Dataset Information

Integrative study of the upper and lower airway microbiome and transcriptome in asthma.

ABSTRACT: Relatively little is known about interactions between the airway microbiome and airway host transcriptome in asthma. Since asthma affects and is affected by the entire airway, studying the upper (e.g., nasal) and lower (e.g., bronchial) airways together represents a powerful approach to understanding asthma. Here, we performed a systematic, integrative study of the nasal and bronchial microbiomes and nasal and bronchial host transcriptomes of children with severe persistent asthma and healthy controls. We found that (a) the microbiomes and host transcriptomes of asthmatic children are each distinct by site (nasal versus bronchial); (b) among asthmatic children, Moraxella and Alloiococcus are hub genera in the nasal microbiome, while there are no hubs among bronchial genera; (c) bronchial Actinomyces is negatively associated with bronchial genes for inflammation, suggesting Actinomyces may be protective; (d) compared with healthy children, asthmatic children express more nasal genes for ciliary function and harbor more nasal Streptococcus; and (e) nasal genera such as Corynebacterium are negatively associated with significantly more nasal genes for inflammation in healthy versus asthmatic children, suggesting a potentially stronger protective role for such nasal genera in healthy versus asthmatic children. Our systematic, integrative study provides a window into host-microbiome associations in asthma.

SUBMITTER: Chun Y

PROVIDER: S-EPMC7141394 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Integrative study of the upper and lower airway microbiome and transcriptome in asthma.

Chun Yoojin Y Do Anh A Grishina Galina G Grishin Alexander A Fang Gang G Rose Samantha S Spencer Chantal C Vicencio Alfin A Schadt Eric E Bunyavanich Supinda S

JCI insight 20200312 5

Relatively little is known about interactions between the airway microbiome and airway host transcriptome in asthma. Since asthma affects and is affected by the entire airway, studying the upper (e.g., nasal) and lower (e.g., bronchial) airways together represents a powerful approach to understanding asthma. Here, we performed a systematic, integrative study of the nasal and bronchial microbiomes and nasal and bronchial host transcriptomes of children with severe persistent asthma and healthy co ...[more]

PMID: 32161195

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Project description:The microbial metagenome in cystic fibrosis (CF) airways was investigated by whole-genome shotgun sequencing of total DNA isolated from nasal lavage samples, oropharyngeal swabs, and induced sputum samples collected from 65 individuals with CF aged 7 to 50 years. Each patient harbored a personalized microbial metagenome unique in microbial load and composition, the exception being monocultures of the most common CF pathogens Staphylococcus aureus and Pseudomonas aeruginosa from patients with advanced lung disease. The sampling of the upper airways by nasal lavage uncovered the fungus Malassezia restricta and the bacterium Staphylococcus epidermidis as prominent species. Healthy and CF donors harbored qualitatively and quantitatively different spectra of commensal bacteria in their sputa, even in the absence of any typical CF pathogen. If P. aeruginosa, S. aureus, or Stenotrophomonas maltophilia belonged to the trio of the most abundant species in the CF sputum metagenome, common inhabitants of the respiratory tract of healthy subjects, i.e., Eubacterium sulci, Fusobacterium periodonticum, and Neisseria subflava, were present only in low numbers or not detectable. Random forest analysis identified the numerical ecological parameters of the bacterial community, such as Shannon and Simpson diversity, as the key parameters that globally distinguish sputum samples from CF and healthy donors. IMPORTANCE Cystic fibrosis (CF) is the most common life-limiting monogenetic disease in European populations and is caused by mutations in the CFTR gene. Chronic airway infections with opportunistic pathogens are the major morbidity that determines prognosis and quality of life in most people with CF. We examined the composition of the microbial communities of the oral cavity and upper and lower airways in CF patients across all age groups. From early on, the spectrum of commensals is different in health and CF. Later on, when the common CF pathogens take up residence in the lungs, we observed differential modes of depletion of the commensal microbiota in the presence of S. aureus, P. aeruginosa, S. maltophilia, or combinations thereof. It remains to be seen whether the implementation of lifelong CFTR (cystic fibrosis transmembrane conductance regulator) modulation will change the temporal evolution of the CF airway metagenome.

Project description:BackgroundPredicting which preschool children with recurrent wheezing (RW) will develop school-age asthma (SA) is difficult, highlighting the critical need to clarify the pathogenesis of RW and the mechanistic relationship between RW and SA. Despite shared environmental exposures and genetic determinants, RW and SA are usually studied in isolation. Based on network analysis of nasal and tracheal transcriptomes, we aimed to identify convergent transcriptomic mechanisms in RW and SA.MethodsRNA-sequencing data from nasal and tracheal brushing samples were acquired from the Gene Expression Omnibus. Combined with single-cell transcriptome data, cell deconvolution was used to infer the composition of 18 cellular components within the airway. Consensus weighted gene co-expression network analysis was performed to identify consensus modules closely related to both RW and SA. Shared pathways underlying consensus modules between RW and SA were explored by enrichment analysis. Hub genes between RW and SA were identified using machine learning strategies and validated using external datasets and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, the potential value of hub genes in defining RW subsets was determined using nasal and tracheal transcriptome data.ResultsCo-expression network analysis revealed similarities in the transcriptional networks of RW and SA in the upper and lower airways. Cell deconvolution analysis revealed an increase in mast cell fraction but decrease in club cell fraction in both RW and SA airways compared to controls. Consensus network analysis identified two consensus modules highly associated with both RW and SA. Enrichment analysis of the two consensus modules indicated that fatty acid metabolism-related pathways were shared key signals between RW and SA. Furthermore, machine learning strategies identified five hub genes, i.e., CST1, CST2, CST4, POSTN, and NRTK2, with the up-regulated hub genes in RW and SA validated using three independent external datasets and qRT-PCR. The gene signatures of the five hub genes could potentially be used to determine type 2 (T2)-high and T2-low subsets in preschoolers with RW.ConclusionsThese findings improve our understanding of the molecular pathogenesis of RW and provide a rationale for future exploration of the mechanistic relationship between RW and SA.

Dataset Information

Integrative study of the upper and lower airway microbiome and transcriptome in asthma.

Publications

Integrative study of the upper and lower airway microbiome and transcriptome in asthma.

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