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O'Donoghue, F.

Publications and source records attributed to O'Donoghue, F..

2 recordsLinked to original sources

Improved gene targeting in vivo using EoHR, a small molecule inhibitor of 53BP1

Precise genome editing by programmable nucleases such as Cas9 has revolutionised medical research by enabling the creation of gene-edited or knock-in mouse models of disease. However, a major limitation of the approach is the inefficient process of homology driven recombination (HDR) from an exogenous DNA repair template. This is because error-prone, 53BP1-dependent non-homologous end joining (NHEJ) predominates at Cas9-induced double strand breaks (DSBs). Here we report the validation of a cell-permeable and non-toxic inhibitor of 53BP1 called EoHR. In vitro, EoHR prevents 53BP1 binding to dimethylated lysine 20 on histone H4, a marker of DSBs. In cells, EoHR prevents localisation of 53BP1 at nuclease mediated DSBs and promotes HDR at a Cas9-induced break. When tested in vivo during mouse Cas9-mediated gene editing, inclusion of EoHR at the time of microinjection more than doubled the recovery of correctly edited mice and halved the time to project success. Our work shows that inhibition of 53BP by EoHR is a simple and robust way to increase HDR at Cas9 breaks that can also dramatically increase the success rates of animal model generation.

biochemistry↗

Network analysis of large phospho-signalling datasets: application to Plasmodium-erythrocyte interactions

Phosphorylation based signalling is a complicated and intertwined series of pathways critical to all domains of life. This interconnectivity, though essential to life, makes understanding and decoding the interactions difficult. Large datasets of phosphorylation interactions through the activity of kinases on their numerous effectors are now being generated, however interpretation of the network environment remains challenging. In humans, many phosphorylation interactions have been identified across published works to form the known phosphorylation interaction network. We overlayed phosphorylation datasets onto this network which provided information to each of the connections. To analyse the datasets now mapped into a network, we designed a pathway analysis that uses random walks to identify chains of phosphorylation events occurring much more or much less frequently than expected. This analysis highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways in a given dataset. Here we used datasets of human red blood cells infected with the notable stages of Plasmodium falciparum asexual development. The analysis identified several known signalling interactions, and additional interactions which could form the basis of numerous future studies. The network analysis designed here is widely applicable to any comparative phosphorylation dataset across infection and disease and can provide a rapid and reliable analysis to guide validation studies.

microbiology↗