Fungal disease is an increasingly recognised global clinical challenge associated with high mortality. Early diagnosis of fungal infection remains problematic due to the poor sensitivity and specificity of current diagnostic modalities. Advances in sequencing technologies hold promise in addressing these shortcomings and for improved fungal detection and identification. To translate such emerging approaches into mainstream clinical care will require refinement of current sequencing and analytical platforms, ensuring standardisation and consistency through robust clinical benchmarking and its validation across a range of patient populations. In this stateof-the-art review, we discuss current diagnostic and therapeutic challenges associated with fungal disease and provide key examples where the application of sequencing technologies has potential diagnostic application in assessing the human 'mycobiome'. We assess how ready access to fungal sequencing may be exploited in broadening our insight into hostfungal interaction, providing scope for clinical diagnostics and the translation of emerging mycobiome research into clinical practice.

SignificanceThis manuscript describes a precise diel cycle carried out by airborne microbiota in the tropics. 795 metagenomes from air samples taken from a single site show that fungi, bacteria, and plants all adhere to a specific timing for their presence in the near-surface atmosphere. The airborne community composition thereby shows an unexpected robustness, with the majority of the dynamics in taxa composition occurring within 24 h, but not across days, weeks, or months. Environmental parameters are the main drivers for the observed phenomenon, with temperature being the most important one.

Rationale: Long-term antibiotic use for managing chronic respiratory disease is increasing; however, the role of the airway resistome and its relationship to host microbiomes remains unknown. Objectives: To evaluate airway resistomes and relate them to host and environmental microbiomes using ultradeep metagenomic shotgun sequencing. Methods: Airway specimens from 85 individuals with and without chronic respiratory disease (severe asthma, chronic obstructive pulmonary disease, and bronchiectasis) were subjected to metagenomic sequencing to an average depth exceeding 20 million reads. Respiratory and device-associated microbiomes were evaluated on the basis of taxonomical classification and functional annotation including the Comprehensive Antibiotic Resistance Database to determine airway resistomes. Co-occurrence networks of gene–microbe association were constructed to determine potential microbial sources of the airway resistome. Paired patient-inhaler metagenomes were compared ( n = 31) to assess for the presence of airway–environment overlap in microbiomes and/or resistomes. Measurements and Main Results: Airway metagenomes exhibit taxonomic and metabolic diversity and distinct antimicrobial resistance patterns. A “core” airway resistome dominated by macrolide but with high prevalence of β-lactam, fluoroquinolone, and tetracycline resistance genes exists and is independent of disease status or antibiotic exposure. Streptococcus and Actinomyces are key potential microbial reservoirs of macrolide resistance including the ermX , ermF , and msrD genes. Significant patient-inhaler overlap in airway microbiomes and their resistomes is identified where the latter may be a proxy for airway microbiome assessment in chronic respiratory disease. Conclusions: Metagenomic analysis of the airway reveals a core macrolide resistome harbored by the host microbiome.