Identifying Candida albicans Gene Networks Involved in Pathogenicity
dc.contributor.author | Thomas, G | |
dc.contributor.author | Bain, JM | |
dc.contributor.author | Budge, S | |
dc.contributor.author | Brown, AJP | |
dc.contributor.author | Ames, RM | |
dc.date.accessioned | 2020-06-30T13:37:19Z | |
dc.date.issued | 2020-04-24 | |
dc.description.abstract | 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. | en_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.description.sponsorship | Microbiology Society | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.description.sponsorship | Medical Research Council (MRC) | en_GB |
dc.identifier.citation | Vol. 11, article 375 | en_GB |
dc.identifier.doi | 10.3389/fgene.2020.00375 | |
dc.identifier.grantnumber | WT105618MA | en_GB |
dc.identifier.grantnumber | RVG16/18 | en_GB |
dc.identifier.grantnumber | EP/S001352/1 | en_GB |
dc.identifier.grantnumber | MR/M026663/1 | en_GB |
dc.identifier.grantnumber | MR/N006364/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/121711 | |
dc.language.iso | en | en_GB |
dc.publisher | Frontiers Media | en_GB |
dc.rights | © 2020 Thomas, Bain, Budge, Brown and Ames. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | en_GB |
dc.subject | Candida albicans | en_GB |
dc.subject | co-expression network | en_GB |
dc.subject | network-extracted ontology | en_GB |
dc.subject | pathogen | en_GB |
dc.subject | pathogenicity genes | en_GB |
dc.subject | PEP8 | en_GB |
dc.title | Identifying Candida albicans Gene Networks Involved in Pathogenicity | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-06-30T13:37:19Z | |
dc.description | This is the final version. Available on open access from Frontiers media via the DOI in this record | en_GB |
dc.description | Data Availability Statement: The publicly-available datasets analyzed for this study can be found in the Gene Expression Omnibus (IDs: GSE41749, GSE45141, GSE49310, GSE56091). The network-extracted ontology generated as part of this study is available in the Supplementary Information. | en_GB |
dc.identifier.eissn | 1664-8021 | |
dc.identifier.journal | Frontiers in Genetics | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-03-26 | |
exeter.funder | ::Wellcome Trust | en_GB |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-04-24 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-06-30T13:33:11Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-06-30T13:37:23Z | |
refterms.panel | A | en_GB |
refterms.depositException | publishedGoldOA |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's licence is described as © 2020 Thomas, Bain, Budge, Brown and Ames. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.