OBJECTIVES:
The International Space Station Microbial Observatory of Pathogenic Virus, Bacteria, and Fungi Project (ISS-MOP) will generate vast amount of data utilizing a number of automated high- throughput molecular methods to provide NASA with an opportunity to understand the total microbial communities of crew-associated environments. The high-throughput nature of molecular methods will not only allow researchers to describe the microbial communities of the International Space Station (ISS), but also to distinguish whether these biological signatures are of any concern to crew health and engineering systems. Focused cultivation-based approaches are likely to reveal a subset of novel and medically important microbes posing particular threats to habitat and crew health. Archival of microbial and viral strains and their availability for extensive sequencing may feed into functional genomics activities. It is expected that a wide range of metadata will allow NASA researchers to correlate microbial community information with temporal or environmental conditions.

The development of an all-encompassing, integrated ISS-MOP database will enable various phylogenetic- and pathogenic-based strategies of screening for and identifying specific subsets of microorganisms (e.g., dominating viral and microbial pathogens, as well as those that bear resistance traits relevant to human or antibiotics). This dataset will (a) create a capability for NASA to compare fluctuating viral and microbial communities to “baseline” standards, (b) enable more accurate assessments of crew health associated with a given mission and future mission planning, (c) allow evidence-based development of future bioload management policies and requirements, particularly for long-duration missions, and (d) capitalize on parallel research from non-NASA institutions such as the Human Microbiome Project (HMP) and Indoor Microbiome Project (IMP) efforts. Such a dataset will be extremely helpful in defining a baseline of what is normal and the extent to which change accompanies various disease states.

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