New Tool Amplifies Tiny Protein Changes Inside Cells

Small changes in protein levels inside cells can determine whether someone stays healthy or develops disease, and whether a drug candidate works or fails. Yet these shifts are notoriously difficult to detect, especially for proteins that are not very abundant to begin with. A new study in Cell, led by Steven Banik from Stanford University describes a tool designed to amplify and visualize these subtle changes.

“Our ideas about what’s important in biology are often defined by the tools that we have to look at it,” said Banik. “There’s a lot of biology happening inside a black box that we can’t see. If we can amplify signals that we haven't been able to see before, we can discover new biology or new molecules that might have therapeutic benefit.”

Small decreases in protein levels can have major consequences on cellular behavior. Tracking such changes also matters for drug development, since using a drug to degrade a malfunctioning protein can help treat diseases like cancer. Yet few techniques are sensitive enough to catch these changes in low-abundance proteins, and studying more than one protein or drug at a time has been difficult.

Traditional methods typically involve extracting proteins from many cells and concentrating a single protein of interest until it can be visualized. Banik’s team instead built a method that produces a strong, easily measured signal using far fewer cells, allowing hundreds of proteins and drugs to be tested in parallel. “If you have many grains of sand dispersed all over a table, and you take one grain away, it would be very hard to see that,” Banik explained. “But if we had a way to make the grain of sand look like a boulder and then took it off the table, that would be noticeable. And that’s what we've done.”

Working with co-author David Solow-Cordero at Stanford’s Nucleus high-throughput screening facility, the team engineered cells so that as a target protein degrades, a fluorescent signal grows brighter, functioning like a dimmer switch rather than a simple on/off light. First author Melissa Gray said the facility’s automation was essential to scaling the approach up. The system can be tuned to track multiple proteins using different-colored signals, or to produce an RNA barcode read out by sequencing instead of light, eventually helping researchers find drug molecules that work by inducing protein degradation.