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Young, N. D.

Publications and source records attributed to Young, N. D..

2 recordsLinked to original sources

Programmed mutation of liver fluke granulin using CRISPR/Cas9 attenuates virulence of infection-induced hepatobiliary morbidity

Infections with several flatworm parasites represent group 1 biological carcinogens, i.e. definite causes of cancer. Infection with the food-borne liver fluke Opisthorchis viverrini causes cholangiocarcinoma (CCA). Whereas the causative agent for most cancers, including CCA in the West, remains obscure, the principal risk factor for CCA in Thailand is opisthorchiasis. We exploited this established link to explore the role of the secreted parasite growth factor termed liver fluke granulin (Ov-GRN-1) in pre-malignant lesions of the biliary tract. We targeted the Ov-grn-1 gene for programmed knockout and investigated gene-edited parasites in vitro and in experimentally infected hamsters. Both adult and juvenile stages of the liver fluke were transfected with a plasmid encoding a guide RNA sequence specific for exon 1 of Ov-grn-1 and the Cas9 nuclease. Deep sequencing of amplicon libraries from genomic DNA from gene-edited parasites exhibited programmed, Cas9-catalyzed mutations within the Ov-grn-1 locus, and tandem analyses by RT-PCR and western blot revealed rapid depletion of Ov-grn-1 transcripts and protein. Newly excysted juvenile flukes that had undergone editing of Ov-grn-1 colonized the biliary tract, grew and developed over a period of 60 days, were active and motile, and induced a clinically relevant pathophysiological tissue phenotype of attenuated biliary hyperplasia and fibrosis in comparison to infection with wild type flukes. This is the first report of gene knock-out using CRISPR/Cas9 in a parasitic flatworm, demonstrating the activity and utility of the process for functional genomics in these pathogens. The striking clinical phenotype highlights the role in virulence that liver fluke growth factors play in biliary tract morbidity during chronic opisthorchiasis.

molecular biology

Best Practice Data Life Cycle Approaches for the Life Sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a life cycle view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain.\n\nHere we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on omics datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

bioinformatics