Indoor fungal composition is geographically patterned and more diverse in temperate zones than in the tropics

Abstract

Fungi are ubiquitous components of indoor human environments, where most contact between humans and microbes occurs. The majority of these organisms apparently play a neutral role, but some are detrimental to human lifestyles and health. Recent studies that used culture-independent sampling methods demonstrated a high diversity of indoor fungi distinct from that of outdoor environments. Others have shown temporal fluctuations of fungal assemblages in human environments and modest correlations with human activity, but global-scale patterns have not been examined, despite the manifest significance of biogeography in other microbial systems. Here we present a global survey of fungi from indoor environments (n = 72), using both taxonomic and phylogeny-informative molecular markers to determine whether global or local indoor factors determine indoor fungal composition. Contrary to common ecological patterns, we show that fungal diversity is significantly higher in temperate zones than in the tropics, with distance from the equator being the best predictor of phylogenetic community similarity. Fungal composition is significantly auto-correlated at the national and hemispheric spatial scales. Remarkably, building function has no significant effect on indoor fungal composition, despite stark contrasts between architecture and materials of some buildings in close proximity. Distribution of individual taxa is significantly range- and latitude-limited compared with a null model of randomized distribution. Our results suggest that factors driving fungal composition are primarily global rather than mediated by building design or function.

Fig. 1.

Dust-sampling locations and distributions of the most cosmopolitan OTUs. All samples were collected between December 2008 and March 2009. (A) Solid lines indicate the Tropic of Cancer and the Tropic of Capricorn. The number of samples analyzed is noted by the open circles (approximate location). (B) The presence of the 45 OTUs found in the most number of samples (from left to right, most cosmopolitan to least cosmopolitan) is indicated by a solid square (samples used in ITS analysis are in rows ordered by latitude). Nomenclature is derived from annotations provided for similar sequences deposited in GenBank. Note the following equivalencies between anamorphic and teleomorphic stages: Cladosporium = Davidiella, Aspergillus = Eurotium, and Gibberella = Fusarium.

Fig. 2.

Sample phylogenetic composition similarity is explained by environmental variables. (A) Nonmetric multidimensional scaling plot demonstrates goodness-of-fit correlations between the first two dimensions and distance from the equator, mean annual temperature, and mean annual rainfall (all correlations were significant at P ≤ 0.001). The ordination was calculated using pairwise unweighted UniFrac phylogenetic distance. Open symbols are indoor environments that are not dwellings (e.g., shops, hospitals, a church); the broken line circles tropical samples. Mantel correlograms show assemblage autocorrelation as (B) a factor of pairwise differences in latitude and (C) pairwise geographic distance between samples. Error bars are 95% confidence intervals. Mean SD of R-values from all distance classes among 10 random draws of 1,200 sequences was 0.005 for both latitude and geographic distance measurements.

Fig. 3.

OTU distribution patterns showed little evidence of differentiation at the class level (A). The most cosmopolitan OTUs, occurring in more than half of the samples (>50%) or in 9 or 10 of the countries sampled, were dominated by taxa in the class Dothideomycetes. Observed OTU rarefactions (B) were calculated at ITS percentage identity thresholds labeled as 100%, 99%, 97%, 95%, and 90%. A 100% identity rarefaction curve is not contained in the figure, but is calculated to be 54,815. OTU frequency distribution (C) has a long tail with 2,541 (56%) OTUs occurring in a single sample only. Within-sample OTU richness (D; Pearson's product moment, R = 0.37, t = 3.57, df = 63, P = <0.001; rarefied to 400 sequences per sample) and phylogenetic diversity, measured as cumulative branch length (E; R = 0.32, t = 2.58, df = 60, P = 0.01; rarefied to 1,200 sequences per sample), were positively correlated with distance from the equator.

Fig. 4.

Mean pairwise distance between samples sharing nonsingleton OTUs is significantly less than would be expected under a null model of random distribution when OTUs are defined at 97% sequence identity (A; n = 1,932;) and at 90% sequence identity (B; n = 1,258). OTUs shared among buildings located within 2,000 km appear to drive this geographic structure, indicating relatively small ranges of some OTUs. Pairwise comparisons of samples from opposite sides of the equator (within-hemisphere pairwise comparisons excluded) showed that OTUs were more likely to be shared among samples taken from similar distances from the equator than would be expected under a null model of random distribution with OTUs defined at 97% sequence identity (C) and 90% sequence identity (D). Histograms represent the frequency of mean pairwise distance between locations of each OTU in distance classes. Expected means and significance value were calculated with 100 randomized permutations of the dataset constrained by sequence abundance at each location. Vertical lines are the mean of all individual OTU calculations. Triangles and circles are the cumulative frequency of OTUs at increasing distance. P value is the likelihood that the observed mean is greater than the expected.