Helena Rintala

Diversity and seasonal dynamics of bacterial community in indoor environment

BackgroundWe 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.ResultsThe composition and dynamics of indoor dust bacterial flora were investigated in two buildings over a period of one year. Four samples were taken in each building, corresponding to the four seasons, and 16S rDNA libraries were constructed. A total of 893 clones were analysed and 283 distinct operational taxonomic units (OTUs) detected among them using 97% sequence similarity as the criterion. All libraries were dominated by Gram-positive sequences, with the most abundant phylum being Firmicutes. Four OTUs having high similarity to Corynebacterium-, Propionibacterium-, Streptococcus- and Staphylococcus- sequences were present in all samples. The most abundant of the Gram-negative OTUs were members of the family Sphingomonadaceae, followed by Oxalobacteraceae, Comamonadaceae, Neisseriaceae and Rhizobiaceae.The relative abundance of alpha- and betaproteobacteria increased slightly towards summer at the expense of firmicutes. The proportion of firmicutes and gammaproteobacteria of the total diversity was highest in winter and that of actinobacteria, alpha- and betaproteobacteria in spring or summer, whereas the diversity of bacteroidetes peaked in fall. A statistical comparison of the libraries revealed that the bacterial flora of the two buildings differed during all seasons except spring, but differences between seasons within one building were not that clear, indicating that differences between the buildings were greater than the differences between seasons.ConclusionThis work demonstrated that the bacterial flora of indoor dust is complex and dominated by Gram-positive species. The dominant phylotypes most probably originated from users of the building. Seasonal variation was observed as proportional changes of the phyla and at the species level. The microflora of the two buildings investigated differed statistically and differences between the buildings were more pronounced than differences between seasons.

Analysis of Fungal Flora in Indoor Dust by Ribosomal DNA Sequence Analysis, Quantitative PCR, and Culture

ABSTRACT 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.

Microbial content of house dust samples determined with qPCR.

This study was designed to produce information about microbial concentrations using qPCR and their variation in different seasons and home environments with analyses of two types of house dust samples. Also the correlations between the two types of samples and the reproducibility of the parallel subsamples were studied. Two types of vacuumed house dust samples, rug dust and vacuum cleaner bag dust, were collected in 5 normal urban homes in four different seasons (N=20+20). From all dust samples, five parallel subsamples were subjected to qPCR analyses of 17 microbial species or assay groups of microbes. The highest fungal concentrations were found for the Penicillium/Aspergillus/Paecilomyces variotii group, and for the species Aspergillus penicillioides, Aureobasidium pullulans, Cladosporium cladosporioides and Cladosporium herbarum. These species/groups were present in almost all samples. The two types of dust samples gave similar results for most microbial species or groups analyzed, but in general, concentrations were slightly higher in rug dust than in dust from vacuum cleaner bag. Microbial concentrations varied significantly between different seasons and hence the similarity of samples within home was mainly low. The concentrations varied significantly also between different home environments. The reproducibility of the parallel subsamples was good or moderate for most of the analyzed species or assay groups. However, further studies are needed to fully understand the factors causing variation in these methods. Nevertheless, in order to show actual differences in fungal concentrations between urban homes with no known microbial sources, all dust samples to be compared should be taken during the same season.

Molecular profiling of fungal communities in moisture damaged buildings before and after remediation - a comparison of culture-dependent and culture-independent methods

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.

Microbial communities associated with house dust.

House dust is a complex mixture of inorganic and organic material with microbes in abundance. Few microbial species are actually able to grow and proliferate in dust and only if enough moisture is provided. Hence, most of the microbial content originates from sources other than the dust itself. The most important sources of microbes in house dust are outdoor air and other outdoor material tracked into the buildings, occupants of the buildings including pets and microbial growth on moist construction materials. Based on numerous cultivation studies, Penicillium, Aspergillus, Cladosporium, and about 20 other fungal genera are the most commonly isolated genera from house dust. The cultivable bacterial flora is dominated by Gram-positive genera, such as Staplylococcus, Corynebacterium, and Lactococcus. Culture-independent studies have shown that both the fungal and the bacterial flora are far more diverse, with estimates of up to 500-1000 different species being present in house dust. Concentrations of microbes in house dust vary from nondetectable to 10(9) cells g(-1) dust, depending on the dust type, detection method, type of the indoor environment and season, among other factors. Microbial assemblages in different house dust types usually share the same core species; however, alterations in the composition are caused by differing sources of microbes for different dust types. For example, mattress dust is dominated by species originating from the user of the mattress, whereas floor dust reflects rather outdoor sources. Farming homes contain higher microbial load than urban homes and according to a recent study, temperate climate zones show higher dust microbial diversity than tropical zones.

Quantity and diversity of environmental microbial exposure and development of asthma: a birth cohort study

Early‐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.

