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Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host–microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD.

Pulmonary mycoses remain a global threat, causing significant morbidity and mortality. Patients with airways disease, including COPD and bronchiectasis, are at increased risks of pulmonary mycoses and its associated complications. Frequent use of antibiotics and corticosteroids coupled with impaired host defenses predispose patients to fungal colonization and airway persistence, which are associated with negative clinical consequences. Notably, Aspergillus species remain the best-studied fungal pathogen and induce a broad spectrum of clinical manifestations in COPD and bronchiectasis ranging from colonization and sensitization to more invasive disease. Next-generation sequencing (NGS) has gained prominence in the field of respiratory infection, and in some cases is beginning to act as a viable alternative to traditional culture. NGS has revolutionized our understanding of airway microbiota and in particular fungi. In this context, it permits the identification of the previously unculturable, fungal composition, and dynamic change within microbial communities of the airway, including potential roles in chronic respiratory disease. Furthermore, inter-kingdom microbial interactions, including fungi, in conjunction with host immunity have recently been shown to have important clinical roles in COPD and bronchiectasis. In this review, we provide an overview of clinical Aspergillus signatures in COPD and bronchiectasis and cover the current advances in the understanding of the mycobiome in these disease states. The challenges and limitations of NGS will be addressed.

Smart wearable sensors are essential for continuous health-monitoring applications and detection accuracy of symptoms and energy efficiency of processing algorithms are key challenges for such devices. While several machine-learning-based algorithms for the detection of abnormal breath sounds are reported in literature, they are either too computationally expensive to implement into a wearable device or inaccurate in multi-class detection. In this paper, a kernel-like minimum distance classifier (K-MDC) for acoustic signal processing in wearable devices was proposed. The proposed algorithm was tested with data acquired from open-source databases, participants, and hospitals. It was observed that the proposed K-MDC classifier achieves accurate detection in up to 91.23% of cases, and it reaches various detection accuracies with a fewer number of features compared with other classifiers. The proposed algorithm’s low computational complexity and classification effectiveness translate to great potential for implementation in health-monitoring wearable devices.

Airway inflammation plays a central role in bronchiectasis. Protease–antiprotease balance is crucial in bronchiectasis pathophysiology and increased presence of unopposed proteases activity may contribute to bronchiectasis onset and progression. Proteases’ over-reactivity and antiprotease deficiency may have a role in increasing inflammation in bronchiectasis airways and may lead to extracellular matrix degradation and tissue damage. Imbalances in serine proteases and matrix-metallo proteinases (MMPs) have been associated to bronchiectasis. Active neutrophil elastase has been associated with disease severity and poor long-term outcomes in this disease. Moreover, high levels of MMPs have been associated with radiological and disease severity. Finally, severe deficiency of α1-antitrypsin (AAT), as PiSZ and PiZZ (proteinase inhibitor SZ and ZZ) phenotype, have been associated with bronchiectasis development. Several treatments are under study to reduce protease activity in lungs. Molecules to inhibit neutrophil elastase activity have been developed in both oral or inhaled form, along with compounds inhibiting dipeptydil-peptidase 1, enzyme responsible for the activation of serine proteases. Finally, supplementation with AAT is in use for patients with severe deficiency. The identification of different targets of therapy within the protease–antiprotease balance contributes to a precision medicine approach in bronchiectasis and eventually interrupts and disrupts the vicious vortex which characterizes the disease.

The respiratory tract harbors a stable and diverse microbial population within an extracellular mucus layer. Mucus provides a formidable defense against infection and maintaining healthy mucus is essential to normal pulmonary physiology, promoting immune tolerance and facilitating a healthy, commensal lung microbiome that can be altered in association with chronic respiratory disease. How one maintains a specialized (healthy) microbiome that resists significant fluctuation remains unknown, although smoking, diet, antimicrobial therapy, and infection have all been observed to influence microbial lung homeostasis. In this review, we outline the specific role of polymerizing mucin, a key functional component of the mucus layer that changes during pulmonary disease. We discuss strategies by which mucin feed and spatial orientation directly influence microbial behavior and highlight how a compromised mucus layer gives rise to inflammation and microbial dysbiosis. This emerging field of respiratory research provides fresh opportunities to examine mucus, and its function as predictors of infection risk or disease progression and severity across a range of chronic pulmonary disease states and consider new perspectives in the development of mucolytic treatments.

