Crewmember microbiome may influence microbial composition of ISS habitable surfaces

Abstract

The International Space Station (ISS) is a complex built environment physically isolated from Earth. Assessing the interplay between the microbial community of the ISS and its crew is important for preventing biomedical and structural complications for long term human spaceflight missions. In this study, we describe one crewmember's microbial profile from body swabs of mouth, nose, ear, skin and saliva that were collected at eight different time points pre-, during and post-flight. Additionally, environmental surface samples from eight different habitable locations in the ISS were collected from two flights. Environmental samples from one flight were collected by the crewmember and samples from the next flight were collected after the crewmember departed. The microbial composition in both environment and crewmember samples was measured using shotgun metagenomic sequencing and processed using the Livermore Metagenomics Analysis Toolkit. Ordination of sample to sample distances showed that of the eight crew body sites analyzed, skin, nostril, and ear samples are more similar in microbial composition to the ISS surfaces than mouth and saliva samples; and that the microbial composition of the crewmember's skin samples are more closely related to the ISS surface samples collected by the crewmember on the same flight than ISS surface samples collected by other crewmembers on different flights. In these collections, species alpha diversity in saliva samples appears to decrease during flight and rebound after returning to Earth. This is the first study to compare the ISS microbiome to a crewmember's microbiome via shotgun metagenomic sequencing. We observed that the microbiome of the surfaces inside the ISS resemble those of the crew's skin. These data support future crew and ISS microbial surveillance efforts and the design of preventive measures to maintain crew habitat onboard spacecraft destined for long term space travel.

Fig 1. Top 12 most abundant species from crewmember samples pre-, during- and post-flight.

The percent of mapped reads from saliva, mouth, nostril, ear and skin samples for each species in each sample (ranked by the average abundance in each panel summed across locations). Each sample’s time point label (day code) and day number are shown.

Fig 2. Alpha diversity for crewmember saliva samples at the species level resolution over time.

Alpha diversity is quantified as Hill numbers corresponding to transformed richness (N₀), Shannon (N₁), and Simpson (N₂) diversity indices. Samples are shown as black points (round). A gamma regression line (blue) is fitted to the points with a 95% confidence interval in grey.

Fig 3. Relative abundances of genera that were differentially abundant among flight state in saliva samples.

The relative abundances of the eight genera with the smallest Kruskall-Wallis P-values are shown in color. The distribution of relative abundances from other genera are shown in grey. Abundances are log transformed and relative to the geometric mean abundance per sample using genera that were present within each flight state (centered log-ratio transform).

Fig 4. Relative abundances of top 12 species in environmental samples in Flights 4 and 5.

The proportion of mapped microbial reads assigned to each genus is shown for each environmental sample. The top 12 genera are shown in colors and light grey (ranked by the average abundance in each panel summed across locations). Other less abundant genera are lumped together in lighter grey.

Fig 5. NMDS ordination of samples by Jaccard distance at species level resolution.

Environmental samples are shown as gray circles (Flights 1–3 [2]) and brown and yellow circles (Flights 4, 5 this analysis). Samples from the crewmember (this analysis) are shown as circles for during flight, plus signs (+) for pre-flight, and crosses (x) for post-flight. Skin samples are colored pink; mouth as red, saliva lighter green, nostril purple, ear darker green. Control samples are semitransparent squares.

Fig 6. Assessment of astronaut contribution to the ISS microbiome.

SourceTracker was used to assess the proportion of crewmember 1 microbiome sequences to Flight 4 and Flight 5 ISS surface microbiome sequences. This was done by comparing the species compositions of reads found in the crewmember inflight samples (“source”) with those of various flight samples (“sink”). The expected proportion of reads contributed by crewmember 1 for each sink (i.e., surface location, by flight) is shown along the x-axis. The standard deviation of the predicted proportions for each sink was either 0.00 or 0.01, computed from 10 Gibbs samples per sink location, and thus treated as point estimates. The mean contribution per flight across surface locations (diamond) and its standard error are shown in red.