Network-assisted genetic dissection of pathogenicity and drug resistance in the opportunistic human pathogenic fungus Cryptococcus neoformans

Scientific Reports
Hanhae KimInsuk Lee

Abstract

Cryptococcus neoformans is an opportunistic human pathogenic fungus that causes meningoencephalitis. Due to the increasing global risk of cryptococcosis and the emergence of drug-resistant strains, the development of predictive genetics platforms for the rapid identification of novel genes governing pathogenicity and drug resistance of C. neoformans is imperative. The analysis of functional genomics data and genome-scale mutant libraries may facilitate the genetic dissection of such complex phenotypes but with limited efficiency. Here, we present a genome-scale co-functional network for C. neoformans, CryptoNet, which covers ~81% of the coding genome and provides an efficient intermediary between functional genomics data and reverse-genetics resources for the genetic dissection of C. neoformans phenotypes. CryptoNet is the first genome-scale co-functional network for any fungal pathogen. CryptoNet effectively identified novel genes for pathogenicity and drug resistance using guilt-by-association and context-associated hub algorithms. CryptoNet is also the first genome-scale co-functional network for fungi in the basidiomycota phylum, as Saccharomyces cerevisiae belongs to the ascomycota phylum. CryptoNet may therefore provide i...Continue Reading

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Citations

Jul 18, 2018·Current Protocols in Microbiology·Kwang-Woo JungYong-Sun Bahn
Sep 30, 2016·Nature Communications·Kyung-Tae LeeYong-Sun Bahn
Apr 13, 2018·Glycobiology·Zhuo A WangTamara L Doering
Apr 2, 2019·Frontiers in Microbiology·Julian C RutherfordChaoyang Xue
Nov 12, 2016·Frontiers in Microbiology·Antoni N MalachowskiMichal A Olszewski

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Methods Mentioned

BETA
RNA-seq
dissection
phylogenetic profile

Software Mentioned

YeastNet
CryptoNet

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