Authors

U Dobramysl¹; RN Neish²; E Ferreira²; R Pereira³; R Etzensperger³; M Young⁴; J Smith⁵; J Damasceno⁶; JD Sunter⁷; J Mottram²; E Gluenz³; R Wheeler⁸;  ¹ University of Oxford, UK;  ² University of York, Centre for Immunology and Infection, UK;  ³ Institute of Cell Biology, University of Bern, Switzerland;  ⁴ University of Glasgow, Institute of Infection, Immunity & Inflammation,, UK;  ⁵ Institute of Infection, Immunity and Inflammation, University of Glasgow, UK;  ⁶ Wellcome Centre for Integrative Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, UK;  ⁷ Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, UK;  ⁸ Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, UK

Discussion

Despite extensive efforts for the functional characterisation of protein-coding genes in Leishmania, the role of most is still unclear. Indeed, according to TriTrypDB only 14% of the 8267 L. mexicana protein-coding genes have been unambiguously named, with the large majority remaining of putative function or hypothetical. The major aims of the Leishmania Genetic Modification (LeishGEM) project are to address this by 1) determining the fitness of protein-coding gene deletion mutants (genome-wide, 8267 genes) and 2) visualising the sub-cellular localisation of the corresponding protein by tagging (if lacking an ortholog in or divergent from T. brucei, 2700 target genes). Using the LeishGEdit toolbox and CRISPR/Cas9, we generate uniquely genetically barcoded deletion cell lines for each gene. These can be mixed into pools and their fitness measured by barcode sequencing (Bar-Seq) as we previously showed. Here, we explain the fitness phenotyping strategies for pools in in vitro and in vivo models of life stages (promastigote culture, axenic amastigote culture, in vitro macrophage infection and mouse footpad infection). Using the Bar-Seq analysis of the first three pools of between 200 and 300 deletion mutants each, we test for A) linearity of the cell abundance using a dilution series of barcode parental cell lines; B) consistency of the fitness phenotypes of six control proteins with known behaviour in specific life stages; and C) potential bottlenecks for cell line survival in various life cycle stages. From this early, not fully randomised sample we detect a significant growth phenotype in 11% of mutants in amastigotes, 10% in macrophages and 21% in mouse footpads. This workflow is quantitative and scalable and will be applied genome-wide over the coming three years for unbiased identification of the most important Leishmania cellular systems for pathogenicity.