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 Supplementary Information The online version contains supplementary material available at 10.1186/s40168-024-01864-3.

: Principal coordinate analyses of frozen dust sample returned from the ISS.Frozen samples were compared to original dust samples (from ISS vacuum bag) as well as 2-week incubations at 50%, 85%, and 100% ERH.Fungi PCoA plots used the Bray-Curtis dissimilarity statistics (C), while bacteria used both weighted (A) and unweighted unifrac (B).
Supplemental Table S13: Adonis statistics for fungal and bacterial frozen sample comparisons.Frozen samples were compared to original dust samples (from ISS vacuum bag) as well as 2-week incubations at 50%, 85%, and 100% RH.

Table S3 :
Summary of Satterthwaite two-sample t-test statistics for fungal and bacterial 2-week incubations.Supplemental TableS4: qPCR values for fungal and bacterial quantities for frozen dust sample and the original dust collected from the ISS vacuum bags.

Table S5 :
Total fungal growth rates for TOW incubations.Values represent the average of the 4 ISS bags collected.

Condition Bag Fungal Growth Rate Constant (k) day -1 Bacterial Growth Rate (k) day -1
Supplemental TableS8: Effective growth constants (R) for all TOW samples.

Table S9 :
Relative growth constants (R/k) for all TOW samples.

Table S10 :
Most common taxa that was present in all sequenced samples sorted by order, genus, and species for bacteria and fungi.

value Bacterial Time of Wetness (50% and 100% RH for 24 hours only)
Supplemental Figure

Table S14 :
Fungal alpha diversity Kruskal-Wallis statistics for richness and Shannon diversity for 2week incubations at each RH conditions tested.Significant changes in both richness and Shannon diversity compared to the original dust began to occur at 80% RH (Q<0.05).

Table S15 :
Richness and Shannon diversity Kruskal-Wallis statistics for fungal time-of-wetness samples.

Fungal Time-of-Wetness 18 hour Only
Supplemental FigureS7: Frozen sample alpha diversity plots for (A) bacteria and (B) fungi.Frozen dust samples were compared to original dust, 50% ERH 2-week, 85% ERH 2-week, and 100% ERH 2-week incubations.Supplemental TableS16: Kruskal-Wallis test statistics for alpha diversity metrics for all sequenced bacterial samples.Supplemental TableS17: Kruskal-Wallis test statistics for fungal and bacterial frozen sample comparisons.

Table S20 :
Differential abundance fungal comparison between unmodified (50% RH) 24-hour TOW samples and 24-hour TOW saturated (100% RH) conditions.There were 29 fungal species more abundant in the unmodified condition compared to 10 species more abundant at saturated conditions.

Table S21 :
Differential abundance fungal comparison between high (85% RH) 24-hour TOW samples and 24-hour TOW saturated (100% RH) conditions.There was 1 fungal species more abundant in the high condition compared to 8 species more abundant at saturated conditions.

More abundant at saturated (100% ERH) conditions (8 species)
Supplemental TableS22: Differential abundance fungal comparison between high (85% RH) for all TOW samples and all TOW saturated (100% RH) conditions.There were 30 fungal species more abundant in the high condition compared to 4 species more abundant at saturated conditions.

value Adjusted FDR P-value More abundant at high (85% ERH) conditions All TOW (30 species)
Supplemental Table23: Example of bacterial differential abundance analysis for non-elevated (original dust and 50% RH) and elevated (80, 85, 90, and 100% RH) conditions for 2-week incubations.No bacterial species were found to be more abundant in either condition.This was true for all time-of-wetness incubation comparisons as well (not shown).