, the George and Lillian Schiff Foundation Studentship, the EMBO Short-Term Fellowship, and the Sidney Sussex College Cambridge Junior Research Fellowship.