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.
Aims: Microbial concentrations in vacuumed house dust samples (n = 71) were analysed by culture and quantitative polymerase chain reaction (qPCR) methods and their association with extent of moisture damage in the house was studied. Methods and Results: Microbial concentrations measured by qPCR correlated with concentrations obtained by culture method, but were orders of magnitude higher. qPCR also had better sensitivity. Concentrations of several microbes in house dust, determined with qPCR, were associated with the extent of moisture damage in the house. This association was strongest for Penicillium brevicompactum, one of the fungi detected in highest concentrations by qPCR. Furthermore, house dust concentrations of Wallemia sebi, Trichoderma viride, Cladosporium sphaerospermum, Eurotium amstelodami and the combined assay group for Penicillium spp., Aspergillus spp. and Paecilomyces variotii were significantly associated with the extent of the moisture damage. Conclusion: These species or assay groups could probably be used as indicators of moisture damage in the house. Significance and Impact of the Study: This finding indicates the benefits of the qPCR method, which is sensitive enough to reveal the differences in microbial concentrations of house dust between moisture‐damaged and undamaged houses.
Airborne microbes and pupils' symptoms were monitored in a moisture-damaged (index) school and a reference school for five consecutive years. These surveys were carried out in two separate years before the renovation of the index school, during the renovation, and one and two years after the renovation. Microbial concentrations were higher in the index school than those in the reference school before and during renovation, but afterwards, the levels decreased to the level of the reference school. The effect of remediation was seen as an altered mycobiota in the index school. Year-to-year variation of microbial concentrations, probably due to climatic factors, caused a peak in both schools but their difference remained. Several symptoms were more prevalent in the moisture-damaged school than in the reference school, but the differences disappeared during the renovations. These results emphasize the importance of using a reference building in assessing the microbial conditions of a moisture damaged building. Furthermore, microbial concentrations reflected well the technical condition of the construction, but the reported symptoms of the occupants did not strictly follow the timely fluctuation in microbial conditions.
Prolonged moisture on building materials can lead to microbial growth on them. Microbes can emit spores, metabolites and structural parts into the indoor air and thus, cause adverse health effects of people living and working in these buildings. So far, culture methods have been used for assessment of microbial contamination of building materials. In this work, we used quantitative PCR (qPCR) for the detection of selected fungal and bacterial groups in 184 building materials of different types and compared the results with culture-based analysis. Nine either commonly found species, genera or groups of fungi, or those considered as moisture damage indicators, and one bacterial genus, Streptomyces, were determined using qPCR. Fungi and mesophilic actinomycetes were also cultivated using standard media and conditions of the routine analysis. The bacterial genus Streptomyces and the fungal group Penicillium/Aspergillus/Paecilomyces were the most prevalent microbial groups in all building material types, followed by Stachybotrys chartarum and Trichoderma viride/atroviride/koningii. The highest prevalences, concentrations and species diversity was observed on wooden materials. In general, the results of the two methods did not correlate well, since concentrations of fungi and streptomycetes were higher and their occurrence more prevalent when determined by qPCR compared to culture-based results. However, with increasing concentrations, the correlation generally increased. The qPCR assay did not detect Aspergillus versicolor and Acremonium strictum as often as culture.
Aims: Streptomycetes are regarded to prefer neutral to alkaline environmental pH, although they commonly occur at remarkably variable pH and nutritional conditions. Therefore, the dependence of 10 Streptomyces spp. pH tolerance on nutrients was determined. Methods and Results: Ten environmental Streptomyces spp. were grown and sporulated between pH 4AE0 and 11AE5, at the interval of 1AE5, on starch-casein-KNO 3 , tryptone-yeast extract-glucose, glycerol-arginine and tryptone-soy agars, and three their modifications. On media with starch and casein; glucose, tryptone and yeast extract; tryptone and soy peptone; and glycerol-arginine and yeast extract strains grew over a broad pH range between 4AE0-5AE5 and 10AE0-11AE5. On glycerol-arginine and on medium with Na-propionate, NH 4 NO 3 and yeast extract, streptomycetes grew optimally at pH 7AE0 and above. The high organic load enabled the growth over a wide pH range. The sporulation pH ranges followed those for growth. Conclusions: The high organic load enabled the growth over a wide pH range. The strain-specific differences in sporulation were greater than those caused by pH. The best medium for sporulation contained glucose and tryptone with minerals of glycerol-arginine agar at pH 5.5. Significance and Impact of the Study: The growth pH ranges, pH ranges for the optimal growth, and sporulation were strongly dependent on nutrients.
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