Dataset Information

Fungal Signature of Moisture Damage in Buildings: Identification by Targeted and Untargeted Approaches with Mycobiome Data.

ABSTRACT: Identifying microbial indicators of damp and moldy buildings remains a challenge at the intersection of microbiology, building science, and public health. Sixty homes in New York City were assessed for moisture-related damage, and three types of dust samples were collected for microbiological analysis. We applied four approaches for detecting fungal signatures of moisture damage in these buildings. Two novel targeted approaches selected specific taxa, identified by a priori hypotheses, from the broad mycobiome as detected with amplicon sequencing. We investigated whether (i) hydrophilic fungi (i.e., requiring high moisture) or (ii) fungi previously reported as indicating damp homes would be more abundant in water-damaged rooms/homes than in nondamaged rooms/homes. Two untargeted approaches compared water-damaged to non-water-damaged homes for (i) differences between indoor and outdoor fungal populations or (ii) differences in the presence or relative abundance of particular fungal taxa. Strong relationships with damage indicators were found for some targeted fungal groups in some sampling types, although not always in the hypothesized direction. For example, for vacuum samples, hydrophilic fungi had significantly higher relative abundance in water-damaged homes, but mesophilic fungi, unexpectedly, had significantly lower relative abundance in homes with visible mold. Untargeted approaches identified no microbial community metrics correlated with water damage variables but did identify specific taxa with at least weak positive links to water-damaged homes. These results, although showing a complex relationship between moisture damage and microbial communities, suggest that targeting particular fungi offers a potential route toward identifying a fungal signature of moisture damage in buildings.IMPORTANCE Living or working in damp or moldy buildings increases the risk of many adverse health effects, including asthma and other respiratory diseases. To date, however, the particular environmental exposure(s) from water-damaged buildings that causes the health effects have not been identified. Likewise, a consistent quantitative measurement that would indicate whether a building is water damaged or poses a health risk to occupants has not been found. In this work, we tried to develop analytical tools that would find a microbial signal of moisture damage amid the noisy background of microorganisms in buildings. The most successful approach taken here focused on particular groups of fungi-those considered likely to grow in damp indoor environments-and their associations with observed moisture damage. With further replication and refinement, this hypothesis-based strategy may be effective in finding still-elusive relationships between building damage and microbiomes.

SUBMITTER: Adams RI

PROVIDER: S-EPMC7440782 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Fungal Signature of Moisture Damage in Buildings: Identification by Targeted and Untargeted Approaches with Mycobiome Data.

Adams Rachel I RI Sylvain Iman I Spilak Michal P MP Taylor John W JW Waring Michael S MS Mendell Mark J MJ

Applied and environmental microbiology 20200818 17

Identifying microbial indicators of damp and moldy buildings remains a challenge at the intersection of microbiology, building science, and public health. Sixty homes in New York City were assessed for moisture-related damage, and three types of dust samples were collected for microbiological analysis. We applied four approaches for detecting fungal signatures of moisture damage in these buildings. Two novel targeted approaches selected specific taxa, identified by <i>a priori</i> hypotheses, fr ...[more]

PMID: 32591374

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Project description:BACKGROUND: Indoor microbial contamination due to excess moisture is an important contributor to human illness in both residential and occupational settings. However, the census of microorganisms in the indoor environment is limited by the use of selective, culture-based detection techniques. By using clone library sequencing of full-length internal transcribed spacer region combined with quantitative polymerase chain reaction (qPCR) for 69 fungal species or assay groups and cultivation, we have been able to generate a more comprehensive description of the total indoor mycoflora. Using this suite of methods, we assessed the impact of moisture damage on the fungal community composition of settled dust and building material samples (n = 8 and 16, correspondingly). Water-damaged buildings (n = 2) were examined pre- and post- remediation, and compared with undamaged reference buildings (n = 2). RESULTS: Culture-dependent and independent methods were consistent in the dominant fungal taxa in dust, but sequencing revealed a five to ten times higher diversity at the genus level than culture or qPCR. Previously unknown, verified fungal phylotypes were detected in dust, accounting for 12% of all diversity. Fungal diversity, especially within classes Dothideomycetes and Agaricomycetes tended to be higher in the water damaged buildings. Fungal phylotypes detected in building materials were present in dust samples, but their proportion of total fungi was similar for damaged and reference buildings. The quantitative correlation between clone library phylotype frequencies and qPCR counts was moderate (r = 0.59, p < 0.01). CONCLUSIONS: We examined a small number of target buildings and found indications of elevated fungal diversity associated with water damage. Some of the fungi in dust were attributable to building growth, but more information on the material-associated communities is needed in order to understand the dynamics of microbial communities between building structures and dust. The sequencing-based method proved indispensable for describing the true fungal diversity in indoor environments. However, making conclusions concerning the effect of building conditions on building mycobiota using this methodology was complicated by the wide natural diversity in the dust samples, the incomplete knowledge of material-associated fungi fungi and the semiquantitative nature of sequencing based methods.

Project description:IntroductionThe gut microbiome is an integral partner in host health and plays a role in immune development, altered nutrition, and pathogen prevention. The mycobiome (fungal microbiome) is considered part of the rare biosphere but is still a critical component in health. Next generation sequencing has improved our understanding of fungi in the gut, but methodological challenges remain. Biases are introduced during DNA isolation, primer design and choice, polymerase selection, sequencing platform selection, and data analyses, as fungal reference databases are often incomplete or contain erroneous sequences.MethodsHere, we compared the accuracy of taxonomic identifications and abundances from mycobiome analyses which vary among three commonly selected target gene regions (18S, ITS1, or ITS2) and the reference database (UNITE - ITS1, ITS2 and SILVA - 18S). We analyze multiple communities including individual fungal isolates, a mixed mock community created from five common fungal isolates found in weanling piglet feces, a purchased commercial fungal mock community, and piglet fecal samples. In addition, we calculated gene copy numbers for the 18S, ITS1, and ITS2 regions of each of the five isolates from the piglet fecal mock community to determine whether copy number affects abundance estimates. Finally, we determined the abundance of taxa from several iterations of our in-house fecal community to assess the effects of community composition on taxon abundance.ResultsOverall, no marker-database combination consistently outperformed the others. Internal transcribed space markers were slightly superior to 18S in the identification of species in tested communities, but Lichtheimia corymbifera, a common member of piglet gut communities, was not amplified by ITS1 and ITS2 primers. Thus, ITS based abundance estimates of taxa in piglet mock communities were skewed while 18S marker profiles were more accurate. Kazachstania slooffiae displayed the most stable copy numbers (83-85) while L. corymbifera displayed significant variability (90-144) across gene regions.DiscussionThis study underscores the importance of preliminary studies to assess primer combinations and database choice for the mycobiome sample of interest and raises questions regarding the validity of fungal abundance estimates.

Dataset Information

Fungal Signature of Moisture Damage in Buildings: Identification by Targeted and Untargeted Approaches with Mycobiome Data.

Publications

Fungal Signature of Moisture Damage in Buildings: Identification by Targeted and Untargeted Approaches with Mycobiome Data.

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