Invasive aspergillosis (IA) is a major opportunistic fungal infection in patients with haematological malignancies. Morbidity and mortality rates are high despite anti-fungal treatment, as the compromised status of immune system prevents the host from responding optimally to conventional therapy. This raises the consideration for immunotherapy as an adjunctive treatment. In this study, we evaluated the utility of expanded human NK cells as treatment against Aspergillus fumigatus infection in vitro and in vivo. The NK cells were expanded and activated by K562 cells genetically modified to express 4-1BB ligand and membrane-bound interleukin-15 (K562-41BBL-mbIL-15) as feeders. The efficacy of these cells was investigated in A. fumigatus killing assays in vitro and as adoptive cellular therapy in vivo. The expanded NK cells possessed potent killing activity at low effector-to-target ratio of 2:1. Fungicidal activity was morphotypal-dependent and most efficacious against A. fumigatus conidia. Fungicidal activity was mediated by dectin-1 receptors on the expanded NK cells leading to augmented release of perforin, resulting in enhanced direct cytolysis. In an immunocompromised mice pulmonary aspergillosis model, we showed that NK cell treatment significantly reduced fungal burden, hence demonstrating the translational potential of expanded NK cells as adjunctive therapy against IA in immunocompromised patients.

Background: Prior studies illustrate the presence and clinical importance of detecting Aspergillus species in the airways of patients with chronic respiratory disease. Despite this, a low fungal biomass and the presence of PCR inhibitors limits the usefulness of quantitative PCR (qPCR) for accurate absolute quantification of Aspergillus in specimens from the human airway. Droplet digital PCR (ddPCR) however, presents an alternative methodology allowing higher sensitivity and accuracy of such quantification but remains to be evaluated in head-to-head fashion using specimens from the human airway. Here, we implement a standard duplex TaqMan PCR protocol, and assess if ddPCR is superior in quantifying airway Aspergillus when compared to standard qPCR. Methods: The molecular approaches of qPCR and ddPCR were applied to DNA fungal extracts in n = 20 sputum specimens obtained from non-diseased (n = 4), chronic obstructive pulmonary disease (COPD; n = 8) and non-cystic fibrosis bronchiectasis (n = 8) patients where Aspergillus status was known. DNA was extracted and qPCR and ddPCR performed on all specimens with appropriate controls and head-to-head comparisons performed. Results: Standard qPCR and ddPCR were both able to detect, even at low abundance, Aspergillus species (Aspergillus fumigatus - A. fumigatus and Aspergillus terreus - A. terreus) from specimens known to contain the respective fungi. Importantly, however, ddPCR was superior for the detection of A. terreus particularly when present at very low abundance and demonstrates greater resistance to PCR inhibition compared to qPCR. Conclusion: ddPCR has greater sensitivity for A. terreus detection from respiratory specimens, and is more resistant to PCR inhibition, important attributes considering the importance of A. terreus species in chronic respiratory disease states such as bronchiectasis.

(1) Background: Firm consensus has yet to be established in relation to taxonomic classification and primer choice in targeted amplicon sequencing of the mycobiome. While the nuclear ribosomal internal transcribed spacer (ITS) region are recognized as the formal fungal taxonomic barcode, appraisal of different ITS sub-regions and the influence of DNA extraction methods have not been comprehensively undertaken using human respiratory specimens. (2) Methods: We performed ITS analysis of respiratory (sputum) samples by assessing (a) the effect of alternate DNA extraction techniques and (b) an evaluation of four different ITS primer pairs (ITS1F and ITS2; ITS1-30F and ITS1-217R; gITS7ngs and ITS4ng; and Fseq and Rseq) on the mycobiome profiles generated for mock fungal communities and their respective clinical (airway) specimens. (3) Results: Primer pairs varied in their resulting ITS mycobiome profiles, suggesting that particular pairs may be more relevant for analysis of respiratory samples compared to others. Assessment of DNA extraction methods highlighted lower final DNA concentrations achieved by mechanical disruption compared to enzymatic lysis. However, despite lower yields, DNA liberated by mechanical lysis more readily yielded ITS bands with highest success in combination with the Fseq and Rseq primers. (4) Conclusion: Choice of extraction method, primers used, and sequencing approach are all important considerations in sequencing the mycobiome and should be tailored to sample type. A standardization of approach to mycobiome studies using respiratory specimens will permit more reliable comparisons between studies and improve our understanding of the role of fungi in the human airway.