Adenine base editing in an adult mouse model of tyrosinaemia

In contrast to traditional CRISPR-Cas9 homology-directed repair, base editing can correct point mutations without supplying a DNA-repair template. Here we show in a mouse model of tyrosinaemia that hydrodynamic tail-vein injection of plasmid DNA encoding the adenine base editor (ABE) and a single-guide RNA (sgRNA) can correct an A\u3eG splice-site mutation. ABE treatment partially restored splicing, generated fumarylacetoacetate hydrolase (FAH)-positive hepatocytes in the liver, and rescued weight loss in mice. We also generated FAH(+) hepatocytes in the liver via lipid-nanoparticle-mediated delivery of a chemically modified sgRNA and an mRNA of a codon-optimized base editor that displayed higher base-editing efficiency than the standard ABEs. Our findings suggest that adenine base editing can be used for the correction of genetic diseases in adult animals

Efficient C•G-to-G•C base editors developed using CRISPRi screens, target-library analysis, and machine learning

Programmable C•G-to-G•C base editors (CGBEs) have broad scientific and therapeutic potential, but their editing outcomes have proved difficult to predict and their editing efficiency and product purity are often low. We describe a suite of engineered CGBEs paired with machine learning models to enable efficient, high-purity C•G-to-G•C base editing. We performed a CRISPR interference (CRISPRi) screen targeting DNA repair genes to identify factors that affect C•G-to-G•C editing outcomes and used these insights to develop CGBEs with diverse editing profiles. We characterized ten promising CGBEs on a library of 10,638 genomically integrated target sites in mammalian cells and trained machine learning models that accurately predict the purity and yield of editing outcomes (R = 0.90) using these data. These CGBEs enable correction to the wild-type coding sequence of 546 disease-related transversion single-nucleotide variants (SNVs) with >90% precision (mean 96%) and up to 70% efficiency (mean 14%). Computational prediction of optimal CGBE-single-guide RNA pairs enables high-purity transversion base editing at over fourfold more target sites than achieved using any single CGBE variant.US NIH (Grants F31NS115380, U01AI142756, UG3AI150551, RM1HG009490, R35GM118062, R35GM138167 and P30CA072720

IspE inhibitors identified by a combination of in silico and in vitro high-throughput screening

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens