iPool-Seq: A novel functional genomics approach to identify fungal insertion mutants enabling large-scale virulence factor mapping in plant fungal interactions

Simon Uhse 1 Florian Pflug 2 Alexandra Stirnberg 1 Klaus Ehrlinger 1 Arndt von Haeseler 2 Armin Djamei 1
1Effectomics, Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
2Bioinformatics and Computational Biology, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna & Medical University of Vienna, Vienna, Austria

Fungal plant-pathogens require virulence factors for the successful infection of their hosts. The elucidation of virulence factors is essential to shed light on fungal infection mechanisms and can pave the way to engineer resistant plants. Ustilago maydis has a large arsenal of putative virulence factors, but methods for comprehensive in vivo analyses are lacking. Here, we developed insertion Pool-Sequencing (iPool-Seq), which enables fast and reliable identification of virulence factors from insertional mutant pools. iPool-seq has a highly efficient Next-Generation Sequencing library generation with unbiased genome-wide incorporation of adapters. Inserted adapters contain unique molecular identifiers (UMIs) which facilitate the accurate assessment of insertional mutant fitness. We identified 16 significantly depleted mutants in a pool of 195 U. maydis insertional mutants. Strikingly, among the top hits we identified recently characterized essential U. maydis effectors ApB73, Pep1 and Pit2, demonstrating that iPool-Seq is functional under in vivo conditions. Moreover, we confirmed the impaired virulence of three candidate mutants via individual infection assays and confocal microscopy of infected plants with WGA-AF488 staining. In summary, iPool-Seq promises to be a versatile tool to identify fitness and colonization factors of plant-infecting or colonizing microbes. iPool-seq may be applicable in various plant-pathogen systems to identify virulence factors due to its highly sensitive and quantitative nature and has the potential to elucidate virulence factors on a genome-wide scale.