Divergence of bacterial communities in the lower airways of CF patients in early childhood

Comparison of the sputum microbiome between patients with stable nontuberculous mycobacterial pulmonary disease and patients requiring treatment

BACKGROUND

We evaluated whether the sputum bacterial microbiome differs between nontuberculous mycobacteria pulmonary disease (NTM-PD) patients with stable disease not requiring antibiotic treatment and those requiring antibiotics.

METHODS

We collected sputum samples from 21 clinically stable NTM-PD patients (stable group) and 14 NTM-PD patients needing antibiotic treatment (treatment group). We also obtained 13 follow-up samples from the stable group. We analyzed the 48 samples using 16S rRNA gene sequencing (V3-V4 region) and compared the groups.

RESULTS

In the linear discriminant analysis effect size (LEfSe) analysis, the species Porphyromonas pasteri, Haemophilus parahaemolyticus, Prevotella nanceiensis, and Gemella haemolysans were significantly more prevalent in the sputum of the stable group compared to the treatment group. No taxa showed significant differences in alpha-/beta-diversity or LEfSe between the 21 baseline and 13 follow-up sputum samples in the stable group. In the stable group, the genus Bergeyella and species Prevotella oris were less common in patients who achieved spontaneous culture conversion (n = 9) compared to those with persistent NTM positivity (n = 12) (effect size 3.04, p = 0.039 for Bergeyella; effect size 3.64, p = 0.033 for P. oris). In the treatment group, H. parainfluenzae was more common in patients with treatment success (n = 7) than in treatment-refractory patients (n = 7) (effect size 4.74, p = 0.013).

CONCLUSIONS

Our study identified distinct bacterial taxa in the sputum of NTM-PD patients based on disease status. These results suggest the presence of a microbial environment that helps maintain disease stability.

Isolated abnormal FEF75% detects unsuspected bronchiolar obstruction in CF children

BACKGROUND

Physiologic detection of bronchiolar obstruction in children with cystic fibrosis (CF) may be clinically unsuspected because of normal routine spirometry despite bronchiectasis on lung CT.

METHODS

Children from two accredited CF facilities had spirometry obtained every 3 months when clinically stable. Pre-bronchodilator maximum expiratory flow volume curves were retrospectively analyzed over 16 years to detect an isolated abnormal FEF75%, despite normal routine spirometry.

RESULTS

At Miller Children's and Women's Hospital (MCWH), an abnormal FEF75% was initially detected in 26 CF children at age 7.5 ± 4 (SD) years despite normal routine spirometry initially. FEF75% remained an isolated abnormality for 2.5 ± 1.5 years after it was initially detected in these 26 CF children. At Cohen Children's Medical Center (CCMC), despite normal routine spirometry initially, abnormal FEF75% occurred in 13 children at age 11.7 ± 4.5 years, and abnormal FEF25-75% in 10 children at age 11.8 ± 5.3 years.

CONCLUSIONS

FEF75% was most sensitive spirometric test for diagnosing both early and isolated progressive bronchiolar obstruction. Data from CCMC in older children demonstrated the simultaneous detection of abnormal FEF75% and FEF25-75% values consistent with greater bronchiolar obstruction when serial spirometry was initiated at an older age.

IMPACT

There is very little published spirometric data regarding diagnosis of isolated small airways obstruction in CF children. FEF75% can easily detect unsuspected small airways obstruction in CF children with normal routine spirometry and bronchiectasis on lung CT and optimize targeted modulatory therapies.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

Detection and identification of fungi in the lower airway of children with and without cystic fibrosis

Introduction

Airway infection and inflammation lead to the progression of obstructive lung disease in persons with cystic fibrosis (PWCF). However, cystic fibrosis (CF) fungal communities, known drivers of CF pathophysiology, remain poorly understood due to the shortcomings of traditional fungal culture. Our objective was to apply a novel small subunit rRNA gene (SSU-rRNA) sequencing approach to characterize the lower airway mycobiome in children with and without CF.

Methods

Bronchoalveolar lavage fluid (BALF) samples and relevant clinical data were collected from pediatric PWCF and disease control (DC) subjects. Total fungal load (TFL) was measured using quantitative PCR, and SSU-rRNA sequencing was used for mycobiome characterization. Results were compared across groups, and Morisita-Horn clustering was performed.

Results

161 (84%) of the BALF samples collected had sufficient load for SSU-rRNA sequencing, with amplification being more common in PWCF. BALF from PWCF had increased TFL and increased neutrophilic inflammation compared to DC subjects. PWCF exhibited increased abundance of Aspergillus and Candida, while Malassezia, Cladosporium, and Pleosporales were prevalent in both groups. CF and DC samples showed no clear differences in clustering when compared to each other or to negative controls. SSU-rRNA sequencing was used to profile the mycobiome in pediatric PWCF and DC subjects. Notable differences were observed between the groups, including the abundance of Aspergillus and Candida.

Discussion

Fungal DNA detected in the airway could represent a combination of pathogenic fungi and environmental exposure (e.g., dust) to fungus indicative of a common background signature. Next steps will require comparisons to airway bacterial communities.

