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High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy.

ABSTRACT: Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as Pseudomonas aeruginosa take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401?days from six adult CF subjects (subject mean?=?179?days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While microbiome profiles were personalized (permutational multivariate analysis of variance [PERMANOVA] r 2?=?0.79, P?

SUBMITTER: Raghuvanshi R

PROVIDER: S-EPMC7311317 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy.

Raghuvanshi Ruma R Vasco Karla K Vázquez-Baeza Yoshiki Y Jiang Lingjing L Morton James T JT Li Danxun D Gonzalez Antonio A DeRight Goldasich Lindsay L Humphrey Gregory G Ackermann Gail G Swafford Austin D AD Conrad Douglas D Knight Rob R Dorrestein Pieter C PC Quinn Robert A RA

mSystems 20200623 3

Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as <i>Pseudomonas aeruginosa</i> take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401 days from six adult CF subjects (subject mean = 179 days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While mic ...[more]

PMID: 32576651

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Project description:BackgroundBronchiectasis is accompanied by chronic bronchial infection that may drive disease progression. However, the evidence base for antibiotic therapy is limited. DNA based methods offer better identification and quantification of microbial constituents of sputum than standard clinical culture and may help inform patient management strategies. Our study objective was to determine the longitudinal variability of the non-cystic fibrosis (CF) bronchiectasis microbiome in sputum with respect to clinical variables. Eighty-five patients with non-CF bronchiectasis and daily sputum production were recruited from outpatient clinics and followed for six months. Monthly sputum samples and clinical measurements were taken, together with additional samples during exacerbations. 16S rRNA gene sequencing of the sputum microbiota was successful for 381 samples from 76 patients and analysed in conjunction with clinical data.ResultsMicrobial communities were highly individual in composition and stability, usually with limited diversity and often containing multiple pathogens. When compared to DNA sequencing, microbial culture had restricted sensitivity in identifying common pathogens such as Pseudomonas aeruginosa, Haemophilus influenzae, Moraxella catarrhalis. With some exceptions, community characteristics showed poor correlations with clinical features including underlying disease, antibiotic use and exacerbations, with the subject showing the strongest association with community structure. When present, the pathogens mucoid Pseudomonas aeruginosa and Haemophilus influenzae may also shape the structure of the rest of the microbial community.ConclusionsThe use of microbial community analysis of sputum added to information from microbial culture. A simple model of exacerbations driven by bacterial overgrowth was not supported, suggesting a need for revision of principles for antibiotic therapy. In individual patients, the management of chronic bronchial infection may be improved by therapy specific to their microbiome, taking into account pathogen load, community stability, and acute and chronic community responses to antibiotics.

Project description:In seeking more specific biomarkers of the cystic fibrosis (CF) lung inflammatory disease that would be sensitive to antibiotic therapy, we sought to evaluate the gene expression profiles of neutrophils in CF patients before treatment in comparison with non-CF healthy individuals and after antibiotic treatment. Genes involved in neutrophil-mediated inflammation, i.e. chemotaxis, respiratory burst, apoptosis, and granule exocytosis, were the targets of this study. Microarray analysis was carried out in blood and airway neutrophils from CF patients and in control subjects. A fold change (log) threshold of 1.4 and a cut-off of p<0.05 were utilized to identify significant genes. Community networks and principal component analysis were used to distinguish the groups of controls, pre- and post-therapy patients. Control subjects and CF patients before therapy were readily separated, whereas a clear distinction between patients before and after antibiotic therapy was not possible. Blood neutrophils before therapy presented 269 genes down-regulated and 56 up-regulated as compared with control subjects. Comparison between the same patients before and after therapy showed instead 44 genes down-regulated and 72 up-regulated. Three genes appeared to be sensitive to therapy and returned to "healthy" condition: phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1), hydrogen voltage-gated channel 1 (HVCN1), and β-arrestin 1 (ARRB1). The up-regulation of these genes after therapy were confirmed by real time PCR. In airway neutrophils, 1029 genes were differentially expressed post- vs pre-therapy. Of these, 30 genes were up-regulated and 75 down-regulated following antibiotic treatment. However, biological plausibility determined that only down-regulated genes belonged to the gene classes studied for blood neutrophils. Finally, it was observed that commonly expressed genes showed a greater variability in airway neutrophils than that found in blood neutrophils, both before and after therapy. These results indicate more specific targets for future interventions in CF patients involving respiratory burst, apoptosis, and granule exocytosis.

Project description:BackgroundEmerging experimental and epidemiological evidence highlights a crucial cross-talk between the intestinal flora and the lungs, termed the "gut-lung axis". However, the function of the gut microbiota in bronchiectasis remains undefined. In this study, we aimed to perform a multi-omics-based approach to identify the gut microbiome and metabolic profiles in patients with bronchiectasis.MethodsFecal samples collected from non-CF bronchiectasis patients (BE group, n = 61) and healthy volunteers (HC group, n = 37) were analyzed by 16 S ribosomal RNA (rRNA) sequencing. The BE group was divided into two groups based on their clinical status: acute exacerbation (AE group, n = 31) and stable phase (SP group, n = 30). Further, metabolome (lipid chromatography-mass spectrometry, LC-MS) analyses were conducted in randomly selected patients (n = 29) and healthy volunteers (n = 31).ResultsDecreased fecal microbial diversity and differential microbial and metabolic compositions were observed in bronchiectasis patients. Correlation analyses indicated associations between the differential genera and clinical parameters such as bronchiectasis severity index (BSI). Disease-associated gut microbiota was screened out, with eight genera exhibited high accuracy in distinguishing SP patients from HCs in the discovery cohort and validation cohort using a random forest model. Further correlation networks were applied to illustrate the relations connecting disease-associated genera and metabolites.ConclusionThe study uncovered the relationships among the decreased fecal microbial diversity, differential microbial and metabolic compositions in bronchiectasis patients by performing a multi-omics-based approach. It is the first study to characterize the gut microbiome and metabolome in bronchiectasis, and to uncover the gut microbiota's potentiality as biomarkers for bronchiectasis.Trial registration This study is registered with ClinicalTrials.gov, number NCT04490447.

Dataset Information

High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy.

Publications

High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy.

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