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

Overview of attention for article published in Frontiers in Microbiology, January 2012
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Title
An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells
Published in
Frontiers in Microbiology, January 2012
DOI 10.3389/fmicb.2012.00085
Pubmed ID
Authors

Lanay Tierney, Jörg Linde, Sebastian Müller, Sascha Brunke, Juan Camilo Molina, Bernhard Hube, Ulrike Schöck, Reinhard Guthke, Karl Kuchler

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.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Brazil 4 2%
United Kingdom 2 <1%
Switzerland 1 <1%
Italy 1 <1%
Germany 1 <1%
Korea, Republic of 1 <1%
Poland 1 <1%
Unknown 196 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 62 29%
Student > Ph. D. Student 51 24%
Student > Master 19 9%
Student > Bachelor 17 8%
Student > Doctoral Student 14 7%
Other 30 14%
Unknown 20 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 104 49%
Biochemistry, Genetics and Molecular Biology 35 16%
Immunology and Microbiology 16 8%
Computer Science 7 3%
Medicine and Dentistry 4 2%
Other 19 9%
Unknown 28 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2012.
All research outputs
#17,656,460
of 22,664,644 outputs
Outputs from Frontiers in Microbiology
#16,893
of 24,446 outputs
Outputs of similar age
#191,272
of 244,051 outputs
Outputs of similar age from Frontiers in Microbiology
#177
of 318 outputs
Altmetric has tracked 22,664,644 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,446 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 244,051 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 318 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.