Dataset Information

Metagenomic Characterization of Indoor Dust Bacterial and Fungal Microbiota in Homes of Asthma and Non-asthma Patients Using Next Generation Sequencing.

ABSTRACT: Background:The exposure of house occupants to indoor air pollutants has increased in recent decades. Among microbiological contaminants, bacterial and fungal aerosols remain poorly studied and the debate on the impact of these aerosols on respiratory health is still open. This study aimed to assess the diversity of indoor microbial communities in relationship with the health of occupants. Methods:Measurements were taken from dwellings of 2 cohorts in Brittany (France), one with children without any pathology and the other with children and adults with asthma. Thirty dust samples were analyzed by next generation sequencing with a 16S and 18S targeted metagenomics approach. Analysis of sequencing data was performed using qiime 2, and univariate and multivariate statistical analysis using R software and phyloseq package. Results:A total of 2,637 prokaryotic (589 at genus level) and 2,153 eukaryotic taxa were identified (856 fungal taxa (39%) and 573 metazoa (26%)). The four main bacterial phyla were identified: Proteobacteria (53%), Firmicutes (27%), Actinobacteria (11%), Bacteroidetes (8%). Among Fungi, only 136 taxa were identified at genus level. Three main fungal phyla were identified: Ascomycota (84%), Basidiomycota (12%) and Mucoromycota (3%). No bacterial nor fungal phyla were significantly associated with asthma versus control group. A significant over representation in control group versus asthma was observed for Christensenellaceae family (p-value = 0.0015, adj. p-value = 0.033). Besides, a trend for over representation in control group was observed with Dermabacteraceae family (p-value = 0.0002, adj. p-value = 0.815). Conclusions:Our findings provide evidence that dust samples harbor a high diversity of human-associated bacteria and fungi. Molecular methods such as next generation sequencing are reliable tools for identifying and tracking the bacterial and fungal diversity in dust samples, a less easy strategy for the detection of eukaryotes at least using18S metagenomics approach. This study showed that the detection of some bacteria might be associated to indoor air of asthmatic patients. Regarding fungi, a higher number of samples and sequencing with more depth could allow reaching significant signatures.

SUBMITTER: Gangneux JP

PROVIDER: S-EPMC7409152 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Metagenomic Characterization of Indoor Dust Bacterial and Fungal Microbiota in Homes of Asthma and Non-asthma Patients Using Next Generation Sequencing.

Gangneux Jean-Pierre JP Sassi Mohamed M Lemire Pierre P Le Cann Pierre P

Frontiers in microbiology 20200730

<h4>Background</h4>The exposure of house occupants to indoor air pollutants has increased in recent decades. Among microbiological contaminants, bacterial and fungal aerosols remain poorly studied and the debate on the impact of these aerosols on respiratory health is still open. This study aimed to assess the diversity of indoor microbial communities in relationship with the health of occupants.<h4>Methods</h4>Measurements were taken from dwellings of 2 cohorts in Brittany (France), one with ch ...[more]

PMID: 32849345

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Project description:UnlabelledDampness and visible mold in homes are associated with asthma development, but causal mechanisms remain unclear. The goal of this research was to explore associations among measured dampness, fungal exposure, and childhood asthma development without the bias of culture-based microbial analysis. In the low-income, Latino CHAMACOS birth cohort, house dust was collected at age 12 months, and asthma status was determined at age 7 years.The current analysis included 13 asthma cases and 28 controls. Next-generation DNA sequencing methods quantified fungal taxa and diversity. Lower fungal diversity (number of fungal operational taxonomic units) was significantly associated with increased risk of asthma development: unadjusted odds ratio(OR) 4.80 (95% confidence interval (CI) 1.04–22.1). Control for potential confounders strengthened this relationship. Decreased diversity within the genus Cryptococcus was significantly associated with increased asthma risk (OR 21.0, 95% CI 2.16–204). No fungal taxon (species, genus, class) was significantly positively associated with asthma development, and one was significantly negatively associated. Elevated moisture was associated with increased fungal diversity, and moisture/mold indicators were associated with four fungal taxa. Next-generation DNA sequencing provided comprehensive estimates of fungal identity and diversity, demonstrating significant associations between low fungal diversity and childhood asthma development in this community.Practical implicationsEarly life exposure to low fungal diversity in house dust was associated with increased risk for later asthma developmen tin this low-income, immigrant community. No individual fungal taxon (species, genus, or class) was associated with asthma development, although exposure to low diversity within the genus Cryptococcus was associated with asthma development. Future asthma development studies should incorporate fungal diversity measurements, in addition to measuring individual fungal taxa. These results represent a step toward identifying the aspect(s) of indoor microbial populations that are associated with asthma development and suggest that understanding the factors that control diversity in the indoor environment may lead to public health recommendations for asthma prevention in the future.