Microbial Communities Associated with House Dust

House dust is a complex mixture of inorganic and organic material with microbes in abundance. Few microbial species are actually able to grow and proliferate in dust and only if enough moisture is provided. Hence, most of the microbial content originates from sources other than the dust itself. The most important sources of microbes in house dust are outdoor air and other outdoor material tracked into the buildings, occupants of the buildings including pets and microbial growth on moist construction materials. Based on numerous cultivation studies, Penicillium, Aspergillus, Cladosporium, and about 20 other fungal genera are the most commonly isolated genera from house dust. The cultivable bacterial flora is dominated by Gram-positive genera, such as Staplylococcus, Corynebacterium, and Lactococcus. Culture-independent studies have shown that both the fungal and the bacterial flora are far more diverse, with estimates of up to 500-1000 different species being present in house dust. Concentrations of microbes in house dust vary from nondetectable to 10(9) cells g(-1) dust, depending on the dust type, detection method, type of the indoor environment and season, among other factors. Microbial assemblages in different house dust types usually share the same core species; however, alterations in the composition are caused by differing sources of microbes for different dust types. For example, mattress dust is dominated by species originating from the user of the mattress, whereas floor dust reflects rather outdoor sources. Farming homes contain higher microbial load than urban homes and according to a recent study, temperate climate zones show higher dust microbial diversity than tropical zones.

Indoor air particles and bioaerosols before and after renovation of moisture-damaged buildings: The effect on biological activity and microbial flora

Many building-related health problems coincide with moisture damage and mold growth within a building. Their elimination is assumed to improve indoor air quality. The aim of this study was to follow the success of remediation in two individual buildings by analyzing the microbial flora and immunotoxicological activity of filter samples. We compare results from samples collected from indoor air in the moisture-damaged buildings before and after renovation and results from matched reference buildings and outdoor air. The microbial characteristics of the samples were studied by analyzing ergosterol content and determining the composition of fungal flora with quantitative polymerase chain reaction (QPCR). In addition, the concentrations of particles were monitored with optical particle counter (OPC). The immunotoxicological activity of collected particle samples was tested by exposing mouse macrophages (RAW264.7) for 24 h to particle suspension extracted from the filters, and measuring the viability of the exposed cells (MTT-test) and production of inflammatory mediators (nitric oxide, IL-6 and TNF*) in cell culture medium by enzyme-linked immunoassay (ELISA). The results show that for Location 1 the renovation decreased the immunotoxicological activity of the particles collected from damaged building, whereas no difference was detected in the corresponding samples collected from the reference building. Interestingly, only slight differences were seen in the concentration of fungi. In the Location 2, a decrease was seen in the concentration of fungi after the renovation, whereas no effect on the immunotoxicological responses was detected. In this case, the immunotoxicological responses to the indoor air samples were almost identical to those caused by the samples from outdoor air. This indicates that the effects of remediation on the indoor air quality may not necessarily be readily measurable either with microbial or toxicological parameters. This may be associated with different spectrum of harmful agents in different mold and moisture-damaged buildings.

Bacterial Exposures and Associations with Atopy and Asthma in Children

Background The increase in prevalence of asthma and atopic diseases in Western countries has been linked to aspects of microbial exposure patterns of people. It remains unclear which microbial aspects contribute to the protective farm effect. Objective The objective of this study was to identify bacterial groups associated with prevalence of asthma and atopy, and to quantify indoor exposure to some of these bacterial groups. Methods A DNA fingerprinting technique, denaturing gradient gel electrophoresis (DGGE), was applied to mattress dust samples of farm children and control children in the context of the GABRIEL Advanced study. Associations between signals in DGGE and atopy, asthma and other allergic health outcomes were analyzed. Quantitative DNA based assays (qPCR) for four bacterial groups were applied on the dust samples to seek quantitative confirmation of associations indicated in DNA fingerprinting. Results Several statistically significant associations between individual bacterial signals and also bacterial diversity in DGGE and health outcomes in children were observed. The majority of these associations showed inverse relationships with atopy, less so with asthma. Also, in a subsequent confirmation study using a quantitative method (qPCR), higher mattress levels of specifically targeted bacterial groups - Mycobacterium spp., Bifidobacteriaceae spp. and two different clusters of Clostridium spp. - were associated with a lower prevalence of atopy. Conclusion DNA fingerprinting proved useful in identifying bacterial signals that were associated with atopy in particular. These findings were quantitatively confirmed for selected bacterial groups with a second method. High correlations between the different bacterial exposures impede a clear attribution of protective effects to one specific bacterial group. More diverse bacterial flora in mattress dust may link to microbial exposure patterns that protect against development of atopic diseases.

Determination of bacterial load in house dust using qPCR, chemical markers and culture

In this study, we developed two novel qPCR-assays for the detection of bacteria in house dust; one that determines the total bacterial amount and another that detects Gram-positive and Gram-negative bacteria separately. The methods were tested in silico and in vitro with microbial strains and vacuum cleaner dust samples, and validated in relation to culture and chemical marker analysis. We also compared the results of these three types of methods (qPCR, culture and chemical marker analysis) in 211 house dust samples from farming and non-farming environments. Microbial concentrations determined by the new qPCR assays (median 7.2 x 10(5) cell equivalents mg(-1)) were about two orders of magnitude higher than concentrations obtained by culture (median 6.7 x 10(3) cfu mg(-1)). The median concentration of muramic acid was 25.67 ng mg(-1) and that of 3-hydroxy fatty acids, expressed as LPS(10-16) was 26.14 pg mg(-1). Correlations between qPCR and chemical markers were moderate, while correlations between culture and qPCR and chemical markers were low to moderate. All the methods used in this study showed that the microbial concentrations are statistically significantly higher (p < 0.001, Mann-Whitney) in farming than non-farming environments.As a conclusion, all tested methods can be used for determining the bacterial load in dust samples, but none of the methods was superior to the others. The results obtained with these methods represent different aspects of bacterial exposure and therefore the results are not expected to be identical with each other.