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Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies

  • David J. Wooten
  • , Jorge Gómez Tejeda Zañudo
  • , David Murrugarra
  • , Austin M. Perry
  • , Anna Dongari-Bagtzoglou
  • , Reinhard Laubenbacher
  • , Clarissa J. Nobile
  • , Réka Albert

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Candida albicans, an opportunistic fungal pathogen, is a significant cause of human infections, particularly in immunocompromised individuals. Phenotypic plasticity between two morphological phenotypes, yeast and hyphae, is a key mechanism by which C. albicans can thrive in many microenvironments and cause disease in the host. Understanding the decision points and key driver genes controlling this important transition and how these genes respond to different environmental signals is critical to understanding how C. albicans causes infections in the host. Here we build and analyze a Boolean dynamical model of the C. albicans yeast to hyphal transition, integrating multiple environmental factors and regulatory mechanisms. We validate the model by a systematic comparison to prior experiments, which led to agreement in 17 out of 22 cases. The discrepancies motivate alternative hypotheses that are testable by follow-up experiments. Analysis of this model revealed two time-constrained windows of opportunity that must be met for the complete transition from the yeast to hyphal phenotype, as well as control strategies that can robustly prevent this transition. We experimentally validate two of these control predictions in C. albicans strains lacking the transcription factor UME6 and the histone deacetylase HDA1, respectively. This model will serve as a strong base from which to develop a systems biology understanding of C. albicans morphogenesis.

Original languageEnglish
Article numbere1008690
JournalPLoS Computational Biology
Volume17
Issue number3
DOIs
StatePublished - Mar 2021

Bibliographical note

Publisher Copyright:
© 2021 Wooten et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding

This work was supported by National Science Foundation (NSF) grants PHY 1545832, MCB-1715826, and IIS-1814405 to R.A., National Institutes of Health (NIH) National Institute of General Medical Sciences (NIGMS) award R35GM124594 to C.J.N., and the Kamangar family in the form of an endowed chair to C.J.N. R.L. was partially supported by NIH grants R011AI135128, U01EB024501, and R01GM127909, and NSF grant CBET-1750183. A.D.B. was supported by NIH grants R01DE013986 and R01GM127909. The content is the sole responsibility of the authors and does not represent the views of the funders. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

FundersFunder number
National Institutes of Health (NIH)
National Science Foundation Arctic Social Science ProgramMCB-1715826, PHY 1545832, 1814405, 1715826, 1750183
National Institute of Biomedical Imaging and BioengineeringU01EB024501
National Institute of Allergy and Infectious F32-AI286447 Cydney N. Johnson Diseases National Institute of Allergy and Infectious R01AI168214 Jason W. Rosch Diseases National Institute of Allergy and Infectious P30 Cydney N. Johnson Diseases National Institute of Allergy and Infectious R00-AI166116 Christopher D. Radka Diseases National Institute of Allergy and Infectious T32-AI106700 Cydney N. Johnson Diseases National Institute of Allergy and Infectious R01AI192221 Jason W. Rosch Diseases National Inst...R01AI135128
National Institute of General Medical Sciences DP2GM119177 Sophie Dumont National Institute of General Medical SciencesR35GM124594, R01GM127909
National Institute of Dental and Craniofacial ResearchR01DE013986
Kamangar familyR011AI135128, R01DE013986, CBET-1750183, U01EB024501, R01GM127909

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Modeling and Simulation
    • Ecology
    • Molecular Biology
    • Genetics
    • Cellular and Molecular Neuroscience
    • Computational Theory and Mathematics

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