Project description:Environmental microbes have been associated with both protective and adverse health effects in children and adults. Epidemiological studies often rely on broad biomarkers of microbial exposure (i.e. endotoxin, 1 → 3-beta-d-glucan), but fail to identify the taxonomic composition of the microbial community. Our aim was to characterize the bacterial and fungal microbiome in different types of environmental samples collected in studies of human health effects. We determined the composition of microbial communities present in home, school and outdoor air samples by amplifying and sequencing regions of rRNA genes from bacteria (16S) and fungi (18S and ITS). Samples for this pilot study included indoor settled dust (from both a Boston area birth cohort study on Home Allergens and Asthma (HAA) (n = 12) and a study of school exposures and asthma symptoms (SICAS) (n = 1)), as well as fine and coarse concentrated outdoor ambient particulate (CAP) samples (n = 9). Sequencing of amplified 16S, 18S, and ITS regions was performed on the Roche-454 Life Sciences Titanium pyrosequencing platform. Indoor dust samples were dominated by Gram-positive bacteria (Firmicutes and Actinobacteria); the most abundant bacterial genera were those related to human flora (Streptococcus, Staphylococcus, Corynebacterium and Lactobacillus). Outdoor CAPs were dominated by Gram-negative Proteobacteria from water and soil sources, in particular the genera Acidovorax, and Brevundimonas (which were present at very low levels or entirely absent in indoor dust). Phylum-level fungal distributions identified by 18S or ITS regions showed very similar findings: a predominance of Ascomycota in indoor dust and Basidiomycota in outdoor CAPs. ITS sequencing of fungal genera in indoor dust showed significant proportions of Aureobasidium and Leptosphaerulina along with some contribution from Cryptococcus, Epicoccum, Aspergillus and the human commensal Malassezia. ITS sequencing detected more than 70 fungal genera in indoor dust not observed by culture. Microbiome sequencing is feasible for different types of archived environmental samples (indoor dust, and low biomass air particulate samples), and offers the potential to study how whole communities of microbes (including unculturable taxa) influence human health.

Project description:BackgroundThe relationship between asthma, atopy, and underlying type 2 (T2) airway inflammation is complex. Although the bacterial airway microbiota is known to differ in asthmatic patients, the fungal and bacterial markers that discriminate T2-high (eosinophilic) and T2-low (neutrophilic/mixed-inflammation) asthma and atopy are still incompletely identified.ObjectivesThe aim of this study was to demonstrate the fungal microbiota structure of airways in asthmatic patients associated with T2 inflammation, atopy, and key clinical parameters.MethodsWe collected endobronchial brush (EB) and bronchoalveolar lavage (BAL) samples from 39 asthmatic patients and 19 healthy subjects followed by 16S gene and internal transcribed spacer-based microbiota sequencing. The microbial sequences were classified into exact sequence variants. The T2 phenotype was defined by using a blood eosinophil count with a threshold of 300 cells/μL.ResultsFungal diversity was significantly lower in EB samples from patients with T2-high compared with T2-low inflammation; key fungal genera enriched in patients with T2-high inflammation included Trichoderma species, whereas Penicillium species was enriched in patients with atopy. In BAL fluid samples the dominant genera were Cladosporium, Fusarium, Aspergillus, and Alternaria. Using generalized linear models, we identified significant associations between specific fungal exact sequence variants and FEV1, fraction of exhaled nitric oxide values, BAL fluid cell counts, and corticosteroid use. Investigation of interkingdom (bacterial-fungal) co-occurrence patterns revealed different topologies between asthmatic patients and healthy control subjects. Random forest models with fungal classifiers predicted asthma status with 75% accuracy for BAL fluid samples and 80% accuracy for EB samples.ConclusionsWe demonstrate clear differences in bacterial and fungal microbiota in asthma-associated phenotypes. Our study provides additional support for considering microbial signatures in delineating asthma phenotypes.

Dataset Information

Metagenomic Characterization of Indoor Dust Bacterial and Fungal Microbiota in Homes of Asthma and Non-asthma Patients Using Next Generation Sequencing.

Publications

Metagenomic Characterization of Indoor Dust Bacterial and Fungal Microbiota in Homes of Asthma and Non-asthma Patients Using Next Generation Sequencing.

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