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Phenotypic landscape of the fungal meningitis pathogen Cryptococcus neoformans

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP538982
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Systematic fitness profiling of mutant libraries can elucidate functions for unstudied genes by correlating genotype and phenotype and placing genes into biological pathways. Here, we performed pooled fitness measurements of 4328 Cryptococcus neoformans knockout strains in 158 growth-limiting environments, including an in vivo murine infection model. We quantified mutant abundances using KO-seq, a modification of Tn-seq that enumerates mutant-specific junctions between an inserted drug resistance marker and the target region of the genome. Comparing mutant abundances in treated conditions versus parallel controls enabled calculation of condition-specific relative fitness differences. We used these measurements to uncover novel fungal biology, identifying factors required for mammalian infectivity and assigning functions to divergent, uncharacterized genes. This work provides a valuable resource for exploring the biology of a neglected fungal pathogen.
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2025-06-05
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