Background: We spend most of our lives in indoor environments and are exposed to microbes present in these environments. Hence, knowledge about this exposure is important for understanding how it impacts on human health. However, the bacterial flora in indoor environments has been only fragmentarily explored and mostly using culture methods. The application of molecular methods previously utilised in other environments has resulted in a substantial increase in our awareness of microbial diversity.

In recent years increasing attention has been given to the potential health effects of fungal exposure in indoor environments. We used large-scale sequencing of the fungal internal transcribed spacer region (ITS) of nuclear ribosomal DNA to describe the mycoflora of two office buildings over the four seasons. DNA sequencing was complemented by cultivation, ergosterol determination, and quantitative PCR analyses. Sequences of 1,339 clones were clustered into 394 nonredundant fungal operational taxonomical units containing sequences from 18 fungal subclasses. The observed flora differed markedly from that recovered by cultivation, the major differences being the near absence of several typical indoor mold genera such as Penicillium and Aspergillus spp. and a high prevalence of basidiomycetes in clone libraries. A total of 55% of the total diversity constituted of unidentifiable ITS sequences, some of which may represent novel fungal species. Dominant species were Cladosporium cladosporioides and C. herbarum, Cryptococcus victoriae, Leptosphaerulina americana and L. chartarum, Aureobasidium pullulans, Thekopsora areolata, Phaeococcomyces nigricans, Macrophoma sp., and several Malassezia species. Seasonal differences were observed for community composition, with ascomycetous molds and basidiomycetous yeasts predominating in the winter and spring and Agaricomycetidae basidiomycetes predominating in the fall. The comparison of methods suggested that the cloning, cultivation, and quantitative PCR methods complemented each other, generating a more comprehensive picture of fungal flora than any of the methods would give alone. The current restrictions of the methods are discussed.

No abstract

No abstract

No abstract

BackgroundIndoor microbial contamination due to excess moisture is an important contributor to human illness in both residential and occupational settings. However, the census of microorganisms in the indoor environment is limited by the use of selective, culture-based detection techniques. By using clone library sequencing of full-length internal transcribed spacer region combined with quantitative polymerase chain reaction (qPCR) for 69 fungal species or assay groups and cultivation, we have been able to generate a more comprehensive description of the total indoor mycoflora. Using this suite of methods, we assessed the impact of moisture damage on the fungal community composition of settled dust and building material samples (n = 8 and 16, correspondingly). Water-damaged buildings (n = 2) were examined pre- and post- remediation, and compared with undamaged reference buildings (n = 2).ResultsCulture-dependent and independent methods were consistent in the dominant fungal taxa in dust, but sequencing revealed a five to ten times higher diversity at the genus level than culture or qPCR. Previously unknown, verified fungal phylotypes were detected in dust, accounting for 12% of all diversity. Fungal diversity, especially within classes Dothideomycetes and Agaricomycetes tended to be higher in the water damaged buildings. Fungal phylotypes detected in building materials were present in dust samples, but their proportion of total fungi was similar for damaged and reference buildings. The quantitative correlation between clone library phylotype frequencies and qPCR counts was moderate (r = 0.59, p < 0.01).ConclusionsWe examined a small number of target buildings and found indications of elevated fungal diversity associated with water damage. Some of the fungi in dust were attributable to building growth, but more information on the material-associated communities is needed in order to understand the dynamics of microbial communities between building structures and dust. The sequencing-based method proved indispensable for describing the true fungal diversity in indoor environments. However, making conclusions concerning the effect of building conditions on building mycobiota using this methodology was complicated by the wide natural diversity in the dust samples, the incomplete knowledge of material-associated fungi fungi and the semiquantitative nature of sequencing based methods.

No abstract

BackgroundEarly-life exposure to environmental microbial agents may be associated with the development of allergies. The aim of the study was to identify better ways to characterize microbial exposure as a predictor of respiratory symptoms and allergies.MethodsA birth cohort of 410 children was followed up until 6 years of age. Bacterial endotoxin, 3-hydroxy fatty acids, N-acetyl-muramic acid, fungal extracellular polysaccharides (EPS) from Penicillium and Aspergillus spp., β-D-glucan, ergosterol, and bacterial or fungal quantitative polymerase chain reactions (qPCRs) were analyzed from dust samples collected at 2 months of age. Asthma, wheezing, cough, and atopic dermatitis were assessed using repeated questionnaires. Specific IgEs were determined at the age of 1 and 6 years.ResultsOnly few associations were found between single microbial markers and the studied outcomes. In contrast, a score for the total quantity of microbial exposure, that is, sum of indicators for fungi (ergosterol), Gram-positive (muramic acid) bacteria, and Gram-negative (endotoxin) bacteria, was significantly (inverted-U shape) associated with asthma incidence (P < 0.001): the highest risk was found at medium levels (adjusted odds ratio (aOR) 2.24, 95% confidence interval (95% CI) 0.87–5.75 for 3rd quintile) and the lowest risk at the highest level (aOR 0.34, 95% CI 0.09–1.36 for 5th quintile). The microbial diversity score, that is, sum of detected qPCRs, was inversely associated with risk of wheezing and was significantly (inverted-U shape) associated with sensitization to inhalant allergens.ConclusionScore for quantity of microbial exposure predicted asthma better than single microbial markers independently of microbial diversity and amount of dust. Better indicators of total quantity and diversity of microbial exposure are needed in studies on the development of asthma.