Network-assisted genetic dissection of pathogenicity and drug resistance in the opportunistic human pathogenic fungus Cryptococcus neoformans.
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 insights into pathway evolution between two distinct phyla of the fungal kingdom. The CryptoNet web server (www.inetbio.org/cryptonet) is a public resource that provides an interactive environment of network-assisted predictive genetics for C. neoformans.
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Hanhae
H
Kim
Department of Biotechnology, Center for Fungal Pathogenesis, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Kwang-Woo
KW
Jung
Department of Biotechnology, Center for Fungal Pathogenesis, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Shinae
S
Maeng
1] Department of Molecular Genetics and Microbiology, Medicine, and Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA [2] Department of Plant Pathology and Microbiology, National Taiwan University, Taipei, Taiwan.
Ying-Lien
YL
Chen
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Junha
J
Shin
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Jung Eun
JE
Shim
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Sohyun
S
Hwang
Institut Pasteur, Unité Biologie et Pathogénicité Fongiques, Département de Mycologie, F-75015, Paris, France.
Guilhem
G
Janbon
Department of Molecular Genetics and Microbiology, Medicine, and Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.
Taeyup
T
Kim
Department of Molecular Genetics and Microbiology, Medicine, and Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.
Joseph
J
Heitman
Department of Biotechnology, Center for Fungal Pathogenesis, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Yong-Sun
YS
Bahn
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.
Insuk
I
Lee
D000935:Antifungal Agents / Q000494:pharmacology*; D019295:Computational Biology / Q000379:methods; D003453:Cryptococcosis / Q000382:microbiology*; D003455:Cryptococcus neoformans / Q000187:drug effects* / Q000235:genetics* / Q000472:pathogenicity; D025141:Drug Resistance, Fungal; D053263:Gene Regulatory Networks; D005800:Genes, Fungal; D016681:Genome, Fungal; D023281:Genomics / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D009894:Opportunistic Infections / Q000382:microbiology*; D010641:Phenotype; D014774:Virulence / Q000235:genetics
D000935:Antifungal Agents