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Updated: Apr 16, 2026

Biolistic Transformation of a Fluorescent Tagged Gene into the Opportunistic Fungal Pathogen Cryptococcus neoformans
07:32

Biolistic Transformation of a Fluorescent Tagged Gene into the Opportunistic Fungal Pathogen Cryptococcus neoformans

Published on: March 19, 2015

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

Hanhae Kim1, Kwang-Woo Jung2, Shinae Maeng2

  • 1Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul. 120-749, Korea.

Scientific Reports
|March 6, 2015
PubMed

Insights

We developed CryptoNet, a novel genome-scale co-functional network for the fungal pathogen Cryptococcus neoformans. This tool aids in identifying genes linked to pathogenicity and drug resistance, crucial for combating cryptococcosis.

Area of Science:

  • Mycology
  • Computational Biology
  • Genomics

Background:

  • Cryptococcus neoformans is an opportunistic pathogen causing meningoencephalitis.
  • Rising cryptococcosis risk and drug resistance necessitate new genetic identification tools.
  • Existing methods for analyzing functional genomics data are often inefficient.

Purpose of the Study:

  • To develop an efficient genome-scale co-functional network for Cryptococcus neoformans.
  • To facilitate the identification of novel genes related to pathogenicity and drug resistance.
  • To provide a resource for network-assisted predictive genetics in C. neoformans.

Main Methods:

  • Construction of a genome-scale co-functional network (CryptoNet) covering ~81% of the C. neoformans coding genome.
  • Application of guilt-by-association and context-associated hub algorithms.
  • Development of a public web server for interactive network analysis.

Main Results:

  • CryptoNet is the first genome-scale co-functional network for any fungal pathogen and for the Basidiomycota phylum.
  • The network successfully identified novel genes associated with pathogenicity and drug resistance.
  • CryptoNet provides insights into fungal pathway evolution.

Conclusions:

  • CryptoNet offers an efficient platform for the genetic dissection of C. neoformans phenotypes.
  • The tool is valuable for identifying virulence and drug resistance factors in fungal pathogens.
  • CryptoNet serves as a public resource for advancing C. neoformans research and predictive genetics.

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