Scaling up CRISPR genome editing with PIXL
How scientists at the Stanford Genome Technology Centre scaled their groundbreaking precision genome editing technology by implementing PIXL with Momentum.
The Stanford Genome Technology Center
The SGTC aims to foster novel technologies that transform what’s possible in the realm of experimental biology. With a core specialism in yeast functional genomics and large-scale sequencing efforts, the Center’s cutting-edge work incorporates development of a range of next-generation synthetic genomic tools.
Dr Kevin Roy’s team are specialised in uncovering how genetic variation gives rise to complex traits and disease risk in natural populations. Using budding yeast as a model organism, they have pioneered an innovative CRISPR technology called MAGESTIC 3.0.
The approach employs genome-integrated trackable barcodes to systematically edit thousands of genetic variants within a single supercharged experiment. Kevin’s team aims to uncover basic rules that have implications for all populations, including humans, to better understand how disease risk is impacted by genetic variation.
Commenting on the significance of this work, Kevin said:
“Together the precision editing and the genomic barcoding comprise the MAGESTIC system. We’re currently working on many different applications of this for yeast biology by collaborating with various groups using MAGESTIC for diverse projects. More broadly, we’re taking the insights we’ve learned from implementing MAGESTIC in yeast, and developing similar technologies for precision editing of human cells.”
The challenge
The systematic engineering and phenotypic characterisation of genetic variants has long been hampered by an inability to screen individual variants at single nucleotide resolution.
MAGESTIC offers a possible solution. But to demonstrate its potential Kevin needed to construct arrays of thousands of genome edited microbial clones.
This would have been been impossible using conventional liquid-based cloning methods, he says:
“Commercially, there are several new colony pickers that were built on the same concept of using pins that would take colonies randomly grown across a plate and inoculate a multi-well plate filled with liquid.
“All of these tools from our standpoint were limited in that we needed to have plates pre-filled with liquid. As you get to the scale of thousands and thousands of individual wells, you’re dealing with large stacks of pre-filled plates. However, this was quite inefficient because ultimately, we were going back to agar for our downstream steps.
“Therefore, we wanted a tool that would pick straight from an agar plate to an agar plate, ideally at high densities of up to 1536 colonies on a single plate. We also didn’t want to have to deal with the maintenance and cleaning of pins, which we knew had issues with accuracy and being bent, for example, when they were being cleaned.”
The solution
Initially Kevin chose a standalone PIXL for its ease of use. But he soon realised that it had other benefits, such as a free API, that left the pathway open for them to upgrade to a fully walkaway system in future:
“The PIXL for us represented a transformative tool that would really simplify our workflow. It allowed us to go directly from agar plate to agar plate at very high density. So minimising the amount of hands-on manual labour that we need to do when dealing with lots of plates.”
Having successfully road-tested MAGESTIC to map causal variants within several genomic regions, the team were keen to further demonstrate its potential in the context of a pooled library. But with anywhere from 10,000 to 50,000 genetic variants between any two yeast strains, they were again facing a colony picking bottleneck.
By adding Momentum software and a robotic arm to their existing setup, Kevin was able to dramatically scale up his experiments. It meant they could go from daily runs of six or seven hours to fully-walkaway, overnight picking bonanzas.
This paved the way for much more high-powered studies, he says:
“With the fully-automated setup, we were able to get really ambitious and go for projects where we have several different strains. We could then begin to address previously unapproachable questions, like: What are the genetic variants that have a background dependent effect? What are the genetic variants that have interactions with other variants in one strain, but not another? And so we were able to scale up the scope of these projects. This is currently ongoing work in our lab.”
Customer experience
The team knew what they needed to do. But they still faced concerns in the department about the time for implementation on such a large-scale project.
They needn’t have worried, says Kevin, referring to his experience as ‘seamless’:
“Initially we weren’t sure which robotic arm company we should partner with. Our main focus was on high throughput colony picking. And we didn’t need the robotic arm to be integrated with other systems. So we largely depended on Singer and their technical support team to handle all of the details in terms of how the robotic arm software would integrate with the PIXL. And it was really a seamless operation.
“Even though we were one of the first labs to get a fully-automated system, we really didn’t have to do too much of the development on our end. We simply described what workflows we wanted and, working together with Thermo Fisher our chosen robotic arm company, the team at Singer largely implemented everything.”
Dr Kevin Roy
Stanford Genome Technology Center