Fungal diversity in homes and asthma morbidity among school-age children in New York City.

BACKGROUND: Asthma development has been inversely associated with exposure to fungal diversity. However, the influence of fungi on measures of asthma morbidity is not well understood. OBJECTIVES: This study aimed to test the hypothesis that fungal diversity is inversely associated with neighborhood asthma prevalence and identify specific fungal species associated with asthma morbidity. METHODS: Children aged 7-8 years (n = 347) living in higher (11-18%) and lower (3-9%) asthma prevalence neighborhoods were recruited within an asthma case-control study. Fungal communities were analyzed from floor dust using high-throughput DNA sequencing. A subset of asthmatic children (n = 140) was followed to age 10-11 to determine asthma persistence. RESULTS: Neighborhood asthma prevalence was inversely associated with fungal species richness (P = 0.010) and Shannon diversity (P = 0.059). Associations between neighborhood asthma prevalence and diversity indices were driven by differences in building type and presence of bedroom carpet. Among children with asthma at age 7-8 years, Shannon fungal diversity was inversely associated with frequent asthma symptoms at that age (OR 0.57, P = 0.025) and with asthma persistence to age 10-11 (OR 0.48, P = 0.043). Analyses of individual fungal species did not show significant associations with asthma outcomes when adjusted for false discovery rates. DISCUSSION: Lower fungal diversity was associated with asthma symptoms in this urban setting. Individual fungal species associated with asthma morbidity were not detected. Further research is warranted into building type, carpeting, and other environmental characteristics which influence fungal exposures in homes.

Persistence of viable MS2 and Phi6 bacteriophages on carpet and dust.

Resuspension of dust from flooring is a major source of human exposure to microbial contaminants, but the persistence of viruses on dust and carpet and the contribution to human exposure are often unknown. The goal of this work is to determine viability of MS2 and Phi6 bacteriophages on cut carpet, looped carpet, and house dust both over time and after cleaning. Bacteriophages were nebulized onto carpet or dust in artificial saliva. Viability was measured at 0, 1, 2, 3, 4, 24, and 48 h and after cleaning by vacuum, steam, hot water extraction, and disinfection. MS2 bacteriophages showed slower viability decay rates in dust (-0.11 hr-1 ), cut carpet (-0.20 hr-1 ), and looped carpet (-0.09 hr-1 ) compared to Phi6 (-3.36 hr-1 , -1.57 hr-1 , and -0.20 hr-1 , respectively). Viable viral concentrations were reduced to below the detection limit for steam and disinfection for both MS2 and Phi6 (p < 0.05), while vacuuming and hot water extraction showed no significant changes in concentration from uncleaned carpet (p > 0.05). These results demonstrate that MS2 and Phi6 bacteriophages can remain viable in carpet and dust for several hours to days, and cleaning with heat and disinfectants may be more effective than standard vacuuming.

Spring is associated with increased total and allergenic fungal concentrations in house dust from a pediatric asthma cohort in New York City.

Introduction: Asthma and allergy symptoms vary seasonally due to exposure to environmental sources of allergen, including fungi. However, we need an improved understanding of seasonal influence on fungal exposures in the indoor environment. We hypothesized that concentrations of total fungi and allergenic species in vacuumed dust vary significantly by season. Objective: Assess seasonal variation of indoor fungi with greater implications related to seasonal asthma control. Methods: We combined next-generation sequencing with quantitative polymerase chain reaction (qPCR) to measure concentrations of fungal DNA in indoor floor dust samples (n = 298) collected from homes participating in the New York City Neighborhood Asthma and Allergy Study (NAAS). Results: Total fungal concentration in spring was significantly higher than the other three seasons (p ≤ 0.005). Mean concentrations for 78% of fungal species were elevated in the spring (26% were significantly highest in spring, p < 0.05). Concentrations of 8 allergenic fungal species were significantly (p < 0.5) higher in spring compared to at least two other seasons. Indoor relative humidity and temperature were significantly highest in spring (p < 0.05) and were associated with total fungal concentration (R2 = 0.049, R2 = 0.11, respectively). Conclusion: There is significant seasonal variation in total fungal concentration and concentration of select allergenic species. Indoor relative humidity and temperature may underlie these associations.

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.

Morphology and quantification of fungal growth in residential dust and carpets.

