Unraveling the mysteries of the human genome using CRISPR
It takes at least a year for a typical academic lab to ask and answer a single question about the genetics of a process in a human cell. Because of current inefficient approaches to clinical testing — everything from patients dropping out to the drug's lack of efficacy to trial design flaws — nine out of ten potential drugs fail.
Dr. Laralynne Przybyla, an Assistant Adjunct Professor at UCSF and Scientific Director of the Laboratory for Genomics Research (LGR), is bringing together her passions for stem cell biology, developmental biology, and functional genomics to improve the pace of research using gene editing technology, CRISPR-Cas9.
What is the Laboratory for Genomics Research?
The LGR is the brainchild of the co-inventor of CRISPR-Cas9, UC Berkeley professor Jennifer Doudna and former UCSF professor Jonathan Weissman, alongside Dr. Hal Barron, the former Chief Scientific Officer and President of R&D for GSK. The partnership began in 2019 to identify technologies, new drug targets, and biological mechanisms that will help foster academic and industrial advances.
Our partnership portfolio has a number of collaborative projects that have evolved from existing technologies with applications to human disease biology. We’re also working to develop next-generation technologies and answer new biological questions, such as how we can study gene regulatory networks in addition to single genes.
Many say CRISPR is one of the most important technologies of our time. Why is that? Talk to us about the breadth of potential applications.
CRISPR-Cas9 enables geneticists and researchers to edit the human genome by removing, adding, or altering pieces of DNA and correcting disease-causing mutations. The Cas9 protein can be targeted to cleave any region of DNA, and researchers have modified this protein to instead activate or repress genes by turning them on or off. These tools can then be used to systematically alter gene expression, which helps us better understand how gene functions contribute to changes in how cells behave or initiate disease phenotypes.
In mammalian systems, CRISPR was initially applied to cancer biology, and we continue working with cancer cells for basic biology and disease applications. Traditionally, you make a hypothesis based on the literature, pick one gene at a time, and knock it out using a laborious process. With CRISPR-Cas9, we can look at the standard of care therapy for a particular cancer and repress specific genes to make the cells more susceptible to this therapeutic. We can do this systematically across the entire genome and use those results to identify new therapeutic avenues, often within a month of running the screen. The potential is limitless.
What inspired the individuals, institutions, and organizations to come together? What was the vision for LGR?
What we do is unique in that the scientists from biopharma, UC Berkeley, and UCSF work side by side. The drug discovery researchers know what diseases and biology matter to them, how to build therapeutics, and take them to the next stage. Researchers in a traditional academic lab often have to publish their work with potential disease-relevant applications and then wait to see if anyone is interested in using the research to develop therapeutic strategies. Here, we have that built-in next step thanks to the scientific expertise and know-how from our academic and industry partners, so that’s one of the advantages of our multi-institutional collaboration. The more tools we build and learn, the more we enable other researchers worldwide to run genetic screens at scale and across different areas of biology.
Can you tell us about some of your projects?
We’re looking into innate immunity and understanding chronic inflammation, as well as applications in kidney disease and neuronal biology. We’re interested in several human diseases, such as autoimmune disease, arthritis, and neurodegenerative disease, which we can design and run functional genomics screens about to come up with therapeutic targets.
Right now, we're excited about developing Induced Pluripotent Stem cell (iPSC)-based models, which start with cells that can be turned into any cell type in the body. The closer we get to the real human cell type we care about, the better the screens will be, and the better the genetic data will be for targeting new treatments. There are a lot of challenges with that because there hasn’t been a lot of functional genomics research performed on specialized cell types, so we hope to make these kinds of screens more systematic and routine.
What led you to partner with Benchling, and how is UCSF using Benchling to deliver on its mission?
I worked with Benchling tools in my previous positions, both in academia at MIT and in biotech. I spoke with Benchling about how we could work together. We knew the key to our success would be our ability to track every step of a screen from the cell model to the guide library to proteins engineered into the cell. I knew Benchling was an electronic laboratory notebook (ELN), but I wasn’t aware of all the other capabilities. We learned that using Benchling Notebook, Registry and Inventory together allows us to look across our screens in aggregate to draw out insights and trends.
If you’re working in a lab with paper notebooks and trying to go back and look across hundreds of entries, that will take a long time. If we want to look at all the screens we’ve ever run, I can easily do that with Benchling software. I can go into the Registry, click on that machinery, and pull up the screens in Insight. Using Benchling also ensures an accessible data record that can be shared through multiple locations.
We have a Benchling-enabled tablet right next to the cell bank in the lab, so as we're amassing more and more data, from checking cell growth to isolating genomic DNA, we can keep track of it immediately, all in a single data source. Our collaborators also use Benchling, so it helps everyone stay on the same page and share protocols. When we finish a project and need to transfer materials and protocols across labs, we can take registry information that we already tracked and send over the templates.
Eventually, this will give us the power of scale and metadata, which wouldn’t be possible without this integrated system. For example, if someone has a question about a screen in ten years, the information will be documented in the same way. It also helps with compliance since you need to have all data recorded for intellectual property tracking.
What are you excited about for the future of the UCSF and Benchling partnership?
I’m excited to see how we can accelerate drug development through the new functional genomics tools we’re creating and implementing. We’ve already seen some cool technologies such as new disease-relevant model systems, improved library generation, arrayed microscopy-based readouts, single cell deep phenotypic approaches, and new CRISPR modalities that allow for repression or activation of multiple gene simultaneously. I’m hopeful we’ll enhance our understanding of human disease biology and ideally see next-generation therapeutics coming out of these soon.
Read more about the LGR.