Deciphering protein degradation. Interview with Ying Lu.

Ying Lu is Associate Professor in the Department of Systems Biology at Harvard Medical School. After a bachelor’s in physics at Peking University and a Ph.D. in biophysics from The Rockefeller University, he moved to Harvard for postdoctoral training and was appointed assistant professor in 2017.

Ying’s research focuses on the cellular protein degradation system, a central component of protein homeostasis linked to many diseases. He has received multiple honors, including the Armenise Harvard Junior Faculty Grant (in 2023 and 2025), the Edward Mallinckrodt Foundation Award, and the Damon-Runyon Cancer Research Fellowship Award.

We know a lot about transcription, but we still don’t know how cells regulate protein degradation. Why?

One technical reason is the relatively simple rules for protein creation, which is based on genetic coding. For protein degradation, there’s no such obvious coding, yet protein turnover needs to be precisely controlled. The first step in protein degradation, the tag system, is very complex. Cells use ubiquitin, a very small protein, to mark proteins that should be removed. But ubiquitins can come in many different flavors, and they can form chains that could have different topologies. Depending on which lysine residues are involved, there could be at least eight different combinations. As for the second step, recognition, cells have a dedicated system. And we are just beginning to understand how that system interprets and senses the different taggingof proteins, and how it sends them to different fates.

One of your recent works, which is also funded by GAHF, is on the recognition system. Can you summarize it?

Previously, we have been mostly focused on solving the structure of the 26S proteasome, the protein shredder, using cryo-EM. Now we focus on the so-called “difficult substrates”, which are, for example, protein aggregates and certain membrane proteins. What’s puzzling about them is that their degradation is very fast in cells, but it becomes very slow if isolated and mixed with purified proteasome. We recently found that for protein aggregates, an amplifier of the ubiquitin signal, the E3 ubiquitin-protein ligase HUWE1, helps the degradation system to handle them. This enzyme primarily recognizes the density of ubiquitin chains on the substrate molecule, hence recognizing protein aggregates, as most of them are modified by ubiquitins. HUWE1 then performs a rapid amplification of ubiquitin modifications on the aggregates, adding more than 30 ubiquitins in a couple of minutes, which makes it one of the most efficient systems we have ever worked with. In turn, it recruits the dedicated unfoldase VCP/p97, an ATP-dependent machinery that can help the proteasome to unfold these protein aggregates.

Protein degradation is also connected with diseases. Which ones are you exploring?

One area is cancer, since 30% of the tumor cell lines are dependent on HUWE1 for proliferation, but we don’t understand why. The other one is neurodegeneration. Since HUWE1 tackles protein aggregates, we are trying to see if we can boost its activity and maybe help neurons eliminate aggregates like tau proteins in Alzheimer’s.

How did the Giovanni Armenise Harvard Foundation grant help your career?

Given the lack of funding, young scientists are spending more time on writing grants than on doing research. The GAHF grant gave me the resources and relief that let me focus on the most important and exciting part of science. Besides, by organising events to meet with other great scientists and grantees, it gave me the opportunity to establish collaborations, which is one of the most efficient ways to gather people and technologies to address research questions.

What would be your dream finding?

I’ll be very excited to see how this “difficult substrates” degradation pathway, the one implying HUWE1, could play a role in human diseases, either positively or negatively. Another dream would be more related to my physics background. Similar to having the fundamental laws of physics, it would be great to have relatively simple mathematical models to interpret some areas of biology, for example, in protein degradation.

What is your idea of successful basic research?

In the short term, I would say it is how many times your work has been cited, and whether it withstands the test of other labs. But in the long term, the real question is whether your work guided other scientists. Doing biology is like exploring a forest, which has a lot of treasures, but without a map, we can’t see them. I think successful research in biology provides a map for other scientists to guide their search for new treasures.