Cells throughout a person’s body share the same DNA. Proteins are what set them apart. But proteins do not live forever. In fact, their fate is largely determined by their environment; a protein that grows old in the brain may last just minutes in the gut.
For years, the standard approach to protein science has involved isolating proteins from living tissue and sorting them by size. Because proteins have distinct physical properties, this method shows researchers the type and amount of proteins present. Now, scientists are exploring a new dimension: protein turnover, or the rate at which new proteins replace old ones.
“Protein turnover is very important for cells,” said Yansheng Liu, PhD, an associate professor of pharmacology at Yale School of Medicine and senior author of the study. Disruptions can upset the delicate balance of proteins in a cell or tissue and cause problems. For example, abnormal protein turnover plays a role in both cancer and neurodegenerative disease. This data may help researchers understand these diseases better and develop drugs to treat them.
In a new study, published March 20 in Cell, Yale researchers collected turnover data on 11,000 proteins from eight tissues and nine brain regions in mice. They measured how long any given protein existed and compared those values across tissues, such as the heart, lung, gut, and different areas of the brain, revealing dramatic variability.
“We are building a biological time clock for proteins,” said Liu.
Because the body is constantly recycling proteins, tracking the life of an individual protein is difficult. Traditional analysis methods have fallen short, noted Liu, limiting the amount of available data.
In this study, the researchers used several highly specialized techniques to measure protein lifespan. They fed mice labeled amino acids—the building blocks of proteins—which allowed them to visualize cycles of protein synthesis and degradation. Then, the researchers ran tissue and brain samples through mass spectrometers and compared protein abundance and turnover time across tissues.
“We found that the lifespan is quite independent of protein abundance,” said Liu, who is also a member of Yale Cancer Center and the Yale Cancer Biology Institute on West Campus. This is an important discovery for basic protein science, he added.
The team also found that proteins known to interact with each other share similar lifespans, suggesting that turnover is not limited to individual proteins—it also applies to their interactions.
The data are available in an open-source web application called TissuePPT. The study was done in collaboration with St. Jude Children’s Research Hospital and the University of Göttingen.
A potential target for treating Alzheimer’s disease
After calculating the lifespan for thousands of proteins, the team turned to protein modifications. After they are assembled, proteins are often subjected to chemical tweaks that can alter their structure and activity level. One common modification is phosphorylation, in which a molecular snippet called a phosphoryl group—a phosphorus atom and four oxygen atoms—is added to the protein. The researchers showed that phosphorylation can extend or abbreviate a protein’s lifespan on a case-by-case basis. TissuePPT now includes data on 40,000 phosphorylation sites.
To better understand the impact of phosphorylation, the team zeroed in on several proteins involved in neurodegenerative disease, including tau. This structural protein helps cells of the nervous system maintain their shape. But in the brains of people with Alzheimer’s Disease, for example, tau accumulates in disruptive tangles.
“Phosphorylated tau is more stable and prone to tangling,” said Liu. When the researchers removed phosphoryl groups from tau, the rate of protein turnover increased, suggesting a possible therapeutic avenue for neurodegenerative disease.
With TissuePPT, scientists now have limitless opportunities to explore protein lifespan. Different analytical tools offer users options for visualizing data, and Liu carefully contemplated the design. In the heat-circle plots, colors and shapes work together to depict abundance and turnover at the same time.
The team is now working on improving their methods by utilizing a new mass spectrometer purchased by Yale last April. This technique separates proteins within a tissue sample by cell type and exact position, allowing for increased specificity.
They are also collecting data on other protein modifications and will explore how sex differences, age, and disease impact protein turnover variability moving forward, said Liu.
“There’s much more to explore.”
The research reported in this news article was supported by the National Institutes of Health (awards R01GM137031, RM1GM149406, RF1AG064909, and RF1AG068581). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was also supported by CZI Collaborative Pairs Pilot Project Awards and the SFB1286, Göttingen, Germany.