Crewmember microbiome may influence microbial composition of ISS habitable surfaces

In a recent study, researchers wanted to understand if the types of microbes found on people's skin changed when they went from one flight (F4) back home after five days in space. To do this, scientists used special tools and techniques that help them look at tiny organisms called bacteria without having to grow or see them directly under a microscope. The study involved comparing the microbial makeup of skin samples from one crew member (S1) before they left for space on flight F4, then after returning home and taking another five days in space on flight F5. The researchers used advanced methods to collect data about these tiny organisms living on S1's skin during each phase - this is important because changes in the types of microbes can affect a person’s health when they are exposed to different environments, like those experienced by astronauts. The scientists then looked at how similar or different the bacteria were between these two flights for S1's skin using special computer programs and statistical tests that help them understand if any changes in microbes might be due to space travel rather than just natural variations from person to person.

In this research, the team sought to investigate potential differences in microbial contributions from a crewmember across two different flight conditions. To achieve their objective, they employed an alternative methodology that leverages phyloseq package capabilities for analyzing complex metagenomic data sets and visualizing distances between samples using Bray-Curtis metrics within the R programming environment (version 3.6). The researchers focused on skin surface microbiota by collecting swab samples from a crewmember, designated as S1, before flight conditions F4 and after condition F5 were established. The raw pairwise distances between these two sets of data points-skin-surfaces (f1 through f5) for preflight to postflight comparisons within the same individual across different flights-were visualized using Bray-Curtis metrics, which are appropriate for ecological and microbiological studies. The key findings of this study were based on a t-test analysis wherein S1's average proportion was treated as point estimates rather than relying solely on multiple tight samples to ensure robust statistical inference.