The Impact of Highly Effective Modulator Therapy on Cystic Fibrosis Microbiology and Inflammation

Highly effective cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator therapy (HEMT) corrects the underlying molecular defect causing CF disease. HEMT decreases symptom burden and improves clinical metrics and quality of life for most people with CF (PwCF) and eligible cftr mutations. Improvements in measures of pulmonary health suggest that restoration of function of defective CFTR anion channels by HEMT not only enhances airway mucociliary clearance, but also reduces chronic pulmonary infection and inflammation. This article reviews the evidence for how HEMT influences the dynamic and interdependent processes of infection and inflammation in the CF airway, and what questions remain unanswered.

Network Analysis to Identify Multi-Omic Correlations in the Lower Airways of Children With Cystic Fibrosis

The leading cause of morbidity and mortality in cystic fibrosis (CF) is progressive lung disease secondary to chronic airway infection and inflammation; however, what drives CF airway infection and inflammation is not well understood. By providing a physiological snapshot of the airway, metabolomics can provide insight into these processes. Linking metabolomic data with microbiome data and phenotypic measures can reveal complex relationships between metabolites, lower airway bacterial communities, and disease outcomes. In this study, we characterize the airway metabolome in bronchoalveolar lavage fluid (BALF) samples from persons with CF (PWCF) and disease control (DC) subjects and use multi-omic network analysis to identify correlations with the airway microbiome. The Biocrates targeted liquid chromatography mass spectrometry (LC-MS) platform was used to measure 409 metabolomic features in BALF obtained during clinically indicated bronchoscopy. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR). The Qiagen EZ1 Advanced automated extraction platform was used to extract DNA, and bacterial profiling was performed using 16S sequencing. Differences in metabolomic features across disease groups were assessed univariately using Wilcoxon rank sum tests, and Random forest (RF) was used to identify features that discriminated across the groups. Features were compared to TBL and markers of inflammation, including white blood cell count (WBC) and percent neutrophils. Sparse supervised canonical correlation network analysis (SsCCNet) was used to assess multi-omic correlations. The CF metabolome was characterized by increased amino acids and decreased acylcarnitines. Amino acids and acylcarnitines were also among the features most strongly correlated with inflammation and bacterial burden. RF identified strong metabolomic predictors of CF status, including L-methionine-S-oxide. SsCCNet identified correlations between the metabolome and the microbiome, including correlations between a traditional CF pathogen, Staphylococcus, a group of nontraditional taxa, including Prevotella, and a subnetwork of specific metabolomic markers. In conclusion, our work identified metabolomic characteristics unique to the CF airway and uncovered multi-omic correlations that merit additional study.

Cystic fibrosis in children: A pediatric anesthesiologist's perspective

Cystic fibrosis is a multi-systemic disease of impaired sodium and chloride transport across epithelial surfaces. Cystic fibrosis is one of the most common autosomal recessive diseases among Caucasian children. However, recent epidemiologic studies suggest that the disease in Hispanic, African American, and Asian American populations may be more common than previously recognized. The phenotypic expression is characterized by the constellation of pulmonary, pancreatic, hepatobiliary, and gastrointestinal dysfunction. Progressive obstructive lung disease is the hallmark of cystic fibrosis, and end-stage respiratory failure is the primary cause of morbidity and mortality. The most significant advance in the care has been the development of cystic fibrosis modulators, a class of drugs that restore cystic fibrosis transmembrane conductance regulator folding, intracellular processing, or function. Improved diagnostic abilities, a multidisciplinary approach to medical management, and the use of cystic fibrosis modulators have led to improvement in the quality of life and life expectancy. These patients undergo range of procedures such as nasal polypectomy, placement of gastrostomy tubes, vascular access device placement, transbronchial lung biopsies, and other thoracic surgeries. The anesthetic care of children with advanced cystic fibrosis disease is complex. Preoperative optimization can help improve postoperative outcomes. Strategies for pain control should rely on non-opiate, multimodal adjuncts, and regional or neuraxial techniques. Unfortunately for some children, a progressive respiratory disease often leads to end-stage respiratory failure and lung transplant surgery remains the only viable treatment option. Widespread use of lung transplant surgery as a treatment option is severely constraint by donor organ availability. Primary graft dysfunction is the most common cause of early death and can be seen within 48 h of surgery. Median long-term survival after lung transplant remains modest. Chronic lung allograft dysfunction, opportunistic infections, and post-transplant lymphoproliferative disorder are the most common causes of morbidity and mortality among long-term survivors.

Oral Prevotella Species and Their Connection to Events of Clinical Relevance in Gastrointestinal and Respiratory Tracts

Prevotella is recognized as one of the core anaerobic genera in the oral microbiome. In addition, members of this genus belong to microbial communities of the gastrointestinal and respiratory tracts. Several novel Prevotella species, most of them of oral origin, have been described, but limited knowledge is still available of their clinical relevance. Prevotella melaninogenica is among the anaerobic commensals on oral mucosae from early months of life onward, and other early colonizing Prevotella species in the oral cavity include Prevotella nigrescens and Prevotella pallens. Oral Prevotella species get constant access to the gastrointestinal tract via saliva swallowing and to lower airways via microaspiration. At these extra-oral sites, they play a role as commensals but also as potentially harmful agents on mucosal surfaces. The aim of this narrative review is to give an updated overview on the involvement of oral Prevotella species in gastrointestinal and respiratory health and disease.