Mold growth indoors is associated with negative human health effects, and this growth is limited by moisture availability. Dust deposited in carpet is an important source of human exposure due to potential elevated resuspension compared to hard floors. However, we need an improved understanding of fungal growth in dust and carpet to better estimate human exposure. The goal of this study was to compare fungal growth quantity and morphology in residential carpet under different environmental conditions, including equilibrium relative humidity (ERH) (50%, 85%, 90%, 95%, 100%), carpet fiber material (nylon, olefin, wool) and presence/absence of dust. We analyzed incubated carpet and dust samples from three Ohio homes for total fungal DNA, fungal allergen Alt a 1, and fungal morphology. Dust presence and elevated ERH (≥85%) were the most important variables that increased fungal growth. Elevated ERH increased mean fungal DNA concentration (P < 0.0001), for instance by approximately 1000 times at 100% compared to 50% ERH after two weeks. Microscopy also revealed more fungal growth at higher ERH. Fungal concentrations were up to 100 times higher in samples containing house dust compared to no dust. For fiber type, olefin had the least total fungal growth, and nylon had the most total fungi and A. alternata growth in unaltered dust. Increased ERH conditions were associated with increased Alt a 1 allergen concentration. The results of this study demonstrate that ERH, presence/absence of house dust, and carpet fiber type influence fungal growth and allergen production in residential carpet, which has implications for human exposure.

Quantitative evaluation of bioaerosols in different particle size fractions in dust collected on the International Space Station (ISS).

Exposure to bioaerosols can adversely influence human health through respiratory tract, eye, and skin irritation. Bioaerosol composition is unique on the International Space Station (ISS), where the size distribution of particles in the air differs from those on Earth. This is due to the lack of gravitational settling and sources of biological particles. However, we do not understand how microbes are influenced by particle size in this environment. We analyzed two types of samples from the ISS: (1) vacuum bag debris which had been sieved into five different size fractions and (2) passively collected particles on a tape substrate with a passive aerosol sampler. Using quantitative polymerase chain reaction (qPCR), the highest concentration of fungal spores was found in the 106-150 µm-sized sieved dust particles, while the highest concentration of bacterial cells was found in the 150-250 µm-sized sieved dust particles. Illumina MiSeq DNA sequencing revealed that particle size was associated with bacterial and fungal communities and statistically significant (p = 0.035, p = 0.036 respectively). Similar fungal and bacterial species were found within the passive aerosol sample and the sieved dust samples. The most abundant fungal species identified in the aerosol and sieved samples are commonly found in food and plant material. Abundant bacterial species were most associated with the oral microbiome and human upper respiratory tract. One limitation to this study was the suboptimal storage conditions of the sieved samples prior to analysis. Overall, our results indicate that microbial exposure in space may depend on particle size. This has implications for ventilation and filtration system design for future space vehicles and habitats.

Ten questions concerning the implications of carpet on indoor chemistry and microbiology.

Carpet and rugs currently represent about half of the United States flooring market and offer many benefits as a flooring type. How carpets influence our exposure to both microorganisms and chemicals in indoor environments has important health implications but is not well understood. The goal of this manuscript is to consolidate what is known about how carpet impacts indoor chemistry and microbiology, as well as to identify the important research gaps that remain. After describing the current use of carpet indoors, questions focus on five specific areas: 1) indoor chemistry, 2) indoor microbiology, 3) resuspension and exposure, 4) current practices and future needs, and 5) sustainability. Overall, it is clear that carpet can influence our exposures to particles and volatile compounds in the indoor environment by acting as a direct source, as a reservoir of environmental contaminants, and as a surface supporting chemical and biological transformations. However, the health implications of these processes are not well known, nor how cleaning practices could be optimized to minimize potential negative impacts. Current standards and recommendations focus largely on carpets as a primary source of chemicals and on limiting moisture that would support microbial growth. Future research should consider enhancing knowledge related to the impact of carpet in the indoor environment and how we might improve the design and maintenance of this common material to reduce our exposure to harmful contaminants while retaining the benefits to consumers.

Community interest and feasibility of using a novel smartphone-based formaldehyde exposure detection technology.

