The Indoor Microbiome: Novel Applications in Mold Prevention, Healthy Spacecraft, and COVID-19

We spend 90% of our time indoors where we are continuously exposed to diverse microbial communities. This talk will highlight three applications where enhanced understanding of the fungi, bacteria, and viruses in our indoor space can improve our health. First, relative humidity in the air is sufficient to support microbial growth in carpet and dust, and this can be modeled quantitatively using the time-of-wetness framework. Prevention of mold growth in homes is especially important for underserved communities who may be more likely to reside in poor quality housing and/or have asthma. Second, these findings can be applied in a wide variety of environments, including on the International Space Station (ISS) to ensure that astronauts can remain healthy during long-duration space travel. Finally, these measurement techniques have resulted in a novel surveillance tool to continue to monitor the COVID-19 pandemic in high-risk buildings, which will be especially important as vaccines are distributed and asymptomatic routine testing is reduced

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 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, R2  = 0.461) than moisture conditions (P = 0.001, R2  = 0.021). Maximum moisture condition was associated with species composition within some individual sites (P = 0.001-0.02, R2  = 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.Alfred P. Sloan Foundation, Grant/Awar

Indoor emissions as a primary source of airborne allergenic fungal particles in classrooms.

This study quantifies the influence of ventilation and indoor emissions on concentrations and particle sizes of airborne indoor allergenic fungal taxa and further examines geographical variability, each of which may affect personal exposures to allergenic fungi. Quantitative PCR and multiplexed DNA sequencing were employed to count and identify allergenic fungal aerosol particles indoors and outdoors in seven school classrooms in four different countries. Quantitative diversity analysis was combined with building characterization and mass balance modeling to apportion source contributions of indoor allergenic airborne fungal particles. Mass balance calculations indicate that 70% of indoor fungal aerosol particles and 80% of airborne allergenic fungal taxa were associated with indoor emissions; on average, 81% of allergenic fungi from indoor sources originated from occupant-generated emissions. Principal coordinate analysis revealed geographical variations in fungal communities among sites in China, Europe, and North America (p < 0.05, analysis of similarity), demonstrating that geography may also affect personal exposures to allergenic fungi. Indoor emissions including those released with occupancy contribute more substantially to allergenic fungal exposures in classrooms sampled than do outdoor contributions from ventilation. The results suggest that design and maintenance of buildings to control indoor emissions may enable reduced indoor inhalation exposures to fungal allergens

A novel systems solution for accurate colorimetric measurement through smartphone-based augmented reality.

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading

A novel systems solution for accurate colorimetric measurement through smartphone-based augmented reality

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading

Translating research to policy at the NCSE 2017 symposium “Microbiology of the Built Environment: Implications for Health and Design”

Abstract Here, we summarize a symposium entitled “Microbiology of the Built Environment: Implications for Health and Design” that was presented at the National Council for Science and the Environment (NCSE) 17th National Conference and Global Forum in January 2017. We covered topics including indoor microbial exposures and childhood asthma, the influence of hospital design on neonatal development, the role of the microbiome in our premise (i.e., building) plumbing systems, antibiotic resistance, and quantitative microbial risk assessment. This symposium engaged the broader scientific and policy communities in a discussion to increase awareness of this critical research area and translate findings to practice

Degradation of phthalate esters in floor dust at elevated relative humidity

Emerging investigator series: Phthalate esters are present at elevated concentrations in floor dust, and resuspension of dust represents a major source for human exposure to chemicals. Biodegradation of phthalates occurs in aquatic systems and soils but has not been demonstrated in house dust. The goal of this study was to quantify indoor phthalate ester degradation through both biotic and abiotic mechanisms. Worn carpet squares were embedded with dust and incubated for one to six weeks at equilibrium relative humidity (ERH) levels of 50, 80, 85, 90, 95, and 100%, and nine phthalates were measured. Removal was observed for DEHP, BBzP, DINP, DiDP, and DMP (p < 0.05) when incubated under elevated relative humidity conditions. Abiotic and biotic losses were examined separately using dust spiked with deuterated di(2-ethylhexyl)phthalate (d-DEHP) that was embedded in carpet and incubated at 100% ERH. Abiotic processes resulted in a 10.1% (±1.1%, standard error) to 69.6% (±4.8%) decrease in total d-DEHP after one week (p = 0.03) and a 27.2% (±1.4%) to 52.0% (±2.1%) decrease after three weeks (p = 0.008). Biodegradation resulted in a decrease in total d-DEHP after one week, ranging from 5.9% (±8.9%) to 8.5% (±1.7%) (p = 0.07) and a 1.7% (±3.9%) to 10.3% (±4.5%) decrease after three weeks (p = 0.044). Metatranscriptomic-based analysis indicates that fungi found in carpet dust express genes capable of degrading phthalate esters via various biochemical processes (including β-oxidation and hydrolysis). Overall, these results support the hypothesis that phthalate losses in floor dust are due to a combination of abiotic and microbial degradation at ≥80% ERH.Funding was provided by a Microbiology of the Built Environmental Postdoctoral Fellowship from the Alfred P. Sloan Foundation. Bridget Hegarty was funded by the Graduate Research Fellowship Program from the National Science Foundation

Indoor Emissions as a Primary Source of Airborne Allergenic Fungal Particles in Classrooms

This study quantifies the influence of ventilation and indoor emissions on concentrations and particle sizes of airborne indoor allergenic fungal taxa and further examines geographical variability, each of which may affect personal exposures to allergenic fungi. Quantitative PCR and multiplexed DNA sequencing were employed to count and identify allergenic fungal aerosol particles indoors and outdoors in seven school classrooms in four different countries. Quantitative diversity analysis was combined with building characterization and mass balance modeling to apportion source contributions of indoor allergenic airborne fungal particles. Mass balance calculations indicate that 70% of indoor fungal aerosol particles and 80% of airborne allergenic fungal taxa were associated with indoor emissions; on average, 81% of allergenic fungi from indoor sources originated from occupant-generated emissions. Principal coordinate analysis revealed geographical variations in fungal communities among sites in China, Europe, and North America (<i>p</i> < 0.05, analysis of similarity), demonstrating that geography may also affect personal exposures to allergenic fungi. Indoor emissions including those released with occupancy contribute more substantially to allergenic fungal exposures in classrooms sampled than do outdoor contributions from ventilation. The results suggest that design and maintenance of buildings to control indoor emissions may enable reduced indoor inhalation exposures to fungal allergens