Cargando…
Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework
Resuspension of microbes in floor dust and subsequent inhalation by human occupants is an important source of human microbial exposure. Microbes in carpet dust grow at elevated levels of relative humidity, but rates of this growth are not well established, especially under changing conditions. The g...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496831/ https://www.ncbi.nlm.nih.gov/pubmed/32403157 http://dx.doi.org/10.1111/ina.12686 |
_version_ | 1783583184488759296 |
---|---|
author | Haines, Sarah R. Siegel, Jeffrey A. Dannemiller, Karen C. |
author_facet | Haines, Sarah R. Siegel, Jeffrey A. Dannemiller, Karen C. |
author_sort | Haines, Sarah R. |
collection | PubMed |
description | Resuspension of microbes in floor dust and subsequent inhalation by human occupants is an important source of human microbial exposure. Microbes in carpet dust grow at elevated levels of relative humidity, but rates of this growth are not well established, especially under changing conditions. The goal of this study was to model fungal growth in carpet dust based on indoor diurnal variations in relative humidity utilizing the time‐of‐wetness framework. A chamber study was conducted on carpet and dust collected from 19 homes in Ohio, USA and exposed to varying moisture conditions of 50%, 85%, and 100% relative humidity. Fungal growth followed the two activation regime model, while bacterial growth could not be evaluated using the framework. Collection site was a stronger driver of species composition (P = 0.001, R (2) = 0.461) than moisture conditions (P = 0.001, R (2) = 0.021). Maximum moisture condition was associated with species composition within some individual sites (P = 0.001‐0.02, R (2) = 0.1‐0.33). Aspergillus, Penicillium, and Wallemia were common fungal genera found among samples at elevated moisture conditions. These findings can inform future studies of associations between dampness/mold in homes and health outcomes and allow for prediction of microbial growth in the indoor environment. |
format | Online Article Text |
id | pubmed-7496831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74968312020-09-25 Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework Haines, Sarah R. Siegel, Jeffrey A. Dannemiller, Karen C. Indoor Air Original Articles Resuspension of microbes in floor dust and subsequent inhalation by human occupants is an important source of human microbial exposure. Microbes in carpet dust grow at elevated levels of relative humidity, but rates of this growth are not well established, especially under changing conditions. The goal of this study was to model fungal growth in carpet dust based on indoor diurnal variations in relative humidity utilizing the time‐of‐wetness framework. A chamber study was conducted on carpet and dust collected from 19 homes in Ohio, USA and exposed to varying moisture conditions of 50%, 85%, and 100% relative humidity. Fungal growth followed the two activation regime model, while bacterial growth could not be evaluated using the framework. Collection site was a stronger driver of species composition (P = 0.001, R (2) = 0.461) than moisture conditions (P = 0.001, R (2) = 0.021). Maximum moisture condition was associated with species composition within some individual sites (P = 0.001‐0.02, R (2) = 0.1‐0.33). Aspergillus, Penicillium, and Wallemia were common fungal genera found among samples at elevated moisture conditions. These findings can inform future studies of associations between dampness/mold in homes and health outcomes and allow for prediction of microbial growth in the indoor environment. John Wiley and Sons Inc. 2020-05-29 2020-09 /pmc/articles/PMC7496831/ /pubmed/32403157 http://dx.doi.org/10.1111/ina.12686 Text en © 2020 The Authors. Indoor Air published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Haines, Sarah R. Siegel, Jeffrey A. Dannemiller, Karen C. Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title | Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title_full | Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title_fullStr | Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title_full_unstemmed | Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title_short | Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “Time‐of‐Wetness” framework |
title_sort | modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the “time‐of‐wetness” framework |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496831/ https://www.ncbi.nlm.nih.gov/pubmed/32403157 http://dx.doi.org/10.1111/ina.12686 |
work_keys_str_mv | AT hainessarahr modelingmicrobialgrowthincarpetdustexposedtodiurnalvariationsinrelativehumidityusingthetimeofwetnessframework AT siegeljeffreya modelingmicrobialgrowthincarpetdustexposedtodiurnalvariationsinrelativehumidityusingthetimeofwetnessframework AT dannemillerkarenc modelingmicrobialgrowthincarpetdustexposedtodiurnalvariationsinrelativehumidityusingthetimeofwetnessframework |