OBJECTIVE: This study is the first community engagement phase of a project to develop a residential formaldehyde detection system. The objectives were to conduct a feasibility assessment for device use, and identify factors associated with concerns about environmental exposure and community interest in this device. DESIGN AND SAMPLE: A cross-sectional, internet-based survey employing community-based participatory research principles was utilized. 147 individuals participated from a focused Waycross, Georgia (58.5%) and broader national sample (41.5%). MEASURES: Variables included acceptable cost and number of testing samples, interest in conducting tests, levels of concern over pollutants, health status, housing, and demographics. RESULTS: The majority of participants desired a system with fewer than 10 samples at ≤$15.00 per sample. Statistically significant higher levels of concern over air quality, formaldehyde exposure, and interest in testing formaldehyde were observed for those with overall worse health status and living in the Waycross, Georgia geographic region. Significant differences in formaldehyde testing interest were observed by health status (OR = 0.31, 95% CI = 0.12-0.81 for home testing) and geographic location (OR = 3.16, 95% CI = 1.22-8.14 for home and OR = 4.06, 95% CI = 1.48-11.12 for ambient testing) in multivariate models. CONCLUSIONS: Geographic location and poorer general health status were associated with concerns over and interest in formaldehyde testing.

Indoor microbial communities: Influence on asthma severity in atopic and nonatopic children.

BACKGROUND: Allergic and nonallergic asthma severity in children can be affected by microbial exposures. OBJECTIVE: We sought to examine associations between exposures to household microbes and childhood asthma severity stratified by atopic status. METHODS: Participants (n = 196) were selected from a cohort of asthmatic children in Connecticut and Massachusetts. Children were grouped according to asthma severity (mild with no or minimal symptoms and medication or moderate to severe persistent) and atopic status (determined by serum IgE levels). Microbial community structure and concentrations in house dust were determined by using next-generation DNA sequencing and quantitative PCR. Logistic regression was used to explore associations between asthma severity and exposure metrics, including richness, taxa identification and quantification, community composition, and concentration of total fungi and bacteria. RESULTS: Among all children, increased asthma severity was significantly associated with an increased concentration of summed allergenic fungal species, high total fungal concentrations, and high bacterial richness by using logistic regression in addition to microbial community composition by using the distance comparison t test. Asthma severity in atopic children was associated with fungal community composition (P = .001). By using logistic regression, asthma severity in nonatopic children was associated with total fungal concentration (odds ratio, 2.40; 95% CI, 1.06-5.44). The fungal genus Volutella was associated with increased asthma severity in atopic children (P = .0001, q = 0.04). The yeast genera Kondoa might be protective; Cryptococcus species might also affect asthma severity. CONCLUSION: Asthma severity among this cohort of children was associated with microbial exposure, and associations differed based on atopic status.

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.

Identification accuracy and diversity reproducibility associated with internal transcribed spacer-based fungal taxonomic library preparation.

This study investigated analytical parameters that are inherently relevant to identifying and quantifying fungal communities based on polymerase chain reaction amplicons. Specifically, we evaluated the accuracy of the BLASTn-based identification for internal transcribed spacer (ITS) sequences generated from pure cultures, and quantified the reproducibility of relative abundances as well as α and ß diversity measurements using duplicated environmental samples. The BLASTn-based method produced accurate fungal identification for the pure culture sequences at the genus rank. Percentages of the sequences assigned to correct genera were 99.8%, 99.8% and 99.9% for Alternaria alternata, Cladosporium cladosporioides and Epicoccum nigrum respectively. These fractions were smaller for Aspergillus fumigatus and Penicillium chrysogenum, which have dual nomenclatures or sibling species that are indistinguishable by ITS sequences. Our duplicate environmental analyses demonstrated that α diversity and relative abundance levels were reproducible (r(2) > 0.9), that variability decreases with increased sequence quantity, and that the differences in distinct environmental samples were larger than differences in replicate samples (ß diversity). These results serve to better characterize the identification and quantification limits of ITS-based fungal taxonomic studies, and demonstrate that while diversity quantification is reproducible, limitations in ITS-based taxonomic identification and dual nomenclature conventions are current barriers to identification accuracy.

Fungal high-throughput taxonomic identification tool for use with next-generation sequencing (FHiTINGS).

Improvements in DNA sequencing technology provide unprecedented opportunities to explore fungal diversity, but also present challenges in data analysis due to the large number of sequences generated. Here, we describe an open source software program "FHiTINGS" that utilizes the output of a BLASTn (blastall) search to rapidly identify, classify, and parse internal transcribed spacer (ITS) DNA sequences produced in fungal ecology studies that utilize next-generation DNA sequencing. This tool was designed for use with 454 pyrosequencing and is also appropriate for use with any sequencing platform that allows for BLAST searches against the indicated ITS database. For each sequence, FHiTINGS uses the lowest common ancestor method (LCA) to produce a single identification from BLAST output results, and then assigns taxonomic ranks from species through kingdom when possible for each sequence based on the Index Fungorum database. The program then sums and sorts this data into tabular form to enable rapid analysis of the sample, including α-diversity measures or richness. In silico testing demonstrates the time required to analyze and classify 1000 sequences is reduced from over 2 h by manual sorting to <1 min of computational time when using FHiTINGS, and that the classification output from the software is consistent with that derived from manual sorting of the data.

