Lung infections play a critical role in cystic fibrosis (CF) pathogenesis. CF respiratory tract is now considered to be a polymicrobial niche and advances in high-throughput sequencing allowed to analyze its microbiota and mycobiota. However, no NGS studies until now have characterized both communities during CF pulmonary exacerbation (CFPE). Thirty-three sputa isolated from patients with and without CFPE were used for metagenomic high-throughput sequencing targeting 16S and ITS2 regions of bacterial and fungal rRNA. We built inter-kingdom network and adapted Phy-Lasso method to highlight correlations in compositional data. The decline in respiratory function was associated with a decrease in bacterial diversity. The inter-kingdom network revealed three main clusters organized around Aspergillus, Candida, and Scedosporium genera. Using Phy-Lasso method, we identified Aspergillus and Malassezia as relevantly associated with CFPE, and Scedosporium plus Pseudomonas with a decline in lung function. We corroborated in vitro the cross-domain interactions between Aspergillus and Streptococcus predicted by the correlation network. For the first time, we included documented mycobiome data into a version of the ecological Climax/Attack model that opens new lines of thoughts about the physiopathology of CF lung disease and future perspectives to improve its therapeutic management. Lung infections play a critical role in cystic fibrosis (CF) pathogenesis where they can lead to significant acute decrease of lung function, known as CF pulmonary exacerbation (CFPE). Developments of next-generation sequencing (NGS) approaches allowed us to understand microbiome composition that can contribute to lung physiopathology in both healthy individuals and patients with lung disease. More recently, NGS together with advances into statistical network inference tools allowed to analyze the microbial airway communities, appreciate the inter-kingdom equilibrium of respiratory floras, and therefore develop understanding of microbial communities as a whole 1-7. Acute CFPEs represent major clinical events that significantly decline the lung function, contribute to disease progression and require adapted, prompt anti-infectious treatment 8-11. Omics approaches confirmed associations between bacterial community and exacerbation 12-20. Apart from bacteria that are well known agents causing dramatic recurrent CFPEs, respiratory viruses have been recently found to be associated with CFPE, independently

In recent years, the gut microbiota has been considered as a full-fledged actor of the gut–brain axis, making it possible to take a new step in understanding the pathophysiology of both neurological and psychiatric diseases. However, most of the studies have been devoted to gut bacterial microbiota, forgetting the non-negligible fungal flora. In this review, we expose how the role of the fungal component in the microbiota-gut-brain axis is legitimate, through its interactions with both the host, especially with the immune system, and the gut bacteria. We also discuss published data that already attest to a role of the mycobiome in the microbiota-gut-brain axis, and the impact of fungi on clinical and therapeutic research.

Fungal respiratory colonization of cystic fibrosis (CF) patients emerges as a new concern; however, the heterogeneity of mycological protocols limits investigations. We first aimed at setting up an efficient standardized protocol for mycological analysis of CF sputa that was assessed during a prospective, multicenter study: "MucoFong" program (PHRC-06/1902). Sputa from 243 CF patients from seven centers in France were collected over a 15-month period and submitted to a standardized protocol based on 6 semi-selective media. After mucolytic pretreatment, sputa were plated in parallel on cycloheximide-enriched (ACT37), erythritol-enriched (ERY37), benomyl dichloran-rose bengal (BENO37) and chromogenic (CAN37) media incubated at 37 °C and on Sabouraud-chloramphenicol (SAB27) and erythritol-enriched (ERY27) media incubated at 20-27 °C. Each plate was checked twice a week during 3 weeks. Fungi were conventionally identified; time for detection of fungal growth was noted for each species. Fungal prevalences and media performances were assessed; an optimal combination of media was determined using the Chi-squared automatic interaction detector method. At least one fungal species was isolated from 81% of sputa. Candida albicans was the most prevalent species (58.8%), followed by Aspergillus fumigatus (35.4%). Cultivation on CAN37, SAB27, ACT37 and ERY27 during 16 days provided an optimal combination, detecting C. albicans, A. fumigatus, Scedosporium apiospermum complex and Exophiala spp. with sensitivities of 96.5, 98.8, 100 and 100%. Combination of these four culture media is recommended to ensure the growth of key fungal pathogens in CF respiratory specimens. The use of such consensual protocol is of major interest for merging results from future epidemiological studies.