City-scale distribution and dispersal routes of mycobiome in residences

Abstract

Background: Pathogenic and allergenic bacteria and fungi within the indoors can bring detrimental health effects on the occupants. We previously studied the bacterial communities found in households located throughout Hong Kong as well as the skin surfaces of the occupants. As a complementary study, here, we investigated the fungal communities (mycobiome) in the same residences and occupants and identified factors that are important in shaping their diversity, composition, distribution, and dispersal patterns.

Results: We observed that common skin and environmental fungal taxa dominated air, surface, and skin samples. Individual and touch frequency strongly and respectively shaped the fungal community structure on occupant skin and residential surfaces. Cross-domain analysis revealed positive correlations between bacterial and fungal community diversity and composition, especially for skin samples. SourceTracker prediction suggested that some fungi can be transferred bidirectionally between surfaces and skin sites, but bacteria showed a stronger dispersal potential. In addition, we detected a modest but significant association between indoor airborne bacterial composition and geographic distance on a city-wide scale, a pattern not observed for fungi. However, the distance-decay effects were more pronounced at shorter local scale for both communities, and airflow might play a prominent role in driving the spatial variation of the indoor airborne mycobiome.

Conclusions: Our study suggests that occupants exert a weaker influence on surface fungal communities compared to bacterial communities, and local environmental factors, including air currents, appear to be stronger determinants of indoor airborne mycobiome than ventilation strategy, human occupancy, and room type.

Keywords: Biogeography; Dispersal potentials; Distance-decay; Indoor built environment; Mycobiome.

Fig. 1

City-wide geographical locations of the 19 households. Households are separated into East-West (red markers, eight households) and North-South transects (blue markers, seven households), while the four households colored with green markers outside the two clusters were excluded from the directionality analysis. The locations of the households were plotted using Google Maps, and the household code names are indicated

Fig. 2

Mean relative abundance of the top 15 genera detected in samples across different households and occupants. The color intensity of the heatmap indicates a scale from 0 to 80%

Fig. 3

Distance-decay patterns of the indoor airborne bacterial and fungal communities for households along the North-South and East-West transects. Each point represents the bacterial or fungal community dissimilarity (based on Binary Jaccard distance) between two air samples at the indicated geographic distance for two households. The regression line between the bacterial or fungal community dissimilarities, and geographic distance is shown. Households located on the North-South and East-West transects for the bacterial (a, b) and fungal (c, d) communities, respectively

Fig. 4

Heatmap based on SourceTracker prediction accuracy for the different dispersal routes. The color intensity of the heatmap indicates a scale from 0 to 40%. A prediction is considered successful only if the source community that contributes largest to the sink community is from the same household. The accuracy rate in percentage is the ratio between the number of successful predictions and total predictions. As an example, skin-to-surface indicates the dispersal route where skin samples act as the sources and surface samples are the sinks. For dispersal routes involving air or surface, occupancy level was tested. For routes involving surface either as a source or sink, the transfer was further evaluated based on high/low deposition potential and high/low touch frequency

Fig. 5

Contribution of the source genera to the corresponding sink community for each household. a The contribution of skin community to each residential surface (x-axis) within each household (households ADMB and HHB without skin samples were excluded from the analysis). Correct prediction indicates that SourceTracker is capable to correctly match the surface community to the corresponding occupant of the households, while false prediction indicates an incorrect match between the surface community and the occupant. The percentage refers to the total contribution of each genus on the five skin sites to each surface community. b The contribution of the surface community to each skin site (right y-axis) of the occupants (x-axis) within each household. The percentage refers to the total contribution of each genus on the eight different types of surfaces to each skin site

Fig. 6

Schematic summary of the bacterial and fungal dispersal potentials for the different routes within households. Double-sided arrow depicts bidirectional dispersal of microbes. Line thickness is proportional to the strength of dispersal potentials (interpreted according to the SourceTracker results). Only the dispersal from outdoor air to indoor air (one direction) was considered. The bacterial results are based on our previous study [15]. Individual clip art images were downloaded from the open-source website Iconfont (http://www.iconfont.cn) and further customized