Fungal diversity differences in the indoor dust microbiome from built environments on earth and in space.

Human occupied built environments are no longer confined to Earth. In fact, there have been humans living and working in low-Earth orbit on the International Space Station (ISS) since November 2000. With NASA's Artemis missions and the age of commercial space stations set to begin, more human-occupied spacecraft than ever will be in Earth's orbit and beyond. On Earth and in the ISS, microbes, especially fungi, can be found in dust and grow when unexpected, elevated moisture conditions occur. However, we do not yet know how indoor microbiomes in Earth-based homes and in the ISS differ due to their unique set of environmental conditions. Here we show that bacterial and fungal communities are different in dust collected from vacuum bags on Earth and the ISS, with Earth-based homes being more diverse (465 fungal OTUs and 237 bacterial ASVs) compared to the ISS (102 fungal OTUs and 102 bacterial ASVs). When dust from these locations were exposed to varying equilibrium relative humidity conditions (ERH), there were also significant fungal community composition changes as ERH and time elevated increased (Bray Curtis: R2 = 0.35, P = 0.001). These findings can inform future spacecraft design to promote healthy indoor microbiomes that support crew health, spacecraft integrity, and planetary protection.

Predicting how varying moisture conditions impact the microbiome of dust collected from the International Space Station.

BACKGROUND: The commercialization of space travel will soon lead to many more people living and working in unique built environments similar to the International Space Station, which is a specialized closed environment that contains its own indoor microbiome. Unintended microbial growth can occur in these environments as in buildings on Earth from elevated moisture, such as from a temporary ventilation system failure. This growth can drive negative health outcomes and degrade building materials. We need a predictive approach for modeling microbial growth in these critical indoor spaces. RESULTS: Here, we demonstrate that even short exposures to varying elevated relative humidity can facilitate rapid microbial growth and microbial community composition changes in dust from spacecraft. We modeled fungal growth in dust from the International Space Station using the time-of-wetness framework with activation and deactivation limited growth occurring at 85% and 100% relative humidity, respectively. Fungal concentrations ranged from an average of 4.4 × 106 spore equivalents per milligram of dust in original dust with no exposure to relative humidity to up to 2.1 × 1010 when exposed to 100% relative humidity for 2 weeks. As relative humidity and time-elevated increased, fungal diversity was significantly reduced for both alpha (Q < 0.05) and beta (R2 = 0.307, P = 0.001) diversity metrics. Bacteria were unable to be modeled using the time-of-wetness framework. However, bacterial communities did change based on constant relative humidity incubations for both beta (R2 = 0.22, P = 0.001) and alpha diversity decreasing with increasing moisture starting at 85% relative humidity (Q < 0.05). CONCLUSION: Our results demonstrate that moisture conditions can be used to develop and predict changes in fungal growth and composition onboard human-occupied spacecraft. This predictive model can be expanded upon to include other spacecraft environmental factors such as microgravity, elevated carbon dioxide conditions, and radiation exposure. Understanding microbial growth in spacecraft can help better protect astronaut health, fortify spacecraft integrity, and promote planetary protection as human activity increases in low-Earth orbit, the moon, Mars, and beyond. Video Abstract.

A mechanistic modeling and estimation framework for environmental pathogen surveillance.

Environmental pathogen surveillance is a promising disease surveillance modality that has been widely adopted for SARS-CoV-2 monitoring. The highly variable nature of environmental pathogen data is a challenge for integrating these data into public health response. One source of this variability is heterogeneous infection both within an individual over the course of infection as well as between individuals in their pathogen shedding over time. We present a mechanistic modeling and estimation framework for connecting environmental pathogen data to the number of infected individuals. Infected individuals are modeled as shedding pathogen into the environment via a Poisson process whose rate parameter λt varies over the course of their infection. These shedding curves λt are themselves random, allowing for variation between individuals. We show that this results in a Poisson process for environmental pathogen levels with rate parameter a function of the number of infected individuals, total shedding over the course of infection, and pathogen removal from the environment. Theoretical results include determination of identifiable parameters for the model from environmental pathogen data and simple, explicit formulas for the likelihood for particular choices of individual shedding curves. We give a two step Bayesian inference framework, where the first step corresponds to calibration from data where the number of infected individuals is known, followed by an estimation step from environmental surveillance data when the number of infected individuals is unknown. We apply this modeling and estimation framework to synthetic data, as well as to an empirical case study of SARS-CoV-2 in environmental dust collected from isolation rooms housing university students. Both the synthetic data and empirical case study indicate high inter-individual variation in shedding, leading to wide credible intervals for the number of infected individuals. We examine how uncertainty in estimates of the number of infected individuals from environmental pathogen levels scales with the true number of infected individuals and model misspecification. While credible intervals for the number of infected individuals are wide, our results suggest that distinguishing between no infection and small-to-moderate levels of infection (≈10 infected individuals) may be possible, and that it is broadly possible to differentiate between moderate (≈40) and high (≈200) numbers of infected individuals.

