Biotechnology

The new platform cuts out time engineering and opts for a genome editor

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A research team from the LKS School of Medicine, University of Hong Kong (HKUMed) has developed a new way to break through the current limited throughput of optimizing precise genomic editors at scale, engineering hundreds of base editor variants in parallel instead of the current one-by-one testing. , and notify the user of the most suitable for therapeutic genome editing.

The findings have been published in Cell Systems and patent applications have been filed based on the work.

Background

Base editing is a newer CRISPR-based genome editing technology and is a safer tool for treating genetic diseases with single base mutations (such as sickle cell disease, familial hypercholesterolemia, etc.) in DNA by correcting it back to its normal shape. However, editing of existing bases can produce different results depending on the type and version of the base editor used, the composition of the target DNA sequence, and the positions of the bases of the DNA to be converted.

Selecting a base editor that is less than optimal for the application can result in erroneous edits and extra mutations around the target DNA base, which can lead to undesired effects. Currently, individual testing should be performed to characterize the editing performance of available basic editors to optimize their use at each therapeutic locus. In addition, many therapeutic loci do not yet have a basic editor optimized for precise editing. Despite worldwide efforts, creating a new base editor can take months or years using conventional methods.

Research findings

The HKUMed research team succeeded in creating a platform that combines a basic reporter editor system with CombiSEAL, existing technologies, to rapidly engineer hundreds (or more) base editor variants in parallel, with combinations of multiple enzymatic deaminase domains and CRISPR/Cas9-based DNA recognition domains.

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The new one-shot method allows for easy testing of all the performance of the barcode-labeled precise genome editor, avoiding the need for laborious one-by-one testing. Image/HKUMed

The compatibility and performance of these variants have yet to be characterized and compared on a head-to-head basis. The team applied the platform to quantitatively read the editing efficiency, purity, sequence motif preference, and bias of each variant in generating single- and multiple-base conversions in human cells, which helps select the best fit for therapeutic targets by generating specific base types. conversion with maximum efficiency and minimal unwanted edits.

The team expanded use of the platform to further increase the efficiency of the current base editor system. Team members performed screens focused on engineering the stem-loop-2 region of the sgRNA scaffold (single guide RNA) used in the basic editor system, and managed to identify two new scaffold sgRNA variants, SV48 and SV240, that outperformed the wild one. -type scaffold to achieve greater basic editing efficiency (up to 2.2 times higher).

The team also demonstrated that the platform is not only usable for basic editor characterization and screening, but also compatible with other genome-appropriate editor systems such as master editors. This could widen the scope of work to find other suitable editors to correct genetic mutations in therapeutic targets where the basic editor cannot be applied.

Research significance

“It’s like an expedited check-out process in a store. Since all product items (i.e. variant base editor) are tagged with a barcode, for a check-out counter barcode scanner, we only need to put all items in bulk into the basket at the check-out counter. The scanner can automatically identify all items and complete payments (i.e. analysis of basic editing performance in our case). There is no need to test basic editors one by one,” said Alan Wong Siu-lun, professor from the School of Biomedical Sciences, HKUMed.

This research was led by Wong Siu-lun. John Fong Hoi-chun, PhD student, is first author, with assistance from Chu Hoi-yee and Zhou Peng, postdoctoral fellows, School of Biomedical Sciences, HKUMed.

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