title: Evolutionary divergence in the fungal response to fluconazole revealed by soft clustering.
abstract: BACKGROUND
  Fungal infections are an emerging health risk, especially those involving yeast that are resistant to antifungal agents. To understand the range of mechanisms by which yeasts can respond to anti-fungals, we compared gene expression patterns across three evolutionarily distant species - Saccharomyces cerevisiae, Candida glabrata and Kluyveromyces lactis - over time following fluconazole exposure.
  
  
  RESULTS
  Conserved and diverged expression patterns were identified using a novel soft clustering algorithm that concurrently clusters data from all species while incorporating sequence orthology. The analysis suggests complementary strategies for coping with ergosterol depletion by azoles - Saccharomyces imports exogenous ergosterol, Candida exports fluconazole, while Kluyveromyces does neither, leading to extreme sensitivity. In support of this hypothesis we find that only Saccharomyces becomes more azole resistant in ergosterol-supplemented media; that this depends on sterol importers Aus1 and Pdr11; and that transgenic expression of sterol importers in Kluyveromyces alleviates its drug sensitivity.
  
  
  CONCLUSIONS
  We have compared the dynamic transcriptional responses of three diverse yeast species to fluconazole treatment using a novel clustering algorithm. This approach revealed significant divergence among regulatory programs associated with fluconazole sensitivity. In future, such approaches might be used to survey a wider range of species, drug concentrations and stimuli to reveal conserved and divergent molecular response pathways.
authors.affiliation: Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
authors.forename: Dwight
authors.initials: D
authors.lastname: Kuo
authors.forename: Kai
authors.initials: K
authors.lastname: Tan
authors.forename: Guy
authors.initials: G
authors.lastname: Zinman
authors.forename: Timothy
authors.initials: T
authors.lastname: Ravasi
authors.forename: Ziv
authors.initials: Z
authors.lastname: Bar-Joseph
authors.forename: Trey
authors.initials: T
authors.lastname: Ideker
mesh_terms: D000465:Algorithms; D001692:Biological Transport / Q000187:drug effects; D002175:Candida / Q000187:drug effects / Q000235:genetics; D016000:Cluster Analysis; D017124:Conserved Sequence / Q000235:genetics; D004351:Drug Resistance / Q000187:drug effects / Q000235:genetics; D019143:Evolution, Molecular; D015725:Fluconazole / Q000494:pharmacology*; D005658:Fungi / Q000187:drug effects* / Q000235:genetics*; D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal / Q000187:drug effects; D014644:Genetic Variation; D007716:Kluyveromyces / Q000187:drug effects / Q000235:genetics; D026901:Membrane Transport Proteins / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics; D013045:Species Specificity; D013261:Sterols / Q000378:metabolism
chemical_list: D026901:Membrane Transport Proteins; D012333:RNA, Messenger; D013261:Sterols; D015725:Fluconazole