Literature DB >> 29318385

Transcription factor network efficiency in the regulation of Candida albicans biofilms: it is a small world.

Virginia E Glazier1, Damian J Krysan2.   

Abstract

Complex biological processes are frequently regulated through networks comprised of multiple signaling pathways, transcription factors, and effector molecules. The identity of specific genes carrying out these functions is usually determined by single mutant genetic analysis. However, to understand how the individual genes/gene products function, it is necessary to determine how they interact with other components of the larger network; one approach to this is to use genetic interaction analysis. The human fungal pathogen Candida albicans regulates biofilm formation through an interconnected set of transcription factor hubs and is, therefore, an example of this type of complex network. Here, we describe experiments and analyses designed to understand how the C. albicans biofilm transcription factor hubs interact and to explore the role of network structure in its overall function. To do so, we analyzed published binding and genetic interaction data to characterize the topology of the network. The hubs are best characterized as a small world network that functions with high efficiency and low robustness (high fragility). Highly efficient networks rapidly transmit perturbations at given nodes to the rest of the network. Consistent with this model, we have found that relatively modest perturbations, such as reduction in the gene dosage of hub transcription factors by one-half, lead to significant alterations in target gene expression and biofilm fitness. C. albicans biofilm formation occurs under very specific environmental conditions and we propose that the fragile, small world structure of the genetic network is part of the mechanism that imposes this stringency.

Entities:  

Keywords:  Biofilm formation; Candida albicans; Epistasis; Genetic networks; Transcription factors

Mesh:

Substances:

Year:  2018        PMID: 29318385     DOI: 10.1007/s00294-018-0804-1

Source DB:  PubMed          Journal:  Curr Genet        ISSN: 0172-8083            Impact factor:   3.886


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