Eric M Kettleson1, Atin Adhikari2, Stephen Vesper3, Kanistha Coombs4, Reshmi Indugula5, Tiina Reponen6. 1. University of Cincinnati, Department of Environmental Health, P.O. Box 670056, 3223 Eden Ave., Cincinnati, OH 45267-0056, United States; ZF Steering Systems NACAM Corp, 15 Spiral Drive, Florence, KY 41042, United States. Electronic address: emkettleson@gmail.com. 2. University of Cincinnati, Department of Environmental Health, P.O. Box 670056, 3223 Eden Ave., Cincinnati, OH 45267-0056, United States; Department of Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, 501 Forest Drive, Statesboro, GA 30460, United States. Electronic address: aadhikari@georgiasouthern.edu. 3. National Exposure Research Laboratory, U.S. Environmental Protection Agency, 26 West M. L. King Drive, Cincinnati, OH 45268, United States. Electronic address: vesper.stephen@epa.gov. 4. University of Cincinnati, Department of Environmental Health, P.O. Box 670056, 3223 Eden Ave., Cincinnati, OH 45267-0056, United States. Electronic address: chatteka@mail.uc.edu. 5. University of Cincinnati, Department of Environmental Health, P.O. Box 670056, 3223 Eden Ave., Cincinnati, OH 45267-0056, United States. Electronic address: induguri@ucmail.uc.edu. 6. University of Cincinnati, Department of Environmental Health, P.O. Box 670056, 3223 Eden Ave., Cincinnati, OH 45267-0056, United States. Electronic address: Tiina.Reponen@uc.edu.
Abstract
BACKGROUND: The microbiome of the home is of great interest because of its possible impact on health. Our goal was to identify some of the factors that determine the richness, evenness and diversity of the home's fungal and bacterial microbiomes. METHOD: Vacuumed settled dust from homes (n=35) in Cincinnati, OH, were analyzed by pyrosequencing to determine the fungal and bacterial relative sequence occurrence. The correlation coefficients between home environmental characteristics, including age of home, Environmental Relative Moldiness Index (ERMI) values, occupant number, relative humidity and temperature, as well as pets (dog and cat) were evaluated for their influence on fungal and bacterial communities. In addition, linear discriminant analysis (LDA) was used for identifying fungal and bacterial genera and species associated with those housing determinants found to be significant. RESULTS: The fungal richness was found to be positively correlated with age of home (p=0.002), ERMI value (p=0.003), and relative humidity (p=0.015) in the home. However, fungal evenness and diversity were only correlated with the age of home (p=0.001). Diversity and evenness (not richness) of the bacterial microbiome in the homes were associated with dog ownership. Linear discriminant analysis showed total of 39 putative fungal genera/species with significantly higher LDA scores in high ERMI homes and 47 genera/species with significantly higher LDA scores in homes with high relative humidity. When categorized according to the age of the home, a total of 67 fungal genera/species had LDA scores above the significance threshold. Dog ownership appeared to have the most influence on the bacterial microbiome, since a total of 130 bacterial genera/species had significantly higher LDA scores in homes with dogs. CONCLUSIONS: Some key determinants of the fungal and bacterial microbiome appear to be excess moisture, age of the home and dog ownership.
BACKGROUND: The microbiome of the home is of great interest because of its possible impact on health. Our goal was to identify some of the factors that determine the richness, evenness and diversity of the home's fungal and bacterial microbiomes. METHOD: Vacuumed settled dust from homes (n=35) in Cincinnati, OH, were analyzed by pyrosequencing to determine the fungal and bacterial relative sequence occurrence. The correlation coefficients between home environmental characteristics, including age of home, Environmental Relative Moldiness Index (ERMI) values, occupant number, relative humidity and temperature, as well as pets (dog and cat) were evaluated for their influence on fungal and bacterial communities. In addition, linear discriminant analysis (LDA) was used for identifying fungal and bacterial genera and species associated with those housing determinants found to be significant. RESULTS: The fungal richness was found to be positively correlated with age of home (p=0.002), ERMI value (p=0.003), and relative humidity (p=0.015) in the home. However, fungal evenness and diversity were only correlated with the age of home (p=0.001). Diversity and evenness (not richness) of the bacterial microbiome in the homes were associated with dog ownership. Linear discriminant analysis showed total of 39 putative fungal genera/species with significantly higher LDA scores in high ERMI homes and 47 genera/species with significantly higher LDA scores in homes with high relative humidity. When categorized according to the age of the home, a total of 67 fungal genera/species had LDA scores above the significance threshold. Dog ownership appeared to have the most influence on the bacterial microbiome, since a total of 130 bacterial genera/species had significantly higher LDA scores in homes with dogs. CONCLUSIONS: Some key determinants of the fungal and bacterial microbiome appear to be excess moisture, age of the home and dog ownership.
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