Environmental shaping of the bacterial and fungal community in infant bed dust and correlations with the airway microbiota

Abstract

Background: From early life, children are exposed to a multitude of environmental exposures, which may be of crucial importance for healthy development. Here, the environmental microbiota may be of particular interest as it represents the interface between environmental factors and the child. As infants in modern societies spend a considerable amount of time indoors, we hypothesize that the indoor bed dust microbiota might be an important factor for the child and for the early colonization of the airway microbiome. To explore this hypothesis, we analyzed the influence of environmental exposures on 577 dust samples from the beds of infants together with 542 airway samples from the Copenhagen Prospective Studies on Asthma in Childhood 2010 cohort. Results: Both bacterial and fungal community was profiled from the bed dust. Bacterial and fungal diversity in the bed dust was positively correlated with each other. Bacterial bed dust microbiota was influenced by multiple environmental factors, such as type of home (house or apartment), living environment (rural or urban), sex of siblings, and presence of pets (cat and/or dog), whereas fungal bed dust microbiota was majorly influenced by the type of home (house or apartment) and sampling season. We further observed minor correlation between bed dust and airway microbiota compositions among infants. We also analyzed the transfer of microbiota from bed dust to the airway, but we did not find evidence of transfer of individual taxa. Conclusions: Current study explores the influence of environmental factors on bed dust microbiota (both bacterial and fungal) and its correlation with airway microbiota (bacterial) in early life using high-throughput sequencing. Our findings demonstrate that bed dust microbiota is influenced by multiple environmental exposures and could represent an interface between environment and child.

FunOMIC: Pipeline with built-in fungal taxonomic and functional databases for human mycobiome profiling

“…In this study, we applied the FunOMIC pipeline to a set of nearly 2,700 metagenomic human samples representing human microbiomes of different body sites from individuals with different health status and from different geographical regions. We corroborated previous human mycobiome results showing that the species S. cerevisiae , C. albicans , and M. restricta dominate the fungal communities in different human body sites [46] , [47] , [48] , [49] . We found that geography and health status were the two most important factors contributing to the variabilities of human mycobiome taxonomic and functional compositions.…”

Follow-up study of airway microbiota in children with persistent wheezing

“…On the other hand, lung microbiota might be affected by many external factors. Environmental factors such as bed dust could influence airway microbiota compositions among infants [ 23 ]. Maternal dietary intervention with long-chain fatty acids and vitamin D supplementation can affect the infant airways but not the infant fecal microbiota [ 24 ].…”

“…Currently, 16S rRNA gene amplicon analysis remains the standard approach for the cultivation independent investigation of microbiota, and the accuracy of these analyses depends mainly on primer selections [ 25 ]. The nine hypervariable regions (V1-V9) of 16S rRNA gene are frequently used for determining of the bacterial taxonomy in the diverse microbial populations [ 4 , 14 , 23 ]. In general, high-throughput short-read sequencing of the 16S rRNA gene amplicon based on the Illumina MiSeq platform specifically targets the V3-V4 hypervariable region [ 26 ].…”

The developing airway and gut microbiota in early life is influenced by age of older siblings

“…We examined the microbiota using 16S rRNA gene amplicon sequencing, as previously described [ 26 , 27 ]. In brief, DNA was extracted from both sample types using the PowerMag® Soil DNA Isolation Kit (MO-BIO Laboratories), after which the hypervariable V4 region of the 16S rRNA gene was amplified, using the modified broad range primers 515F and 806R.…”