Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio.

"Green" housing is designed to use low-impact materials, increase energy efficiency and improve occupant health. However, little is known about the indoor mycobiome of green homes. The current study is a subset of a multicenter study that aims to investigate the indoor environment of green homes and the respiratory health of asthmatic children. In the current study, the mycobiome in air, bed dust and floor dust was compared between green (study site) and non-green (control site), low-income homes in Cincinnati, Ohio. The samples were collected at baseline (within four months following renovation), and 12months after the baseline at the study site. Parallel sample collection was conducted in non-green control homes. Air samples were collected by PM2.5 samplers over 5-days. Bed and floor dust samples were vacuumed after the air sampling was completed. The DNA sample extracts were analyzed using ITS amplicon sequencing. Analysis indicated that there was no clear trend in the fungal communities between green and non-green homes. Instead, fungal community differences were greatest between sample types - air, bed, and floor. Microbial communities also changed substantially between sampling intervals in both green and non-green homes for all sample types, potentially indicating that there was very little stability in the mycobiomes. Research gaps remain regarding how indoor mycobiome fluctuates over time. Longer follow-up periods might elucidate the effect of green renovation on microbial load in buildings.

[1]  Tiina Reponen,et al.  Comparison of concentrations and size distributions of fungal spores in buildings with and without mould problems , 1994 .

[2]  Rob Knight,et al.  Diversity, distribution and sources of bacteria in residential kitchens. , 2013, Environmental microbiology.

[3]  T. Bruns,et al.  Dispersal in microbes: fungi in indoor air are dominated by outdoor air and show dispersal limitation at short distances , 2013, The ISME Journal.

[4]  W W Nazaroff,et al.  Size-resolved emission rates of airborne bacteria and fungi in an occupied classroom , 2012, Indoor air.

[5]  B. Leaderer,et al.  Comparisons of seasonal fungal prevalence in indoor and outdoor air and in house dusts of dwellings in one Northeast American county1 , 1999, Journal of Exposure Analysis and Environmental Epidemiology.

[6]  R. Margalef.  Homage to Evelyn Hutchinson, or why there is an upper limit to diversity , 1972 .

[7]  Kessy Abarenkov,et al.  Fungal community analysis by high-throughput sequencing of amplified markers – a user's guide , 2013, The New phytologist.

[8]  S. Vesper,et al.  Phylogenetic relationships of Memnoniella and Stachybotrys species and evaluation of morphological features for Memnoniella species identification , 2001 .

[9]  J. Miller,et al.  Fungi and fungal products in some Canadian houses , 1988 .

[10]  J. Levy,et al.  A simulation model of building intervention impacts on indoor environmental quality, pediatric asthma, and costs. , 2014, The Journal of allergy and clinical immunology.

[11]  J. Portnoy,et al.  Infant pulmonary hemorrhage in a suburban home with water damage and mold (Stachybotrys atra). , 1999, Environmental health perspectives.

[12]  Tiina Reponen,et al.  Key determinants of the fungal and bacterial microbiomes in homes. , 2015, Environmental research.

[13]  Charles J. Kibert,et al.  Sustainable Construction : Green Building Design and Delivery , 2005 .

[14]  M. Mendell,et al.  Higher measured moisture in California homes with qualitative evidence of dampness. , 2016, Indoor air.

[15]  A. Augustyniuk-Kram,et al.  Spectrum and Concentration of Culturable Fungi in House Dust from Flats in Warsaw, Poland , 2013 .

[16]  Noah Fierer,et al.  Home Life: Factors Structuring the Bacterial Diversity Found within and between Homes , 2013, PloS one.

[17]  D. Beezhold,et al.  Internal transcribed spacer rRNA gene sequencing analysis of fungal diversity in Kansas City indoor environments. , 2014, Environmental Science: Processes & Impacts.

[18]  Assessing the aerodynamic diameters of taxon-specific fungal bioaerosols by quantitative PCR and next-generation DNA sequencing , 2014 .

[19]  N. Beaudet,et al.  The Breathe-Easy Home: the impact of asthma-friendly home construction on clinical outcomes and trigger exposure. , 2011, American journal of public health.

[20]  Tiina Reponen,et al.  Indoor air quality in green-renovated vs. non-green low-income homes of children living in a temperate region of US (Ohio). , 2016, The Science of the total environment.

[21]  Pierre Taberlet,et al.  ITS as an environmental DNA barcode for fungi: an in silico approach reveals potential PCR biases , 2010, BMC Microbiology.

[22]  S. Vesper,et al.  Dustborne and airborne Gram-positive and Gram-negative bacteria in high versus low ERMI homes. , 2014, The Science of the total environment.

[23]  Sarah L. Westcott,et al.  Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform , 2013, Applied and Environmental Microbiology.

[24]  Kyle Bibby,et al.  Particle-size distributions and seasonal diversity of allergenic and pathogenic fungi in outdoor air , 2012, The ISME Journal.

