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Genetic analysis of the Candida albicans biofilm transcription factor network using simple and complex haploinsufficiency

  • Virginia E. Glazier
  • , Thomas Murante
  • , Daniel Murante
  • , Kristy Koselny
  • , Yuan Liu
  • , Dongyeop Kim
  • , Hyun Koo
  • , Damian J. Krysan*
  • *Corresponding author for this work
  • University of Rochester
  • University of Pennsylvania

Research output: Contribution to journalJournal articlepeer-review

Abstract

Biofilm formation by Candida albicans is a key aspect of its pathobiology and is regulated by an integrated network of transcription factors (Bcr1, Brg1, Efg1, Ndt80, Rob1, and Tec1). To understand the details of how the transcription factors function together to regulate biofilm formation, we used a systematic genetic interaction approach based on generating all possible double heterozygous mutants of the network genes and quantitatively analyzing the genetic interactions between them. Overall, the network is highly susceptible to genetic perturbation with the six network heterozygous mutants all showing alterations in biofilm formation (haploinsufficiency). In addition, many double heterozygous mutants are as severely affected as homozygous deletions. As a result, the network shows properties of a highly interdependent ‘small-world’ network that is highly efficient but not robust. In addition, these genetic interaction data indicate that TEC1 represents a network component whose expression is highly sensitive to small perturbations in the function of other networks TFs. We have also found that expression of ROB1 is dependent on both auto-regulation and cooperative interactions with other network TFs. Finally, the heterozygous NDT80 deletion mutant is hyperfilamentous under both biofilm and hyphae-inducing conditions in a TEC1-dependent manner. Taken together, genetic interaction analysis of this network has provided new insights into the functions of individual TFs as well as into the role of the overall network topology in its function.

Original languageEnglish
Article numbere1006948
JournalPLoS Genetics
Volume13
Issue number8
DOIs
StatePublished - 2017.08

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