Honokiol reduces fungal burden and ameliorate inflammation lesions of Aspergillus fumigatus keratitis via Dectin-2 down-regulation

Fungal diseases kill more than 1.5 million and affect over a billion people. However, they are still a neglected topic by public health authorities even though most deaths from fungal diseases are avoidable. Serious fungal infections occur as a consequence of other health problems including asthma, AIDS, cancer, organ transplantation and corticosteroid therapies. Early accurate diagnosis allows prompt antifungal therapy; however this is often delayed or unavailable leading to death, serious chronic illness or blindness. Recent global estimates have found 3,000,000 cases of chronic pulmonary aspergillosis, ~223,100 cases of cryptococcal meningitis complicating HIV/AIDS, ~700,000 cases of invasive candidiasis, ~500,000 cases of Pneumocystis jirovecii pneumonia, ~250,000 cases of invasive aspergillosis, ~100,000 cases of disseminated histoplasmosis, over 10,000,000 cases of fungal asthma and ~1,000,000 cases of fungal keratitis occur annually. Since 2013, the Leading International Fungal Education (LIFE) portal has facilitated the estimation of the burden of serious fungal infections country by country for over 5.7 billion people (>80% of the world’s population). These studies have shown differences in the global burden between countries, within regions of the same country and between at risk populations. Here we interrogate the accuracy of these fungal infection burden estimates in the 43 published papers within the LIFE initiative.

Fungal infections represent a serious threat, particularly in immunocompromised patients. Interleukin-1beta (IL-1beta) is a key pro-inflammatory factor in innate antifungal immunity. The mechanism by which the mammalian immune system regulates IL-1beta production after fungal recognition is unclear. Two signals are generally required for IL-1beta production: an NF-kappaB-dependent signal that induces the synthesis of pro-IL-1beta (p35), and a second signal that triggers proteolytic pro-IL-1beta processing to produce bioactive IL-1beta (p17) via Caspase-1-containing multiprotein complexes called inflammasomes. Here we demonstrate that the tyrosine kinase Syk, operating downstream of several immunoreceptor tyrosine-based activation motif (ITAM)-coupled fungal pattern recognition receptors, controls both pro-IL-1beta synthesis and inflammasome activation after cell stimulation with Candida albicans. Whereas Syk signalling for pro-IL-1beta synthesis selectively uses the Card9 pathway, inflammasome activation by the fungus involves reactive oxygen species production and potassium efflux. Genetic deletion or pharmalogical inhibition of Syk selectively abrogated inflammasome activation by C. albicans but not by inflammasome activators such as Salmonella typhimurium or the bacterial toxin nigericin. Nlrp3 (also known as NALP3) was identified as the critical NOD-like receptor family member that transduces the fungal recognition signal to the inflammasome adaptor Asc (Pycard) for Caspase-1 (Casp1) activation and pro-IL-1beta processing. Consistent with an essential role for Nlrp3 inflammasomes in antifungal immunity, we show that Nlrp3-deficient mice are hypersusceptible to Candida albicans infection. Thus, our results demonstrate the molecular basis for IL-1beta production after fungal infection and identify a crucial function for the Nlrp3 inflammasome in mammalian host defence in vivo.

Advances in omics technologies — such as genomics, transcriptomics, proteomics and metabolomics — have begun to enable personalized medicine at an extraordinarily detailed molecular level. Individually, these technologies have contributed medical advances that have begun to enter clinical practice. However, each technology individually cannot capture the entire biological complexity of most human diseases. Integration of multiple technologies has emerged as an approach to provide a more comprehensive view of biology and disease. In this Review, we discuss the potential for combining diverse types of data and the utility of this approach in human health and disease. We provide examples of data integration to understand, diagnose and inform treatment of diseases, including rare and common diseases as well as cancer and transplant biology. Finally, we discuss technical and other challenges to clinical implementation of integrative omics.