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BackgroundAspergillus fumigatus is a ubiquitous airborne fungal pathogen that presents a life-threatening health risk to individuals with weakened immune systems. A. fumigatus pathogenicity depends on its ability to acquire iron from the host and to resist host-generated oxidative stress. Gaining a deeper understanding of the molecular mechanisms governing A. fumigatus iron acquisition and oxidative stress response may ultimately help to improve the diagnosis and treatment of invasive aspergillus infections.ResultsThis study follows a systems biology approach to investigate how adaptive behaviors emerge from molecular interactions underlying A. fumigatus iron regulation and oxidative stress response. We construct a Boolean network model from known interactions and simulate how changes in environmental iron and superoxide levels affect network dynamics. We propose rules for linking long term model behavior to qualitative estimates of cell growth and cell death. These rules are used to predict phenotypes of gene deletion strains. The model is validated on the basis of its ability to reproduce literature data not used in model generation.ConclusionsThe model reproduces gene expression patterns in experimental time course data when A. fumigatus is switched from a low iron to a high iron environment. In addition, the model is able to accurately represent the phenotypes of many knockout strains under varying iron and superoxide conditions. Model simulations support the hypothesis that intracellular iron regulates A. fumigatus transcription factors, SreA and HapX, by a post-translational, rather than transcriptional, mechanism. Finally, the model predicts that blocking siderophore-mediated iron uptake reduces resistance to oxidative stress. This indicates that combined targeting of siderophore-mediated iron uptake and the oxidative stress response network may act synergistically to increase fungal cell killing.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0163-1) contains supplementary material, which is available to authorized users.

Allergens are molecules that elicit a hypersensitive inflammatory response in sensitized individuals and are derived from a variety of sources. Alt a 1 is the most clinically important secreted allergen of the ubiquitous fungus, Alternaria. It has been shown to be a major allergen causing IgE-mediated allergic response in the vast majority of Alternaria-sensitized individuals. However, no studies have been conducted in regards to the innate immune eliciting activities of this clinically relevant protein. In this study, recombinant Alt a 1 was produced, purified, labeled, and incubated with BEAS-2B, NHBE, and DHBE human lung epithelial cells. Alt a 1 elicited strong induction of IL-8, MCP-1, and Gro-a/b/g. Using gene-specific siRNAs, blocking antibodies, and chemical inhibitors such as LPS-RS, it was determined that Alt a 1-induced immune responses were dependent upon toll-like receptors (TLRs) 2 and 4, and the adaptor proteins MYD88 and TIRAP. Studies utilizing human embryonic kidney cells engineered to express single receptors on the cell surface such as TLRs, further confirmed that Alt a 1-induced innate immunity is dependent upon TLR4 and to a lesser extent TLR2.

Highlights d Human airway epithelial cells display the receptor LYSMD3 on their surface d LYSMD3 contains a LysM (chitin-binding) domain and is able to bind chitin and fungi d Chitin and fungi fuel cytokine release by binding LYSMD3 on airway epithelial cells d LYSMD3 also binds b-glucan and therefore may also sense b-glucan

Clostridium difficile infections are associated with the use of broad-spectrum antibiotics and result in an exuberant inflammatory response, leading to nosocomial diarrhea, colitis and even death. To better understand the dynamics of mucosal immunity during C. difficile infection from initiation through expansion to resolution, we built a computational model of the mucosal immune response to the bacterium. The model was calibrated using data from a mouse model of C. difficile infection. The model demonstrates a crucial role of T helper 17 (Th17) effector responses in the colonic lamina propria and luminal commensal bacteria populations in the clearance of C. difficile and colonic pathology, whereas regulatory T (Treg) cells responses are associated with the recovery phase. In addition, the production of anti-microbial peptides by inflamed epithelial cells and activated neutrophils in response to C. difficile infection inhibit the re-growth of beneficial commensal bacterial species. Computational simulations suggest that the removal of neutrophil and epithelial cell derived anti-microbial inhibitions, separately and together, on commensal bacterial regrowth promote recovery and minimize colonic inflammatory pathology. Simulation results predict a decrease in colonic inflammatory markers, such as neutrophilic influx and Th17 cells in the colonic lamina propria, and length of infection with accelerated commensal bacteria re-growth through altered anti-microbial inhibition. Computational modeling provides novel insights on the therapeutic value of repopulating the colonic microbiome and inducing regulatory mucosal immune responses during C. difficile infection. Thus, modeling mucosal immunity-gut microbiota interactions has the potential to guide the development of targeted fecal transplantation therapies in the context of precision medicine interventions.