[25]  Robert A. Samson,et al.  Microorganisms in Home and Indoor Work Environments : Diversity, Health Impacts, Investigation and Control , 2001 .

[26]  P. Crous,et al.  Generic hyper-diversity in Stachybotriaceae , 2016, Persoonia.

[27]  Jiajie Zhang,et al.  PEAR: a fast and accurate Illumina Paired-End reAd mergeR , 2013, Bioinform..

[28]  Shibu Yooseph,et al.  A Metagenomic Framework for the Study of Airborne Microbial Communities , 2013, PloS one.

[29]  M J Mendell,et al.  Next-generation DNA sequencing reveals that low fungal diversity in house dust is associated with childhood asthma development. , 2014, Indoor air.

[30]  H. Burge,et al.  Dustborne and airborne fungal propagules represent a different spectrum of fungi with differing relations to home characteristics , 2003, Allergy.

[31]  L. Weyrich,et al.  Residual soil DNA extraction increases the discriminatory power between samples , 2015, Forensic Science, Medicine, and Pathology.

[32]  Brent Stephens,et al.  Tools to improve built environment data collection for indoor microbial ecology investigations , 2014 .

[33]  C. Tischer,et al.  Pediatric Asthma and the Indoor Microbial Environment , 2016, Current Environmental Health Reports.

[34]  A. Hyvärinen,et al.  Characterizing Microbial Exposure With Ergosterol, 3-Hydroxy Fatty Acids, and Viable Microbes in House Dust: Determinants and Association With Childhood Asthma , 2006, Archives of environmental & occupational health.

[35]  Rob Knight,et al.  UCHIME improves sensitivity and speed of chimera detection , 2011, Bioinform..

[36]  M. Mendell,et al.  Development of a method to relate the moisture content of a building material to its water activity , 2017, Indoor air.

[37]  Jeff Kline,et al.  Architectural Design Drives the Biogeography of Indoor Bacterial Communities , 2014, PloS one.

[38]  M. Mendell,et al.  Indoor Environmental Exposures and Exacerbation of Asthma: An Update to the 2000 Review by the Institute of Medicine , 2014, Environmental health perspectives.

[39]  S. Vesper,et al.  High environmental relative moldiness index during infancy as a predictor of asthma at 7 years of age. , 2011, Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology.

[40]  Largus T. Angenent,et al.  Molecular Analysis of Shower Curtain Biofilm Microbes , 2004, Applied and Environmental Microbiology.

[41]  Thomas D. Bruns,et al.  The Diversity and Distribution of Fungi on Residential Surfaces , 2013, PloS one.

[42]  T. Reponen,et al.  Susceptibility of green and conventional building materials to microbial growth. , 2015, Indoor air.

[43]  T. Konya,et al.  Recent Advances in the Microbiology of the Built Environment , 2014, Current Sustainable/Renewable Energy Reports.

[44]  D. Speijer,et al.  UvA-DARE ( Digital Academic Repository ) Identification of a novel anti-sigmaE factor in Neisseria meningitidis Hopman , 2010 .

[45]  Mark J. Mendell,et al.  Respiratory and Allergic Health Effects of Dampness, Mold, and Dampness-Related Agents: A Review of the Epidemiologic Evidence , 2011, Environmental health perspectives.

[46]  William W. Nazaroff,et al.  Chamber Bioaerosol Study: Outdoor Air and Human Occupants as Sources of Indoor Airborne Microbes , 2015, PloS one.

[47]  T. Reponen,et al.  House dust (1–3)‐β‐d‐glucan and wheezing in infants , 2007 .

[48]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[49]  Andy F. S. Taylor,et al.  The UNITE database for molecular identification of fungi--recent updates and future perspectives. , 2010, The New phytologist.

[50]  J. Douwes,et al.  Bioaerosol health effects and exposure assessment: progress and prospects. , 2003, The Annals of occupational hygiene.

[51]  M. Jaakkola,et al.  Home dampness and molds as determinants of allergic rhinitis in childhood: a 6-year, population-based cohort study. , 2010, American journal of epidemiology.

[52]  Andrew J. Hoisington,et al.  Impact of sampler selection on the characterization of the indoor microbiome via high-throughput sequencing , 2014 .

[53]  C. Huttenhower,et al.  Metagenomic biomarker discovery and explanation , 2011, Genome Biology.

[54]  N. Fierer,et al.  High temporal variability in airborne bacterial diversity and abundance inside single‐family residences , 2017, Indoor air.

[55]  D K Milton,et al.  Longitudinal study of dust and airborne endotoxin in the home. , 2000, Environmental health perspectives.

[56]  L. Tedersoo,et al.  454 Pyrosequencing and Sanger sequencing of tropical mycorrhizal fungi provide similar results but reveal substantial methodological biases. , 2010, The New phytologist.