The human gut harbors millions of microbes, primarily bacteria, which have positive and adverse health effects. A recent paper evaluated how indoor microbiomes and metabolites affect the human gut microbiota.
This pilot study assessed the impact of indoor microbiome and metabolites on the human gut microbiota. A total of 56 children between the age of 3 and 10, were recruited in this study. Electronic questionnaires were used to collect health information and relevant environmental characteristics. A distance-weighted method was used to estimate the annual outdoor air pollutants.
Fecal samples were obtained from the participants, and dust samples were collected using a sterile sampler. DNA was extracted from the dust samples and was analyzed using a culture-independent shotgun metagenomic sequencing technique. In addition, liquid chromatography-mass spectrometry (LC-MS) was used for the chemical profiling of the dust samples.
The associations between environmental microbial and non-microbial characteristics and the diversity/composition of the gut microbiota were investigated using PERMANOVA and regression models. In addition, the effect of environmental characteristics on GMHI was also examined.
The children recruited in this study were randomly selected from twelve out of sixteen districts in Shanghai, China. The study cohort consisted of 38% boys and 62% girls. More than half of the cohort had siblings, and around 59% of children had pets or indoor plants during their early childhood. Twenty-one children resided in an area of heavy traffic. Some children had started kindergarten. Around 16% of children were exposed to environmental tobacco smoking during their early childhood.
A total of 6,247 microbes were characterized from the indoor dust samples. The majority of microbes belonged to classes Bacilli, Gammaproteobacteria, and Actinobacteria, followed by Bacteroidia, Flavobacteria, Alphaproteobacteria, Betaproteobacteria, Clostridia, and Tissierellia. Some of the most abundantly found microbial species are Cutibacterium acnes, Staphylococcus aureus, Staphylococcus epidermidis, and Micrococcus luteus.
Facultative pathogens, such as Pseudomonas aeruginosa, Mycobacterium tuberculosis, and Klebsiella pneumoniae, were also detected. Virulence factors (VFs) and antimicrobial resistance genes (ARGs) were determined using molecular sequencing techniques. VFs were predominantly derived from facultative pathogens.
A total of 1,442 metabolites and chemicals were characterized via the second stage of mass spectrometry (MS2). Metabolites, such as primarily lipids (e.g., fatty acyl, flavonoid, and steroid derivatives), xenobiotics, amino acids, carbohydrates, cofactors, and vitamins, were identified during chemical profiling.
A total of 318 bacteria were characterized from gut samples that belong to phyla Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. Children's gut was enriched with Flavonifractor plautii, Oscillibacter, and Faecalibacterium. The age of children and the time when they started kindergarten had a significant impact on gut microbial composition. In addition, residing near heavy traffic also influenced gut microbial composition.
Among dietary characteristics, the frequency of drinking soft drinks substantially impacted gut microbial composition. The abundance of indoor metabolites and chemicals did not have any impact on the overall gut microbial composition.
The authors claim this study to be the first to examine the association between indoor microbiome/metabolites and gut microbiota. This study highlighted how indoor microbe exposure influences the human gut microbiota.