Corrigendum: Persisting Cryptococcus yeast species Vishniacozyma victoriae and Cryptococcus neoformans elicit unique airway inflammation in mice following repeated exposure.

[This corrects the article DOI: 10.3389/fcimb.2023.1067475.].

Identification of SARS-CoV-2 variants in indoor dust.

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

The chemical assessment of surfaces and air (CASA) study: using chemical and physical perturbations in a test house to investigate indoor processes.

The Chemical Assessment of Surfaces and Air (CASA) study aimed to understand how chemicals transform in the indoor environment using perturbations (e.g., cooking, cleaning) or additions of indoor and outdoor pollutants in a well-controlled test house. Chemical additions ranged from individual compounds (e.g., gaseous ammonia or ozone) to more complex mixtures (e.g., a wildfire smoke proxy and a commercial pesticide). Physical perturbations included varying temperature, ventilation rates, and relative humidity. The objectives for CASA included understanding (i) how outdoor air pollution impacts indoor air chemistry, (ii) how wildfire smoke transports and transforms indoors, (iii) how gases and particles interact with building surfaces, and (iv) how indoor environmental conditions impact indoor chemistry. Further, the combined measurements under unperturbed and experimental conditions enable investigation of mitigation strategies following outdoor and indoor air pollution events. A comprehensive suite of instruments measured different chemical components in the gas, particle, and surface phases throughout the study. We provide an overview of the test house, instrumentation, experimental design, and initial observations - including the role of humidity in controlling the air concentrations of many semi-volatile organic compounds, the potential for ozone to generate indoor nitrogen pentoxide (N2O5), the differences in microbial composition between the test house and other occupied buildings, and the complexity of deposited particles and gases on different indoor surfaces.

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.

Persisting Cryptococcus yeast species Vishniacozyma victoriae and Cryptococcus neoformans elicit unique airway inflammation in mice following repeated exposure.

Background: Allergic airway disease (AAD) is a growing concern in industrialized nations and can be influenced by fungal exposures. Basidiomycota yeast species such as Cryptococcus neoformans are known to exacerbate allergic airway disease; however, recent indoor assessments have identified other Basidiomycota yeasts, including Vishniacozyma victoriae (syn. Cryptococcus victoriae), to be prevalent and potentially associated with asthma. Until now, the murine pulmonary immune response to repeated V. victoriae exposure was previously unexplored. Objective: This study aimed to compare the immunological impact of repeated pulmonary exposure to Cryptococcus yeasts. Methods: Mice were repeatedly exposed to an immunogenic dose of C. neoformans or V. victoriae via oropharyngeal aspiration. Bronchoalveolar lavage fluid (BALF) and lungs were collected to examine airway remodeling, inflammation, mucous production, cellular influx, and cytokine responses at 1 day and 21 days post final exposure. The responses to C. neoformans and V. victoriae were analyzed and compared. Results: Following repeated exposure, both C. neoformans and V. victoriae cells were still detectable in the lungs 21 days post final exposure. Repeated C. neoformans exposure initiated myeloid and lymphoid cellular infiltration into the lung that worsened over time, as well as an IL-4 and IL-5 response compared to PBS-exposed controls. In contrast, repeated V. victoriae exposure induced a strong CD4+ T cell-driven lymphoid response that started to resolve by 21 days post final exposure. Discussion: C. neoformans remained in the lungs and exacerbated the pulmonary immune responses as expected following repeated exposure. The persistence of V. victoriae in the lung and strong lymphoid response following repeated exposure were unexpected given its lack of reported involvement in AAD. Given the abundance in indoor environments and industrial utilization of V. victoriae, these results highlight the importance to investigate the impact of frequently detected fungal organisms on the pulmonary response following inhalational exposure. Moreover, it is important to continue to address the knowledge gap involving Basidiomycota yeasts and their impact on AAD.