An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells

Christian Doppler Laboratory for Infection Biology, Max F. Perutz Laboratories, Medical University of Vienna Vienna, Austria.
Frontiers in Microbiology (Impact Factor: 3.99). 03/2012; 3:85. DOI: 10.3389/fmicb.2012.00085
Source: PubMed

ABSTRACT The ability to adapt to diverse micro-environmental challenges encountered within a host is of pivotal importance to the opportunistic fungal pathogen Candida albicans. We have quantified C. albicans and M. musculus gene expression dynamics during phagocytosis by dendritic cells in a genome-wide, time-resolved analysis using simultaneous RNA-seq. A robust network inference map was generated from this dataset using NetGenerator, predicting novel interactions between the host and the pathogen. We experimentally verified predicted interdependent sub-networks comprising Hap3 in C. albicans, and Ptx3 and Mta2 in M. musculus. Remarkably, binding of recombinant Ptx3 to the C. albicans cell wall was found to regulate the expression of fungal Hap3 target genes as predicted by the network inference model. Pre-incubation of C. albicans with recombinant Ptx3 significantly altered the expression of Mta2 target cytokines such as IL-2 and IL-4 in a Hap3-dependent manner, further suggesting a role for Mta2 in host-pathogen interplay as predicted in the network inference model. We propose an integrated model for the functionality of these sub-networks during fungal invasion of immune cells, according to which binding of Ptx3 to the C. albicans cell wall induces remodeling via fungal Hap3 target genes, thereby altering the immune response to the pathogen. We show the applicability of network inference to predict interactions between host-pathogen pairs, demonstrating the usefulness of this systems biology approach to decipher mechanisms of microbial pathogenesis.

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Available from: Sascha Brunke, Sep 29, 2015
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    • "As RNA sequencing costs continue to drop, it will increasingly be feasible to simultaneously study gene expression profiles of multiple categories of socially interacting individuals within social insect colonies, to provide social systems-level insight into the molecular basis of social regulation of the behaviour, physiology, development and fitness of colony members. Such a more systems-level focused strategy of profiling gene expression of multiple interacting organisms simultaneously has already been used to study the molecular mechanisms underlying host–pathogen interactions (Kollmus et al., 2014; Reid and Berriman, 2012; Tierney et al., 2012; Westermann et al., 2012), and this approach is a conceptually straightforward next step to study the molecular mechanisms underlying social interactions (Linksvayer et al., 2012; Vojvodic et al., 2014). Once candidate genes and gene networks are identified in the various classes of interacting individuals , gene-level approaches can be used to experimentally manipulate expression and quantify effects at the individual-and colony-levels. "
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    ABSTRACT: The social complexity that characterizes the eusocial insects strongly affects all aspects of social insect life, including the molecular and evolutionary genetic basis of social insect traits. Quantitative genetic theory and empirical approaches have been developed over the past 60 years specifically to study the genetic implications of social interactions. Surprisingly, given the obvious biological importance of social interactions in social insects, this research tradition has been and continues to be widely overlooked throughout the social insect literature, including in recent sociogenomic studies focused on understanding the molecular underpinnings of social life. Instead, the overwhelming majority of social insect genetic research has relied on conventional genetic approaches developed for solitary organisms focused on the one-to-one association of an individual's genes to its own traits. I survey social insect studies that conclusively demonstrate the importance of indirect genetic effects (IGEs), which arise from social interactions, for social insect trait expression and evolution. I explain why these genetically based social effects are expected to be ubiquitous in social insects and I explain the relevance of the IGE framework, originally developed within quantitative genetics, for molecular genetic studies of social insect traits such as behaviour and caste. I discuss the problems of ignoring IGEs and relying solely on conventional direct genetic effect approaches. Finally, I discuss the strong potential of using the IGE approach and other more systems-level-focused approaches to complement conventional reductionist approaches in elucidating the genetic basis of social insect trait expression and evolution.
    Advances in insect physiology 12/2015; in press. DOI:10.1016/bs.aiip.2014.12.003 · 2.71 Impact Factor
    • "Significant insight into the exact nature of the various microenvironments that this fungal pathogen occupies in mammalian hosts can be provided by high-throughput technologies that enable the quantification of fluctuations in the abundance of RNA transcripts (transcriptomic), proteins (proteomic), and other biomolecular components (metabolomic) (Fradin et al., 2003; Tierney et al.; 2012, Reales-Calderón et al., 2014; Muszkieta et al., 2013). These technologies will aid in painting " the big picture " of the battle happening between Sporothrix spp. "
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    FEMS Yeast Research 08/2015; 15(6). DOI:10.1093/femsyr/fov065 · 2.82 Impact Factor
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    • "multi-drugresistancepumpshavebeenpublished(Westerhoff etal.,2000).Alargebodyofliteratureonthemodelingof biofilmformationisavailable(Audretschetal.,2013),though mostlyonbacterialratherthanfungalbiofilms,forareview seeHornandLackner(2014).Moreover,ageneregulatory networkwasinferred(Tierneyetal.,2012).Allofthosemodeling techniquescouldinprinciplebeappliedtoinvestigateC.albicans' interactionswiththehost. "
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