Identifying Candida albicans Gene Networks Involved in Pathogenicity

Graham Thomas, Judith M. Bain, Susan Budge, Alistair J. P. Brown, Ryan M. Ames*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
2 Downloads (Pure)


Candida albicans is a normal member of the human microbiome. It is also an opportunistic pathogen, which can cause life-threatening systemic infections in severely immunocompromized individuals. Despite the availability of antifungal drugs, mortality rates of systemic infections are high and new drugs are needed to overcome therapeutic challenges including the emergence of drug resistance. Targeting known disease pathways has been suggested as a promising avenue for the development of new antifungals. However, <30% of C. albicans genes are verified with experimental evidence of a gene product, and the full complement of genes involved in important disease processes is currently unknown. Tools to predict the function of partially or uncharacterized genes and generate testable hypotheses will, therefore, help to identify potential targets for new antifungal development. Here, we employ a network-extracted ontology to leverage publicly available transcriptomics data and identify potential candidate genes involved in disease processes. A subset of these genes has been phenotypically screened using available deletion strains and we present preliminary data that one candidate, PEP8, is involved in hyphal development and immune evasion. This work demonstrates the utility of network-extracted ontologies in predicting gene function to generate testable hypotheses that can be applied to pathogenic systems. This could represent a novel first step to identifying targets for new antifungal therapies.
Original languageEnglish
Article number375
Number of pages12
JournalFrontiers in Genetics
Early online date24 Apr 2020
Publication statusPublished - Apr 2020

Bibliographical note

This is a short text to acknowledge the contributions of specific colleagues, institutions, or agencies that aided the efforts of the authors.

RA was generously supported by a Wellcome Trust Institutional Strategic Support Award [WT105618MA], a Microbiology Research Visit Grant [RVG16/18], and a EPSRC/BBSRC Innovation Fellowship [EP/S001352/1]. AB was supported by a programme grant from the UK Medical Research Council [MR/M026663/1] and by the Medical Research Council Centre for Medical Mycology at the University of Aberdeen [MR/N006364/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


  • Candida albicans
  • co-expression network
  • network-extracted ontology
  • pathogen
  • pathogenicity genes
  • PEP8
  • CELL


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