Image - left: image of cryo-EM sample taken by electron microscope. The small grey/black dots represent the protein complex, as discussed in the article. Upper right: these tiny particles are combined and classified into 2D classes. This example shows 2D classes of PCNA. Lower right: A 3D model can be made by combining all particles which have been selected in 2D classification.
The team is using a cryo-EM microscope that was partially funded by the Oncode Equipment and Infrastructure program. Sixma: “I am impressed how well the microscope is performing. It was a bit of a struggle in the beginning. This is high-tech equipment, so components easily break down. For instance, a screw was missing and it took us three months to obtain a replacement. And when the machine was finally working properly in March 2020, the lockdown started. We had just generated the first dataset and then nobody could use it for two months. But since then, it has functioned very well. It is truly amazing what you can do with this microscope.”
The electron microscope creates thousands of blurry grey images that need to be aligned and averaged to obtain a high-resolution structure. Keijzer: “One data set may consist of 4000 images and on every image, you have to pick around 2000 very tiny particles which might be your protein complex. Luckily, there is sophisticated software that can locate the particles, but the algorithm needs to be trained. So, I usually spend the whole afternoon picking particles by hand to train the algorithm.”
Sixma: “In addition, the complex of PCNA and USP1 is transient, so it takes a lot of time to trap the right enzyme-substrate complex. In the end, we need at least 10,000 good particles which are in the same state to generate a high-resolution three-dimensional structure. For PCNA itself, Niels has already managed to reconstruct a high-resolution three-dimensional image. But it has been more difficult to obtain a structure for the full complex. The USP1 molecule is shifted relative to PCNA, this makes it hard to find particles in which we can identify both proteins. We really need to instruct the algorithm to search for USP1. This requires brute force when it comes to computational power. Therefore, we are using the Oncode GPU cluster a lot, which was set up to service Oncode researchers who need high amounts of computer power. In the end, we hope to obtain data at atomic resolution about the three-dimensional structure of the PCNA-USP1 complex, revealing exactly where USP1 binds to PCNA and how the different parts of the proteins are oriented with respect to each other.”
Studying the structure of the protein complex is one thing, but Keijzer is also looking at a more functional level with quantitative biochemical experiments. Sixma: “Niels has recently performed some beautiful experiments together with a student, observing how fast USP1 removes ubiquitin from PCNA. We can make use of fluorescent labels on different components of the protein complex. We started this with the ambition to fit this data with the structural data to obtain mechanistic insights. In reality, some things worked out differently and there are a few puzzles left. But I think we already have beautiful kinetic data that shed new light on how USP1 removes ubiquitin. This is important because PCNA has a different role in dealing with DNA damage if there is a chain of ubiquitins on it or a single ubiquitin. We need to perform more of these sophisticated experiments to confirm our findings, but we are getting excited”, says Sixma.
So, what does this mean for cancer patients? Sixma: “It has been suggested that inhibition of USP1 may be used to selectively target specific types of cancer cells. In certain situations, ubiquitination could be critical for cancer cells to survive. Understanding the high-resolution structure and regulation of USP1 may help us identify novel drug targets. In addition, our data on the kinetics of the reaction may help to understand the role of this enzyme in DNA replication and the DNA damage response, which is relevant for cancer research as well.”
In addition to working in her lab, Sixma is an active member of the Oncode community. She was a member of the Scientific Committee for the last Oncode Annual Meeting. “We hoped for a proper hybrid meeting, but it was too early for that. As an organizing committee, we were allowed to be there physically, and it was very nice to talk to each other face-to-face. There is a lot of ‘How do you do this? How do you do that?’ even though we all work on different subjects. That technical exchange has almost stalled due to corona. I am looking forward to having proper meetings with the other Oncode researchers again. That is the beauty of Oncode: you meet these people two or three times a year and there is time to informally talk about our research projects. That is truly valuable, and I do miss that.”