Comparative Cross-Kingdom\nDDA- and DIA-PASEF Proteomic\nProfiling Reveals Novel Determinants of Fungal Virulence and a Putative\nDruggable Target

Accurate and reliable\ndetection of fungal pathogens presents an\nimportant hurdle to manage infections, especially considering that\nfungal pathogens, including the globally important human pathogen, Cryptococcus neoformans, have adapted diverse mechanisms\nto survive the hostile host environment and moderate virulence determinant\nproduction during coinfections. These pathogen adaptations present\nan opportunity for improvements (e.g., technological and computational)\nto better understand the interplay between a host and a pathogen during\ndisease to uncover new strategies to overcome infection. In this study,\nwe performed comparative proteomic profiling of an in vitro coinfection\nmodel across a range of fungal and bacterial burden loads in macrophages.\nComparing data-dependent acquisition and data-independent acquisition\nenabled with parallel accumulation serial fragmentation technology,\nwe quantified changes in dual-perspective proteome remodeling. We\nreport enhanced and novel detection of pathogen proteins with data-independent\nacquisition-parallel accumulation serial fragmentation (DIA-PASEF),\nespecially for fungal proteins during single and dual infection of\nmacrophages. Further characterization of a fungal protein detected\nonly with DIA-PASEF uncovered a novel determinant of fungal virulence,\nincluding altered capsule and melanin production, thermotolerance,\nand macrophage infectivity, supporting proteomics advances for the\ndiscovery of a novel putative druggable target to suppress C. neoformans pathogenicity.